2025-08-26T20:04:53.4888049Z Current runner version: '2.328.0' 2025-08-26T20:04:53.4893245Z Runner name: 'linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln' 2025-08-26T20:04:53.4893633Z Runner group name: 'default' 2025-08-26T20:04:53.4894151Z Machine name: 'linux' 2025-08-26T20:04:53.4895661Z ##[group]GITHUB_TOKEN Permissions 2025-08-26T20:04:53.4896978Z Contents: read 2025-08-26T20:04:53.4897209Z Metadata: read 2025-08-26T20:04:53.4897433Z ##[endgroup] 2025-08-26T20:04:53.4898700Z Secret source: Actions 2025-08-26T20:04:53.4898999Z Prepare workflow directory 2025-08-26T20:04:53.5225655Z Prepare all required actions 2025-08-26T20:04:53.5246298Z Getting action download info 2025-08-26T20:04:53.8475136Z Download action repository 'pytorch/pytorch@main' (SHA:9f6e1b8730d6a7a7d012be90ae08674294aa4933) 2025-08-26T20:04:56.4331972Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-08-26T20:04:56.8039772Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-08-26T20:04:57.1182307Z Download action repository 'pytorch/test-infra@main' (SHA:0192d56cb596bb73b125bd368553908cc5c513f0) 2025-08-26T20:04:57.6887407Z Download action repository 'actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-08-26T20:04:58.1223458Z Getting action download info 2025-08-26T20:04:58.2580622Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-08-26T20:04:58.6142573Z Getting action download info 2025-08-26T20:04:58.8098113Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-08-26T20:04:59.1675934Z Getting action download info 2025-08-26T20:04:59.3164715Z Uses: pytorch/pytorch/.github/workflows/_rocm-test.yml@refs/heads/main (262640fd220236042fbf4443cc163c8838c84c3d) 2025-08-26T20:04:59.3167268Z ##[group] Inputs 2025-08-26T20:04:59.3167469Z build-environment: linux-noble-rocm-py3.12-mi300 2025-08-26T20:04:59.3168333Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 2, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 3, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 4, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 5, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 6, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}]} 2025-08-26T20:04:59.3169112Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:04:59.3169394Z sync-tag: 2025-08-26T20:04:59.3170023Z timeout-minutes: 300 2025-08-26T20:04:59.3170133Z tests-to-include: 2025-08-26T20:04:59.3170241Z dashboard-tag: 2025-08-26T20:04:59.3170639Z disable-monitor: true 2025-08-26T20:04:59.3170748Z monitor-log-interval: 5 2025-08-26T20:04:59.3170874Z monitor-data-collect-interval: 1 2025-08-26T20:04:59.3173971Z ##[endgroup] 2025-08-26T20:04:59.3174153Z Complete job name: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:04:59.3516308Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-08-26T20:04:59.3516566Z with: 2025-08-26T20:04:59.3516650Z no-sudo: true 2025-08-26T20:04:59.3516739Z submodules: recursive 2025-08-26T20:04:59.3516831Z fetch-depth: 0 2025-08-26T20:04:59.3516956Z env: 2025-08-26T20:04:59.3517049Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:04:59.3517164Z ##[endgroup] 2025-08-26T20:04:59.3574735Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T20:04:59.3575117Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T20:04:59.3584083Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:04:59.3584230Z env: 2025-08-26T20:04:59.3584313Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:04:59.3584409Z ##[endgroup] 2025-08-26T20:04:59.3777771Z ##[group]Run # Use all available CPUs for fetching 2025-08-26T20:04:59.3780878Z # Use all available CPUs for fetching 2025-08-26T20:04:59.3781017Z cd "${GITHUB_WORKSPACE}" 2025-08-26T20:04:59.3781143Z git config --global fetch.parallel 0 2025-08-26T20:04:59.3781280Z git config --global submodule.fetchJobs 0 2025-08-26T20:04:59.3781501Z  2025-08-26T20:04:59.3781631Z # Clean workspace. The default checkout action should also do this, but 2025-08-26T20:04:59.3781794Z # do it here as well just in case 2025-08-26T20:04:59.3781910Z if [[ -d .git ]]; then 2025-08-26T20:04:59.3782016Z  if [ -z "${NO_SUDO}" ]; then 2025-08-26T20:04:59.3782135Z  sudo git clean -ffdx 2025-08-26T20:04:59.3782234Z  else 2025-08-26T20:04:59.3782320Z  git clean -ffdx 2025-08-26T20:04:59.3782414Z  fi 2025-08-26T20:04:59.3784438Z fi 2025-08-26T20:04:59.3788579Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:04:59.3788711Z env: 2025-08-26T20:04:59.3788791Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:04:59.3788885Z NO_SUDO: true 2025-08-26T20:04:59.3788965Z ##[endgroup] 2025-08-26T20:04:59.3941331Z ##[group]Run actions/checkout@v4 2025-08-26T20:04:59.3941550Z with: 2025-08-26T20:04:59.3941688Z ref: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:04:59.3941862Z fetch-depth: 0 2025-08-26T20:04:59.3942003Z submodules: recursive 2025-08-26T20:04:59.3942143Z show-progress: false 2025-08-26T20:04:59.3942287Z repository: pytorch/pytorch 2025-08-26T20:04:59.3942572Z token: *** 2025-08-26T20:04:59.3942693Z ssh-strict: true 2025-08-26T20:04:59.3942838Z ssh-user: git 2025-08-26T20:04:59.3942967Z persist-credentials: true 2025-08-26T20:04:59.3943116Z clean: true 2025-08-26T20:04:59.3943249Z sparse-checkout-cone-mode: true 2025-08-26T20:04:59.3943410Z fetch-tags: false 2025-08-26T20:04:59.3943534Z lfs: false 2025-08-26T20:04:59.3943653Z set-safe-directory: true 2025-08-26T20:04:59.3943808Z env: 2025-08-26T20:04:59.3943921Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:04:59.3944057Z ##[endgroup] 2025-08-26T20:04:59.4822350Z Syncing repository: pytorch/pytorch 2025-08-26T20:04:59.4823222Z ##[group]Getting Git version info 2025-08-26T20:04:59.4823398Z Working directory is '/home/runner/_work/pytorch/pytorch' 2025-08-26T20:04:59.4823696Z [command]/usr/bin/git version 2025-08-26T20:04:59.4824617Z git version 2.51.0 2025-08-26T20:04:59.4836238Z ##[endgroup] 2025-08-26T20:04:59.4840948Z Copying '/home/runner/.gitconfig' to '/home/runner/_work/_temp/e66a8a57-d377-456c-9c9c-0129f62fbe3e/.gitconfig' 2025-08-26T20:04:59.4847962Z Temporarily overriding HOME='/home/runner/_work/_temp/e66a8a57-d377-456c-9c9c-0129f62fbe3e' before making global git config changes 2025-08-26T20:04:59.4848309Z Adding repository directory to the temporary git global config as a safe directory 2025-08-26T20:04:59.4881026Z [command]/usr/bin/git config --global --add safe.directory /home/runner/_work/pytorch/pytorch 2025-08-26T20:04:59.4881443Z Deleting the contents of '/home/runner/_work/pytorch/pytorch' 2025-08-26T20:04:59.4881726Z ##[group]Initializing the repository 2025-08-26T20:04:59.4892882Z [command]/usr/bin/git init /home/runner/_work/pytorch/pytorch 2025-08-26T20:04:59.4907466Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-08-26T20:04:59.4907724Z hint: is subject to change. To configure the initial branch name to use in all 2025-08-26T20:04:59.4907931Z hint: of your new repositories, which will suppress this warning, call: 2025-08-26T20:04:59.4908081Z hint: 2025-08-26T20:04:59.4908207Z hint: git config --global init.defaultBranch 2025-08-26T20:04:59.4908532Z hint: 2025-08-26T20:04:59.4908669Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-08-26T20:04:59.4908872Z hint: 'development'. The just-created branch can be renamed via this command: 2025-08-26T20:04:59.4909027Z hint: 2025-08-26T20:04:59.4909114Z hint: git branch -m 2025-08-26T20:04:59.4909224Z hint: 2025-08-26T20:04:59.4909356Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-08-26T20:04:59.4909587Z Initialized empty Git repository in /home/runner/_work/pytorch/pytorch/.git/ 2025-08-26T20:04:59.4913943Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-08-26T20:04:59.4935241Z ##[endgroup] 2025-08-26T20:04:59.4935819Z ##[group]Disabling automatic garbage collection 2025-08-26T20:04:59.4937623Z [command]/usr/bin/git config --local gc.auto 0 2025-08-26T20:04:59.4959991Z ##[endgroup] 2025-08-26T20:04:59.4960166Z ##[group]Setting up auth 2025-08-26T20:04:59.4964467Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-08-26T20:04:59.4991239Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-08-26T20:04:59.5161458Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-08-26T20:04:59.5181459Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-08-26T20:04:59.5409048Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-08-26T20:04:59.5425244Z ##[endgroup] 2025-08-26T20:04:59.5425527Z ##[group]Fetching the repository 2025-08-26T20:04:59.5430091Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-08-26T20:05:36.9217190Z From https://github.com/pytorch/pytorch 2025-08-26T20:05:36.9233223Z * [new branch] 160583 -> origin/160583 2025-08-26T20:05:36.9233483Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-08-26T20:05:36.9233690Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-08-26T20:05:36.9233925Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-08-26T20:05:36.9234183Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-08-26T20:05:36.9234405Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-08-26T20:05:36.9234636Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-08-26T20:05:36.9234891Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-08-26T20:05:36.9235113Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-08-26T20:05:36.9235319Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-08-26T20:05:36.9236005Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-08-26T20:05:36.9236203Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-08-26T20:05:36.9236487Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-08-26T20:05:36.9236690Z * [new branch] VLA_exp -> origin/VLA_exp 2025-08-26T20:05:36.9236938Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-08-26T20:05:36.9237181Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-08-26T20:05:36.9237534Z * [new branch] addVllmPin -> origin/addVllmPin 2025-08-26T20:05:36.9237737Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-08-26T20:05:36.9237947Z * [new branch] add_windows_testing_back -> origin/add_windows_testing_back 2025-08-26T20:05:36.9238148Z * [new branch] addbuildvllm -> origin/addbuildvllm 2025-08-26T20:05:36.9238340Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-08-26T20:05:36.9238526Z * [new branch] addsimde -> origin/addsimde 2025-08-26T20:05:36.9238702Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-08-26T20:05:36.9238884Z * [new branch] adi/test -> origin/adi/test 2025-08-26T20:05:36.9239064Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-08-26T20:05:36.9239252Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-08-26T20:05:36.9239460Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-08-26T20:05:36.9239661Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-08-26T20:05:36.9239983Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-08-26T20:05:36.9240228Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-08-26T20:05:36.9240548Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-08-26T20:05:36.9240757Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-08-26T20:05:36.9240949Z * [new branch] alt-disable -> origin/alt-disable 2025-08-26T20:05:36.9241153Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-08-26T20:05:36.9241385Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-08-26T20:05:36.9241628Z * [new branch] angelayi/assert_tensor_metadata_device -> origin/angelayi/assert_tensor_metadata_device 2025-08-26T20:05:36.9241863Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-08-26T20:05:36.9242054Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-08-26T20:05:36.9242282Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-08-26T20:05:36.9242509Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-08-26T20:05:36.9242715Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-08-26T20:05:36.9242918Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-08-26T20:05:36.9243121Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-08-26T20:05:36.9243331Z * [new branch] angelayi/logging.bak -> origin/angelayi/logging.bak 2025-08-26T20:05:36.9243520Z * [new branch] angelayi/logging2 -> origin/angelayi/logging2 2025-08-26T20:05:36.9243771Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-08-26T20:05:36.9243965Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-08-26T20:05:36.9244152Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-08-26T20:05:36.9244337Z * [new branch] angelayi/save_error -> origin/angelayi/save_error 2025-08-26T20:05:36.9244523Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-08-26T20:05:36.9244717Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-08-26T20:05:36.9244981Z * [new branch] angelayi/tensor_nn_module_meta -> origin/angelayi/tensor_nn_module_meta 2025-08-26T20:05:36.9245186Z * [new branch] angelayi/test_cpp -> origin/angelayi/test_cpp 2025-08-26T20:05:36.9245378Z * [new branch] angelayi/torch_size -> origin/angelayi/torch_size 2025-08-26T20:05:36.9245562Z * [new branch] aoti-cuda-alloc -> origin/aoti-cuda-alloc 2025-08-26T20:05:36.9245744Z * [new branch] aoti_weight_sharing -> origin/aoti_weight_sharing 2025-08-26T20:05:36.9245938Z * [new branch] arsh/symint_mm_ind_decomp -> origin/arsh/symint_mm_ind_decomp 2025-08-26T20:05:36.9246157Z * [new branch] atalman-inductor-perf-cu124 -> origin/atalman-inductor-perf-cu124 2025-08-26T20:05:36.9246399Z * [new branch] atalman-inductor-perf-cu124.1 -> origin/atalman-inductor-perf-cu124.1 2025-08-26T20:05:36.9246613Z * [new branch] atalman-patch-1 -> origin/atalman-patch-1 2025-08-26T20:05:36.9246798Z * [new branch] atalman-patch-2 -> origin/atalman-patch-2 2025-08-26T20:05:36.9246975Z * [new branch] atalman-patch-3 -> origin/atalman-patch-3 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2025-08-26T20:05:37.0133291Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-08-26T20:05:37.0133479Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-08-26T20:05:37.0133655Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-08-26T20:05:37.0133837Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-08-26T20:05:37.0134025Z * [new branch] zainr/uv-pip-fix -> origin/zainr/uv-pip-fix 2025-08-26T20:05:37.0134268Z * [new branch] zainr/vs-aarch64 -> origin/zainr/vs-aarch64 2025-08-26T20:05:37.0134465Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-08-26T20:05:37.0134652Z * [new branch] zb2p -> origin/zb2p 2025-08-26T20:05:37.0147289Z * [new branch] zdevito-patch-1 -> origin/zdevito-patch-1 2025-08-26T20:05:37.0147623Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-08-26T20:05:37.0147940Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-08-26T20:05:37.0148254Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-08-26T20:05:37.0148559Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-08-26T20:05:37.0148840Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-08-26T20:05:37.0149121Z * [new branch] zxiiro/test -> origin/zxiiro/test 2025-08-26T20:05:37.0149530Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-08-26T20:05:37.0149946Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-08-26T20:05:37.0150201Z * [new tag] ciflow/binaries/153920 -> ciflow/binaries/153920 2025-08-26T20:05:37.0150549Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-08-26T20:05:37.0150805Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-08-26T20:05:37.0151054Z * [new tag] ciflow/binaries/160853 -> ciflow/binaries/160853 2025-08-26T20:05:37.0151306Z * [new tag] ciflow/binaries/161257 -> ciflow/binaries/161257 2025-08-26T20:05:37.0151588Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-08-26T20:05:37.0151901Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-08-26T20:05:37.0152187Z * [new tag] ciflow/binaries_wheel/158733 -> ciflow/binaries_wheel/158733 2025-08-26T20:05:37.0152470Z * [new tag] ciflow/binaries_wheel/160207 -> ciflow/binaries_wheel/160207 2025-08-26T20:05:37.0152750Z * [new tag] ciflow/h100-symm-mem/151845 -> ciflow/h100-symm-mem/151845 2025-08-26T20:05:37.0153015Z * [new tag] ciflow/h100-symm-mem/155923 -> ciflow/h100-symm-mem/155923 2025-08-26T20:05:37.0153281Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-08-26T20:05:37.0153546Z * [new tag] ciflow/h100-symm-mem/159562 -> ciflow/h100-symm-mem/159562 2025-08-26T20:05:37.0153802Z * [new tag] ciflow/h100-symm-mem/159889 -> ciflow/h100-symm-mem/159889 2025-08-26T20:05:37.0154064Z * [new tag] ciflow/h100-symm-mem/160825 -> ciflow/h100-symm-mem/160825 2025-08-26T20:05:37.0154323Z * [new tag] ciflow/h100-symm-mem/161008 -> ciflow/h100-symm-mem/161008 2025-08-26T20:05:37.0154584Z * [new tag] ciflow/h100-symm-mem/161090 -> ciflow/h100-symm-mem/161090 2025-08-26T20:05:37.0155118Z * [new tag] ciflow/h100-symm-mem/161214 -> ciflow/h100-symm-mem/161214 2025-08-26T20:05:37.0155377Z * [new tag] ciflow/h100-symm-mem/161217 -> ciflow/h100-symm-mem/161217 2025-08-26T20:05:37.0155642Z * [new tag] ciflow/h100-symm-mem/161232 -> ciflow/h100-symm-mem/161232 2025-08-26T20:05:37.0158861Z * [new tag] ciflow/h100-symm-mem/161257 -> ciflow/h100-symm-mem/161257 2025-08-26T20:05:37.0159151Z * [new tag] ciflow/h100-symm-mem/161309 -> ciflow/h100-symm-mem/161309 2025-08-26T20:05:37.0159422Z * [new tag] ciflow/h100-symm-mem/161470 -> ciflow/h100-symm-mem/161470 2025-08-26T20:05:37.0159848Z * [new tag] ciflow/h100-symm-mem/161471 -> ciflow/h100-symm-mem/161471 2025-08-26T20:05:37.0160121Z * [new tag] ciflow/h100-symm-mem/161532 -> ciflow/h100-symm-mem/161532 2025-08-26T20:05:37.0160482Z * [new tag] ciflow/h100-symm-mem/161533 -> ciflow/h100-symm-mem/161533 2025-08-26T20:05:37.0160736Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-08-26T20:05:37.0160975Z * [new tag] ciflow/h100/161225 -> ciflow/h100/161225 2025-08-26T20:05:37.0161329Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/151845 -> ciflow/inductor-perf-test-nightly-rocm/151845 2025-08-26T20:05:37.0161816Z * [new tag] ciflow/inductor-perf-test-nightly-x86-zen/161512 -> ciflow/inductor-perf-test-nightly-x86-zen/161512 2025-08-26T20:05:37.0162227Z * [new tag] ciflow/inductor-periodic/158137 -> ciflow/inductor-periodic/158137 2025-08-26T20:05:37.0162555Z * [new tag] ciflow/inductor-periodic/160807 -> ciflow/inductor-periodic/160807 2025-08-26T20:05:37.0164895Z * [new tag] ciflow/inductor-periodic/161461 -> ciflow/inductor-periodic/161461 2025-08-26T20:05:37.0165230Z * [new tag] ciflow/inductor-periodic/161536 -> ciflow/inductor-periodic/161536 2025-08-26T20:05:37.0165729Z * [new tag] ciflow/inductor-periodic/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 -> ciflow/inductor-periodic/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 2025-08-26T20:05:37.0166387Z * [new tag] ciflow/inductor-periodic/3e5b021f217a42ae55dc690083f67a28126808ed -> ciflow/inductor-periodic/3e5b021f217a42ae55dc690083f67a28126808ed 2025-08-26T20:05:37.0167025Z * [new tag] ciflow/inductor-periodic/f912c93344caa74e24c8164a2e25fe84a8203073 -> ciflow/inductor-periodic/f912c93344caa74e24c8164a2e25fe84a8203073 2025-08-26T20:05:37.0167486Z * [new tag] ciflow/inductor-rocm/151845 -> ciflow/inductor-rocm/151845 2025-08-26T20:05:37.0167868Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-08-26T20:05:37.0168143Z * [new tag] ciflow/inductor-rocm/160671 -> ciflow/inductor-rocm/160671 2025-08-26T20:05:37.0168418Z * [new tag] ciflow/inductor-rocm/161180 -> ciflow/inductor-rocm/161180 2025-08-26T20:05:37.0168692Z * [new tag] ciflow/inductor-rocm/161225 -> ciflow/inductor-rocm/161225 2025-08-26T20:05:37.0168962Z * [new tag] ciflow/inductor-rocm/161521 -> ciflow/inductor-rocm/161521 2025-08-26T20:05:37.0169257Z * [new tag] ciflow/inductor-windows/160406 -> ciflow/inductor-windows/160406 2025-08-26T20:05:37.0169537Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-08-26T20:05:37.0171738Z * [new tag] ciflow/inductor/151845 -> ciflow/inductor/151845 2025-08-26T20:05:37.0171987Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-08-26T20:05:37.0172236Z * [new tag] ciflow/inductor/155072 -> ciflow/inductor/155072 2025-08-26T20:05:37.0172482Z * [new tag] ciflow/inductor/155152 -> ciflow/inductor/155152 2025-08-26T20:05:37.0172830Z * [new tag] ciflow/inductor/155153 -> ciflow/inductor/155153 2025-08-26T20:05:37.0173073Z * [new tag] ciflow/inductor/155154 -> ciflow/inductor/155154 2025-08-26T20:05:37.0173318Z * [new tag] ciflow/inductor/155501 -> ciflow/inductor/155501 2025-08-26T20:05:37.0173562Z * [new tag] ciflow/inductor/155502 -> ciflow/inductor/155502 2025-08-26T20:05:37.0173805Z * [new tag] ciflow/inductor/155503 -> ciflow/inductor/155503 2025-08-26T20:05:37.0174049Z * [new tag] ciflow/inductor/155557 -> ciflow/inductor/155557 2025-08-26T20:05:37.0174291Z * [new tag] ciflow/inductor/155608 -> ciflow/inductor/155608 2025-08-26T20:05:37.0174638Z * [new tag] ciflow/inductor/155923 -> ciflow/inductor/155923 2025-08-26T20:05:37.0176653Z * [new tag] ciflow/inductor/155928 -> ciflow/inductor/155928 2025-08-26T20:05:37.0176901Z * [new tag] ciflow/inductor/156875 -> ciflow/inductor/156875 2025-08-26T20:05:37.0177143Z * [new tag] ciflow/inductor/156967 -> ciflow/inductor/156967 2025-08-26T20:05:37.0177385Z * [new tag] ciflow/inductor/157298 -> ciflow/inductor/157298 2025-08-26T20:05:37.0177628Z * [new tag] ciflow/inductor/157572 -> ciflow/inductor/157572 2025-08-26T20:05:37.0177871Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-08-26T20:05:37.0178116Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-08-26T20:05:37.0178356Z * [new tag] ciflow/inductor/157767 -> ciflow/inductor/157767 2025-08-26T20:05:37.0178601Z * [new tag] ciflow/inductor/157944 -> ciflow/inductor/157944 2025-08-26T20:05:37.0178846Z * [new tag] ciflow/inductor/158061 -> ciflow/inductor/158061 2025-08-26T20:05:37.0179090Z * [new tag] ciflow/inductor/158097 -> ciflow/inductor/158097 2025-08-26T20:05:37.0179332Z * [new tag] ciflow/inductor/158098 -> ciflow/inductor/158098 2025-08-26T20:05:37.0181316Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-08-26T20:05:37.0181570Z * [new tag] ciflow/inductor/158137 -> ciflow/inductor/158137 2025-08-26T20:05:37.0181813Z * [new tag] ciflow/inductor/158321 -> ciflow/inductor/158321 2025-08-26T20:05:37.0182059Z * [new tag] ciflow/inductor/158609 -> ciflow/inductor/158609 2025-08-26T20:05:37.0182303Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-08-26T20:05:37.0182546Z * [new tag] ciflow/inductor/159003 -> ciflow/inductor/159003 2025-08-26T20:05:37.0182791Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-08-26T20:05:37.0183034Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-08-26T20:05:37.0183279Z * [new tag] ciflow/inductor/159387 -> ciflow/inductor/159387 2025-08-26T20:05:37.0183522Z * [new tag] ciflow/inductor/159473 -> ciflow/inductor/159473 2025-08-26T20:05:37.0183765Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-08-26T20:05:37.0184006Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-08-26T20:05:37.0184249Z * [new tag] ciflow/inductor/159786 -> ciflow/inductor/159786 2025-08-26T20:05:37.0186139Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-08-26T20:05:37.0186388Z * [new tag] ciflow/inductor/159889 -> ciflow/inductor/159889 2025-08-26T20:05:37.0186631Z * [new tag] ciflow/inductor/159923 -> ciflow/inductor/159923 2025-08-26T20:05:37.0186874Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-08-26T20:05:37.0187203Z * [new tag] ciflow/inductor/160080 -> ciflow/inductor/160080 2025-08-26T20:05:37.0187448Z * [new tag] ciflow/inductor/160111 -> ciflow/inductor/160111 2025-08-26T20:05:37.0187692Z * [new tag] ciflow/inductor/160138 -> ciflow/inductor/160138 2025-08-26T20:05:37.0187934Z * [new tag] ciflow/inductor/160156 -> ciflow/inductor/160156 2025-08-26T20:05:37.0188176Z * [new tag] ciflow/inductor/160180 -> ciflow/inductor/160180 2025-08-26T20:05:37.0188420Z * [new tag] ciflow/inductor/160198 -> ciflow/inductor/160198 2025-08-26T20:05:37.0188748Z * [new tag] ciflow/inductor/160258 -> ciflow/inductor/160258 2025-08-26T20:05:37.0188990Z * [new tag] ciflow/inductor/160266 -> ciflow/inductor/160266 2025-08-26T20:05:37.0191474Z * [new tag] ciflow/inductor/160282 -> ciflow/inductor/160282 2025-08-26T20:05:37.0191728Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-08-26T20:05:37.0191971Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-08-26T20:05:37.0192214Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-08-26T20:05:37.0192458Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-08-26T20:05:37.0192702Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-08-26T20:05:37.0192947Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-08-26T20:05:37.0193187Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-08-26T20:05:37.0193435Z * [new tag] ciflow/inductor/160431 -> ciflow/inductor/160431 2025-08-26T20:05:37.0193679Z * [new tag] ciflow/inductor/160448 -> ciflow/inductor/160448 2025-08-26T20:05:37.0193926Z * [new tag] ciflow/inductor/160449 -> ciflow/inductor/160449 2025-08-26T20:05:37.0194167Z * [new tag] ciflow/inductor/160467 -> ciflow/inductor/160467 2025-08-26T20:05:37.0196067Z * [new tag] ciflow/inductor/160470 -> ciflow/inductor/160470 2025-08-26T20:05:37.0196320Z * [new tag] ciflow/inductor/160483 -> ciflow/inductor/160483 2025-08-26T20:05:37.0196565Z * [new tag] ciflow/inductor/160527 -> ciflow/inductor/160527 2025-08-26T20:05:37.0196806Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-08-26T20:05:37.0197050Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-08-26T20:05:37.0197294Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-08-26T20:05:37.0197539Z * [new tag] ciflow/inductor/160601 -> ciflow/inductor/160601 2025-08-26T20:05:37.0197783Z * [new tag] ciflow/inductor/160611 -> ciflow/inductor/160611 2025-08-26T20:05:37.0198027Z * [new tag] ciflow/inductor/160669 -> ciflow/inductor/160669 2025-08-26T20:05:37.0200440Z * [new tag] ciflow/inductor/160670 -> ciflow/inductor/160670 2025-08-26T20:05:37.0200687Z * [new tag] ciflow/inductor/160671 -> ciflow/inductor/160671 2025-08-26T20:05:37.0200929Z * [new tag] ciflow/inductor/160677 -> ciflow/inductor/160677 2025-08-26T20:05:37.0202848Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-08-26T20:05:37.0203097Z * [new tag] ciflow/inductor/160763 -> ciflow/inductor/160763 2025-08-26T20:05:37.0203346Z * [new tag] ciflow/inductor/160772 -> ciflow/inductor/160772 2025-08-26T20:05:37.0203586Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-08-26T20:05:37.0203935Z * [new tag] ciflow/inductor/160807 -> ciflow/inductor/160807 2025-08-26T20:05:37.0204180Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-08-26T20:05:37.0204420Z * [new tag] ciflow/inductor/160861 -> ciflow/inductor/160861 2025-08-26T20:05:37.0204661Z * [new tag] ciflow/inductor/160883 -> ciflow/inductor/160883 2025-08-26T20:05:37.0204902Z * [new tag] ciflow/inductor/160888 -> ciflow/inductor/160888 2025-08-26T20:05:37.0205150Z * [new tag] ciflow/inductor/160903 -> ciflow/inductor/160903 2025-08-26T20:05:37.0205394Z * [new tag] ciflow/inductor/160913 -> ciflow/inductor/160913 2025-08-26T20:05:37.0205716Z * [new tag] ciflow/inductor/160941 -> ciflow/inductor/160941 2025-08-26T20:05:37.0205956Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-08-26T20:05:37.0207985Z * [new tag] ciflow/inductor/160991 -> ciflow/inductor/160991 2025-08-26T20:05:37.0208234Z * [new tag] ciflow/inductor/160997 -> ciflow/inductor/160997 2025-08-26T20:05:37.0208473Z * [new tag] ciflow/inductor/161003 -> ciflow/inductor/161003 2025-08-26T20:05:37.0208715Z * [new tag] ciflow/inductor/161026 -> ciflow/inductor/161026 2025-08-26T20:05:37.0208959Z * [new tag] ciflow/inductor/161032 -> ciflow/inductor/161032 2025-08-26T20:05:37.0209201Z * [new tag] ciflow/inductor/161040 -> ciflow/inductor/161040 2025-08-26T20:05:37.0209445Z * [new tag] ciflow/inductor/161055 -> ciflow/inductor/161055 2025-08-26T20:05:37.0209688Z * [new tag] ciflow/inductor/161062 -> ciflow/inductor/161062 2025-08-26T20:05:37.0209932Z * [new tag] ciflow/inductor/161069 -> ciflow/inductor/161069 2025-08-26T20:05:37.0210172Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-08-26T20:05:37.0210656Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-08-26T20:05:37.0210897Z * [new tag] ciflow/inductor/161097 -> ciflow/inductor/161097 2025-08-26T20:05:37.0212812Z * [new tag] ciflow/inductor/161098 -> ciflow/inductor/161098 2025-08-26T20:05:37.0213058Z * [new tag] ciflow/inductor/161100 -> ciflow/inductor/161100 2025-08-26T20:05:37.0213298Z * [new tag] ciflow/inductor/161107 -> ciflow/inductor/161107 2025-08-26T20:05:37.0213533Z * [new tag] ciflow/inductor/161110 -> ciflow/inductor/161110 2025-08-26T20:05:37.0213774Z * [new tag] ciflow/inductor/161117 -> ciflow/inductor/161117 2025-08-26T20:05:37.0214011Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-08-26T20:05:37.0214249Z * [new tag] ciflow/inductor/161123 -> ciflow/inductor/161123 2025-08-26T20:05:37.0214488Z * [new tag] ciflow/inductor/161124 -> ciflow/inductor/161124 2025-08-26T20:05:37.0214726Z * [new tag] ciflow/inductor/161125 -> ciflow/inductor/161125 2025-08-26T20:05:37.0214964Z * [new tag] ciflow/inductor/161126 -> ciflow/inductor/161126 2025-08-26T20:05:37.0215199Z * [new tag] ciflow/inductor/161144 -> ciflow/inductor/161144 2025-08-26T20:05:37.0215436Z * [new tag] ciflow/inductor/161148 -> ciflow/inductor/161148 2025-08-26T20:05:37.0217327Z * [new tag] ciflow/inductor/161158 -> ciflow/inductor/161158 2025-08-26T20:05:37.0217578Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-08-26T20:05:37.0217828Z * [new tag] ciflow/inductor/161190 -> ciflow/inductor/161190 2025-08-26T20:05:37.0218071Z * [new tag] ciflow/inductor/161208 -> ciflow/inductor/161208 2025-08-26T20:05:37.0218421Z * [new tag] ciflow/inductor/161225 -> ciflow/inductor/161225 2025-08-26T20:05:37.0218667Z * [new tag] ciflow/inductor/161229 -> ciflow/inductor/161229 2025-08-26T20:05:37.0218910Z * [new tag] ciflow/inductor/161237 -> ciflow/inductor/161237 2025-08-26T20:05:37.0219154Z * [new tag] ciflow/inductor/161241 -> ciflow/inductor/161241 2025-08-26T20:05:37.0219400Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-08-26T20:05:37.0219646Z * [new tag] ciflow/inductor/161274 -> ciflow/inductor/161274 2025-08-26T20:05:37.0219891Z * [new tag] ciflow/inductor/161278 -> ciflow/inductor/161278 2025-08-26T20:05:37.0220212Z * [new tag] ciflow/inductor/161279 -> ciflow/inductor/161279 2025-08-26T20:05:37.0220544Z * [new tag] ciflow/inductor/161288 -> ciflow/inductor/161288 2025-08-26T20:05:37.0222512Z * [new tag] ciflow/inductor/161314 -> ciflow/inductor/161314 2025-08-26T20:05:37.0222764Z * [new tag] ciflow/inductor/161320 -> ciflow/inductor/161320 2025-08-26T20:05:37.0223010Z * [new tag] ciflow/inductor/161336 -> ciflow/inductor/161336 2025-08-26T20:05:37.0223254Z * [new tag] ciflow/inductor/161337 -> ciflow/inductor/161337 2025-08-26T20:05:37.0223497Z * [new tag] ciflow/inductor/161338 -> ciflow/inductor/161338 2025-08-26T20:05:37.0223738Z * [new tag] ciflow/inductor/161339 -> ciflow/inductor/161339 2025-08-26T20:05:37.0223980Z * [new tag] ciflow/inductor/161340 -> ciflow/inductor/161340 2025-08-26T20:05:37.0224224Z * [new tag] ciflow/inductor/161341 -> ciflow/inductor/161341 2025-08-26T20:05:37.0224469Z * [new tag] ciflow/inductor/161342 -> ciflow/inductor/161342 2025-08-26T20:05:37.0224711Z * [new tag] ciflow/inductor/161343 -> ciflow/inductor/161343 2025-08-26T20:05:37.0224954Z * [new tag] ciflow/inductor/161344 -> ciflow/inductor/161344 2025-08-26T20:05:37.0225197Z * [new tag] ciflow/inductor/161345 -> ciflow/inductor/161345 2025-08-26T20:05:37.0225439Z * [new tag] ciflow/inductor/161346 -> ciflow/inductor/161346 2025-08-26T20:05:37.0225681Z * [new tag] ciflow/inductor/161347 -> ciflow/inductor/161347 2025-08-26T20:05:37.0227937Z * [new tag] ciflow/inductor/161348 -> ciflow/inductor/161348 2025-08-26T20:05:37.0228184Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-08-26T20:05:37.0228430Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-08-26T20:05:37.0228672Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-08-26T20:05:37.0228917Z * [new tag] ciflow/inductor/161353 -> ciflow/inductor/161353 2025-08-26T20:05:37.0229165Z * [new tag] ciflow/inductor/161354 -> ciflow/inductor/161354 2025-08-26T20:05:37.0229406Z * [new tag] ciflow/inductor/161355 -> ciflow/inductor/161355 2025-08-26T20:05:37.0229653Z * [new tag] ciflow/inductor/161362 -> ciflow/inductor/161362 2025-08-26T20:05:37.0229899Z * [new tag] ciflow/inductor/161363 -> ciflow/inductor/161363 2025-08-26T20:05:37.0230145Z * [new tag] ciflow/inductor/161382 -> ciflow/inductor/161382 2025-08-26T20:05:37.0230488Z * [new tag] ciflow/inductor/161383 -> ciflow/inductor/161383 2025-08-26T20:05:37.0230737Z * [new tag] ciflow/inductor/161385 -> ciflow/inductor/161385 2025-08-26T20:05:37.0232813Z * [new tag] ciflow/inductor/161396 -> ciflow/inductor/161396 2025-08-26T20:05:37.0233162Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-08-26T20:05:37.0233409Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-08-26T20:05:37.0233653Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-08-26T20:05:37.0233895Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-08-26T20:05:37.0234139Z * [new tag] ciflow/inductor/161409 -> ciflow/inductor/161409 2025-08-26T20:05:37.0234381Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-08-26T20:05:37.0235323Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-08-26T20:05:37.0235653Z * [new tag] ciflow/inductor/161416 -> ciflow/inductor/161416 2025-08-26T20:05:37.0235901Z * [new tag] ciflow/inductor/161420 -> ciflow/inductor/161420 2025-08-26T20:05:37.0236145Z * [new tag] ciflow/inductor/161431 -> ciflow/inductor/161431 2025-08-26T20:05:37.0236392Z * [new tag] ciflow/inductor/161435 -> ciflow/inductor/161435 2025-08-26T20:05:37.0238467Z * [new tag] ciflow/inductor/161440 -> ciflow/inductor/161440 2025-08-26T20:05:37.0238716Z * [new tag] ciflow/inductor/161447 -> ciflow/inductor/161447 2025-08-26T20:05:37.0238957Z * [new tag] ciflow/inductor/161452 -> ciflow/inductor/161452 2025-08-26T20:05:37.0239205Z * [new tag] ciflow/inductor/161453 -> ciflow/inductor/161453 2025-08-26T20:05:37.0239448Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-08-26T20:05:37.0239697Z * [new tag] ciflow/inductor/161461 -> ciflow/inductor/161461 2025-08-26T20:05:37.0239941Z * [new tag] ciflow/inductor/161464 -> ciflow/inductor/161464 2025-08-26T20:05:37.0240185Z * [new tag] ciflow/inductor/161466 -> ciflow/inductor/161466 2025-08-26T20:05:37.0240527Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-08-26T20:05:37.0240771Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-08-26T20:05:37.0241017Z * [new tag] ciflow/inductor/161474 -> ciflow/inductor/161474 2025-08-26T20:05:37.0241265Z * [new tag] ciflow/inductor/161477 -> ciflow/inductor/161477 2025-08-26T20:05:37.0243445Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-08-26T20:05:37.0243727Z * [new tag] ciflow/inductor/161486 -> ciflow/inductor/161486 2025-08-26T20:05:37.0243976Z * [new tag] ciflow/inductor/161487 -> ciflow/inductor/161487 2025-08-26T20:05:37.0244221Z * [new tag] ciflow/inductor/161495 -> ciflow/inductor/161495 2025-08-26T20:05:37.0244466Z * [new tag] ciflow/inductor/161497 -> ciflow/inductor/161497 2025-08-26T20:05:37.0244711Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-08-26T20:05:37.0244954Z * [new tag] ciflow/inductor/161512 -> ciflow/inductor/161512 2025-08-26T20:05:37.0245196Z * [new tag] ciflow/inductor/161521 -> ciflow/inductor/161521 2025-08-26T20:05:37.0245442Z * [new tag] ciflow/inductor/161526 -> ciflow/inductor/161526 2025-08-26T20:05:37.0245688Z * [new tag] ciflow/inductor/161530 -> ciflow/inductor/161530 2025-08-26T20:05:37.0245930Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-08-26T20:05:37.0246171Z * [new tag] ciflow/inductor/161536 -> ciflow/inductor/161536 2025-08-26T20:05:37.0246423Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-08-26T20:05:37.0248507Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-08-26T20:05:37.0248860Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-08-26T20:05:37.0249129Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-08-26T20:05:37.0249396Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-08-26T20:05:37.0249662Z * [new tag] ciflow/linux-aarch64/160080 -> ciflow/linux-aarch64/160080 2025-08-26T20:05:37.0249910Z * [new tag] ciflow/mps/155923 -> ciflow/mps/155923 2025-08-26T20:05:37.0250139Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-08-26T20:05:37.0250446Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-08-26T20:05:37.0250718Z * [new tag] ciflow/mps/160839 -> ciflow/mps/160839 2025-08-26T20:05:37.0250938Z * [new tag] ciflow/mps/161511 -> ciflow/mps/161511 2025-08-26T20:05:37.0251175Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-08-26T20:05:37.0251467Z * [new tag] ciflow/periodic-rocm-mi300/161180 -> ciflow/periodic-rocm-mi300/161180 2025-08-26T20:05:37.0253541Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-08-26T20:05:37.0253963Z * [new tag] ciflow/periodic/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 -> ciflow/periodic/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 2025-08-26T20:05:37.0254373Z * [new tag] ciflow/periodic/156491 -> ciflow/periodic/156491 2025-08-26T20:05:37.0254620Z * [new tag] ciflow/periodic/161013 -> ciflow/periodic/161013 2025-08-26T20:05:37.0254875Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-08-26T20:05:37.0255129Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-08-26T20:05:37.0255376Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-08-26T20:05:37.0255623Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-08-26T20:05:37.0255887Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-08-26T20:05:37.0256317Z * [new tag] ciflow/periodic/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 -> ciflow/periodic/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 2025-08-26T20:05:37.0256752Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-08-26T20:05:37.0257047Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-08-26T20:05:37.0258930Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-08-26T20:05:37.0259225Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-08-26T20:05:37.0259517Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-08-26T20:05:37.0259807Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-08-26T20:05:37.0260071Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-08-26T20:05:37.0260320Z * [new tag] ciflow/rocm-mi300/161040 -> ciflow/rocm-mi300/161040 2025-08-26T20:05:37.0260654Z * [new tag] ciflow/rocm-mi300/161180 -> ciflow/rocm-mi300/161180 2025-08-26T20:05:37.0260898Z * [new tag] ciflow/rocm-mi300/161225 -> ciflow/rocm-mi300/161225 2025-08-26T20:05:37.0261143Z * [new tag] ciflow/rocm-mi300/161429 -> ciflow/rocm-mi300/161429 2025-08-26T20:05:37.0261389Z * [new tag] ciflow/rocm-mi355/160215 -> ciflow/rocm-mi355/160215 2025-08-26T20:05:37.0261626Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-08-26T20:05:37.0261853Z * [new tag] ciflow/rocm/151845 -> ciflow/rocm/151845 2025-08-26T20:05:37.0262175Z * [new tag] ciflow/rocm/152526 -> ciflow/rocm/152526 2025-08-26T20:05:37.0264032Z * [new tag] ciflow/rocm/154864 -> ciflow/rocm/154864 2025-08-26T20:05:37.0264258Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-08-26T20:05:37.0264481Z * [new tag] ciflow/rocm/158352 -> ciflow/rocm/158352 2025-08-26T20:05:37.0264702Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-08-26T20:05:37.0264925Z * [new tag] ciflow/rocm/160215 -> ciflow/rocm/160215 2025-08-26T20:05:37.0265147Z * [new tag] ciflow/rocm/160671 -> ciflow/rocm/160671 2025-08-26T20:05:37.0265453Z * [new tag] ciflow/rocm/160676 -> ciflow/rocm/160676 2025-08-26T20:05:37.0265676Z * [new tag] ciflow/rocm/161180 -> ciflow/rocm/161180 2025-08-26T20:05:37.0265899Z * [new tag] ciflow/rocm/161225 -> ciflow/rocm/161225 2025-08-26T20:05:37.0266122Z * [new tag] ciflow/rocm/161277 -> ciflow/rocm/161277 2025-08-26T20:05:37.0266344Z * [new tag] ciflow/rocm/161429 -> ciflow/rocm/161429 2025-08-26T20:05:37.0266568Z * [new tag] ciflow/rocm/161496 -> ciflow/rocm/161496 2025-08-26T20:05:37.0268402Z * [new tag] ciflow/s390/160893 -> ciflow/s390/160893 2025-08-26T20:05:37.0268627Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-08-26T20:05:37.0268856Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-08-26T20:05:37.0269271Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-08-26T20:05:37.0269674Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-08-26T20:05:37.0269903Z * [new tag] ciflow/slow/161182 -> ciflow/slow/161182 2025-08-26T20:05:37.0270125Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-08-26T20:05:37.0270507Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-08-26T20:05:37.0270743Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-08-26T20:05:37.0270969Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-08-26T20:05:37.0271235Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-08-26T20:05:37.0271468Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-08-26T20:05:37.0273423Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-08-26T20:05:37.0273658Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-08-26T20:05:37.0273884Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-08-26T20:05:37.0274270Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-08-26T20:05:37.0274646Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-08-26T20:05:37.0274874Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-08-26T20:05:37.0275102Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-08-26T20:05:37.0275327Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-08-26T20:05:37.0275554Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-08-26T20:05:37.0275950Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-08-26T20:05:37.0276357Z * [new tag] ciflow/torchbench/158137 -> ciflow/torchbench/158137 2025-08-26T20:05:37.0276707Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-08-26T20:05:37.0276932Z * [new tag] ciflow/trunk/151845 -> ciflow/trunk/151845 2025-08-26T20:05:37.0278962Z * [new tag] ciflow/trunk/153784 -> ciflow/trunk/153784 2025-08-26T20:05:37.0279186Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-08-26T20:05:37.0279413Z * [new tag] ciflow/trunk/154864 -> ciflow/trunk/154864 2025-08-26T20:05:37.0279637Z * [new tag] ciflow/trunk/156418 -> ciflow/trunk/156418 2025-08-26T20:05:37.0279971Z * [new tag] ciflow/trunk/157196 -> ciflow/trunk/157196 2025-08-26T20:05:37.0280197Z * [new tag] ciflow/trunk/157537 -> ciflow/trunk/157537 2025-08-26T20:05:37.0280527Z * [new tag] ciflow/trunk/157767 -> ciflow/trunk/157767 2025-08-26T20:05:37.0280753Z * [new tag] ciflow/trunk/157944 -> ciflow/trunk/157944 2025-08-26T20:05:37.0280977Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-08-26T20:05:37.0281200Z * [new tag] ciflow/trunk/158541 -> ciflow/trunk/158541 2025-08-26T20:05:37.0281425Z * [new tag] ciflow/trunk/158733 -> ciflow/trunk/158733 2025-08-26T20:05:37.0281649Z * [new tag] ciflow/trunk/158747 -> ciflow/trunk/158747 2025-08-26T20:05:37.0283555Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-08-26T20:05:37.0283780Z * [new tag] ciflow/trunk/159387 -> ciflow/trunk/159387 2025-08-26T20:05:37.0284006Z * [new tag] ciflow/trunk/159562 -> ciflow/trunk/159562 2025-08-26T20:05:37.0284230Z * [new tag] ciflow/trunk/159786 -> ciflow/trunk/159786 2025-08-26T20:05:37.0284455Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-08-26T20:05:37.0284679Z * [new tag] ciflow/trunk/159889 -> ciflow/trunk/159889 2025-08-26T20:05:37.0284906Z * [new tag] ciflow/trunk/159923 -> ciflow/trunk/159923 2025-08-26T20:05:37.0285128Z * [new tag] ciflow/trunk/160156 -> ciflow/trunk/160156 2025-08-26T20:05:37.0285352Z * [new tag] ciflow/trunk/160180 -> ciflow/trunk/160180 2025-08-26T20:05:37.0285579Z * [new tag] ciflow/trunk/160198 -> ciflow/trunk/160198 2025-08-26T20:05:37.0285802Z * [new tag] ciflow/trunk/160258 -> ciflow/trunk/160258 2025-08-26T20:05:37.0286029Z * [new tag] ciflow/trunk/160431 -> ciflow/trunk/160431 2025-08-26T20:05:37.0287933Z * [new tag] ciflow/trunk/160448 -> ciflow/trunk/160448 2025-08-26T20:05:37.0288165Z * [new tag] ciflow/trunk/160449 -> ciflow/trunk/160449 2025-08-26T20:05:37.0288392Z * [new tag] ciflow/trunk/160527 -> ciflow/trunk/160527 2025-08-26T20:05:37.0288617Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-08-26T20:05:37.0288841Z * [new tag] ciflow/trunk/160671 -> ciflow/trunk/160671 2025-08-26T20:05:37.0289066Z * [new tag] ciflow/trunk/160677 -> ciflow/trunk/160677 2025-08-26T20:05:37.0289292Z * [new tag] ciflow/trunk/160692 -> ciflow/trunk/160692 2025-08-26T20:05:37.0289516Z * [new tag] ciflow/trunk/160781 -> ciflow/trunk/160781 2025-08-26T20:05:37.0289741Z * [new tag] ciflow/trunk/160825 -> ciflow/trunk/160825 2025-08-26T20:05:37.0289968Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-08-26T20:05:37.0290192Z * [new tag] ciflow/trunk/160866 -> ciflow/trunk/160866 2025-08-26T20:05:37.0290601Z * [new tag] ciflow/trunk/160915 -> ciflow/trunk/160915 2025-08-26T20:05:37.0290830Z * [new tag] ciflow/trunk/160991 -> ciflow/trunk/160991 2025-08-26T20:05:37.0292727Z * [new tag] ciflow/trunk/160992 -> ciflow/trunk/160992 2025-08-26T20:05:37.0292952Z * [new tag] ciflow/trunk/161004 -> ciflow/trunk/161004 2025-08-26T20:05:37.0293178Z * [new tag] ciflow/trunk/161016 -> ciflow/trunk/161016 2025-08-26T20:05:37.0293402Z * [new tag] ciflow/trunk/161023 -> ciflow/trunk/161023 2025-08-26T20:05:37.0293626Z * [new tag] ciflow/trunk/161026 -> ciflow/trunk/161026 2025-08-26T20:05:37.0293943Z * [new tag] ciflow/trunk/161032 -> ciflow/trunk/161032 2025-08-26T20:05:37.0294167Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-08-26T20:05:37.0294392Z * [new tag] ciflow/trunk/161040 -> ciflow/trunk/161040 2025-08-26T20:05:37.0294619Z * [new tag] ciflow/trunk/161094 -> ciflow/trunk/161094 2025-08-26T20:05:37.0294844Z * [new tag] ciflow/trunk/161097 -> ciflow/trunk/161097 2025-08-26T20:05:37.0295068Z * [new tag] ciflow/trunk/161098 -> ciflow/trunk/161098 2025-08-26T20:05:37.0295293Z * [new tag] ciflow/trunk/161100 -> ciflow/trunk/161100 2025-08-26T20:05:37.0297165Z * [new tag] ciflow/trunk/161106 -> ciflow/trunk/161106 2025-08-26T20:05:37.0297390Z * [new tag] ciflow/trunk/161110 -> ciflow/trunk/161110 2025-08-26T20:05:37.0297614Z * [new tag] ciflow/trunk/161114 -> ciflow/trunk/161114 2025-08-26T20:05:37.0297837Z * [new tag] ciflow/trunk/161117 -> ciflow/trunk/161117 2025-08-26T20:05:37.0298060Z * [new tag] ciflow/trunk/161123 -> ciflow/trunk/161123 2025-08-26T20:05:37.0298289Z * [new tag] ciflow/trunk/161124 -> ciflow/trunk/161124 2025-08-26T20:05:37.0298514Z * [new tag] ciflow/trunk/161126 -> ciflow/trunk/161126 2025-08-26T20:05:37.0298737Z * [new tag] ciflow/trunk/161131 -> ciflow/trunk/161131 2025-08-26T20:05:37.0298960Z * [new tag] ciflow/trunk/161143 -> ciflow/trunk/161143 2025-08-26T20:05:37.0299182Z * [new tag] ciflow/trunk/161144 -> ciflow/trunk/161144 2025-08-26T20:05:37.0299403Z * [new tag] ciflow/trunk/161164 -> ciflow/trunk/161164 2025-08-26T20:05:37.0299626Z * [new tag] ciflow/trunk/161180 -> ciflow/trunk/161180 2025-08-26T20:05:37.0301537Z * [new tag] ciflow/trunk/161214 -> ciflow/trunk/161214 2025-08-26T20:05:37.0301771Z * [new tag] ciflow/trunk/161217 -> ciflow/trunk/161217 2025-08-26T20:05:37.0301996Z * [new tag] ciflow/trunk/161225 -> ciflow/trunk/161225 2025-08-26T20:05:37.0302220Z * [new tag] ciflow/trunk/161236 -> ciflow/trunk/161236 2025-08-26T20:05:37.0302443Z * [new tag] ciflow/trunk/161237 -> ciflow/trunk/161237 2025-08-26T20:05:37.0302667Z * [new tag] ciflow/trunk/161241 -> ciflow/trunk/161241 2025-08-26T20:05:37.0302890Z * [new tag] ciflow/trunk/161262 -> ciflow/trunk/161262 2025-08-26T20:05:37.0303111Z * [new tag] ciflow/trunk/161263 -> ciflow/trunk/161263 2025-08-26T20:05:37.0303334Z * [new tag] ciflow/trunk/161279 -> ciflow/trunk/161279 2025-08-26T20:05:37.0303561Z * [new tag] ciflow/trunk/161306 -> ciflow/trunk/161306 2025-08-26T20:05:37.0303783Z * [new tag] ciflow/trunk/161311 -> ciflow/trunk/161311 2025-08-26T20:05:37.0304004Z * [new tag] ciflow/trunk/161354 -> ciflow/trunk/161354 2025-08-26T20:05:37.0304329Z * [new tag] ciflow/trunk/161355 -> ciflow/trunk/161355 2025-08-26T20:05:37.0307206Z * [new tag] ciflow/trunk/161362 -> ciflow/trunk/161362 2025-08-26T20:05:37.0307429Z * [new tag] ciflow/trunk/161363 -> ciflow/trunk/161363 2025-08-26T20:05:37.0307654Z * [new tag] ciflow/trunk/161370 -> ciflow/trunk/161370 2025-08-26T20:05:37.0307877Z * [new tag] ciflow/trunk/161383 -> ciflow/trunk/161383 2025-08-26T20:05:37.0308100Z * [new tag] ciflow/trunk/161385 -> ciflow/trunk/161385 2025-08-26T20:05:37.0308326Z * [new tag] ciflow/trunk/161389 -> ciflow/trunk/161389 2025-08-26T20:05:37.0308646Z * [new tag] ciflow/trunk/161392 -> ciflow/trunk/161392 2025-08-26T20:05:37.0308870Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-08-26T20:05:37.0309095Z * [new tag] ciflow/trunk/161396 -> ciflow/trunk/161396 2025-08-26T20:05:37.0309318Z * [new tag] ciflow/trunk/161409 -> ciflow/trunk/161409 2025-08-26T20:05:37.0309539Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-08-26T20:05:37.0309762Z * [new tag] ciflow/trunk/161435 -> ciflow/trunk/161435 2025-08-26T20:05:37.0311963Z * [new tag] ciflow/trunk/161437 -> ciflow/trunk/161437 2025-08-26T20:05:37.0312188Z * [new tag] ciflow/trunk/161451 -> ciflow/trunk/161451 2025-08-26T20:05:37.0312408Z * [new tag] ciflow/trunk/161453 -> ciflow/trunk/161453 2025-08-26T20:05:37.0312629Z * [new tag] ciflow/trunk/161454 -> ciflow/trunk/161454 2025-08-26T20:05:37.0312849Z * [new tag] ciflow/trunk/161489 -> ciflow/trunk/161489 2025-08-26T20:05:37.0313070Z * [new tag] ciflow/trunk/161517 -> ciflow/trunk/161517 2025-08-26T20:05:37.0313299Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-08-26T20:05:37.0313531Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-08-26T20:05:37.0313773Z * [new tag] ciflow/win-arm64/159562 -> ciflow/win-arm64/159562 2025-08-26T20:05:37.0314008Z * [new tag] ciflow/win-arm64/160258 -> ciflow/win-arm64/160258 2025-08-26T20:05:37.0314242Z * [new tag] ciflow/win-arm64/161504 -> ciflow/win-arm64/161504 2025-08-26T20:05:37.0314468Z * [new tag] ciflow/xpu/143553 -> ciflow/xpu/143553 2025-08-26T20:05:37.0316394Z * [new tag] ciflow/xpu/158733 -> ciflow/xpu/158733 2025-08-26T20:05:37.0316618Z * [new tag] ciflow/xpu/159473 -> ciflow/xpu/159473 2025-08-26T20:05:37.0316834Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-08-26T20:05:37.0317051Z * [new tag] ciflow/xpu/160067 -> ciflow/xpu/160067 2025-08-26T20:05:37.0317266Z * [new tag] ciflow/xpu/160158 -> ciflow/xpu/160158 2025-08-26T20:05:37.0317484Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-08-26T20:05:37.0317699Z * [new tag] ciflow/xpu/161041 -> ciflow/xpu/161041 2025-08-26T20:05:37.0317914Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-08-26T20:05:37.0318133Z * [new tag] ciflow/xpu/161142 -> ciflow/xpu/161142 2025-08-26T20:05:37.0318351Z * [new tag] ciflow/xpu/161152 -> ciflow/xpu/161152 2025-08-26T20:05:37.0318569Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-08-26T20:05:37.0318783Z * [new tag] ciflow/xpu/161389 -> ciflow/xpu/161389 2025-08-26T20:05:37.0319090Z * [new tag] ciflow/xpu/161392 -> ciflow/xpu/161392 2025-08-26T20:05:37.0321175Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-08-26T20:05:37.0321397Z * [new tag] ciflow/xpu/161477 -> ciflow/xpu/161477 2025-08-26T20:05:37.0321650Z * [new tag] ciflow/xpu/161489 -> ciflow/xpu/161489 2025-08-26T20:05:37.0321871Z * [new tag] cslpull75 -> cslpull75 2025-08-26T20:05:37.0322080Z * [new tag] cslpull76 -> cslpull76 2025-08-26T20:05:37.0322285Z * [new tag] cslpull77 -> cslpull77 2025-08-26T20:05:37.0322487Z * [new tag] cslpull78 -> cslpull78 2025-08-26T20:05:37.0322773Z * [new tag] cslpull79 -> cslpull79 2025-08-26T20:05:37.0322975Z * [new tag] cslpull80 -> cslpull80 2025-08-26T20:05:37.0323176Z * [new tag] cslpull81 -> cslpull81 2025-08-26T20:05:37.0323379Z * [new tag] cslpull82 -> cslpull82 2025-08-26T20:05:37.0323582Z * [new tag] cslpull83 -> cslpull83 2025-08-26T20:05:37.0323785Z * [new tag] cslpull84 -> cslpull84 2025-08-26T20:05:37.0325816Z * [new tag] cslpull85 -> cslpull85 2025-08-26T20:05:37.0326024Z * [new tag] cslpull86 -> cslpull86 2025-08-26T20:05:37.0326226Z * [new tag] cslpull87 -> cslpull87 2025-08-26T20:05:37.0326427Z * [new tag] cslpull88 -> cslpull88 2025-08-26T20:05:37.0326630Z * [new tag] cslpull89 -> cslpull89 2025-08-26T20:05:37.0326831Z * [new tag] cslpull90 -> cslpull90 2025-08-26T20:05:37.0327031Z * [new tag] cslpull91 -> cslpull91 2025-08-26T20:05:37.0327236Z * [new tag] cslpull92 -> cslpull92 2025-08-26T20:05:37.0327444Z * [new tag] flight_5 -> flight_5 2025-08-26T20:05:37.0327742Z * [new tag] flight_5.1 -> flight_5.1 2025-08-26T20:05:37.0327954Z * [new tag] flight_5.2 -> flight_5.2 2025-08-26T20:05:37.0328160Z * [new tag] flight_5.3 -> flight_5.3 2025-08-26T20:05:37.0330168Z * [new tag] forpull1 -> forpull1 2025-08-26T20:05:37.0330470Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-08-26T20:05:37.0330713Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-08-26T20:05:37.0330950Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-08-26T20:05:37.0331183Z * [new tag] nightly-binary -> nightly-binary 2025-08-26T20:05:37.0331423Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-08-26T20:05:37.0331657Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-08-26T20:05:37.0332008Z * [new tag] trunk/00efeabc295e072fb9d6e68b008a31fb04201fd1 -> trunk/00efeabc295e072fb9d6e68b008a31fb04201fd1 2025-08-26T20:05:37.0332464Z * [new tag] trunk/037c43d3b24d4db733011cb904c385eaa6e11bcf -> trunk/037c43d3b24d4db733011cb904c385eaa6e11bcf 2025-08-26T20:05:37.0332916Z * [new tag] trunk/0533ff2ccba7e77622ac3c6758f1032bdc10feff -> trunk/0533ff2ccba7e77622ac3c6758f1032bdc10feff 2025-08-26T20:05:37.0333374Z * [new tag] trunk/05e8fac4f374c4dbf0cd0e85e925e9112cf234a2 -> trunk/05e8fac4f374c4dbf0cd0e85e925e9112cf234a2 2025-08-26T20:05:37.0333831Z * [new tag] trunk/089ad1d88bf31ddab769a4f87750b474ed1214c8 -> trunk/089ad1d88bf31ddab769a4f87750b474ed1214c8 2025-08-26T20:05:37.0336147Z * [new tag] trunk/0924304e728b9507a54eced28c812fbd5b13c397 -> trunk/0924304e728b9507a54eced28c812fbd5b13c397 2025-08-26T20:05:37.0336612Z * [new tag] trunk/0a5ab612dd2b9fc5bb2e1281ec7ca8730c5c3c89 -> trunk/0a5ab612dd2b9fc5bb2e1281ec7ca8730c5c3c89 2025-08-26T20:05:37.0337060Z * [new tag] trunk/0d19541284c38212235f78db24e3ac3ae4787e45 -> trunk/0d19541284c38212235f78db24e3ac3ae4787e45 2025-08-26T20:05:37.0337506Z * [new tag] trunk/0d9da384ef76e3ce2e7eaf951252ae9edb922863 -> trunk/0d9da384ef76e3ce2e7eaf951252ae9edb922863 2025-08-26T20:05:37.0337959Z * [new tag] trunk/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 -> trunk/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 2025-08-26T20:05:37.0338490Z * [new tag] trunk/0f801a510f5f185543388717241adb7237c3d46a -> trunk/0f801a510f5f185543388717241adb7237c3d46a 2025-08-26T20:05:37.0338693Z * [new tag] trunk/10e67f5ec3834da93fc2022caa7ac69cf97c01f0 -> trunk/10e67f5ec3834da93fc2022caa7ac69cf97c01f0 2025-08-26T20:05:37.0338892Z * [new tag] trunk/1113e7de30da95973c1eac7921601f9a0e94f2db -> trunk/1113e7de30da95973c1eac7921601f9a0e94f2db 2025-08-26T20:05:37.0339089Z * [new tag] trunk/117f11adb4b41a5485b570c4337c22ecc8e00aeb -> trunk/117f11adb4b41a5485b570c4337c22ecc8e00aeb 2025-08-26T20:05:37.0339283Z * [new tag] trunk/1471b20cb3fc502931ef12b1420414e32facd5b0 -> trunk/1471b20cb3fc502931ef12b1420414e32facd5b0 2025-08-26T20:05:37.0339478Z * [new tag] trunk/16e811e0b5073c7b42fe76f650ca2b79e339e053 -> trunk/16e811e0b5073c7b42fe76f650ca2b79e339e053 2025-08-26T20:05:37.0339676Z * [new tag] trunk/17b0263e86aec8aed068bb8b6744b129233e8084 -> trunk/17b0263e86aec8aed068bb8b6744b129233e8084 2025-08-26T20:05:37.0339871Z * [new tag] trunk/18271148d32da3d48897e9e7515de45066fce5bc -> trunk/18271148d32da3d48897e9e7515de45066fce5bc 2025-08-26T20:05:37.0340069Z * [new tag] trunk/19c70c2f3dc345a6555318f5f8b46cd55c42d0b4 -> trunk/19c70c2f3dc345a6555318f5f8b46cd55c42d0b4 2025-08-26T20:05:37.0340270Z * [new tag] trunk/1a566c4909ccf16ace1fbf1f65d90c995b362712 -> trunk/1a566c4909ccf16ace1fbf1f65d90c995b362712 2025-08-26T20:05:37.0340581Z * [new tag] trunk/1d458e294755ff2bfa314c67ddc5cb1dacc2aee8 -> trunk/1d458e294755ff2bfa314c67ddc5cb1dacc2aee8 2025-08-26T20:05:37.0340782Z * [new tag] trunk/1d46aa736fc8870dc88015c729a8c64470fa985c -> trunk/1d46aa736fc8870dc88015c729a8c64470fa985c 2025-08-26T20:05:37.0340981Z * [new tag] trunk/1de4540449ad6b9df8f452ab72da30ce8908af60 -> trunk/1de4540449ad6b9df8f452ab72da30ce8908af60 2025-08-26T20:05:37.0341175Z * [new tag] trunk/1e3fe78a104776cd708f150116348540346dae25 -> trunk/1e3fe78a104776cd708f150116348540346dae25 2025-08-26T20:05:37.0343180Z * [new tag] trunk/1ea918caf990c84bcb4e4ee5eee90f1102815b0a -> trunk/1ea918caf990c84bcb4e4ee5eee90f1102815b0a 2025-08-26T20:05:37.0343392Z * [new tag] trunk/1eccfb157ab9855b3f81872a23502fb15f455e0a -> trunk/1eccfb157ab9855b3f81872a23502fb15f455e0a 2025-08-26T20:05:37.0343597Z * [new tag] trunk/1fbe230b0d82251c6de8b5ae86c4da456b1db05c -> trunk/1fbe230b0d82251c6de8b5ae86c4da456b1db05c 2025-08-26T20:05:37.0343794Z * [new tag] trunk/209143ddeb99b0b075d16525088cee4893be7492 -> trunk/209143ddeb99b0b075d16525088cee4893be7492 2025-08-26T20:05:37.0343994Z * [new tag] trunk/22df59efc0a845b3ff37019029efd07c5a25c456 -> trunk/22df59efc0a845b3ff37019029efd07c5a25c456 2025-08-26T20:05:37.0344186Z * [new tag] trunk/23b033452fb1d4b404216279bbf5b6d06d8570c3 -> trunk/23b033452fb1d4b404216279bbf5b6d06d8570c3 2025-08-26T20:05:37.0344390Z * [new tag] trunk/24e7f3c21c9452c81d72bbd4b0c6b1f96f33536a -> trunk/24e7f3c21c9452c81d72bbd4b0c6b1f96f33536a 2025-08-26T20:05:37.0344751Z * [new tag] trunk/25df65afd8b5e2fffbcaf2b7ed63ef7a1e37ecb9 -> trunk/25df65afd8b5e2fffbcaf2b7ed63ef7a1e37ecb9 2025-08-26T20:05:37.0344942Z * [new tag] trunk/262640fd220236042fbf4443cc163c8838c84c3d -> trunk/262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:05:37.0345136Z * [new tag] trunk/266784ec6ae82f823abe406582e7a91f2ebb564a -> trunk/266784ec6ae82f823abe406582e7a91f2ebb564a 2025-08-26T20:05:37.0345340Z * [new tag] trunk/2835cc5e91eda8cbc4ac59de2ca990fa17107409 -> trunk/2835cc5e91eda8cbc4ac59de2ca990fa17107409 2025-08-26T20:05:37.0345532Z * [new tag] trunk/284b7190054686e68d9cc683b6ce43e45dd22338 -> trunk/284b7190054686e68d9cc683b6ce43e45dd22338 2025-08-26T20:05:37.0345726Z * [new tag] trunk/29afde20203ee6773641b4e3552942a37315316f -> trunk/29afde20203ee6773641b4e3552942a37315316f 2025-08-26T20:05:37.0346008Z * [new tag] trunk/2a7a7ad7116d930fde86cda02f668e624d26ec3e -> trunk/2a7a7ad7116d930fde86cda02f668e624d26ec3e 2025-08-26T20:05:37.0346206Z * [new tag] trunk/2b62ef74208792c7c4bf923f872e54b5f384efc8 -> trunk/2b62ef74208792c7c4bf923f872e54b5f384efc8 2025-08-26T20:05:37.0346404Z * [new tag] trunk/2beffb3311a41589021c121dac543994a7cbdff2 -> trunk/2beffb3311a41589021c121dac543994a7cbdff2 2025-08-26T20:05:37.0346605Z * [new tag] trunk/2c0650a00a0a0dd2bbf25ed22780fdd881bcda54 -> trunk/2c0650a00a0a0dd2bbf25ed22780fdd881bcda54 2025-08-26T20:05:37.0346808Z * [new tag] trunk/2cf69fe0e1bdb1413fe9e802c4b84d8958708421 -> trunk/2cf69fe0e1bdb1413fe9e802c4b84d8958708421 2025-08-26T20:05:37.0347012Z * [new tag] trunk/2cf7ac2fb7ab4067e17cc5ca71034b1c61a4fb10 -> trunk/2cf7ac2fb7ab4067e17cc5ca71034b1c61a4fb10 2025-08-26T20:05:37.0347212Z * [new tag] trunk/2f0cba934de7094a66c6ce68f5e937254f23142a -> trunk/2f0cba934de7094a66c6ce68f5e937254f23142a 2025-08-26T20:05:37.0347418Z * [new tag] trunk/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 -> trunk/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 2025-08-26T20:05:37.0347616Z * [new tag] trunk/2f50ae7d2022cb096c4156f5a207c291e36ddecf -> trunk/2f50ae7d2022cb096c4156f5a207c291e36ddecf 2025-08-26T20:05:37.0347816Z * [new tag] trunk/2fdd4f918cdc5fc8070e4c9c0d87b9045d316c06 -> trunk/2fdd4f918cdc5fc8070e4c9c0d87b9045d316c06 2025-08-26T20:05:37.0348014Z * [new tag] trunk/30384abcb1d181e774c0ac21b580aa34336a96c6 -> trunk/30384abcb1d181e774c0ac21b580aa34336a96c6 2025-08-26T20:05:37.0349909Z * [new tag] trunk/31a41daff49f2cde941d8b9e35cb2eaeeb606c0d -> trunk/31a41daff49f2cde941d8b9e35cb2eaeeb606c0d 2025-08-26T20:05:37.0350109Z * [new tag] trunk/332fa5b388521c05a19217649745c6edfdc2836d -> trunk/332fa5b388521c05a19217649745c6edfdc2836d 2025-08-26T20:05:37.0350298Z * [new tag] trunk/33346b58148c55592994a43385c321ae8c8808f2 -> trunk/33346b58148c55592994a43385c321ae8c8808f2 2025-08-26T20:05:37.0350583Z * [new tag] trunk/3373b074f5ea5277974fa6e945544fdfb16bb446 -> trunk/3373b074f5ea5277974fa6e945544fdfb16bb446 2025-08-26T20:05:37.0350771Z * [new tag] trunk/33c3794533844236a6e30ba377e0a6802b279fc8 -> trunk/33c3794533844236a6e30ba377e0a6802b279fc8 2025-08-26T20:05:37.0350969Z * [new tag] trunk/35e4d97e047bff8b38fee1dcf6ef6503f0fc9208 -> trunk/35e4d97e047bff8b38fee1dcf6ef6503f0fc9208 2025-08-26T20:05:37.0351154Z * [new tag] trunk/36ac916929ca67b533cc45932970297e9824324e -> trunk/36ac916929ca67b533cc45932970297e9824324e 2025-08-26T20:05:37.0351351Z * [new tag] trunk/371909cfd10e0da1bab1e12fb54a2403c37c5f76 -> trunk/371909cfd10e0da1bab1e12fb54a2403c37c5f76 2025-08-26T20:05:37.0351542Z * [new tag] trunk/373e25c2eb9f882356a9c7a2f18020935ff1d78b -> trunk/373e25c2eb9f882356a9c7a2f18020935ff1d78b 2025-08-26T20:05:37.0351734Z * [new tag] trunk/37a34022b59a6ff2757e5cec0fdc72278418f339 -> trunk/37a34022b59a6ff2757e5cec0fdc72278418f339 2025-08-26T20:05:37.0352027Z * [new tag] trunk/38a492d40d7ebb2856cb120df337c6cdac244528 -> trunk/38a492d40d7ebb2856cb120df337c6cdac244528 2025-08-26T20:05:37.0352221Z * [new tag] trunk/394728bab2de21e8002fc6a47aa4d3acb2d7a728 -> trunk/394728bab2de21e8002fc6a47aa4d3acb2d7a728 2025-08-26T20:05:37.0352416Z * [new tag] trunk/39862acb2e320783245d2a03acfd1b14cae28038 -> trunk/39862acb2e320783245d2a03acfd1b14cae28038 2025-08-26T20:05:37.0352647Z * [new tag] trunk/3a4140bf8e783db3f0094d2a2ce1d8534066432f -> trunk/3a4140bf8e783db3f0094d2a2ce1d8534066432f 2025-08-26T20:05:37.0352844Z * [new tag] trunk/3caddd4daa5b1a167663c07219e065e86247ad76 -> trunk/3caddd4daa5b1a167663c07219e065e86247ad76 2025-08-26T20:05:37.0353228Z * [new tag] trunk/3dacaf0e1eb3286e70bf8d572000ecebf2c1f4c9 -> trunk/3dacaf0e1eb3286e70bf8d572000ecebf2c1f4c9 2025-08-26T20:05:37.0353434Z * [new tag] trunk/3e210f90c2cbd5817aa23d430da10cad200a3ffa -> trunk/3e210f90c2cbd5817aa23d430da10cad200a3ffa 2025-08-26T20:05:37.0353627Z * [new tag] trunk/3e3e83418d0f6b1495f79380f3a3dbc8b2d23062 -> trunk/3e3e83418d0f6b1495f79380f3a3dbc8b2d23062 2025-08-26T20:05:37.0353819Z * [new tag] trunk/3e5b021f217a42ae55dc690083f67a28126808ed -> trunk/3e5b021f217a42ae55dc690083f67a28126808ed 2025-08-26T20:05:37.0354013Z * [new tag] trunk/3ea6cc8c2d443d6104159d50e8328c144f6caa39 -> trunk/3ea6cc8c2d443d6104159d50e8328c144f6caa39 2025-08-26T20:05:37.0354207Z * [new tag] trunk/3f1a97a99cad4cc682b20b43c1178ed9e1b81f24 -> trunk/3f1a97a99cad4cc682b20b43c1178ed9e1b81f24 2025-08-26T20:05:37.0354402Z * [new tag] trunk/3f5a8e2003f2234ca8be19fdc307ba7b995f9be3 -> trunk/3f5a8e2003f2234ca8be19fdc307ba7b995f9be3 2025-08-26T20:05:37.0354595Z * [new tag] trunk/40c0e700a488191cd8f541b30d8e3b9f2c0bc759 -> trunk/40c0e700a488191cd8f541b30d8e3b9f2c0bc759 2025-08-26T20:05:37.0354790Z * [new tag] trunk/419a2dbf5f69cee52382090200b532a81da92c69 -> trunk/419a2dbf5f69cee52382090200b532a81da92c69 2025-08-26T20:05:37.0356775Z * [new tag] trunk/431846a6323c6f1d02da49e311ac694324f386f4 -> trunk/431846a6323c6f1d02da49e311ac694324f386f4 2025-08-26T20:05:37.0356975Z * [new tag] trunk/44549c7146bd6c4166f97e856037babe1b7f4f49 -> trunk/44549c7146bd6c4166f97e856037babe1b7f4f49 2025-08-26T20:05:37.0357175Z * [new tag] trunk/447d34b5f80fb7350f79decd855cb599cab39083 -> trunk/447d34b5f80fb7350f79decd855cb599cab39083 2025-08-26T20:05:37.0357360Z * [new tag] trunk/46429be72323c1807a785234164bd91011f68d08 -> trunk/46429be72323c1807a785234164bd91011f68d08 2025-08-26T20:05:37.0357562Z * [new tag] trunk/4651aaac47ff855e08a74e2fdbfa605bc53afba8 -> trunk/4651aaac47ff855e08a74e2fdbfa605bc53afba8 2025-08-26T20:05:37.0357759Z * [new tag] trunk/46576f5a164fcf95ec7fceaa13516bcb1ca4f6ab -> trunk/46576f5a164fcf95ec7fceaa13516bcb1ca4f6ab 2025-08-26T20:05:37.0357956Z * [new tag] trunk/47d267364cad407b5612bf4a5faa160d2f4a7121 -> trunk/47d267364cad407b5612bf4a5faa160d2f4a7121 2025-08-26T20:05:37.0358154Z * [new tag] trunk/49ff884b1edc3b872eeb2387ec60ef230cae7f24 -> trunk/49ff884b1edc3b872eeb2387ec60ef230cae7f24 2025-08-26T20:05:37.0358353Z * [new tag] trunk/4a1aca11c20cfa29a1513b9f289d75bfe32d05d4 -> trunk/4a1aca11c20cfa29a1513b9f289d75bfe32d05d4 2025-08-26T20:05:37.0358551Z * [new tag] trunk/4acdbb8311f760513556e2e4fdd7bfd88c225e52 -> trunk/4acdbb8311f760513556e2e4fdd7bfd88c225e52 2025-08-26T20:05:37.0358740Z * [new tag] trunk/4c36c8a99463c898190a462300ba7f05b5b3384e -> trunk/4c36c8a99463c898190a462300ba7f05b5b3384e 2025-08-26T20:05:37.0358928Z * [new tag] trunk/4e19c1906a830714c1d9d71361357ce616a034d6 -> trunk/4e19c1906a830714c1d9d71361357ce616a034d6 2025-08-26T20:05:37.0359182Z * [new tag] trunk/4ed3184dee1bf4f775839bfd1448a7a34fe5a898 -> trunk/4ed3184dee1bf4f775839bfd1448a7a34fe5a898 2025-08-26T20:05:37.0359375Z * [new tag] trunk/50cfe76231768ee2c784f68a1eba03369f386019 -> trunk/50cfe76231768ee2c784f68a1eba03369f386019 2025-08-26T20:05:37.0359572Z * [new tag] trunk/510825e5fed8b56eb5e9352c12f0df1feeadb810 -> trunk/510825e5fed8b56eb5e9352c12f0df1feeadb810 2025-08-26T20:05:37.0359769Z * [new tag] trunk/512fc768e94c937df350911aaa4ebce757d1f9df -> trunk/512fc768e94c937df350911aaa4ebce757d1f9df 2025-08-26T20:05:37.0359963Z * [new tag] trunk/517d38d3406abbba35d0694bff259a698cad3ec9 -> trunk/517d38d3406abbba35d0694bff259a698cad3ec9 2025-08-26T20:05:37.0360209Z * [new tag] trunk/5255e65c01bf48bbcd916ecf16ed81cf28d3c6e2 -> trunk/5255e65c01bf48bbcd916ecf16ed81cf28d3c6e2 2025-08-26T20:05:37.0360573Z * [new tag] trunk/543896fcf3312f2053018edf9ee74c0fbb1d28ed -> trunk/543896fcf3312f2053018edf9ee74c0fbb1d28ed 2025-08-26T20:05:37.0360776Z * [new tag] trunk/54c2b66592d168e4a7525f7a58f8ca020517a9cb -> trunk/54c2b66592d168e4a7525f7a58f8ca020517a9cb 2025-08-26T20:05:37.0360969Z * [new tag] trunk/54cc63b467f24242cf0d6538d3e1df39e553daf1 -> trunk/54cc63b467f24242cf0d6538d3e1df39e553daf1 2025-08-26T20:05:37.0361167Z * [new tag] trunk/56ebed627a23eea36190e1ced5024a18ffcedbd7 -> trunk/56ebed627a23eea36190e1ced5024a18ffcedbd7 2025-08-26T20:05:37.0361367Z * [new tag] trunk/576a0e64ed2470abd2c430205d1984a11951ce05 -> trunk/576a0e64ed2470abd2c430205d1984a11951ce05 2025-08-26T20:05:37.0361557Z * [new tag] trunk/5805c4210b477f0a7315d6038078dc4a8be1c8fa -> trunk/5805c4210b477f0a7315d6038078dc4a8be1c8fa 2025-08-26T20:05:37.0363566Z * [new tag] trunk/58f9a3dd6391397e439c5f5075837e8f983735aa -> trunk/58f9a3dd6391397e439c5f5075837e8f983735aa 2025-08-26T20:05:37.0363760Z * [new tag] trunk/595987d28d4c8aee68de83734af919c7710ad58b -> trunk/595987d28d4c8aee68de83734af919c7710ad58b 2025-08-26T20:05:37.0363954Z * [new tag] trunk/599f639ddb8bb45abb2dc305542f38288427183d -> trunk/599f639ddb8bb45abb2dc305542f38288427183d 2025-08-26T20:05:37.0364147Z * [new tag] trunk/5afa4187dfe1e99278f8e372ec09102d5b937572 -> trunk/5afa4187dfe1e99278f8e372ec09102d5b937572 2025-08-26T20:05:37.0364340Z * [new tag] trunk/5d9653d90ee003173dd03f93e09fed236500ef06 -> trunk/5d9653d90ee003173dd03f93e09fed236500ef06 2025-08-26T20:05:37.0364539Z * [new tag] trunk/5dad5b4f57ade4001c0f421dbdad2e418304870e -> trunk/5dad5b4f57ade4001c0f421dbdad2e418304870e 2025-08-26T20:05:37.0364730Z * [new tag] trunk/5ee464db5c4293ac09521f9069fa7d2106680a7f -> trunk/5ee464db5c4293ac09521f9069fa7d2106680a7f 2025-08-26T20:05:37.0364919Z * [new tag] trunk/6096d277c543f5dd40351431ef9a8d556134c74d -> trunk/6096d277c543f5dd40351431ef9a8d556134c74d 2025-08-26T20:05:37.0365111Z * [new tag] trunk/62db8ec39116544ae247f876b3e06753178db49b -> trunk/62db8ec39116544ae247f876b3e06753178db49b 2025-08-26T20:05:37.0365304Z * [new tag] trunk/639b8cc51ddebf10361f3840a6b0a244eb6092a1 -> trunk/639b8cc51ddebf10361f3840a6b0a244eb6092a1 2025-08-26T20:05:37.0365494Z * [new tag] trunk/6443ea337df843681bc558d99efa84a3e5559b7f -> trunk/6443ea337df843681bc558d99efa84a3e5559b7f 2025-08-26T20:05:37.0365686Z * [new tag] trunk/6598f00c18dfcc4fc50427305b6b5724e617246f -> trunk/6598f00c18dfcc4fc50427305b6b5724e617246f 2025-08-26T20:05:37.0365882Z * [new tag] trunk/65d21dae18a34e8bd1b2f0e5aec7144b9dd33611 -> trunk/65d21dae18a34e8bd1b2f0e5aec7144b9dd33611 2025-08-26T20:05:37.0366076Z * [new tag] trunk/660b5656a436dcccb0275ea5421d3eb4f1157b43 -> trunk/660b5656a436dcccb0275ea5421d3eb4f1157b43 2025-08-26T20:05:37.0366271Z * [new tag] trunk/66166cf1e7696bf25f6f7bb815a93df367db48dc -> trunk/66166cf1e7696bf25f6f7bb815a93df367db48dc 2025-08-26T20:05:37.0366569Z * [new tag] trunk/667245dc60242a35ae0a6b0072628eb8e15a6d03 -> trunk/667245dc60242a35ae0a6b0072628eb8e15a6d03 2025-08-26T20:05:37.0366759Z * [new tag] trunk/67b98da1b262317f9c0375d64a4b467c82712548 -> trunk/67b98da1b262317f9c0375d64a4b467c82712548 2025-08-26T20:05:37.0366952Z * [new tag] trunk/67d31f6b281d3b15b205756fc7ebc450cdde1dab -> trunk/67d31f6b281d3b15b205756fc7ebc450cdde1dab 2025-08-26T20:05:37.0367148Z * [new tag] trunk/67fc16c7447f4fc04e7d28bfe201a4a0c78f3ea4 -> trunk/67fc16c7447f4fc04e7d28bfe201a4a0c78f3ea4 2025-08-26T20:05:37.0367339Z * [new tag] trunk/6aef9f3a6906c011a57541c1de7a246222bc9ac9 -> trunk/6aef9f3a6906c011a57541c1de7a246222bc9ac9 2025-08-26T20:05:37.0367624Z * [new tag] trunk/6ea4be1e2eca952ea66090182bd2eede89799a45 -> trunk/6ea4be1e2eca952ea66090182bd2eede89799a45 2025-08-26T20:05:37.0367948Z * [new tag] trunk/7006fd0c8874cb0228d3f2bfd83a989bde4b7021 -> trunk/7006fd0c8874cb0228d3f2bfd83a989bde4b7021 2025-08-26T20:05:37.0368143Z * [new tag] trunk/710514a2a51facaba445d2c188541d778f9fdb59 -> trunk/710514a2a51facaba445d2c188541d778f9fdb59 2025-08-26T20:05:37.0370100Z * [new tag] trunk/7131bfab89c46ffe31b61ea4937a8727e9cf33c1 -> trunk/7131bfab89c46ffe31b61ea4937a8727e9cf33c1 2025-08-26T20:05:37.0370324Z * [new tag] trunk/726dce3c944cbda16e54d3b15cdb4b6ced05af72 -> trunk/726dce3c944cbda16e54d3b15cdb4b6ced05af72 2025-08-26T20:05:37.0370592Z * [new tag] trunk/72e4786d1635681b8d053d0168c7d16b980e5124 -> trunk/72e4786d1635681b8d053d0168c7d16b980e5124 2025-08-26T20:05:37.0370782Z * [new tag] trunk/7376111d59f3170c2814d565c09d09435189692a -> trunk/7376111d59f3170c2814d565c09d09435189692a 2025-08-26T20:05:37.0370975Z * [new tag] trunk/74124d1b46774f2a73aa1aadc2b0874cb523b1c1 -> trunk/74124d1b46774f2a73aa1aadc2b0874cb523b1c1 2025-08-26T20:05:37.0371165Z * [new tag] trunk/74280d091321343b47a2975e17584b973d7c22c4 -> trunk/74280d091321343b47a2975e17584b973d7c22c4 2025-08-26T20:05:37.0371362Z * [new tag] trunk/74c4c758afa8c28162f00a456c185552e1159fd3 -> trunk/74c4c758afa8c28162f00a456c185552e1159fd3 2025-08-26T20:05:37.0371552Z * [new tag] trunk/763053dc536341997641e920d8887b3010901b3b -> trunk/763053dc536341997641e920d8887b3010901b3b 2025-08-26T20:05:37.0371741Z * [new tag] trunk/774b4befa18741b3115802cae71000168a40c384 -> trunk/774b4befa18741b3115802cae71000168a40c384 2025-08-26T20:05:37.0371945Z * [new tag] trunk/77bc959fe122bfd131e339ca36cab445a1860806 -> trunk/77bc959fe122bfd131e339ca36cab445a1860806 2025-08-26T20:05:37.0372138Z * [new tag] trunk/78a8e6a671c5631bc0e89b0e674790a424540547 -> trunk/78a8e6a671c5631bc0e89b0e674790a424540547 2025-08-26T20:05:37.0372336Z * [new tag] trunk/7e4bfa74eafab994b01f8b5501d4d061cbf64808 -> trunk/7e4bfa74eafab994b01f8b5501d4d061cbf64808 2025-08-26T20:05:37.0372531Z * [new tag] trunk/7e6ce41555d595e3fa0d91059491f21cee3eb5ea -> trunk/7e6ce41555d595e3fa0d91059491f21cee3eb5ea 2025-08-26T20:05:37.0372720Z * [new tag] trunk/7f201baf414301b3312576893b7f6f2698acd9ba -> trunk/7f201baf414301b3312576893b7f6f2698acd9ba 2025-08-26T20:05:37.0372921Z * [new tag] trunk/7fcdd8d6afeda6a4c8630816e12bf7cca44b8f8a -> trunk/7fcdd8d6afeda6a4c8630816e12bf7cca44b8f8a 2025-08-26T20:05:37.0373106Z * [new tag] trunk/801851086d09506d081800108c9e214edb3f5b7d -> trunk/801851086d09506d081800108c9e214edb3f5b7d 2025-08-26T20:05:37.0373298Z * [new tag] trunk/8047cde0f3a27f3afa218792b8464d5e0c9d942f -> trunk/8047cde0f3a27f3afa218792b8464d5e0c9d942f 2025-08-26T20:05:37.0373495Z * [new tag] trunk/80df27a612be3433516d7e6dfc8d8be058425d3e -> trunk/80df27a612be3433516d7e6dfc8d8be058425d3e 2025-08-26T20:05:37.0373799Z * [new tag] trunk/818ba434c7de4cd604184b2857d544e0ad95735f -> trunk/818ba434c7de4cd604184b2857d544e0ad95735f 2025-08-26T20:05:37.0373994Z * [new tag] trunk/83283ce7f5a7847b4e561e22be9b0f4530b05527 -> trunk/83283ce7f5a7847b4e561e22be9b0f4530b05527 2025-08-26T20:05:37.0374186Z * [new tag] trunk/85adf80cf15538a7e010fa235036fe8e06f8bede -> trunk/85adf80cf15538a7e010fa235036fe8e06f8bede 2025-08-26T20:05:37.0374391Z * [new tag] trunk/8aad3a60ce16a4acab17a8e46e5df339db2ff740 -> trunk/8aad3a60ce16a4acab17a8e46e5df339db2ff740 2025-08-26T20:05:37.0374578Z * [new tag] trunk/8c442e4fd3310e15f57770944f883ac1d73e77e2 -> trunk/8c442e4fd3310e15f57770944f883ac1d73e77e2 2025-08-26T20:05:37.0374842Z * [new tag] trunk/8c506e6310b9b5295151fb725be479d0f80ce5e8 -> trunk/8c506e6310b9b5295151fb725be479d0f80ce5e8 2025-08-26T20:05:37.0376859Z * [new tag] trunk/8cfc119491f533c4edded4263a78eb0af782a2d5 -> trunk/8cfc119491f533c4edded4263a78eb0af782a2d5 2025-08-26T20:05:37.0377113Z * [new tag] trunk/8dbe7f99bd707ee28ae12ecb9cab54e1785bf13e -> trunk/8dbe7f99bd707ee28ae12ecb9cab54e1785bf13e 2025-08-26T20:05:37.0377312Z * [new tag] trunk/8e1770905565cd67d6c3a91c7afa462f4ef6e6aa -> trunk/8e1770905565cd67d6c3a91c7afa462f4ef6e6aa 2025-08-26T20:05:37.0377570Z * [new tag] trunk/8f31aa97a3e1e17bed29b6cedf9884f0c6b145e9 -> trunk/8f31aa97a3e1e17bed29b6cedf9884f0c6b145e9 2025-08-26T20:05:37.0377770Z * [new tag] trunk/8f766d68397736053883aa281cae0eb46bb233bb -> trunk/8f766d68397736053883aa281cae0eb46bb233bb 2025-08-26T20:05:37.0377967Z * [new tag] trunk/908b0ccb1f70ed2cfa830484e05ee32af13b1836 -> trunk/908b0ccb1f70ed2cfa830484e05ee32af13b1836 2025-08-26T20:05:37.0378172Z * [new tag] trunk/90ea9ccefe3e2d9a9e4840016d1af10c1814d48b -> trunk/90ea9ccefe3e2d9a9e4840016d1af10c1814d48b 2025-08-26T20:05:37.0378377Z * [new tag] trunk/9225c6199412f8a2ee99b7c29f533fb98b9ff62e -> trunk/9225c6199412f8a2ee99b7c29f533fb98b9ff62e 2025-08-26T20:05:37.0378566Z * [new tag] trunk/923bc46122d173a7964c646311a3bea3cd8dd561 -> trunk/923bc46122d173a7964c646311a3bea3cd8dd561 2025-08-26T20:05:37.0378758Z * [new tag] trunk/92ab18482459a63e97f1374e27e8411964da9762 -> trunk/92ab18482459a63e97f1374e27e8411964da9762 2025-08-26T20:05:37.0378951Z * [new tag] trunk/94b9569c4a86e12b944ca66e3125357a14d0eb9e -> trunk/94b9569c4a86e12b944ca66e3125357a14d0eb9e 2025-08-26T20:05:37.0379152Z * [new tag] trunk/957b170d8efe2a51147e0cdb7515acc345ba81da -> trunk/957b170d8efe2a51147e0cdb7515acc345ba81da 2025-08-26T20:05:37.0379374Z * [new tag] trunk/958f9ca88e9a1580de7c94a5a2ca8a750b1335ae -> trunk/958f9ca88e9a1580de7c94a5a2ca8a750b1335ae 2025-08-26T20:05:37.0379564Z * [new tag] trunk/96682103026b5ea27f19e6db9303e17572095b0e -> trunk/96682103026b5ea27f19e6db9303e17572095b0e 2025-08-26T20:05:37.0379773Z * [new tag] trunk/97200c971110d54030feaad999698c7341f8acc7 -> trunk/97200c971110d54030feaad999698c7341f8acc7 2025-08-26T20:05:37.0379975Z * [new tag] trunk/981ac533c6e69a77538aaa7a9747c3d840dfa8be -> trunk/981ac533c6e69a77538aaa7a9747c3d840dfa8be 2025-08-26T20:05:37.0380165Z * [new tag] trunk/995397d47a0e27394ee1010f158e181eb304100a -> trunk/995397d47a0e27394ee1010f158e181eb304100a 2025-08-26T20:05:37.0380434Z * [new tag] trunk/9a41570199155eee92ebd28452a556075e34e1b4 -> trunk/9a41570199155eee92ebd28452a556075e34e1b4 2025-08-26T20:05:37.0380635Z * [new tag] trunk/9b3ebd25acfd2ff4e9b7428079ba364d6f8a14da -> trunk/9b3ebd25acfd2ff4e9b7428079ba364d6f8a14da 2025-08-26T20:05:37.0380842Z * [new tag] trunk/9b4adc4db7494dbc4dbbac5dd85ccbf5babaef44 -> trunk/9b4adc4db7494dbc4dbbac5dd85ccbf5babaef44 2025-08-26T20:05:37.0381035Z * [new tag] trunk/9d18bf01b1661d227f6af41ac07a1e9ef20a9e1a -> trunk/9d18bf01b1661d227f6af41ac07a1e9ef20a9e1a 2025-08-26T20:05:37.0381330Z * [new tag] trunk/9d7cecdd6c44c5421d341bcc359be4097ea9a2f5 -> trunk/9d7cecdd6c44c5421d341bcc359be4097ea9a2f5 2025-08-26T20:05:37.0381528Z * [new tag] trunk/9d882fd9ffc6ad2a292fee548740aabfea745002 -> trunk/9d882fd9ffc6ad2a292fee548740aabfea745002 2025-08-26T20:05:37.0381733Z * [new tag] trunk/9d9cc9897ac44a1a8df38211b03d8342a8af48c3 -> trunk/9d9cc9897ac44a1a8df38211b03d8342a8af48c3 2025-08-26T20:05:37.0383708Z * [new tag] trunk/9e1c9541344b2aa1c946edb779d275072f3b8f4a -> trunk/9e1c9541344b2aa1c946edb779d275072f3b8f4a 2025-08-26T20:05:37.0383918Z * [new tag] trunk/9e491f753ee521a70e6a7e7dbb36f96c9350f5ea -> trunk/9e491f753ee521a70e6a7e7dbb36f96c9350f5ea 2025-08-26T20:05:37.0384197Z * [new tag] trunk/a03cc53e6f6e2fe67316cb8c74c25f5b953f445b -> trunk/a03cc53e6f6e2fe67316cb8c74c25f5b953f445b 2025-08-26T20:05:37.0384385Z * [new tag] trunk/a154c2093c0f2646346f032e1f30012779b3c51d -> trunk/a154c2093c0f2646346f032e1f30012779b3c51d 2025-08-26T20:05:37.0384582Z * [new tag] trunk/a391fa1c42dd32e32a2e5b1cb196bac56daaca88 -> trunk/a391fa1c42dd32e32a2e5b1cb196bac56daaca88 2025-08-26T20:05:37.0384781Z * [new tag] trunk/a3a82e3da85a53afc4bbf3d75bd3d3dcc2e06645 -> trunk/a3a82e3da85a53afc4bbf3d75bd3d3dcc2e06645 2025-08-26T20:05:37.0384978Z * [new tag] trunk/a3fe1ced409d186628ff2975f05ba529a86fae84 -> trunk/a3fe1ced409d186628ff2975f05ba529a86fae84 2025-08-26T20:05:37.0385167Z * [new tag] trunk/a43480d19cdd68e544163b1a07c328a9c54723b8 -> trunk/a43480d19cdd68e544163b1a07c328a9c54723b8 2025-08-26T20:05:37.0385373Z * [new tag] trunk/a445b41e4f11daa82a53a21ec413c15d5079ae77 -> trunk/a445b41e4f11daa82a53a21ec413c15d5079ae77 2025-08-26T20:05:37.0385576Z * [new tag] trunk/a44a0d3671b4ccf2fe915896a8a5204fe79b1e7b -> trunk/a44a0d3671b4ccf2fe915896a8a5204fe79b1e7b 2025-08-26T20:05:37.0385771Z * [new tag] trunk/a6401cb5aa51622045c3f9a03b2cebef236e4182 -> trunk/a6401cb5aa51622045c3f9a03b2cebef236e4182 2025-08-26T20:05:37.0385959Z * [new tag] trunk/a68f63e33161b4665e0f4c399bf8072135a35a57 -> trunk/a68f63e33161b4665e0f4c399bf8072135a35a57 2025-08-26T20:05:37.0386160Z * [new tag] trunk/a72803f1e3c69c780b7d7bcdd9b35360fd98148b -> trunk/a72803f1e3c69c780b7d7bcdd9b35360fd98148b 2025-08-26T20:05:37.0386353Z * [new tag] trunk/a7b5955ea8851d73e35f50a0de5bb0626bae24cb -> trunk/a7b5955ea8851d73e35f50a0de5bb0626bae24cb 2025-08-26T20:05:37.0386539Z * [new tag] trunk/a818fa77e3a72271f144514ef349c5a666313205 -> trunk/a818fa77e3a72271f144514ef349c5a666313205 2025-08-26T20:05:37.0386728Z * [new tag] trunk/a825557ed53507e85ac613862311a81eb88710a4 -> trunk/a825557ed53507e85ac613862311a81eb88710a4 2025-08-26T20:05:37.0386922Z * [new tag] trunk/a85711d565f37b0095af9f7dafa77f392c9aa31e -> trunk/a85711d565f37b0095af9f7dafa77f392c9aa31e 2025-08-26T20:05:37.0387119Z * [new tag] trunk/a941d7ffe54b5f256c1fbd3959ddbf608b7eea88 -> trunk/a941d7ffe54b5f256c1fbd3959ddbf608b7eea88 2025-08-26T20:05:37.0387312Z * [new tag] trunk/a9fabeb012a4b804836a2b8d4b3742b92c9a6b58 -> trunk/a9fabeb012a4b804836a2b8d4b3742b92c9a6b58 2025-08-26T20:05:37.0387507Z * [new tag] trunk/ab7787fb82dd777b2f777ef58bc20dbb7bd8289b -> trunk/ab7787fb82dd777b2f777ef58bc20dbb7bd8289b 2025-08-26T20:05:37.0387736Z * [new tag] trunk/ab8d60f4c86ca19ed00d6e79ae8e6939266f28e6 -> trunk/ab8d60f4c86ca19ed00d6e79ae8e6939266f28e6 2025-08-26T20:05:37.0387935Z * [new tag] trunk/ac8d9418aee4543fa193c86ae0bc3e63707bcd3b -> trunk/ac8d9418aee4543fa193c86ae0bc3e63707bcd3b 2025-08-26T20:05:37.0388131Z * [new tag] trunk/acb00d3ccf5f2d566225f07ed66bd579d5d3e44e -> trunk/acb00d3ccf5f2d566225f07ed66bd579d5d3e44e 2025-08-26T20:05:37.0388373Z * [new tag] trunk/adecb0c9e89e0dfe18d944d292c98c97b686fc83 -> trunk/adecb0c9e89e0dfe18d944d292c98c97b686fc83 2025-08-26T20:05:37.0390208Z * [new tag] trunk/ae8d319fd4a0b0fa7b1372aa07690a36ce823abc -> trunk/ae8d319fd4a0b0fa7b1372aa07690a36ce823abc 2025-08-26T20:05:37.0390492Z * [new tag] trunk/af3265d20f763e5366bfa37e3d4a6307036d0c18 -> trunk/af3265d20f763e5366bfa37e3d4a6307036d0c18 2025-08-26T20:05:37.0390706Z * [new tag] trunk/b0420d24386263f2727fd5714b63cfa6bc89f3e6 -> trunk/b0420d24386263f2727fd5714b63cfa6bc89f3e6 2025-08-26T20:05:37.0390905Z * [new tag] trunk/b1380f434da2fa2de0e5ff6fd70f73082dc08687 -> trunk/b1380f434da2fa2de0e5ff6fd70f73082dc08687 2025-08-26T20:05:37.0391210Z * [new tag] trunk/b2632e79828300302fd11e093d765196c3c0db58 -> trunk/b2632e79828300302fd11e093d765196c3c0db58 2025-08-26T20:05:37.0391400Z * [new tag] trunk/b2e06e0194c3fa8f7578a1b48751cc027394fb67 -> trunk/b2e06e0194c3fa8f7578a1b48751cc027394fb67 2025-08-26T20:05:37.0391599Z * [new tag] trunk/b3e215b864e6ca43b2c4e50ce666673f80feee27 -> trunk/b3e215b864e6ca43b2c4e50ce666673f80feee27 2025-08-26T20:05:37.0391794Z * [new tag] trunk/b708966201811b31ee765ec57715ac21d06ef652 -> trunk/b708966201811b31ee765ec57715ac21d06ef652 2025-08-26T20:05:37.0391988Z * [new tag] trunk/b9e9e92817fd7d1a778f074105603efb07e05004 -> trunk/b9e9e92817fd7d1a778f074105603efb07e05004 2025-08-26T20:05:37.0392242Z * [new tag] trunk/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 -> trunk/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 2025-08-26T20:05:37.0392503Z * [new tag] trunk/bcfe1b2d714cbb2716495e09ae010e7c34daf045 -> trunk/bcfe1b2d714cbb2716495e09ae010e7c34daf045 2025-08-26T20:05:37.0392703Z * [new tag] trunk/bd5857a1d6d5455d4f0057c182dff5e8ad2a4c8a -> trunk/bd5857a1d6d5455d4f0057c182dff5e8ad2a4c8a 2025-08-26T20:05:37.0392901Z * [new tag] trunk/be2e6b3158552405acc13ef7829a0217826fb271 -> trunk/be2e6b3158552405acc13ef7829a0217826fb271 2025-08-26T20:05:37.0393158Z * [new tag] trunk/be87f22dfba4488963fcc854699829e2782ee0f2 -> trunk/be87f22dfba4488963fcc854699829e2782ee0f2 2025-08-26T20:05:37.0393381Z * [new tag] trunk/becd6cd744bdf950578519437652a0d1f4b48781 -> trunk/becd6cd744bdf950578519437652a0d1f4b48781 2025-08-26T20:05:37.0393585Z * [new tag] trunk/bf8431ba062efa9ff0cdd5032a3ddf2e007a3216 -> trunk/bf8431ba062efa9ff0cdd5032a3ddf2e007a3216 2025-08-26T20:05:37.0393793Z * [new tag] trunk/c02e26bf31eb3da301158a061aa68527dbfb4d32 -> trunk/c02e26bf31eb3da301158a061aa68527dbfb4d32 2025-08-26T20:05:37.0393996Z * [new tag] trunk/c081481bbebdb568d07ee19cfe2cd3125de6cba7 -> trunk/c081481bbebdb568d07ee19cfe2cd3125de6cba7 2025-08-26T20:05:37.0394199Z * [new tag] trunk/c2390087c34c964ef648addf43efb8c6a34e30c2 -> trunk/c2390087c34c964ef648addf43efb8c6a34e30c2 2025-08-26T20:05:37.0394395Z * [new tag] trunk/c4670e40c9b741d50a79b714e3830149833be908 -> trunk/c4670e40c9b741d50a79b714e3830149833be908 2025-08-26T20:05:37.0394596Z * [new tag] trunk/c5cb255625deb4cdbc5780e6911b73498e17ed5a -> trunk/c5cb255625deb4cdbc5780e6911b73498e17ed5a 2025-08-26T20:05:37.0394790Z * [new tag] trunk/c60dea5261d9648d1da51528a07731966bb6823e -> trunk/c60dea5261d9648d1da51528a07731966bb6823e 2025-08-26T20:05:37.0394988Z * [new tag] trunk/c74e5f60611b7eac4321f53a9e4a15b077fb1bcc -> trunk/c74e5f60611b7eac4321f53a9e4a15b077fb1bcc 2025-08-26T20:05:37.0395182Z * [new tag] trunk/c7a77470c54b28e555319e34048af14d1d66198a -> trunk/c7a77470c54b28e555319e34048af14d1d66198a 2025-08-26T20:05:37.0397171Z * [new tag] trunk/c7fb031706330684fc3a2d8d169bebea874d4e95 -> trunk/c7fb031706330684fc3a2d8d169bebea874d4e95 2025-08-26T20:05:37.0397477Z * [new tag] trunk/c8bb0e4720ddddf3cd1b0b48b336978f763c71ca -> trunk/c8bb0e4720ddddf3cd1b0b48b336978f763c71ca 2025-08-26T20:05:37.0397665Z * [new tag] trunk/ca9fe0107e165a4a4147325ff6d34235ebde447f -> trunk/ca9fe0107e165a4a4147325ff6d34235ebde447f 2025-08-26T20:05:37.0397864Z * [new tag] trunk/caf98fde0d5c47452af45dc77099449edd521579 -> trunk/caf98fde0d5c47452af45dc77099449edd521579 2025-08-26T20:05:37.0398055Z * [new tag] trunk/cb579532150c9e87e7c143adcb020fb7de7cc6b1 -> trunk/cb579532150c9e87e7c143adcb020fb7de7cc6b1 2025-08-26T20:05:37.0398253Z * [new tag] trunk/cc2b65a91ae7773d4ecf9a600dda48fc3e69aa8f -> trunk/cc2b65a91ae7773d4ecf9a600dda48fc3e69aa8f 2025-08-26T20:05:37.0398443Z * [new tag] trunk/cc791d5857f4aa06b8d4e567b1fb2852e3ae963d -> trunk/cc791d5857f4aa06b8d4e567b1fb2852e3ae963d 2025-08-26T20:05:37.0398680Z * [new tag] trunk/cd31be28ec5cd0c4d9cdb6742efe151eee1406ec -> trunk/cd31be28ec5cd0c4d9cdb6742efe151eee1406ec 2025-08-26T20:05:37.0398870Z * [new tag] trunk/cd87f3029582cedb3b88747a3bd7d200b05c1138 -> trunk/cd87f3029582cedb3b88747a3bd7d200b05c1138 2025-08-26T20:05:37.0399054Z * [new tag] trunk/ce048de608180fa88335e5821070472539968b54 -> trunk/ce048de608180fa88335e5821070472539968b54 2025-08-26T20:05:37.0399246Z * [new tag] trunk/ce467df5d1d763d1648aee51c93ce3e9a4699936 -> trunk/ce467df5d1d763d1648aee51c93ce3e9a4699936 2025-08-26T20:05:37.0399435Z * [new tag] trunk/cee72119b2dec7776bc2550dd39a9b1349772751 -> trunk/cee72119b2dec7776bc2550dd39a9b1349772751 2025-08-26T20:05:37.0399638Z * [new tag] trunk/cf94cadbeee31a4d1d46a57f11bce7c9fd1cebc0 -> trunk/cf94cadbeee31a4d1d46a57f11bce7c9fd1cebc0 2025-08-26T20:05:37.0399843Z * [new tag] trunk/cfdaaaaa26d7f34427ba941569eca46f02f79f3e -> trunk/cfdaaaaa26d7f34427ba941569eca46f02f79f3e 2025-08-26T20:05:37.0400048Z * [new tag] trunk/d1faf2ef0476eb60b42c057baee9af0f48ae849a -> trunk/d1faf2ef0476eb60b42c057baee9af0f48ae849a 2025-08-26T20:05:37.0400277Z * [new tag] trunk/d228a776e90368bb693837ae23285ad8fc33def5 -> trunk/d228a776e90368bb693837ae23285ad8fc33def5 2025-08-26T20:05:37.0400565Z * [new tag] trunk/d2b8c0d431e00ad57354c5247e46c1bea0b8cd31 -> trunk/d2b8c0d431e00ad57354c5247e46c1bea0b8cd31 2025-08-26T20:05:37.0400767Z * [new tag] trunk/d2bd55d8de784df439b38378f161271dc43b744c -> trunk/d2bd55d8de784df439b38378f161271dc43b744c 2025-08-26T20:05:37.0400959Z * [new tag] trunk/d4703fb91c3510460d71f648da113177edf593c8 -> trunk/d4703fb91c3510460d71f648da113177edf593c8 2025-08-26T20:05:37.0401152Z * [new tag] trunk/d875d3ca1e5099636c766c9df70ac5888c25215a -> trunk/d875d3ca1e5099636c766c9df70ac5888c25215a 2025-08-26T20:05:37.0401356Z * [new tag] trunk/d8fcb2a4acb506f9c72a1f44fc8b857158bda892 -> trunk/d8fcb2a4acb506f9c72a1f44fc8b857158bda892 2025-08-26T20:05:37.0401558Z * [new tag] trunk/daeb3a6094c62d1881ea68091fcadb02d1dc687e -> trunk/daeb3a6094c62d1881ea68091fcadb02d1dc687e 2025-08-26T20:05:37.0401761Z * [new tag] trunk/db38c44ad639e7ada3e9df2ba026a2cb5e40feb0 -> trunk/db38c44ad639e7ada3e9df2ba026a2cb5e40feb0 2025-08-26T20:05:37.0401966Z * [new tag] trunk/db44de4c0d3e9f1fe5334ff4cc261fb8fe4390c8 -> trunk/db44de4c0d3e9f1fe5334ff4cc261fb8fe4390c8 2025-08-26T20:05:37.0403862Z * [new tag] trunk/dbef6066311a1ce6e60e1f2b6084249d1ad45769 -> trunk/dbef6066311a1ce6e60e1f2b6084249d1ad45769 2025-08-26T20:05:37.0404064Z * [new tag] trunk/df571ae7ad7dacf77ce42c00189cf369d7993387 -> trunk/df571ae7ad7dacf77ce42c00189cf369d7993387 2025-08-26T20:05:37.0404260Z * [new tag] trunk/df6073641079c781e66a905e4f15ee49ac257eb2 -> trunk/df6073641079c781e66a905e4f15ee49ac257eb2 2025-08-26T20:05:37.0404457Z * [new tag] trunk/e1a64b75ff3dc834774a9174c2e7b1c46dea35ec -> trunk/e1a64b75ff3dc834774a9174c2e7b1c46dea35ec 2025-08-26T20:05:37.0404734Z * [new tag] trunk/e20f6d798606f3245686e950c43635bbe526232d -> trunk/e20f6d798606f3245686e950c43635bbe526232d 2025-08-26T20:05:37.0404930Z * [new tag] trunk/e25ee0290ef16503f178e04890c15717f6e9ea44 -> trunk/e25ee0290ef16503f178e04890c15717f6e9ea44 2025-08-26T20:05:37.0405128Z * [new tag] trunk/e34b6a01039df5d8940acdccd8d8989f3cd827aa -> trunk/e34b6a01039df5d8940acdccd8d8989f3cd827aa 2025-08-26T20:05:37.0405333Z * [new tag] trunk/e3d68dfae2dee15e74d3b95beaed7149b6afb94a -> trunk/e3d68dfae2dee15e74d3b95beaed7149b6afb94a 2025-08-26T20:05:37.0405535Z * [new tag] trunk/e3ebf364e6d2fb8008da113a596d3cc426ba9c79 -> trunk/e3ebf364e6d2fb8008da113a596d3cc426ba9c79 2025-08-26T20:05:37.0405787Z * [new tag] trunk/e4839470470168648dee5997f57347bb8541ea2b -> trunk/e4839470470168648dee5997f57347bb8541ea2b 2025-08-26T20:05:37.0405988Z * [new tag] trunk/e63155751825ba026ced3a1fc89563231bc85ccc -> trunk/e63155751825ba026ced3a1fc89563231bc85ccc 2025-08-26T20:05:37.0406187Z * [new tag] trunk/e6aa7287f8c8cac76d792097f20ba1dae6dc8717 -> trunk/e6aa7287f8c8cac76d792097f20ba1dae6dc8717 2025-08-26T20:05:37.0406385Z * [new tag] trunk/e6e45e6ae8452f0bc5e3e258027c42eb9a1394fb -> trunk/e6e45e6ae8452f0bc5e3e258027c42eb9a1394fb 2025-08-26T20:05:37.0406578Z * [new tag] trunk/e795450a35bca909902e12de99245e1c0e7e2872 -> trunk/e795450a35bca909902e12de99245e1c0e7e2872 2025-08-26T20:05:37.0406775Z * [new tag] trunk/e7e270a33a3f368c3ef0c3339950a47fdbfadd71 -> trunk/e7e270a33a3f368c3ef0c3339950a47fdbfadd71 2025-08-26T20:05:37.0406968Z * [new tag] trunk/e836323a23f5750e800abe04ef8ca386b3066b58 -> trunk/e836323a23f5750e800abe04ef8ca386b3066b58 2025-08-26T20:05:37.0407165Z * [new tag] trunk/e83825f91cb2901567fedbf31ba7cc434a897271 -> trunk/e83825f91cb2901567fedbf31ba7cc434a897271 2025-08-26T20:05:37.0407367Z * [new tag] trunk/e9d42b3880dcdbd823bbdc9370c8b0b3af0ba2e3 -> trunk/e9d42b3880dcdbd823bbdc9370c8b0b3af0ba2e3 2025-08-26T20:05:37.0407563Z * [new tag] trunk/eb5549a43164cdf8689cd7d177c03b2508c699f4 -> trunk/eb5549a43164cdf8689cd7d177c03b2508c699f4 2025-08-26T20:05:37.0407840Z * [new tag] trunk/eba1ad09e47b66478f973e03cece7f314ac3b412 -> trunk/eba1ad09e47b66478f973e03cece7f314ac3b412 2025-08-26T20:05:37.0408043Z * [new tag] trunk/eba20d2d748cb17dce9aa26e5513e4567bfd8282 -> trunk/eba20d2d748cb17dce9aa26e5513e4567bfd8282 2025-08-26T20:05:37.0408243Z * [new tag] trunk/ec21cafd85d491d2d220e4e54080fe340a37c4c2 -> trunk/ec21cafd85d491d2d220e4e54080fe340a37c4c2 2025-08-26T20:05:37.0408451Z * [new tag] trunk/ed8bcccf31e1ba01a35e818a4afbb74c333e8dc3 -> trunk/ed8bcccf31e1ba01a35e818a4afbb74c333e8dc3 2025-08-26T20:05:37.0410488Z * [new tag] trunk/eddaaa6c2a66a84e17b17bf8af5131852067b259 -> trunk/eddaaa6c2a66a84e17b17bf8af5131852067b259 2025-08-26T20:05:37.0410717Z * [new tag] trunk/ef761c43538abae5bccc0c4b6ebaf42ff676db7a -> trunk/ef761c43538abae5bccc0c4b6ebaf42ff676db7a 2025-08-26T20:05:37.0410957Z * [new tag] trunk/f085f299584b06a2a7d8855eda2a411313e782ad -> trunk/f085f299584b06a2a7d8855eda2a411313e782ad 2025-08-26T20:05:37.0411181Z * [new tag] trunk/f09458c2e16b4fe7063d73d80fd3e7e354bad3f8 -> trunk/f09458c2e16b4fe7063d73d80fd3e7e354bad3f8 2025-08-26T20:05:37.0411426Z * [new tag] trunk/f0e0a6897ee5cb31ccee10ee8e2d3c01140ff999 -> trunk/f0e0a6897ee5cb31ccee10ee8e2d3c01140ff999 2025-08-26T20:05:37.0411614Z * [new tag] trunk/f30501937738a2440f90988d1d46920529309ba8 -> trunk/f30501937738a2440f90988d1d46920529309ba8 2025-08-26T20:05:37.0411817Z * [new tag] trunk/f391afe9bf8c542fdbb822423d2a1e454b3d9744 -> trunk/f391afe9bf8c542fdbb822423d2a1e454b3d9744 2025-08-26T20:05:37.0412096Z * [new tag] trunk/f521e82a4e80df502fa57e5852af14d8779dcbd1 -> trunk/f521e82a4e80df502fa57e5852af14d8779dcbd1 2025-08-26T20:05:37.0412292Z * [new tag] trunk/f5bf5147ad18994c9a6e0f565d7831362bf5a18a -> trunk/f5bf5147ad18994c9a6e0f565d7831362bf5a18a 2025-08-26T20:05:37.0412482Z * [new tag] trunk/f795e92802c55608ad4f4f198726d250056d0232 -> trunk/f795e92802c55608ad4f4f198726d250056d0232 2025-08-26T20:05:37.0412677Z * [new tag] trunk/f8bd85827d465a8a2a610c27ed9e62a4c27ac07d -> trunk/f8bd85827d465a8a2a610c27ed9e62a4c27ac07d 2025-08-26T20:05:37.0412873Z * [new tag] trunk/f90ccad1651b5a1698b2232acc3e92e2829b7935 -> trunk/f90ccad1651b5a1698b2232acc3e92e2829b7935 2025-08-26T20:05:37.0413155Z * [new tag] trunk/f912c93344caa74e24c8164a2e25fe84a8203073 -> trunk/f912c93344caa74e24c8164a2e25fe84a8203073 2025-08-26T20:05:37.0413347Z * [new tag] trunk/f9875166a953a51bbd454d963ee03d41818a27e8 -> trunk/f9875166a953a51bbd454d963ee03d41818a27e8 2025-08-26T20:05:37.0413554Z * [new tag] trunk/f9df4ec2af0ac19b42f658ae87acf12067e67b36 -> trunk/f9df4ec2af0ac19b42f658ae87acf12067e67b36 2025-08-26T20:05:37.0413752Z * [new tag] trunk/fab5dac734344105ae107e85c08151758a4a9b4d -> trunk/fab5dac734344105ae107e85c08151758a4a9b4d 2025-08-26T20:05:37.0413946Z * [new tag] trunk/fb241d0a448f1dd88471098ac149418124a7c4aa -> trunk/fb241d0a448f1dd88471098ac149418124a7c4aa 2025-08-26T20:05:37.0414142Z * [new tag] trunk/fc0683b1e75fdf3182e0855b3f79e80fe0124ef1 -> trunk/fc0683b1e75fdf3182e0855b3f79e80fe0124ef1 2025-08-26T20:05:37.0414337Z * [new tag] trunk/fc69c2bc67672c3b2d0c62c1821895f09288f1c0 -> trunk/fc69c2bc67672c3b2d0c62c1821895f09288f1c0 2025-08-26T20:05:37.0414547Z * [new tag] trunk/febfc3ec03004116dfd6d504e6853ff02a1dd6e0 -> trunk/febfc3ec03004116dfd6d504e6853ff02a1dd6e0 2025-08-26T20:05:37.0414758Z * [new tag] trunk/fecc5f600110209aaaedead11770a445b3c879e6 -> trunk/fecc5f600110209aaaedead11770a445b3c879e6 2025-08-26T20:05:37.0414965Z * [new tag] trunk/ff4f5dd8ed8e2aaee903c7d30cd4f8bd04d883c8 -> trunk/ff4f5dd8ed8e2aaee903c7d30cd4f8bd04d883c8 2025-08-26T20:05:37.0415171Z * [new tag] trunk/ffa1ce7650766c2ae6eaa96415dfc29e9eb0b3ec -> trunk/ffa1ce7650766c2ae6eaa96415dfc29e9eb0b3ec 2025-08-26T20:05:37.0415256Z * [new tag] v0.1.1 -> v0.1.1 2025-08-26T20:05:37.0417084Z * [new tag] v0.1.10 -> v0.1.10 2025-08-26T20:05:37.0417162Z * [new tag] v0.1.11 -> v0.1.11 2025-08-26T20:05:37.0417235Z * [new tag] v0.1.12 -> v0.1.12 2025-08-26T20:05:37.0417311Z * [new tag] v0.1.2 -> v0.1.2 2025-08-26T20:05:37.0417382Z * [new tag] v0.1.3 -> v0.1.3 2025-08-26T20:05:37.0417451Z * [new tag] v0.1.4 -> v0.1.4 2025-08-26T20:05:37.0417523Z * [new tag] v0.1.5 -> v0.1.5 2025-08-26T20:05:37.0417592Z * [new tag] v0.1.6 -> v0.1.6 2025-08-26T20:05:37.0417660Z * [new tag] v0.1.7 -> v0.1.7 2025-08-26T20:05:37.0417732Z * [new tag] v0.1.8 -> v0.1.8 2025-08-26T20:05:37.0417803Z * [new tag] v0.1.9 -> v0.1.9 2025-08-26T20:05:37.0417871Z * [new tag] v0.2.0 -> v0.2.0 2025-08-26T20:05:37.0417940Z * [new tag] v0.3.0 -> v0.3.0 2025-08-26T20:05:37.0418011Z * [new tag] v0.3.1 -> v0.3.1 2025-08-26T20:05:37.0418079Z * [new tag] v0.4.0 -> v0.4.0 2025-08-26T20:05:37.0418149Z * [new tag] v0.4.1 -> v0.4.1 2025-08-26T20:05:37.0418221Z * [new tag] v1.0.0 -> v1.0.0 2025-08-26T20:05:37.0418352Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-08-26T20:05:37.0418422Z * [new tag] v1.0.1 -> v1.0.1 2025-08-26T20:05:37.0418496Z * [new tag] v1.0rc0 -> v1.0rc0 2025-08-26T20:05:37.0418568Z * [new tag] v1.0rc1 -> v1.0rc1 2025-08-26T20:05:37.0418637Z * [new tag] v1.1.0 -> v1.1.0 2025-08-26T20:05:37.0418713Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-08-26T20:05:37.0418784Z * [new tag] v1.10.0 -> v1.10.0 2025-08-26T20:05:37.0418915Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-08-26T20:05:37.0420817Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-08-26T20:05:37.0420902Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-08-26T20:05:37.0421017Z * [new tag] v1.10.1 -> v1.10.1 2025-08-26T20:05:37.0421097Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-08-26T20:05:37.0421237Z * [new tag] v1.10.2 -> v1.10.2 2025-08-26T20:05:37.0421311Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-08-26T20:05:37.0421382Z * [new tag] v1.11.0 -> v1.11.0 2025-08-26T20:05:37.0421456Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-08-26T20:05:37.0421529Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-08-26T20:05:37.0421610Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-08-26T20:05:37.0421682Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-08-26T20:05:37.0421755Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-08-26T20:05:37.0421830Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-08-26T20:05:37.0421904Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-08-26T20:05:37.0421974Z * [new tag] v1.12.0 -> v1.12.0 2025-08-26T20:05:37.0422047Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-08-26T20:05:37.0422122Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-08-26T20:05:37.0422195Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-08-26T20:05:37.0422268Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-08-26T20:05:37.0422343Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-08-26T20:05:37.0422418Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-08-26T20:05:37.0422491Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-08-26T20:05:37.0422566Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-08-26T20:05:37.0422637Z * [new tag] v1.12.1 -> v1.12.1 2025-08-26T20:05:37.0424466Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-08-26T20:05:37.0424552Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-08-26T20:05:37.0424629Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-08-26T20:05:37.0424702Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-08-26T20:05:37.0424776Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-08-26T20:05:37.0424846Z * [new tag] v1.13.0 -> v1.13.0 2025-08-26T20:05:37.0424922Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-08-26T20:05:37.0424994Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-08-26T20:05:37.0425074Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-08-26T20:05:37.0425228Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-08-26T20:05:37.0425302Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-08-26T20:05:37.0425376Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-08-26T20:05:37.0425446Z * [new tag] v1.13.1 -> v1.13.1 2025-08-26T20:05:37.0425519Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-08-26T20:05:37.0425592Z * [new tag] v1.2.0 -> v1.2.0 2025-08-26T20:05:37.0425666Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-08-26T20:05:37.0425802Z * [new tag] v1.3.0 -> v1.3.0 2025-08-26T20:05:37.0425881Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-08-26T20:05:37.0425952Z * [new tag] v1.3.1 -> v1.3.1 2025-08-26T20:05:37.0426023Z * [new tag] v1.4.0 -> v1.4.0 2025-08-26T20:05:37.0426095Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-08-26T20:05:37.0426166Z * [new tag] v1.4.1 -> v1.4.1 2025-08-26T20:05:37.0426235Z * [new tag] v1.5.0 -> v1.5.0 2025-08-26T20:05:37.0426311Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-08-26T20:05:37.0428120Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-08-26T20:05:37.0428201Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-08-26T20:05:37.0428284Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-08-26T20:05:37.0428359Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-08-26T20:05:37.0428428Z * [new tag] v1.5.1 -> v1.5.1 2025-08-26T20:05:37.0428503Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-08-26T20:05:37.0428574Z * [new tag] v1.6.0 -> v1.6.0 2025-08-26T20:05:37.0428647Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-08-26T20:05:37.0428719Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-08-26T20:05:37.0428793Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-08-26T20:05:37.0428865Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-08-26T20:05:37.0428937Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-08-26T20:05:37.0429011Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-08-26T20:05:37.0429085Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-08-26T20:05:37.0429155Z * [new tag] v1.7.0 -> v1.7.0 2025-08-26T20:05:37.0429228Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-08-26T20:05:37.0429303Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-08-26T20:05:37.0429376Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-08-26T20:05:37.0429448Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-08-26T20:05:37.0429520Z * [new tag] v1.7.1 -> v1.7.1 2025-08-26T20:05:37.0429592Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-08-26T20:05:37.0429665Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-08-26T20:05:37.0429738Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-08-26T20:05:37.0429811Z * [new tag] v1.8.0 -> v1.8.0 2025-08-26T20:05:37.0429884Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-08-26T20:05:37.0431755Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-08-26T20:05:37.0431929Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-08-26T20:05:37.0432006Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-08-26T20:05:37.0432079Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-08-26T20:05:37.0432150Z * [new tag] v1.8.1 -> v1.8.1 2025-08-26T20:05:37.0432222Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-08-26T20:05:37.0432296Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-08-26T20:05:37.0432371Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-08-26T20:05:37.0432520Z * [new tag] v1.8.2 -> v1.8.2 2025-08-26T20:05:37.0432594Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-08-26T20:05:37.0432664Z * [new tag] v1.9.0 -> v1.9.0 2025-08-26T20:05:37.0432738Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-08-26T20:05:37.0432810Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-08-26T20:05:37.0432883Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-08-26T20:05:37.0432956Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-08-26T20:05:37.0433025Z * [new tag] v1.9.1 -> v1.9.1 2025-08-26T20:05:37.0433100Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-08-26T20:05:37.0433172Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-08-26T20:05:37.0433242Z * [new tag] v2.0.0 -> v2.0.0 2025-08-26T20:05:37.0433318Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-08-26T20:05:37.0433393Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-08-26T20:05:37.0433465Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-08-26T20:05:37.0433539Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-08-26T20:05:37.0433613Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-08-26T20:05:37.0435424Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-08-26T20:05:37.0435510Z * [new tag] v2.0.1 -> v2.0.1 2025-08-26T20:05:37.0435582Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-08-26T20:05:37.0435655Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-08-26T20:05:37.0435728Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-08-26T20:05:37.0435803Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-08-26T20:05:37.0435872Z * [new tag] v2.1.0 -> v2.1.0 2025-08-26T20:05:37.0435947Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-08-26T20:05:37.0436026Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-08-26T20:05:37.0436097Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-08-26T20:05:37.0436170Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-08-26T20:05:37.0436243Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-08-26T20:05:37.0436315Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-08-26T20:05:37.0436384Z * [new tag] v2.1.1 -> v2.1.1 2025-08-26T20:05:37.0436457Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-08-26T20:05:37.0436531Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-08-26T20:05:37.0436604Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-08-26T20:05:37.0436676Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-08-26T20:05:37.0436799Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-08-26T20:05:37.0436874Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-08-26T20:05:37.0436944Z * [new tag] v2.1.2 -> v2.1.2 2025-08-26T20:05:37.0437017Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-08-26T20:05:37.0437089Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-08-26T20:05:37.0437161Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-08-26T20:05:37.0438838Z * [new tag] v2.2.0 -> v2.2.0 2025-08-26T20:05:37.0438921Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-08-26T20:05:37.0439041Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-08-26T20:05:37.0439115Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-08-26T20:05:37.0439186Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-08-26T20:05:37.0439260Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-08-26T20:05:37.0439334Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-08-26T20:05:37.0439406Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-08-26T20:05:37.0439484Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-08-26T20:05:37.0439555Z * [new tag] v2.2.1 -> v2.2.1 2025-08-26T20:05:37.0439626Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-08-26T20:05:37.0439698Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-08-26T20:05:37.0439777Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-08-26T20:05:37.0439846Z * [new tag] v2.2.2 -> v2.2.2 2025-08-26T20:05:37.0439917Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-08-26T20:05:37.0439993Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-08-26T20:05:37.0440066Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-08-26T20:05:37.0440134Z * [new tag] v2.3.0 -> v2.3.0 2025-08-26T20:05:37.0440206Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-08-26T20:05:37.0440284Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-08-26T20:05:37.0440427Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-08-26T20:05:37.0440506Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-08-26T20:05:37.0440583Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-08-26T20:05:37.0440655Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-08-26T20:05:37.0440727Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-08-26T20:05:37.0442690Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-08-26T20:05:37.0442772Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-08-26T20:05:37.0442844Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-08-26T20:05:37.0442917Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-08-26T20:05:37.0442989Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-08-26T20:05:37.0443059Z * [new tag] v2.3.1 -> v2.3.1 2025-08-26T20:05:37.0443133Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-08-26T20:05:37.0443208Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-08-26T20:05:37.0443282Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-08-26T20:05:37.0443354Z * [new tag] v2.4.0 -> v2.4.0 2025-08-26T20:05:37.0443426Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-08-26T20:05:37.0443604Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-08-26T20:05:37.0443677Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-08-26T20:05:37.0443750Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-08-26T20:05:37.0443822Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-08-26T20:05:37.0443894Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-08-26T20:05:37.0443968Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-08-26T20:05:37.0444040Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-08-26T20:05:37.0444182Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-08-26T20:05:37.0444253Z * [new tag] v2.4.1 -> v2.4.1 2025-08-26T20:05:37.0444325Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-08-26T20:05:37.0444400Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-08-26T20:05:37.0444472Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-08-26T20:05:37.0444542Z * [new tag] v2.5.0 -> v2.5.0 2025-08-26T20:05:37.0446570Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-08-26T20:05:37.0446657Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-08-26T20:05:37.0446730Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-08-26T20:05:37.0446802Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-08-26T20:05:37.0446877Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-08-26T20:05:37.0446949Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-08-26T20:05:37.0447023Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-08-26T20:05:37.0447097Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-08-26T20:05:37.0447171Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-08-26T20:05:37.0447245Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-08-26T20:05:37.0447315Z * [new tag] v2.5.1 -> v2.5.1 2025-08-26T20:05:37.0447388Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-08-26T20:05:37.0447457Z * [new tag] v2.6.0 -> v2.6.0 2025-08-26T20:05:37.0447529Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-08-26T20:05:37.0447603Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-08-26T20:05:37.0450463Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-08-26T20:05:37.0450544Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-08-26T20:05:37.0450617Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-08-26T20:05:37.0450691Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-08-26T20:05:37.0450763Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-08-26T20:05:37.0450835Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-08-26T20:05:37.0450908Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-08-26T20:05:37.0450977Z * [new tag] v2.7.0 -> v2.7.0 2025-08-26T20:05:37.0451049Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-08-26T20:05:37.0452801Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-08-26T20:05:37.0452880Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-08-26T20:05:37.0452952Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-08-26T20:05:37.0453025Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-08-26T20:05:37.0453191Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-08-26T20:05:37.0453263Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-08-26T20:05:37.0453337Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-08-26T20:05:37.0453409Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-08-26T20:05:37.0453481Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-08-26T20:05:37.0453552Z * [new tag] v2.7.1 -> v2.7.1 2025-08-26T20:05:37.0453624Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-08-26T20:05:37.0453775Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-08-26T20:05:37.0453852Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-08-26T20:05:37.0453924Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-08-26T20:05:37.0453997Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-08-26T20:05:37.0454070Z * [new tag] v2.8.0 -> v2.8.0 2025-08-26T20:05:37.0454143Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-08-26T20:05:37.0454215Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-08-26T20:05:37.0454287Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-08-26T20:05:37.0454362Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-08-26T20:05:37.0454433Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-08-26T20:05:37.0454507Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-08-26T20:05:37.0454580Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-08-26T20:05:37.0454652Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-08-26T20:05:37.0454734Z * [new tag] whc_flight_1 -> whc_flight_1 2025-08-26T20:05:37.0456591Z * [new tag] whc_flight_2 -> whc_flight_2 2025-08-26T20:05:37.0456675Z * [new tag] whc_flight_4 -> whc_flight_4 2025-08-26T20:05:37.3337396Z [command]/usr/bin/git rev-parse --verify --quiet 262640fd220236042fbf4443cc163c8838c84c3d^{object} 2025-08-26T20:05:37.3382360Z 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:05:37.3388033Z ##[endgroup] 2025-08-26T20:05:37.3388278Z ##[group]Determining the checkout info 2025-08-26T20:05:37.3388914Z ##[endgroup] 2025-08-26T20:05:37.3395359Z [command]/usr/bin/git sparse-checkout disable 2025-08-26T20:05:37.3447758Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-08-26T20:05:37.3475180Z ##[group]Checking out the ref 2025-08-26T20:05:37.3477500Z [command]/usr/bin/git checkout --progress --force 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:05:38.1023198Z Note: switching to '262640fd220236042fbf4443cc163c8838c84c3d'. 2025-08-26T20:05:38.1023373Z 2025-08-26T20:05:38.1023505Z You are in 'detached HEAD' state. You can look around, make experimental 2025-08-26T20:05:38.1029064Z changes and commit them, and you can discard any commits you make in this 2025-08-26T20:05:38.1029401Z state without impacting any branches by switching back to a branch. 2025-08-26T20:05:38.1029571Z 2025-08-26T20:05:38.1029683Z If you want to create a new branch to retain commits you create, you may 2025-08-26T20:05:38.1029952Z do so (now or later) by using -c with the switch command. Example: 2025-08-26T20:05:38.1030122Z 2025-08-26T20:05:38.1030195Z git switch -c 2025-08-26T20:05:38.1030325Z 2025-08-26T20:05:38.1030502Z Or undo this operation with: 2025-08-26T20:05:38.1030606Z 2025-08-26T20:05:38.1030700Z git switch - 2025-08-26T20:05:38.1030777Z 2025-08-26T20:05:38.1031471Z Turn off this advice by setting config variable advice.detachedHead to false 2025-08-26T20:05:38.1032344Z 2025-08-26T20:05:38.1034151Z HEAD is now at 262640fd220 [ROCm][CI] restore test_flex_attention tests (#161519) 2025-08-26T20:05:38.1107410Z ##[endgroup] 2025-08-26T20:05:38.1107598Z ##[group]Setting up auth for fetching submodules 2025-08-26T20:05:38.1107865Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-08-26T20:05:38.1151713Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-08-26T20:05:38.1186059Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-08-26T20:05:38.1224022Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-08-26T20:05:38.1253179Z ##[endgroup] 2025-08-26T20:05:38.1261162Z ##[group]Fetching submodules 2025-08-26T20:05:38.1261374Z [command]/usr/bin/git submodule sync --recursive 2025-08-26T20:05:38.1723552Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-08-26T20:05:38.2000700Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-08-26T20:05:38.2005916Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-08-26T20:05:38.2015969Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-08-26T20:05:38.2041890Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-08-26T20:05:38.2042830Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-08-26T20:05:38.2044967Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-08-26T20:05:38.2045771Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-08-26T20:05:38.2050903Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-08-26T20:05:38.2051683Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-08-26T20:05:38.2052282Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-08-26T20:05:38.2052856Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-08-26T20:05:38.2053363Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-08-26T20:05:38.2053900Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-08-26T20:05:38.2054426Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-08-26T20:05:38.2054878Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-08-26T20:05:38.2055403Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-08-26T20:05:38.2055968Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-08-26T20:05:38.2056445Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-08-26T20:05:38.2056945Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-08-26T20:05:38.2060055Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-08-26T20:05:38.2062160Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-08-26T20:05:38.2081307Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-08-26T20:05:38.2082798Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-08-26T20:05:38.2085571Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-08-26T20:05:38.2088679Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-08-26T20:05:38.2092681Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-08-26T20:05:38.2094789Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-08-26T20:05:38.2098357Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-08-26T20:05:38.2100650Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-08-26T20:05:38.2103706Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-08-26T20:05:38.2107422Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-08-26T20:05:38.2113160Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-08-26T20:05:38.2113998Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-08-26T20:05:38.2116371Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-08-26T20:05:38.2118746Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-08-26T20:05:38.2121997Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-08-26T20:05:38.2125174Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-08-26T20:05:38.2187172Z Cloning into '/home/runner/_work/pytorch/pytorch/android/libs/fbjni'... 2025-08-26T20:05:38.6229858Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/psimd'... 2025-08-26T20:05:38.6231019Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/FXdiv'... 2025-08-26T20:05:38.6231708Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/FP16'... 2025-08-26T20:05:38.6232821Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-08-26T20:05:38.6377860Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/NNPACK'... 2025-08-26T20:05:38.6391406Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/NVTX'... 2025-08-26T20:05:38.8372183Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/pocketfft'... 2025-08-26T20:05:38.8389583Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-08-26T20:05:38.8389973Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-08-26T20:05:38.8390293Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/gloo'... 2025-08-26T20:05:38.8390935Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/benchmark'... 2025-08-26T20:05:38.8391236Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/ideep'... 2025-08-26T20:05:38.8391570Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-08-26T20:05:38.8531326Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-08-26T20:05:39.9052516Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kleidiai'... 2025-08-26T20:05:39.9060640Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/ittapi'... 2025-08-26T20:05:39.9061086Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/flash-attention'... 2025-08-26T20:05:39.9061415Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-08-26T20:05:39.9061723Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-08-26T20:05:39.9062032Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/sleef'... 2025-08-26T20:05:39.9062326Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/mimalloc'... 2025-08-26T20:05:39.9062857Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/googletest'... 2025-08-26T20:05:39.9063167Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/pybind11'... 2025-08-26T20:05:39.9063478Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-08-26T20:05:39.9063793Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto'... 2025-08-26T20:05:40.0051407Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-08-26T20:05:49.4635266Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fmt'... 2025-08-26T20:05:49.4635610Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-08-26T20:05:49.4635920Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm'... 2025-08-26T20:05:49.4636215Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/cutlass'... 2025-08-26T20:05:49.4636501Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/onnx'... 2025-08-26T20:05:49.4637016Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-08-26T20:05:49.4638263Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/aiter'... 2025-08-26T20:05:49.4638564Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-08-26T20:05:49.4638827Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/nlohmann'... 2025-08-26T20:05:49.4646537Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/protobuf'... 2025-08-26T20:05:49.4758270Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-08-26T20:05:49.4901667Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-08-26T20:05:49.4991976Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-08-26T20:05:49.5179963Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-08-26T20:05:49.5705639Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-08-26T20:05:49.6077825Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-08-26T20:05:49.9584196Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-08-26T20:05:50.0436590Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-08-26T20:05:50.0471642Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T20:05:50.0490993Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-08-26T20:05:53.5571954Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-08-26T20:05:53.5754598Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-08-26T20:05:53.7293202Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-08-26T20:05:53.7616879Z Submodule path 'third_party/cpp-httplib': checked out '3af7f2c16147f3fbc6e4d717032daf505dc1652c' 2025-08-26T20:05:53.8182636Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-08-26T20:05:53.8494251Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-08-26T20:05:54.2164606Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-08-26T20:05:54.2901510Z Submodule path 'third_party/fbgemm': checked out '21c7d30c526c0f1ad873ecc632dca6cfa8a69067' 2025-08-26T20:05:54.2926186Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-08-26T20:05:54.2928548Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-08-26T20:05:54.2930859Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-08-26T20:05:54.2933106Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-08-26T20:05:54.2935232Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-08-26T20:05:54.2937439Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-08-26T20:05:54.2939517Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-08-26T20:05:54.3002350Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-08-26T20:05:55.4628258Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-08-26T20:05:55.4634313Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-08-26T20:05:55.4634592Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-08-26T20:05:55.4634896Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-08-26T20:05:55.5628301Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-08-26T20:05:56.1366373Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-08-26T20:05:58.9618443Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-08-26T20:05:59.0937896Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-08-26T20:05:59.1523572Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-08-26T20:05:59.5050684Z Submodule path 'third_party/fbgemm/external/cutlass': checked out 'b40777404c174b9694a870bff5c13ce6b7f656ad' 2025-08-26T20:05:59.5365784Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-08-26T20:05:59.5437207Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out 'a4337c69fe0e2552a7b7b0669178926beeed828c' 2025-08-26T20:05:59.5991325Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-08-26T20:05:59.6359668Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-08-26T20:05:59.6416645Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T20:05:59.6418062Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-08-26T20:05:59.6449727Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-08-26T20:06:02.9205673Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-08-26T20:06:03.0419922Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-08-26T20:06:03.3211262Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-08-26T20:06:03.4182043Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-08-26T20:06:03.4421602Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-08-26T20:06:03.4697832Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-08-26T20:06:03.4863657Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-08-26T20:06:03.5151032Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-08-26T20:06:03.5260690Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-08-26T20:06:03.5273519Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-08-26T20:06:03.5301440Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-08-26T20:06:13.0845185Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-08-26T20:06:13.0963983Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-08-26T20:06:13.1541918Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-08-26T20:06:13.1576179Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T20:06:13.1579477Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T20:06:13.1581026Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T20:06:13.1619548Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-08-26T20:06:13.9538509Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-08-26T20:06:14.3812027Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-08-26T20:06:14.4261948Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-08-26T20:06:14.4287356Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T20:06:14.4322926Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T20:06:14.4324874Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T20:06:14.4327711Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T20:06:14.4329959Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T20:06:14.4332419Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T20:06:14.4334598Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T20:06:14.4337309Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T20:06:14.4387163Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-08-26T20:06:15.7032140Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-08-26T20:06:15.7032924Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-08-26T20:06:15.7033570Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-08-26T20:06:15.7034538Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-08-26T20:06:15.7035150Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-08-26T20:06:15.7035726Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-08-26T20:06:15.8032064Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-08-26T20:06:18.9742492Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-08-26T20:06:18.9858857Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-08-26T20:06:19.0138782Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-08-26T20:06:19.0267310Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-08-26T20:06:19.0312002Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T20:06:19.0334018Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-08-26T20:06:19.4705780Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-08-26T20:06:19.4828119Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-08-26T20:06:19.5079078Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-08-26T20:06:19.5632012Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-08-26T20:06:19.5734130Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-08-26T20:06:19.6012949Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-08-26T20:06:19.6396578Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-08-26T20:06:19.6693130Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-08-26T20:06:19.6993475Z Submodule path 'third_party/mimalloc': checked out 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'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T20:06:21.0746836Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T20:06:21.0748805Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T20:06:21.0751334Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T20:06:21.0753825Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T20:06:21.0790789Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T20:06:21.0799520Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T20:06:21.0814888Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T20:06:21.0875788Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-08-26T20:06:21.6461294Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-08-26T20:06:21.6467438Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-08-26T20:06:21.6467774Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-08-26T20:06:21.6468073Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-08-26T20:06:21.7462223Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-08-26T20:06:22.1738424Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-08-26T20:06:25.4875258Z Cloning into '/home/runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-08-26T20:06:27.0012760Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-08-26T20:06:27.0271497Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-08-26T20:06:27.0380755Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-08-26T20:06:27.1012661Z Submodule path 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file:/home/runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-08-26T20:06:32.9043562Z Entering 'third_party/FP16' 2025-08-26T20:06:32.9060970Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-08-26T20:06:32.9069848Z Entering 'third_party/FXdiv' 2025-08-26T20:06:32.9090509Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-08-26T20:06:32.9104623Z Entering 'third_party/NNPACK' 2025-08-26T20:06:32.9132139Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-08-26T20:06:32.9161815Z Entering 'third_party/NVTX' 2025-08-26T20:06:32.9208394Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-08-26T20:06:32.9240793Z Entering 'third_party/VulkanMemoryAllocator' 2025-08-26T20:06:32.9252647Z 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file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-08-26T20:06:33.0484598Z Entering 'third_party/gloo' 2025-08-26T20:06:33.0506981Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-08-26T20:06:33.0517413Z Entering 'third_party/googletest' 2025-08-26T20:06:33.0538492Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-08-26T20:06:33.0548891Z Entering 'third_party/ideep' 2025-08-26T20:06:33.0569510Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-08-26T20:06:33.0579641Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T20:06:33.0611072Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-08-26T20:06:33.0611379Z Entering 'third_party/ittapi' 2025-08-26T20:06:33.0633311Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-08-26T20:06:33.0644890Z Entering 'third_party/kineto' 2025-08-26T20:06:33.0667898Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-08-26T20:06:33.0679446Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T20:06:33.0697717Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-08-26T20:06:33.0716110Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T20:06:33.0749500Z file:/home/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-08-26T20:06:33.0767262Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T20:06:33.0800924Z 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2025-08-26T20:06:33.4755178Z Entering 'third_party/FP16' 2025-08-26T20:06:33.4776702Z Entering 'third_party/FXdiv' 2025-08-26T20:06:33.4795305Z Entering 'third_party/NNPACK' 2025-08-26T20:06:33.4814764Z Entering 'third_party/NVTX' 2025-08-26T20:06:33.4836548Z Entering 'third_party/VulkanMemoryAllocator' 2025-08-26T20:06:33.4856709Z Entering 'third_party/XNNPACK' 2025-08-26T20:06:33.4882002Z Entering 'third_party/aiter' 2025-08-26T20:06:33.4904160Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T20:06:33.4929784Z Entering 'third_party/benchmark' 2025-08-26T20:06:33.4953723Z Entering 'third_party/composable_kernel' 2025-08-26T20:06:33.4977145Z Entering 'third_party/cpp-httplib' 2025-08-26T20:06:33.4996027Z Entering 'third_party/cpuinfo' 2025-08-26T20:06:33.5017175Z Entering 'third_party/cudnn_frontend' 2025-08-26T20:06:33.5036881Z Entering 'third_party/cutlass' 2025-08-26T20:06:33.5059529Z Entering 'third_party/fbgemm' 2025-08-26T20:06:33.5079952Z Entering 'third_party/fbgemm/external/asmjit' 2025-08-26T20:06:33.5102974Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-08-26T20:06:33.5161938Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-08-26T20:06:33.5220797Z Entering 'third_party/fbgemm/external/cutlass' 2025-08-26T20:06:33.5235017Z Entering 'third_party/fbgemm/external/googletest' 2025-08-26T20:06:33.5288957Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-08-26T20:06:33.5320428Z Entering 'third_party/fbgemm/external/json' 2025-08-26T20:06:33.5355884Z Entering 'third_party/flash-attention' 2025-08-26T20:06:33.5389996Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T20:06:33.5444596Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-08-26T20:06:33.5486422Z Entering 'third_party/flatbuffers' 2025-08-26T20:06:33.5529624Z Entering 'third_party/fmt' 2025-08-26T20:06:33.5562311Z Entering 'third_party/gemmlowp/gemmlowp' 2025-08-26T20:06:33.5597233Z Entering 'third_party/gloo' 2025-08-26T20:06:33.5628821Z Entering 'third_party/googletest' 2025-08-26T20:06:33.5659245Z Entering 'third_party/ideep' 2025-08-26T20:06:33.5688507Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T20:06:33.5749572Z Entering 'third_party/ittapi' 2025-08-26T20:06:33.5779262Z Entering 'third_party/kineto' 2025-08-26T20:06:33.5815388Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T20:06:33.5839853Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T20:06:33.5865469Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T20:06:33.5888449Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T20:06:33.5913755Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T20:06:33.5936352Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T20:06:33.5966959Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T20:06:33.6031005Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T20:06:33.6057376Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T20:06:33.6121099Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T20:06:33.6147069Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T20:06:33.6177367Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T20:06:33.6202992Z Entering 'third_party/kleidiai' 2025-08-26T20:06:33.6231100Z Entering 'third_party/mimalloc' 2025-08-26T20:06:33.6262749Z Entering 'third_party/nlohmann' 2025-08-26T20:06:33.6314291Z Entering 'third_party/onnx' 2025-08-26T20:06:33.6349949Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T20:06:33.6382866Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T20:06:33.6413262Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T20:06:33.6439666Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T20:06:33.6484461Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T20:06:33.6512265Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T20:06:33.6539171Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T20:06:33.6565419Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T20:06:33.6592109Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T20:06:33.6614838Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T20:06:33.6640413Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T20:06:33.6688861Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T20:06:33.6724024Z Entering 'third_party/pocketfft' 2025-08-26T20:06:33.6751297Z Entering 'third_party/protobuf' 2025-08-26T20:06:33.6780429Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T20:06:33.6802272Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T20:06:33.6833830Z Entering 'third_party/psimd' 2025-08-26T20:06:33.6861970Z Entering 'third_party/pthreadpool' 2025-08-26T20:06:33.6891435Z Entering 'third_party/pybind11' 2025-08-26T20:06:33.6923099Z Entering 'third_party/python-peachpy' 2025-08-26T20:06:33.6950260Z Entering 'third_party/sleef' 2025-08-26T20:06:33.6978043Z Entering 'third_party/tensorpipe' 2025-08-26T20:06:33.7006812Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T20:06:33.7034749Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T20:06:33.7062742Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T20:06:33.7090255Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T20:06:33.7114352Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T20:06:33.7159113Z ##[endgroup] 2025-08-26T20:06:33.7198299Z [command]/usr/bin/git log -1 --format=%H 2025-08-26T20:06:33.7224943Z 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:06:33.7418459Z Prepare all required actions 2025-08-26T20:06:33.7418846Z Getting action download info 2025-08-26T20:06:33.9473140Z ##[group]Run ./.github/actions/setup-rocm 2025-08-26T20:06:33.9473279Z env: 2025-08-26T20:06:33.9473372Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:33.9473475Z ##[endgroup] 2025-08-26T20:06:33.9491303Z ##[group]Run dpkg -l | grep -E " rocm" 2025-08-26T20:06:33.9491499Z dpkg -l | grep -E " rocm" 2025-08-26T20:06:33.9497891Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:33.9498039Z env: 2025-08-26T20:06:33.9498140Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:33.9498243Z ##[endgroup] 2025-08-26T20:06:33.9573683Z ii rocm-cmake 0.14.0.60401-83~22.04 amd64 rocm-cmake built using CMake 2025-08-26T20:06:33.9574595Z ii rocm-core 6.4.1.60401-83~22.04 amd64 ROCm Runtime software stack 2025-08-26T20:06:33.9574912Z ii rocm-dbgapi 0.77.2.60401-83~22.04 amd64 Library to provide AMD GPU debugger API 2025-08-26T20:06:33.9575160Z ii rocm-debug-agent 2.0.4.60401-83~22.04 amd64 Radeon Open Compute Debug Agent (ROCdebug-agent) 2025-08-26T20:06:33.9575409Z ii rocm-dev 6.4.1.60401-83~22.04 amd64 Radeon Open Compute (ROCm) Runtime software stack 2025-08-26T20:06:33.9575829Z ii rocm-device-libs 1.0.0.60401-83~22.04 amd64 Radeon Open Compute - device libraries 2025-08-26T20:06:33.9576037Z ii rocm-gdb 15.2.60401-83~22.04 amd64 ROCgdb 2025-08-26T20:06:33.9576231Z ii rocm-llvm 19.0.0.25184.60401-83~22.04 amd64 ROCm core compiler 2025-08-26T20:06:33.9576435Z ii rocm-opencl 2.0.0.60401-83~22.04 amd64 clr built using CMake 2025-08-26T20:06:33.9576646Z ii rocm-opencl-dev 2.0.0.60401-83~22.04 amd64 clr built using CMake 2025-08-26T20:06:33.9576862Z ii rocm-smi-lib 7.5.0.60401-83~22.04 amd64 AMD System Management libraries 2025-08-26T20:06:33.9577082Z ii rocm-utils 6.4.1.60401-83~22.04 amd64 Radeon Open Compute (ROCm) Runtime software stack 2025-08-26T20:06:33.9577321Z ii rocminfo 1.0.0.60401-83~22.04 amd64 Radeon Open Compute (ROCm) Runtime rocminfo tool 2025-08-26T20:06:33.9588691Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T20:06:33.9588920Z # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T20:06:33.9589079Z # shellcheck disable=SC2046 2025-08-26T20:06:33.9589210Z docker stop $(docker ps -q) || true 2025-08-26T20:06:33.9589343Z # Prune all stopped containers. 2025-08-26T20:06:33.9589475Z docker container prune -f 2025-08-26T20:06:33.9595158Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:33.9595303Z env: 2025-08-26T20:06:33.9595398Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:33.9595507Z ##[endgroup] 2025-08-26T20:06:33.9907425Z docker: 'docker stop' requires at least 1 argument 2025-08-26T20:06:33.9907877Z 2025-08-26T20:06:33.9908207Z Usage: docker stop [OPTIONS] CONTAINER [CONTAINER...] 2025-08-26T20:06:33.9908553Z 2025-08-26T20:06:33.9918110Z See 'docker stop --help' for more information 2025-08-26T20:06:34.0059540Z Total reclaimed space: 0B 2025-08-26T20:06:34.0099853Z ##[group]Run cat /etc/os-release || true 2025-08-26T20:06:34.0100130Z cat /etc/os-release || true 2025-08-26T20:06:34.0100503Z cat /etc/apt/sources.list.d/rocm.list || true 2025-08-26T20:06:34.0100764Z cat /opt/rocm/.info/version || true 2025-08-26T20:06:34.0100955Z whoami 2025-08-26T20:06:34.0107843Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.0108072Z env: 2025-08-26T20:06:34.0108268Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.0108460Z ##[endgroup] 2025-08-26T20:06:34.0156585Z PRETTY_NAME="Ubuntu 22.04.5 LTS" 2025-08-26T20:06:34.0156732Z NAME="Ubuntu" 2025-08-26T20:06:34.0156850Z VERSION_ID="22.04" 2025-08-26T20:06:34.0157037Z VERSION="22.04.5 LTS (Jammy Jellyfish)" 2025-08-26T20:06:34.0157215Z VERSION_CODENAME=jammy 2025-08-26T20:06:34.0157343Z ID=ubuntu 2025-08-26T20:06:34.0157459Z ID_LIKE=debian 2025-08-26T20:06:34.0157600Z HOME_URL="https://www.ubuntu.com/" 2025-08-26T20:06:34.0157753Z SUPPORT_URL="https://help.ubuntu.com/" 2025-08-26T20:06:34.0157947Z BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/" 2025-08-26T20:06:34.0158178Z PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy" 2025-08-26T20:06:34.0158398Z UBUNTU_CODENAME=jammy 2025-08-26T20:06:34.0158637Z deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/6.4.1 jammy main 2025-08-26T20:06:34.0158861Z 6.4.1-83 2025-08-26T20:06:34.0192114Z runner 2025-08-26T20:06:34.0208816Z ##[group]Run dpkg -l | grep -E " amdgpu" 2025-08-26T20:06:34.0209020Z dpkg -l | grep -E " amdgpu" 2025-08-26T20:06:34.0214736Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.0214912Z env: 2025-08-26T20:06:34.0215050Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.0215326Z ##[endgroup] 2025-08-26T20:06:34.0272692Z ii amdgpu-core 1:6.4.60401-2164967.22.04 all Core meta package for unified amdgpu driver. 2025-08-26T20:06:34.0272990Z ii amdgpu-install 6.4.60401-2164967.22.04 all AMDGPU driver repository and installer 2025-08-26T20:06:34.0288503Z ##[group]Run rocm-smi 2025-08-26T20:06:34.0288703Z rocm-smi 2025-08-26T20:06:34.0294387Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.0294633Z env: 2025-08-26T20:06:34.0294783Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.0295033Z ##[endgroup] 2025-08-26T20:06:34.0811111Z 2025-08-26T20:06:34.0812039Z 2025-08-26T20:06:34.0812297Z ============================================ ROCm System Management Interface ============================================ 2025-08-26T20:06:34.0816761Z ====================================================== Concise Info ====================================================== 2025-08-26T20:06:34.0817105Z Device Node IDs Temp Power Partitions SCLK MCLK Fan Perf PwrCap VRAM% GPU% 2025-08-26T20:06:34.0817634Z  (DID, GUID) (Junction) (Socket) (Mem, Compute, ID)  2025-08-26T20:06:34.0817900Z ========================================================================================================================== 2025-08-26T20:06:34.0818391Z 0 8 0x74b9, 27976 50.0°C 144.0W NPS1, SPX, 0 148Mhz 900Mhz 0% auto 1000.0W 0% 0% 2025-08-26T20:06:34.0818660Z ========================================================================================================================== 2025-08-26T20:06:34.0818887Z ================================================== End of ROCm SMI Log =================================================== 2025-08-26T20:06:34.0838763Z ##[group]Run rocminfo 2025-08-26T20:06:34.0838915Z rocminfo 2025-08-26T20:06:34.0845206Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.0845355Z env: 2025-08-26T20:06:34.0845444Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.0845550Z ##[endgroup] 2025-08-26T20:06:34.1596575Z ROCk module version 6.12.12 is loaded 2025-08-26T20:06:34.1598509Z ===================== 2025-08-26T20:06:34.1598624Z HSA System Attributes 2025-08-26T20:06:34.1598735Z ===================== 2025-08-26T20:06:34.1598835Z Runtime Version: 1.15 2025-08-26T20:06:34.1598971Z Runtime Ext Version: 1.7 2025-08-26T20:06:34.1599396Z System Timestamp Freq.: 1000.000000MHz 2025-08-26T20:06:34.1599588Z Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count) 2025-08-26T20:06:34.1599779Z Machine Model: LARGE 2025-08-26T20:06:34.1599936Z System Endianness: LITTLE 2025-08-26T20:06:34.1600080Z Mwaitx: DISABLED 2025-08-26T20:06:34.1600203Z XNACK enabled: NO 2025-08-26T20:06:34.1600308Z DMAbuf Support: YES 2025-08-26T20:06:34.1600488Z VMM Support: YES 2025-08-26T20:06:34.1600559Z 2025-08-26T20:06:34.1600594Z ========== 2025-08-26T20:06:34.1600685Z HSA Agents 2025-08-26T20:06:34.1600952Z ========== 2025-08-26T20:06:34.1601046Z ******* 2025-08-26T20:06:34.1601281Z Agent 1 2025-08-26T20:06:34.1601383Z ******* 2025-08-26T20:06:34.1601507Z Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:06:34.1601716Z Uuid: CPU-XX 2025-08-26T20:06:34.1601863Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:06:34.1602021Z Vendor Name: CPU 2025-08-26T20:06:34.1602160Z Feature: None specified 2025-08-26T20:06:34.1602450Z Profile: FULL_PROFILE 2025-08-26T20:06:34.1602643Z Float Round Mode: NEAR 2025-08-26T20:06:34.1602799Z Max Queue Number: 0(0x0) 2025-08-26T20:06:34.1602946Z Queue Min Size: 0(0x0) 2025-08-26T20:06:34.1603086Z Queue Max Size: 0(0x0) 2025-08-26T20:06:34.1603225Z Queue Type: MULTI 2025-08-26T20:06:34.1603357Z Node: 0 2025-08-26T20:06:34.1606145Z Device Type: CPU 2025-08-26T20:06:34.1606556Z Cache Info: 2025-08-26T20:06:34.1606699Z L1: 65536(0x10000) KB 2025-08-26T20:06:34.1606837Z Chip ID: 0(0x0) 2025-08-26T20:06:34.1606973Z ASIC Revision: 0(0x0) 2025-08-26T20:06:34.1607143Z Cacheline Size: 64(0x40) 2025-08-26T20:06:34.1607288Z Max Clock Freq. (MHz): 0 2025-08-26T20:06:34.1607430Z BDFID: 0 2025-08-26T20:06:34.1607572Z Internal Node ID: 0 2025-08-26T20:06:34.1614519Z Compute Unit: 80 2025-08-26T20:06:34.1614709Z SIMDs per CU: 0 2025-08-26T20:06:34.1614858Z Shader Engines: 0 2025-08-26T20:06:34.1615017Z Shader Arrs. per Eng.: 0 2025-08-26T20:06:34.1615169Z WatchPts on Addr. Ranges:1 2025-08-26T20:06:34.1615304Z Memory Properties: 2025-08-26T20:06:34.1615410Z Features: None 2025-08-26T20:06:34.1615512Z Pool Info: 2025-08-26T20:06:34.1615627Z Pool 1 2025-08-26T20:06:34.1615757Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:06:34.1615904Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:06:34.1616049Z Allocatable: TRUE 2025-08-26T20:06:34.1616192Z Alloc Granule: 4KB 2025-08-26T20:06:34.1616343Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1616495Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1616760Z Accessible by all: TRUE 2025-08-26T20:06:34.1616888Z Pool 2 2025-08-26T20:06:34.1617010Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:06:34.1617152Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:06:34.1617291Z Allocatable: TRUE 2025-08-26T20:06:34.1617439Z Alloc Granule: 4KB 2025-08-26T20:06:34.1617588Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1617739Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1617887Z Accessible by all: TRUE 2025-08-26T20:06:34.1618022Z Pool 3 2025-08-26T20:06:34.1618144Z Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED 2025-08-26T20:06:34.1618290Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:06:34.1618431Z Allocatable: TRUE 2025-08-26T20:06:34.1618601Z Alloc Granule: 4KB 2025-08-26T20:06:34.1619183Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1619911Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1620135Z Accessible by all: TRUE 2025-08-26T20:06:34.1620287Z Pool 4 2025-08-26T20:06:34.1620469Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:06:34.1620617Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:06:34.1620758Z Allocatable: TRUE 2025-08-26T20:06:34.1620908Z Alloc Granule: 4KB 2025-08-26T20:06:34.1621072Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1621220Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1621372Z Accessible by all: TRUE 2025-08-26T20:06:34.1621567Z ISA Info: 2025-08-26T20:06:34.1621810Z ******* 2025-08-26T20:06:34.1621900Z Agent 2 2025-08-26T20:06:34.1621994Z ******* 2025-08-26T20:06:34.1622138Z Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:06:34.1622474Z Uuid: CPU-XX 2025-08-26T20:06:34.1623651Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:06:34.1623806Z Vendor Name: CPU 2025-08-26T20:06:34.1623951Z Feature: None specified 2025-08-26T20:06:34.1624092Z Profile: FULL_PROFILE 2025-08-26T20:06:34.1624241Z Float Round Mode: NEAR 2025-08-26T20:06:34.1624395Z Max Queue Number: 0(0x0) 2025-08-26T20:06:34.1624541Z Queue Min Size: 0(0x0) 2025-08-26T20:06:34.1624682Z Queue Max Size: 0(0x0) 2025-08-26T20:06:34.1624829Z Queue Type: MULTI 2025-08-26T20:06:34.1624964Z Node: 1 2025-08-26T20:06:34.1625096Z Device Type: CPU 2025-08-26T20:06:34.1625227Z Cache Info: 2025-08-26T20:06:34.1625341Z L1: 65536(0x10000) KB 2025-08-26T20:06:34.1625481Z Chip ID: 0(0x0) 2025-08-26T20:06:34.1625639Z ASIC Revision: 0(0x0) 2025-08-26T20:06:34.1625855Z Cacheline Size: 64(0x40) 2025-08-26T20:06:34.1626048Z Max Clock Freq. (MHz): 0 2025-08-26T20:06:34.1626190Z BDFID: 0 2025-08-26T20:06:34.1626399Z Internal Node ID: 1 2025-08-26T20:06:34.1626619Z Compute Unit: 80 2025-08-26T20:06:34.1626844Z SIMDs per CU: 0 2025-08-26T20:06:34.1626985Z Shader Engines: 0 2025-08-26T20:06:34.1627140Z Shader Arrs. per Eng.: 0 2025-08-26T20:06:34.1627293Z WatchPts on Addr. Ranges:1 2025-08-26T20:06:34.1627427Z Memory Properties: 2025-08-26T20:06:34.1627532Z Features: None 2025-08-26T20:06:34.1627635Z Pool Info: 2025-08-26T20:06:34.1627737Z Pool 1 2025-08-26T20:06:34.1627867Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:06:34.1628018Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:06:34.1628159Z Allocatable: TRUE 2025-08-26T20:06:34.1628305Z Alloc Granule: 4KB 2025-08-26T20:06:34.1628542Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1628694Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1628846Z Accessible by all: TRUE 2025-08-26T20:06:34.1628970Z Pool 2 2025-08-26T20:06:34.1629092Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:06:34.1629228Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:06:34.1629373Z Allocatable: TRUE 2025-08-26T20:06:34.1629528Z Alloc Granule: 4KB 2025-08-26T20:06:34.1629674Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1629830Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1629974Z Accessible by all: TRUE 2025-08-26T20:06:34.1630132Z Pool 3 2025-08-26T20:06:34.1630278Z Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED 2025-08-26T20:06:34.1630696Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:06:34.1630834Z Allocatable: TRUE 2025-08-26T20:06:34.1630976Z Alloc Granule: 4KB 2025-08-26T20:06:34.1631129Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1631286Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1631443Z Accessible by all: TRUE 2025-08-26T20:06:34.1631572Z Pool 4 2025-08-26T20:06:34.1631689Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:06:34.1631835Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:06:34.1631977Z Allocatable: TRUE 2025-08-26T20:06:34.1632130Z Alloc Granule: 4KB 2025-08-26T20:06:34.1632278Z Alloc Recommended Granule:4KB 2025-08-26T20:06:34.1632428Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1632574Z Accessible by all: TRUE 2025-08-26T20:06:34.1632704Z ISA Info: 2025-08-26T20:06:34.1632800Z ******* 2025-08-26T20:06:34.1632892Z Agent 3 2025-08-26T20:06:34.1632984Z ******* 2025-08-26T20:06:34.1633136Z Name: gfx942 2025-08-26T20:06:34.1633274Z Uuid: GPU-59b2d2c78b3baecf 2025-08-26T20:06:34.1633424Z Marketing Name: AMD Instinct Mi325X VF 2025-08-26T20:06:34.1633577Z Vendor Name: AMD 2025-08-26T20:06:34.1633716Z Feature: KERNEL_DISPATCH 2025-08-26T20:06:34.1633855Z Profile: BASE_PROFILE 2025-08-26T20:06:34.1634002Z Float Round Mode: NEAR 2025-08-26T20:06:34.1634150Z Max Queue Number: 128(0x80) 2025-08-26T20:06:34.1634298Z Queue Min Size: 64(0x40) 2025-08-26T20:06:34.1634440Z Queue Max Size: 131072(0x20000) 2025-08-26T20:06:34.1638545Z Queue Type: MULTI 2025-08-26T20:06:34.1638696Z Node: 2 2025-08-26T20:06:34.1638839Z Device Type: GPU 2025-08-26T20:06:34.1638967Z Cache Info: 2025-08-26T20:06:34.1639071Z L1: 32(0x20) KB 2025-08-26T20:06:34.1639192Z L2: 4096(0x1000) KB 2025-08-26T20:06:34.1639388Z L3: 262144(0x40000) KB 2025-08-26T20:06:34.1639513Z Chip ID: 29881(0x74b9) 2025-08-26T20:06:34.1639651Z ASIC Revision: 1(0x1) 2025-08-26T20:06:34.1639796Z Cacheline Size: 128(0x80) 2025-08-26T20:06:34.1639954Z Max Clock Freq. (MHz): 2100 2025-08-26T20:06:34.1640086Z BDFID: 35584 2025-08-26T20:06:34.1640232Z Internal Node ID: 2 2025-08-26T20:06:34.1640445Z Compute Unit: 304 2025-08-26T20:06:34.1642534Z SIMDs per CU: 4 2025-08-26T20:06:34.1642676Z Shader Engines: 32 2025-08-26T20:06:34.1642819Z Shader Arrs. per Eng.: 1 2025-08-26T20:06:34.1642973Z WatchPts on Addr. Ranges:4 2025-08-26T20:06:34.1643121Z Coherent Host Access: FALSE 2025-08-26T20:06:34.1643253Z Memory Properties: 2025-08-26T20:06:34.1643360Z Features: KERNEL_DISPATCH 2025-08-26T20:06:34.1643494Z Fast F16 Operation: TRUE 2025-08-26T20:06:34.1643660Z Wavefront Size: 64(0x40) 2025-08-26T20:06:34.1643812Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:06:34.1643950Z Workgroup Max Size per Dimension: 2025-08-26T20:06:34.1644064Z x 1024(0x400) 2025-08-26T20:06:34.1645707Z y 1024(0x400) 2025-08-26T20:06:34.1645829Z z 1024(0x400) 2025-08-26T20:06:34.1645957Z Max Waves Per CU: 32(0x20) 2025-08-26T20:06:34.1646109Z Max Work-item Per CU: 2048(0x800) 2025-08-26T20:06:34.1646250Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:06:34.1646377Z Grid Max Size per Dimension: 2025-08-26T20:06:34.1646481Z x 4294967295(0xffffffff) 2025-08-26T20:06:34.1646600Z y 4294967295(0xffffffff) 2025-08-26T20:06:34.1646724Z z 4294967295(0xffffffff) 2025-08-26T20:06:34.1646859Z Max fbarriers/Workgrp: 32 2025-08-26T20:06:34.1649748Z Packet Processor uCode:: 177 2025-08-26T20:06:34.1649914Z SDMA engine uCode:: 24 2025-08-26T20:06:34.1652001Z IOMMU Support:: None 2025-08-26T20:06:34.1652143Z Pool Info: 2025-08-26T20:06:34.1652239Z Pool 1 2025-08-26T20:06:34.1652371Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:06:34.1652514Z Size: 268107776(0xffb0000) KB 2025-08-26T20:06:34.1652653Z Allocatable: TRUE 2025-08-26T20:06:34.1652795Z Alloc Granule: 4KB 2025-08-26T20:06:34.1652946Z Alloc Recommended Granule:2048KB 2025-08-26T20:06:34.1653097Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1653249Z Accessible by all: FALSE 2025-08-26T20:06:34.1653377Z Pool 2 2025-08-26T20:06:34.1653495Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:06:34.1653635Z Size: 268107776(0xffb0000) KB 2025-08-26T20:06:34.1655052Z Allocatable: TRUE 2025-08-26T20:06:34.1655253Z Alloc Granule: 4KB 2025-08-26T20:06:34.1655402Z Alloc Recommended Granule:2048KB 2025-08-26T20:06:34.1655549Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1655694Z Accessible by all: FALSE 2025-08-26T20:06:34.1655820Z Pool 3 2025-08-26T20:06:34.1655936Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:06:34.1656067Z Size: 268107776(0xffb0000) KB 2025-08-26T20:06:34.1656207Z Allocatable: TRUE 2025-08-26T20:06:34.1656347Z Alloc Granule: 4KB 2025-08-26T20:06:34.1656493Z Alloc Recommended Granule:2048KB 2025-08-26T20:06:34.1656640Z Alloc Alignment: 4KB 2025-08-26T20:06:34.1657979Z Accessible by all: FALSE 2025-08-26T20:06:34.1658108Z Pool 4 2025-08-26T20:06:34.1658221Z Segment: GROUP 2025-08-26T20:06:34.1658350Z Size: 64(0x40) KB 2025-08-26T20:06:34.1658482Z Allocatable: FALSE 2025-08-26T20:06:34.1658622Z Alloc Granule: 0KB 2025-08-26T20:06:34.1658769Z Alloc Recommended Granule:0KB 2025-08-26T20:06:34.1658924Z Alloc Alignment: 0KB 2025-08-26T20:06:34.1659067Z Accessible by all: FALSE 2025-08-26T20:06:34.1659193Z ISA Info: 2025-08-26T20:06:34.1659285Z ISA 1 2025-08-26T20:06:34.1659406Z Name: amdgcn-amd-amdhsa--gfx942:sramecc+:xnack- 2025-08-26T20:06:34.1659567Z Machine Models: HSA_MACHINE_MODEL_LARGE 2025-08-26T20:06:34.1660948Z Profiles: HSA_PROFILE_BASE 2025-08-26T20:06:34.1661099Z Default Rounding Mode: NEAR 2025-08-26T20:06:34.1661249Z Default Rounding Mode: NEAR 2025-08-26T20:06:34.1661389Z Fast f16: TRUE 2025-08-26T20:06:34.1661529Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:06:34.1661711Z Workgroup Max Size per Dimension: 2025-08-26T20:06:34.1661831Z x 1024(0x400) 2025-08-26T20:06:34.1661950Z y 1024(0x400) 2025-08-26T20:06:34.1662065Z z 1024(0x400) 2025-08-26T20:06:34.1662194Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:06:34.1662330Z Grid Max Size per Dimension: 2025-08-26T20:06:34.1662440Z x 4294967295(0xffffffff) 2025-08-26T20:06:34.1663707Z y 4294967295(0xffffffff) 2025-08-26T20:06:34.1663827Z z 4294967295(0xffffffff) 2025-08-26T20:06:34.1663958Z FBarrier Max Size: 32 2025-08-26T20:06:34.1664081Z ISA 2 2025-08-26T20:06:34.1664217Z Name: amdgcn-amd-amdhsa--gfx9-4-generic:sramecc+:xnack- 2025-08-26T20:06:34.1664379Z Machine Models: HSA_MACHINE_MODEL_LARGE 2025-08-26T20:06:34.1664526Z Profiles: HSA_PROFILE_BASE 2025-08-26T20:06:34.1664673Z Default Rounding Mode: NEAR 2025-08-26T20:06:34.1664822Z Default Rounding Mode: NEAR 2025-08-26T20:06:34.1665007Z Fast f16: TRUE 2025-08-26T20:06:34.1665148Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:06:34.1665280Z Workgroup Max Size per Dimension: 2025-08-26T20:06:34.1666736Z x 1024(0x400) 2025-08-26T20:06:34.1667020Z y 1024(0x400) 2025-08-26T20:06:34.1667260Z z 1024(0x400) 2025-08-26T20:06:34.1667397Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:06:34.1667535Z Grid Max Size per Dimension: 2025-08-26T20:06:34.1667643Z x 4294967295(0xffffffff) 2025-08-26T20:06:34.1667771Z y 4294967295(0xffffffff) 2025-08-26T20:06:34.1667889Z z 4294967295(0xffffffff) 2025-08-26T20:06:34.1668031Z FBarrier Max Size: 32 2025-08-26T20:06:34.1668157Z *** Done *** 2025-08-26T20:06:34.1683444Z ##[group]Run ngpu=$(rocminfo | grep -c -E 'Name:.*\sgfx') 2025-08-26T20:06:34.1683634Z ngpu=$(rocminfo | grep -c -E 'Name:.*\sgfx') 2025-08-26T20:06:34.1683908Z msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified" 2025-08-26T20:06:34.1684162Z if [[ $ngpu -eq 0 ]]; then 2025-08-26T20:06:34.1684313Z  echo "Error: Failed to detect any GPUs on the runner" 2025-08-26T20:06:34.1684449Z  echo "$msg" 2025-08-26T20:06:34.1684542Z  exit 1 2025-08-26T20:06:34.1684624Z fi 2025-08-26T20:06:34.1689278Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.1689416Z env: 2025-08-26T20:06:34.1692367Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.1692485Z ##[endgroup] 2025-08-26T20:06:34.2611415Z ##[group]Run pytorch/pytorch/.github/actions/diskspace-cleanup@main 2025-08-26T20:06:34.2611570Z with: 2025-08-26T20:06:34.2611661Z diskspace-cutoff: 70 2025-08-26T20:06:34.2611757Z env: 2025-08-26T20:06:34.2611841Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.2611951Z ##[endgroup] 2025-08-26T20:06:34.2638533Z ##[group]Run set -ex 2025-08-26T20:06:34.2638675Z set -ex 2025-08-26T20:06:34.2638768Z diskspace_cutoff=70 2025-08-26T20:06:34.2638912Z docker_root_dir=$(docker info -f '{{.DockerRootDir}}') 2025-08-26T20:06:34.2639253Z if [ ! -d "$docker_root_dir" ]; then 2025-08-26T20:06:34.2639453Z  echo "Docker root directory ($docker_root_dir) does not exist. Skipping disk space check." 2025-08-26T20:06:34.2639634Z  exit 0 2025-08-26T20:06:34.2639724Z fi 2025-08-26T20:06:34.2639885Z diskspace=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //') 2025-08-26T20:06:34.2640222Z msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified" 2025-08-26T20:06:34.2640664Z if [[ "$diskspace" -ge "$diskspace_cutoff" ]] ; then 2025-08-26T20:06:34.2640806Z  docker system prune -af 2025-08-26T20:06:34.2640990Z  diskspace_new=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //') 2025-08-26T20:06:34.2641194Z  if [[ "$diskspace_new" -gt "$diskspace_cutoff" ]] ; then 2025-08-26T20:06:34.2641413Z  echo "Error: Available diskspace is less than $diskspace_cutoff percent. Not enough diskspace." 2025-08-26T20:06:34.2641603Z  echo "$msg" 2025-08-26T20:06:34.2641710Z  exit 1 2025-08-26T20:06:34.2641800Z  else 2025-08-26T20:06:34.2641915Z  difference=$((diskspace - diskspace_new)) 2025-08-26T20:06:34.2642216Z  echo "Diskspace saved: $difference percent" 2025-08-26T20:06:34.2642343Z  fi 2025-08-26T20:06:34.2642422Z fi 2025-08-26T20:06:34.2647502Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.2647636Z env: 2025-08-26T20:06:34.2647714Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.2647813Z ##[endgroup] 2025-08-26T20:06:34.2669977Z + diskspace_cutoff=70 2025-08-26T20:06:34.2672964Z ++ docker info -f '{{.DockerRootDir}}' 2025-08-26T20:06:34.3129579Z + docker_root_dir=/home/runner/docker-data 2025-08-26T20:06:34.3129964Z + '[' '!' -d /home/runner/docker-data ']' 2025-08-26T20:06:34.3136034Z ++ df -H --output=pcent /home/runner/docker-data 2025-08-26T20:06:34.3136325Z ++ sed -n 2p 2025-08-26T20:06:34.3136769Z ++ sed s/%// 2025-08-26T20:06:34.3137623Z ++ sed 's/ //' 2025-08-26T20:06:34.3151670Z + diskspace=14 2025-08-26T20:06:34.3152030Z + msg='Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified' 2025-08-26T20:06:34.3152478Z + [[ 14 -ge 70 ]] 2025-08-26T20:06:34.3187369Z ##[group]Run RUNNER_ARTIFACT_DIR="${RUNNER_TEMP}/artifacts" 2025-08-26T20:06:34.3187704Z RUNNER_ARTIFACT_DIR="${RUNNER_TEMP}/artifacts" 2025-08-26T20:06:34.3187933Z rm -rf "${RUNNER_ARTIFACT_DIR}" 2025-08-26T20:06:34.3188123Z mkdir -p "${RUNNER_ARTIFACT_DIR}" 2025-08-26T20:06:34.3188373Z echo "RUNNER_ARTIFACT_DIR=${RUNNER_ARTIFACT_DIR}" >> "${GITHUB_ENV}" 2025-08-26T20:06:34.3188600Z  2025-08-26T20:06:34.3188775Z RUNNER_TEST_RESULTS_DIR="${RUNNER_TEMP}/test-results" 2025-08-26T20:06:34.3189029Z rm -rf "${RUNNER_TEST_RESULTS_DIR}" 2025-08-26T20:06:34.3189223Z mkdir -p "${RUNNER_TEST_RESULTS_DIR}" 2025-08-26T20:06:34.3189486Z echo "RUNNER_TEST_RESULTS_DIR=${RUNNER_TEST_RESULTS_DIR}" >> "${GITHUB_ENV}" 2025-08-26T20:06:34.3189729Z  2025-08-26T20:06:34.3189868Z RUNNER_DOCS_DIR="${RUNNER_TEMP}/docs" 2025-08-26T20:06:34.3190085Z rm -rf "${RUNNER_DOCS_DIR}" 2025-08-26T20:06:34.3190263Z mkdir -p "${RUNNER_DOCS_DIR}" 2025-08-26T20:06:34.3200974Z echo "RUNNER_DOCS_DIR=${RUNNER_DOCS_DIR}" >> "${GITHUB_ENV}" 2025-08-26T20:06:34.3209289Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.3209499Z env: 2025-08-26T20:06:34.3209625Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.3209777Z ##[endgroup] 2025-08-26T20:06:34.3323840Z ##[group]Run env | grep '^GITHUB' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}" 2025-08-26T20:06:34.3324248Z env | grep '^GITHUB' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}" 2025-08-26T20:06:34.3324430Z env | grep '^CI' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}" 2025-08-26T20:06:34.3331248Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.3331392Z env: 2025-08-26T20:06:34.3331488Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.3331616Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:34.3331813Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:34.3331967Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:34.3332104Z ##[endgroup] 2025-08-26T20:06:34.3449225Z ##[group]Run # All GPUs are visible to the runner; visibility, if needed, will be set by run_test.py. 2025-08-26T20:06:34.3449659Z # All GPUs are visible to the runner; visibility, if needed, will be set by run_test.py. 2025-08-26T20:06:34.3449939Z # Add render group for container creation. 2025-08-26T20:06:34.3450214Z render_gid=`cat /etc/group | grep render | cut -d: -f3` 2025-08-26T20:06:34.3450605Z # Ensure GPU isolation if pod is part of kubernetes setup with DEVICE_FLAG. 2025-08-26T20:06:34.3450896Z if [ -f "/etc/podinfo/gha-render-devices" ]; then 2025-08-26T20:06:34.3451130Z  DEVICE_FLAG=$(cat /etc/podinfo/gha-render-devices) 2025-08-26T20:06:34.3451325Z else 2025-08-26T20:06:34.3451684Z  DEVICE_FLAG="--device /dev/dri" 2025-08-26T20:06:34.3451842Z fi 2025-08-26T20:06:34.3452095Z # The --group-add daemon and --group-add bin are needed in the Ubuntu 24.04 and Almalinux OSs respectively. 2025-08-26T20:06:34.3452490Z # This is due to the device files (/dev/kfd & /dev/dri) being owned by video group on bare metal. 2025-08-26T20:06:34.3452855Z # This video group ID maps to subgid 1 inside the docker image due to the /etc/subgid entries. 2025-08-26T20:06:34.3456205Z # The group name corresponding to group ID 1 can change depending on the OS, so both are necessary. 2025-08-26T20:06:34.3456847Z echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd $DEVICE_FLAG --group-add video --group-add $render_gid --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host" >> "${GITHUB_ENV}" 2025-08-26T20:06:34.3462790Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:34.3463004Z env: 2025-08-26T20:06:34.3463124Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.3463309Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:34.3463553Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:34.3463774Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:34.3463952Z ##[endgroup] 2025-08-26T20:06:34.3584860Z ##[group]Run aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 2025-08-26T20:06:34.3585146Z with: 2025-08-26T20:06:34.3585343Z role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only 2025-08-26T20:06:34.3585578Z aws-region: us-east-1 2025-08-26T20:06:34.3585724Z role-duration-seconds: 18000 2025-08-26T20:06:34.3585882Z audience: sts.amazonaws.com 2025-08-26T20:06:34.3586026Z env: 2025-08-26T20:06:34.3586143Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:34.3586323Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:34.3586586Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:34.3586809Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:34.3587376Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:34.3587897Z ##[endgroup] 2025-08-26T20:06:37.8811553Z Assuming role with OIDC 2025-08-26T20:06:38.0015852Z Authenticated as assumedRoleId AROAUPVRELQNLLCOPFEJR:GitHubActions 2025-08-26T20:06:38.0486903Z ##[group]Run aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076 2025-08-26T20:06:38.0487093Z with: 2025-08-26T20:06:38.0487183Z mask-password: true 2025-08-26T20:06:38.0487288Z registry-type: private 2025-08-26T20:06:38.0487390Z skip-logout: false 2025-08-26T20:06:38.0487482Z env: 2025-08-26T20:06:38.0487571Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:38.0487713Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:38.0487960Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:38.0488118Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:38.0488492Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:38.0488846Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:38.0488979Z AWS_REGION: us-east-1 2025-08-26T20:06:38.0489377Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:38.0489520Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:38.0491731Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:38.0491829Z ##[endgroup] 2025-08-26T20:06:38.2318249Z Logging into registry 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4568263Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-08-26T20:06:38.4568731Z with: 2025-08-26T20:06:38.4569107Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4569530Z use-custom-docker-registry: true 2025-08-26T20:06:38.4569714Z docker-build-dir: .ci/docker 2025-08-26T20:06:38.4569875Z docker-build-script: ./build.sh 2025-08-26T20:06:38.4570003Z working-directory: . 2025-08-26T20:06:38.4570146Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4570308Z force-push: false 2025-08-26T20:06:38.4570521Z env: 2025-08-26T20:06:38.4570617Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:38.4570762Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:38.4570977Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:38.4571188Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:38.4571580Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:38.4571966Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:38.4572093Z AWS_REGION: us-east-1 2025-08-26T20:06:38.4572350Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:38.4572509Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:38.4574902Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:38.4575064Z ##[endgroup] 2025-08-26T20:06:38.4593009Z ##[group]Run set -ex 2025-08-26T20:06:38.4593182Z set -ex 2025-08-26T20:06:38.4593323Z  2025-08-26T20:06:38.4593489Z # If the docker build directory or the build script doesn't exist, the action will 2025-08-26T20:06:38.4593736Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-08-26T20:06:38.4594013Z # job could then download the pre-built image as usual 2025-08-26T20:06:38.4594389Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-08-26T20:06:38.4594715Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4594905Z else 2025-08-26T20:06:38.4595047Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4595279Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4595504Z  2025-08-26T20:06:38.4595796Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-08-26T20:06:38.4596117Z  exit 0 2025-08-26T20:06:38.4596248Z fi 2025-08-26T20:06:38.4600675Z  2025-08-26T20:06:38.4600873Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-08-26T20:06:38.4601181Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-08-26T20:06:38.4601472Z  # use it as it is, but first let's extract the tag 2025-08-26T20:06:38.4601724Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-08-26T20:06:38.4601983Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4602255Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4602461Z else 2025-08-26T20:06:38.4602607Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-08-26T20:06:38.4602809Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-08-26T20:06:38.4603017Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-08-26T20:06:38.4603193Z  fi 2025-08-26T20:06:38.4603592Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-08-26T20:06:38.4603911Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4604316Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4604675Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4604891Z fi 2025-08-26T20:06:38.4612064Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:38.4612209Z env: 2025-08-26T20:06:38.4612301Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:38.4612433Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:38.4612606Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:38.4615330Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:38.4615727Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:38.4616100Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:38.4616214Z AWS_REGION: us-east-1 2025-08-26T20:06:38.4616401Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:38.4616547Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:38.4618712Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:38.4618814Z REPO_NAME: pytorch 2025-08-26T20:06:38.4619089Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4619382Z DOCKER_BUILD_DIR: .ci/docker 2025-08-26T20:06:38.4619496Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-08-26T20:06:38.4621787Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4621945Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-08-26T20:06:38.4622060Z CUSTOM_TAG_PREFIX: 2025-08-26T20:06:38.4622160Z ##[endgroup] 2025-08-26T20:06:38.4652975Z + [[ -d .ci/docker ]] 2025-08-26T20:06:38.4653519Z + [[ -f .ci/docker/./build.sh ]] 2025-08-26T20:06:38.4660023Z + [[ true == \t\r\u\e ]] 2025-08-26T20:06:38.4660167Z + echo skip=false 2025-08-26T20:06:38.4660742Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]] 2025-08-26T20:06:38.4678632Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4678934Z ++ awk -F '[:,]' '{print $2}' 2025-08-26T20:06:38.4691418Z + DOCKER_TAG=pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4691775Z + echo docker-tag=pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4692201Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4735431Z ##[group]Run set +e 2025-08-26T20:06:38.4738371Z set +e 2025-08-26T20:06:38.4738512Z set -x 2025-08-26T20:06:38.4738641Z  2025-08-26T20:06:38.4738763Z login() { 2025-08-26T20:06:38.4739035Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-08-26T20:06:38.4739307Z } 2025-08-26T20:06:38.4739425Z  2025-08-26T20:06:38.4739546Z retry () { 2025-08-26T20:06:38.4739700Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-08-26T20:06:38.4739875Z } 2025-08-26T20:06:38.4742438Z  2025-08-26T20:06:38.4742577Z retry login "${DOCKER_REGISTRY}" 2025-08-26T20:06:38.4742748Z  2025-08-26T20:06:38.4742874Z START_TIME=$(date +%s) 2025-08-26T20:06:38.4743038Z # Wait up to 120 minutes 2025-08-26T20:06:38.4743467Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-08-26T20:06:38.4743731Z  # Check if image already exists, if it does then skip building it 2025-08-26T20:06:38.4744165Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-08-26T20:06:38.4744360Z  exit 0 2025-08-26T20:06:38.4744491Z  fi 2025-08-26T20:06:38.4744613Z  2025-08-26T20:06:38.4744822Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-08-26T20:06:38.4745172Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-08-26T20:06:38.4745516Z  # latter, it will wait for the Docker images to become available before continuing 2025-08-26T20:06:38.4747903Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-08-26T20:06:38.4748127Z  # It's a Docker build job, let's build the image 2025-08-26T20:06:38.4748313Z  break 2025-08-26T20:06:38.4748450Z  else 2025-08-26T20:06:38.4748634Z  # It's a regular build job, wait for the image to become available 2025-08-26T20:06:38.4748858Z  sleep 300 2025-08-26T20:06:38.4748994Z  fi 2025-08-26T20:06:38.4749115Z done 2025-08-26T20:06:38.4749235Z  2025-08-26T20:06:38.4749422Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-08-26T20:06:38.4749714Z # be empty. The default action would be to continue rebuild the image 2025-08-26T20:06:38.4752114Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-08-26T20:06:38.4752363Z  # if we're on the base branch then use the parent commit 2025-08-26T20:06:38.4752577Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-08-26T20:06:38.4752746Z else 2025-08-26T20:06:38.4752921Z  # otherwise we're on a PR, so use the most recent base commit 2025-08-26T20:06:38.4753178Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-08-26T20:06:38.4753368Z fi 2025-08-26T20:06:38.4753490Z  2025-08-26T20:06:38.4753619Z if [[ -z "${MERGE_BASE}" ]]; then 2025-08-26T20:06:38.4753814Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4753990Z  2025-08-26T20:06:38.4756213Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-08-26T20:06:38.4756499Z  exit 0 2025-08-26T20:06:38.4756624Z fi 2025-08-26T20:06:38.4756740Z  2025-08-26T20:06:38.4756905Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-08-26T20:06:38.4757254Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-08-26T20:06:38.4757552Z  exit 1 2025-08-26T20:06:38.4757675Z fi 2025-08-26T20:06:38.4757790Z  2025-08-26T20:06:38.4757989Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-08-26T20:06:38.4758331Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-08-26T20:06:38.4760676Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-08-26T20:06:38.4761028Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-08-26T20:06:38.4761419Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-08-26T20:06:38.4761656Z fi 2025-08-26T20:06:38.4761772Z  2025-08-26T20:06:38.4761915Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-08-26T20:06:38.4769693Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:38.4769898Z env: 2025-08-26T20:06:38.4770026Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:38.4770217Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:38.4773002Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:38.4773319Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:38.4773876Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:38.4774415Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:38.4774576Z AWS_REGION: us-east-1 2025-08-26T20:06:38.4774893Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:38.4775118Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:38.4778489Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:38.4778642Z DOCKER_BUILD_DIR: .ci/docker 2025-08-26T20:06:38.4778831Z BASE_REVISION: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:06:38.4781666Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4782215Z DOCKER_TAG: pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:38.4782560Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4782777Z DOCKER_PUSH: 2025-08-26T20:06:38.4782911Z ##[endgroup] 2025-08-26T20:06:38.4822228Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4822688Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4822873Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:38.4823135Z /home/runner/_work/_temp/8b1d6946-c450-4b05-829d-1d9103fe2667.sh: line 5: aws: command not found 2025-08-26T20:06:38.4823429Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:38.4991590Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:38.5010534Z + sleep 1 2025-08-26T20:06:39.5026790Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:39.5028092Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:39.5028435Z /home/runner/_work/_temp/8b1d6946-c450-4b05-829d-1d9103fe2667.sh: line 5: aws: command not found 2025-08-26T20:06:39.5028847Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:39.5169889Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:39.5185024Z + sleep 2 2025-08-26T20:06:41.5222297Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:41.5224824Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:41.5261362Z /home/runner/_work/_temp/8b1d6946-c450-4b05-829d-1d9103fe2667.sh: line 5: aws: command not found 2025-08-26T20:06:41.5263786Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:41.5357140Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:41.5400218Z ++ date +%s 2025-08-26T20:06:41.5410958Z + START_TIME=1756238801 2025-08-26T20:06:41.5413646Z ++ date +%s 2025-08-26T20:06:41.5418360Z + [[ 1756231601 -lt 1756238801 ]] 2025-08-26T20:06:41.5418793Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:42.1142278Z { 2025-08-26T20:06:42.1148880Z "schemaVersion": 2, 2025-08-26T20:06:42.1149130Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-08-26T20:06:42.1149316Z "config": { 2025-08-26T20:06:42.1149455Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-08-26T20:06:42.1149617Z "size": 28683, 2025-08-26T20:06:42.1149791Z 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"sha256:175354e949d8ca7e0011ecf31fcbc8cadc0d9b0caeb3b03b2b7187988708ab3a" 2025-08-26T20:06:42.1178026Z }, 2025-08-26T20:06:42.1178101Z { 2025-08-26T20:06:42.1178217Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1178359Z "size": 1556, 2025-08-26T20:06:42.1178502Z "digest": "sha256:353055e75788a3b2be9bc7993478f2d11c1ecb0f915718122c183bc953996acf" 2025-08-26T20:06:42.1178661Z }, 2025-08-26T20:06:42.1178729Z { 2025-08-26T20:06:42.1178844Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1178987Z "size": 107, 2025-08-26T20:06:42.1179221Z "digest": "sha256:b3e4bfbe567432cee4b0e83efddac7dfcc5b60da6140bf8af07704d2dfba24de" 2025-08-26T20:06:42.1179422Z }, 2025-08-26T20:06:42.1180615Z { 2025-08-26T20:06:42.1180736Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1180878Z "size": 166, 2025-08-26T20:06:42.1181024Z "digest": "sha256:0766a0a2d9c14b317beb592c08fe1a94224a1b5f0a1a96bfa776c79a8a39df27" 2025-08-26T20:06:42.1181185Z }, 2025-08-26T20:06:42.1181253Z { 2025-08-26T20:06:42.1181369Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1181512Z "size": 2935819, 2025-08-26T20:06:42.1181662Z "digest": "sha256:f5e863d38b24f4c7693aa71acfb2760eb4fe36d8b727644dca1d30f8eac6c86d" 2025-08-26T20:06:42.1181823Z }, 2025-08-26T20:06:42.1181892Z { 2025-08-26T20:06:42.1183025Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1183173Z "size": 107, 2025-08-26T20:06:42.1183326Z "digest": "sha256:73977e43e6de5e1155366aba3c542484b24a2dc61b744a6247fd362a54f1be69" 2025-08-26T20:06:42.1183490Z }, 2025-08-26T20:06:42.1183558Z { 2025-08-26T20:06:42.1183675Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1183817Z "size": 801, 2025-08-26T20:06:42.1183961Z "digest": "sha256:0780d907ae807ef4dd1a41727c5956ed8649b1fd8aa1e97b1eb36b4e86c25c3b" 2025-08-26T20:06:42.1184120Z }, 2025-08-26T20:06:42.1184188Z { 2025-08-26T20:06:42.1184302Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1185450Z "size": 26116693, 2025-08-26T20:06:42.1185614Z "digest": "sha256:ca98eafdf4d46d0bc2bdc9c7df537c84227b6d9dee92bd7fffa34d38082bd5eb" 2025-08-26T20:06:42.1185781Z }, 2025-08-26T20:06:42.1185850Z { 2025-08-26T20:06:42.1185967Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1186110Z "size": 104, 2025-08-26T20:06:42.1186268Z "digest": "sha256:0c6dc4dd8b3325b46d5bb1b8d16afc490a8f1e88e14cac557b1609f9905328ee" 2025-08-26T20:06:42.1186431Z }, 2025-08-26T20:06:42.1186503Z { 2025-08-26T20:06:42.1186617Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1186759Z "size": 425, 2025-08-26T20:06:42.1187983Z "digest": "sha256:ed513177343626d0fc58cb7e560eeac3b73103e15afae1ce0ca4e3d5fa7cbf82" 2025-08-26T20:06:42.1188158Z }, 2025-08-26T20:06:42.1188228Z { 2025-08-26T20:06:42.1188343Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1188486Z "size": 19316502, 2025-08-26T20:06:42.1188640Z "digest": "sha256:115f187abeac13153e7bdd41d434cce086fdfaa7e7f262adec545227ebb27f4f" 2025-08-26T20:06:42.1188802Z }, 2025-08-26T20:06:42.1188871Z { 2025-08-26T20:06:42.1188985Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1189126Z "size": 638, 2025-08-26T20:06:42.1189274Z "digest": "sha256:c4ac9ebc03ab58a5a35c219b20ce28f6b9668650431756557bc83c229a80da81" 2025-08-26T20:06:42.1190540Z }, 2025-08-26T20:06:42.1190614Z { 2025-08-26T20:06:42.1190734Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1190878Z "size": 724, 2025-08-26T20:06:42.1191023Z "digest": "sha256:13792f6142bb7a1ef0a78094cc19143b3302ac9aec9b5b76d8714461dbaec2f7" 2025-08-26T20:06:42.1191183Z }, 2025-08-26T20:06:42.1191252Z { 2025-08-26T20:06:42.1191369Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1191512Z "size": 150, 2025-08-26T20:06:42.1191661Z "digest": "sha256:0f80df9ec0a8a113633055bdc12da0fabd29444b5aea12d835a7cfe369e53091" 2025-08-26T20:06:42.1191825Z }, 2025-08-26T20:06:42.1192956Z { 2025-08-26T20:06:42.1193078Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1193261Z "size": 135, 2025-08-26T20:06:42.1193409Z "digest": "sha256:d773426c510cfaf9ad3ef6fa9f286b3d5012ba21d3d4402d9900fa3eb7a0294a" 2025-08-26T20:06:42.1193571Z }, 2025-08-26T20:06:42.1193692Z { 2025-08-26T20:06:42.1193807Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1193999Z "size": 139, 2025-08-26T20:06:42.1194143Z "digest": "sha256:bc0360305afdd11186fb1562b4cc1ea276b8b611c049061e5e6acab2b35de3bc" 2025-08-26T20:06:42.1194304Z }, 2025-08-26T20:06:42.1194373Z { 2025-08-26T20:06:42.1195510Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1195658Z "size": 32, 2025-08-26T20:06:42.1195808Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-08-26T20:06:42.1195972Z }, 2025-08-26T20:06:42.1196039Z { 2025-08-26T20:06:42.1196154Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1196297Z "size": 222, 2025-08-26T20:06:42.1196447Z "digest": "sha256:71e9cdca0882ba84e9d3040ac1ee71f879929e638a16643d25a9671dfbf2a9d0" 2025-08-26T20:06:42.1196607Z }, 2025-08-26T20:06:42.1196675Z { 2025-08-26T20:06:42.1196795Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1197907Z "size": 346, 2025-08-26T20:06:42.1198059Z "digest": "sha256:e7c2dba69e4cc3eb122ff81875cb8b8c60a9a27a806a43bd425887025833b7c1" 2025-08-26T20:06:42.1198222Z }, 2025-08-26T20:06:42.1198290Z { 2025-08-26T20:06:42.1198404Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1198548Z "size": 88301, 2025-08-26T20:06:42.1198698Z "digest": "sha256:ec50dcb9c55427e3c0bf246d386eb7286fa64ce3235626ad04486c101000cb3a" 2025-08-26T20:06:42.1198858Z }, 2025-08-26T20:06:42.1198926Z { 2025-08-26T20:06:42.1199042Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1199184Z "size": 106, 2025-08-26T20:06:42.1200418Z "digest": "sha256:f0fca222de7a6a26df422d6e670746322853c39ad9c9c429b2900d013cd50c77" 2025-08-26T20:06:42.1200579Z }, 2025-08-26T20:06:42.1200648Z { 2025-08-26T20:06:42.1200770Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1200912Z "size": 1664, 2025-08-26T20:06:42.1201063Z "digest": "sha256:22a030503b345b73b860c6182ae3e2d7e0cd1b2668a744d31494827167bc4517" 2025-08-26T20:06:42.1201220Z }, 2025-08-26T20:06:42.1201288Z { 2025-08-26T20:06:42.1201402Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1201543Z "size": 724, 2025-08-26T20:06:42.1201687Z "digest": "sha256:13792f6142bb7a1ef0a78094cc19143b3302ac9aec9b5b76d8714461dbaec2f7" 2025-08-26T20:06:42.1202831Z }, 2025-08-26T20:06:42.1202901Z { 2025-08-26T20:06:42.1203018Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1203162Z "size": 138, 2025-08-26T20:06:42.1203310Z "digest": "sha256:69f78ebbc5f8918051c3894a8fcc363e137fbefb1bb3379547cda2e08e0ff682" 2025-08-26T20:06:42.1203473Z }, 2025-08-26T20:06:42.1203542Z { 2025-08-26T20:06:42.1203654Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1203801Z "size": 120, 2025-08-26T20:06:42.1203946Z "digest": "sha256:1a37b62fcfe458ec818b986cfa5e326596551091acb548856a5e1fef880c95db" 2025-08-26T20:06:42.1204111Z }, 2025-08-26T20:06:42.1209091Z { 2025-08-26T20:06:42.1209228Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1209379Z "size": 5381424049, 2025-08-26T20:06:42.1209538Z "digest": "sha256:d8bb6a144a063086947836baaaabe1db6772a053c8791eae8cc4a7ebd8b71d7f" 2025-08-26T20:06:42.1209704Z }, 2025-08-26T20:06:42.1209774Z { 2025-08-26T20:06:42.1209892Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1210037Z "size": 176, 2025-08-26T20:06:42.1210186Z "digest": "sha256:e140e9e2b329095fe6ccfcccf30f32683e738d7a790b9e2acad2896ba8646805" 2025-08-26T20:06:42.1210434Z }, 2025-08-26T20:06:42.1210504Z { 2025-08-26T20:06:42.1211759Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1211910Z "size": 1896, 2025-08-26T20:06:42.1212124Z "digest": "sha256:434bc8db92449889e8fbdcc32442ffeba611d4b681f1d8dab72226ece5d19d27" 2025-08-26T20:06:42.1212321Z }, 2025-08-26T20:06:42.1212389Z { 2025-08-26T20:06:42.1212504Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1212650Z "size": 162685319, 2025-08-26T20:06:42.1212805Z "digest": "sha256:ea883bc4ae08b29aa9b79235c1134677ff4355abe3ea7ce8b447a51a63e27bb6" 2025-08-26T20:06:42.1212967Z }, 2025-08-26T20:06:42.1213035Z { 2025-08-26T20:06:42.1213150Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1214220Z "size": 305, 2025-08-26T20:06:42.1214367Z "digest": "sha256:d221e08864cf57e509d72910147549a620ea91ca3e9e210651539991b1fc9428" 2025-08-26T20:06:42.1214524Z }, 2025-08-26T20:06:42.1214592Z { 2025-08-26T20:06:42.1214706Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1214851Z "size": 32, 2025-08-26T20:06:42.1215003Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-08-26T20:06:42.1215167Z }, 2025-08-26T20:06:42.1215243Z { 2025-08-26T20:06:42.1215357Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1215497Z "size": 108, 2025-08-26T20:06:42.1216589Z "digest": "sha256:b677407565cc9bc8283544481263c9abcce1f6c9ebd694eb647d9b5985ad9e61" 2025-08-26T20:06:42.1216754Z }, 2025-08-26T20:06:42.1216824Z { 2025-08-26T20:06:42.1216938Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T20:06:42.1217082Z "size": 54145698, 2025-08-26T20:06:42.1217229Z "digest": "sha256:95980b29f13507a56065db990925f057374e0373a460bf92afa310b6088f8ab6" 2025-08-26T20:06:42.1217385Z } 2025-08-26T20:06:42.1217453Z ] 2025-08-26T20:06:42.1217525Z } 2025-08-26T20:06:42.1217607Z + exit 0 2025-08-26T20:06:42.1245489Z ##[group]Run set -eux 2025-08-26T20:06:42.1245611Z set -eux 2025-08-26T20:06:42.1245771Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-08-26T20:06:42.1246176Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin || true 2025-08-26T20:06:42.1252363Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:42.1252505Z env: 2025-08-26T20:06:42.1252597Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:42.1252724Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:42.1254961Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:42.1255122Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:42.1255492Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:42.1255852Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:42.1255961Z AWS_REGION: us-east-1 2025-08-26T20:06:42.1256206Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:42.1256348Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:42.1258392Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:42.1258489Z ##[endgroup] 2025-08-26T20:06:42.1286145Z + jq --raw-output .SecretString 2025-08-26T20:06:42.1286317Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-08-26T20:06:42.1286489Z + jq -r .docker_hub_readonly_token 2025-08-26T20:06:42.1287411Z /home/runner/_work/_temp/518579dc-732c-4b0c-a494-10a779f51fb5.sh: line 3: aws: command not found 2025-08-26T20:06:42.1287644Z + docker login --username pytorchbot --password-stdin 2025-08-26T20:06:42.1374078Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:42.1381503Z + true 2025-08-26T20:06:42.1469713Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-08-26T20:06:42.1469894Z with: 2025-08-26T20:06:42.1470161Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:42.1470716Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:42.1470859Z env: 2025-08-26T20:06:42.1470945Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:42.1471073Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:42.1473531Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:42.1473700Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:42.1474078Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:42.1474460Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:42.1474571Z AWS_REGION: us-east-1 2025-08-26T20:06:42.1474765Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:42.1474906Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:42.1476964Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:42.1477062Z ##[endgroup] 2025-08-26T20:06:42.1492016Z ##[group]Run set -x 2025-08-26T20:06:42.1492193Z set -x 2025-08-26T20:06:42.1492323Z set +e 2025-08-26T20:06:42.1492451Z  2025-08-26T20:06:42.1492570Z login() { 2025-08-26T20:06:42.1495091Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-08-26T20:06:42.1495278Z } 2025-08-26T20:06:42.1495360Z  2025-08-26T20:06:42.1495439Z retry () { 2025-08-26T20:06:42.1495545Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-08-26T20:06:42.1495662Z } 2025-08-26T20:06:42.1495741Z  2025-08-26T20:06:42.1495833Z retry login "${DOCKER_REGISTRY}" 2025-08-26T20:06:42.1495944Z  2025-08-26T20:06:42.1496120Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-08-26T20:06:42.1496364Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-08-26T20:06:42.1498542Z  2025-08-26T20:06:42.1498622Z set -e 2025-08-26T20:06:42.1498751Z # ignore output since only exit code is used for conditional 2025-08-26T20:06:42.1498930Z # only pull docker image if it's not available locally 2025-08-26T20:06:42.1499124Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-08-26T20:06:42.1499303Z  retry docker pull "${DOCKER_IMAGE}" 2025-08-26T20:06:42.1499418Z fi 2025-08-26T20:06:42.1505642Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:06:42.1505835Z env: 2025-08-26T20:06:42.1505954Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:06:42.1509261Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:06:42.1509511Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:06:42.1509741Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:06:42.1510282Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:06:42.1511117Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:06:42.1511276Z AWS_REGION: us-east-1 2025-08-26T20:06:42.1511476Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:06:42.1511680Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:06:42.1514983Z AWS_SESSION_TOKEN: *** 2025-08-26T20:06:42.1515380Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:42.1515994Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:42.1519081Z ##[endgroup] 2025-08-26T20:06:42.1540290Z + set +e 2025-08-26T20:06:42.1547638Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:42.1548185Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:42.1548513Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:42.1548738Z /home/runner/_work/_temp/c9a1baa1-5f83-4419-952f-a26b19be5c6c.sh: line 5: aws: command not found 2025-08-26T20:06:42.1549009Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:42.1684115Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:42.1727218Z + sleep 1 2025-08-26T20:06:43.1739622Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:43.1740865Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:43.1742044Z /home/runner/_work/_temp/c9a1baa1-5f83-4419-952f-a26b19be5c6c.sh: line 5: aws: command not found 2025-08-26T20:06:43.1747750Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:43.1925381Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:43.1957773Z + sleep 2 2025-08-26T20:06:45.1983258Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:45.1988035Z + aws ecr get-login-password --region us-east-1 2025-08-26T20:06:45.1996486Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T20:06:45.1996775Z /home/runner/_work/_temp/c9a1baa1-5f83-4419-952f-a26b19be5c6c.sh: line 5: aws: command not found 2025-08-26T20:06:45.2163895Z Error: Cannot perform an interactive login from a non TTY device 2025-08-26T20:06:45.2207507Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:45.2208920Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-08-26T20:06:45.7593201Z + IMAGE_SIZE=18052.863626480103 2025-08-26T20:06:45.7593980Z + echo 'Compressed size of image in MB: 18052.863626480103' 2025-08-26T20:06:45.7594127Z + set -e 2025-08-26T20:06:45.7594427Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:45.7594767Z Compressed size of image in MB: 18052.863626480103 2025-08-26T20:06:45.7791014Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:45.7791648Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:06:46.2343401Z pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6: Pulling from pytorch/ci-image 2025-08-26T20:06:46.2343723Z baa9e71a063a: Pulling fs layer 2025-08-26T20:06:46.2343863Z bc6828dc3a67: Pulling fs layer 2025-08-26T20:06:46.2343977Z b887bec4cf5f: Pulling fs layer 2025-08-26T20:06:46.2344085Z ac0275b0c502: Pulling fs layer 2025-08-26T20:06:46.2344192Z 211b0b40d45c: Pulling fs layer 2025-08-26T20:06:46.2351222Z ab2a2f72897f: Pulling fs layer 2025-08-26T20:06:46.2351346Z eaee181d3395: Pulling fs layer 2025-08-26T20:06:46.2351455Z 2fe00c81249f: Pulling fs layer 2025-08-26T20:06:46.2351572Z c6de97442ffc: Pulling fs layer 2025-08-26T20:06:46.2351679Z 13792f6142bb: Pulling fs layer 2025-08-26T20:06:46.2351786Z e5ac4d48efc3: Pulling fs layer 2025-08-26T20:06:46.2351894Z 949734882de5: Pulling fs layer 2025-08-26T20:06:46.2352003Z f8723952d07e: Pulling fs layer 2025-08-26T20:06:46.2352111Z c4b66cb3e145: Pulling fs layer 2025-08-26T20:06:46.2352219Z 8baee5f65179: Pulling fs layer 2025-08-26T20:06:46.2352325Z 7e9e15046c34: Pulling fs layer 2025-08-26T20:06:46.2352431Z 871987a9d99e: Pulling fs layer 2025-08-26T20:06:46.2352542Z f0d522e2a878: Pulling fs layer 2025-08-26T20:06:46.2352956Z ed2742eeca4e: Pulling fs layer 2025-08-26T20:06:46.2353069Z bb3b42ec04fa: Pulling fs layer 2025-08-26T20:06:46.2353180Z efd60625e6e3: Pulling fs layer 2025-08-26T20:06:46.2355402Z 79e4bc31cb69: Pulling fs layer 2025-08-26T20:06:46.2355648Z af0f3532665e: Pulling fs layer 2025-08-26T20:06:46.2355753Z 175354e949d8: Pulling fs layer 2025-08-26T20:06:46.2355857Z 353055e75788: Pulling fs layer 2025-08-26T20:06:46.2355961Z b3e4bfbe5674: Pulling fs layer 2025-08-26T20:06:46.2356065Z 0766a0a2d9c1: Pulling fs layer 2025-08-26T20:06:46.2356170Z f5e863d38b24: Pulling fs layer 2025-08-26T20:06:46.2356274Z 73977e43e6de: Pulling fs layer 2025-08-26T20:06:46.2356376Z 0780d907ae80: Pulling fs layer 2025-08-26T20:06:46.2356481Z ca98eafdf4d4: Pulling fs layer 2025-08-26T20:06:46.2356586Z 0c6dc4dd8b33: Pulling fs layer 2025-08-26T20:06:46.2357968Z ed5131773436: Pulling fs layer 2025-08-26T20:06:46.2358079Z 115f187abeac: Pulling fs layer 2025-08-26T20:06:46.2358183Z c4ac9ebc03ab: Pulling fs layer 2025-08-26T20:06:46.2358298Z 0f80df9ec0a8: Pulling fs layer 2025-08-26T20:06:46.2358403Z d773426c510c: Pulling fs layer 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ac0275b0c502: Waiting 2025-08-26T20:06:46.2362686Z 211b0b40d45c: Waiting 2025-08-26T20:06:46.2362781Z ab2a2f72897f: Waiting 2025-08-26T20:06:46.2362872Z eaee181d3395: Waiting 2025-08-26T20:06:46.2362967Z 2fe00c81249f: Waiting 2025-08-26T20:06:46.2363054Z c6de97442ffc: Waiting 2025-08-26T20:06:46.2363140Z 13792f6142bb: Waiting 2025-08-26T20:06:46.2363226Z e5ac4d48efc3: Waiting 2025-08-26T20:06:46.2363313Z 949734882de5: Waiting 2025-08-26T20:06:46.2363397Z f8723952d07e: Waiting 2025-08-26T20:06:46.2363483Z c4b66cb3e145: Waiting 2025-08-26T20:06:46.2363571Z 8baee5f65179: Waiting 2025-08-26T20:06:46.2364715Z 7e9e15046c34: Waiting 2025-08-26T20:06:46.2364805Z 871987a9d99e: Waiting 2025-08-26T20:06:46.2364892Z f0d522e2a878: Waiting 2025-08-26T20:06:46.2364979Z ed2742eeca4e: Waiting 2025-08-26T20:06:46.2365066Z bb3b42ec04fa: Waiting 2025-08-26T20:06:46.2365152Z efd60625e6e3: Waiting 2025-08-26T20:06:46.2365239Z 79e4bc31cb69: Waiting 2025-08-26T20:06:46.2365333Z af0f3532665e: Waiting 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complete 2025-08-26T20:06:49.6138022Z c4b66cb3e145: Verifying Checksum 2025-08-26T20:06:49.6160738Z c4b66cb3e145: Download complete 2025-08-26T20:06:49.8045660Z 8baee5f65179: Verifying Checksum 2025-08-26T20:06:49.8046664Z 8baee5f65179: Download complete 2025-08-26T20:06:49.8051867Z b887bec4cf5f: Verifying Checksum 2025-08-26T20:06:49.8058795Z b887bec4cf5f: Download complete 2025-08-26T20:06:50.0314278Z 7e9e15046c34: Verifying Checksum 2025-08-26T20:06:50.0314505Z 7e9e15046c34: Download complete 2025-08-26T20:06:50.2695360Z f0d522e2a878: Verifying Checksum 2025-08-26T20:06:50.2695519Z f0d522e2a878: Download complete 2025-08-26T20:06:50.4723174Z ed2742eeca4e: Verifying Checksum 2025-08-26T20:06:50.4723373Z ed2742eeca4e: Download complete 2025-08-26T20:06:55.4348168Z 871987a9d99e: Verifying Checksum 2025-08-26T20:06:55.4358092Z 871987a9d99e: Download complete 2025-08-26T20:06:55.7117342Z efd60625e6e3: Verifying Checksum 2025-08-26T20:06:55.7117512Z efd60625e6e3: Download complete 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308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:10:06.0201459Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:10:06.0268939Z Prepare all required actions 2025-08-26T20:10:06.0290042Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-08-26T20:10:06.0290176Z with: 2025-08-26T20:10:06.0290566Z github-token: *** 2025-08-26T20:10:06.0290663Z env: 2025-08-26T20:10:06.0290749Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:06.0290878Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:06.0291046Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:06.0291206Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:06.0291582Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:06.0291941Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:06.0292049Z AWS_REGION: us-east-1 2025-08-26T20:10:06.0292174Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:06.0292330Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:06.0294460Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:06.0294554Z ##[endgroup] 2025-08-26T20:10:06.0304615Z ##[group]Run set -eux 2025-08-26T20:10:06.0304725Z set -eux 2025-08-26T20:10:06.0304893Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-08-26T20:10:06.0313437Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:06.0313581Z env: 2025-08-26T20:10:06.0313668Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:06.0313797Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:06.0313964Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:06.0314122Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:06.0314496Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:06.0314851Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:06.0314959Z AWS_REGION: us-east-1 2025-08-26T20:10:06.0315096Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:06.0317501Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:06.0319682Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:06.0319827Z GITHUB_TOKEN: *** 2025-08-26T20:10:06.0319918Z ##[endgroup] 2025-08-26T20:10:06.0347626Z + python3 .github/scripts/get_workflow_job_id.py 17248463563 linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln 2025-08-26T20:10:06.4819348Z Setting output job-id=48946667439 2025-08-26T20:10:06.4819774Z Setting output job-name=linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:06.4956353Z Prepare all required actions 2025-08-26T20:10:06.4956568Z Getting action download info 2025-08-26T20:10:06.7156462Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-08-26T20:10:07.0882108Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-08-26T20:10:07.4809204Z ##[group]Run ./.github/actions/download-build-artifacts 2025-08-26T20:10:07.4809356Z with: 2025-08-26T20:10:07.4809455Z name: linux-noble-rocm-py3.12-mi300 2025-08-26T20:10:07.4809595Z s3-bucket: gha-artifacts 2025-08-26T20:10:07.4809696Z env: 2025-08-26T20:10:07.4809783Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:07.4809910Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:07.4810079Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:07.4810239Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:07.4810738Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:07.4811095Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:07.4811204Z AWS_REGION: us-east-1 2025-08-26T20:10:07.4811378Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:07.4811519Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:07.4813554Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:07.4813650Z ##[endgroup] 2025-08-26T20:10:07.4833184Z ##[group]Run seemethere/download-artifact-s3@v4 2025-08-26T20:10:07.4833313Z with: 2025-08-26T20:10:07.4833411Z name: linux-noble-rocm-py3.12-mi300 2025-08-26T20:10:07.4833536Z s3-bucket: gha-artifacts 2025-08-26T20:10:07.4833642Z region: us-east-1 2025-08-26T20:10:07.4833729Z env: 2025-08-26T20:10:07.4833813Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:07.4833939Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:07.4834114Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:07.4834270Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:07.4834637Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:07.4834988Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:07.4835099Z AWS_REGION: us-east-1 2025-08-26T20:10:07.4835234Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:07.4835373Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:07.4837484Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:07.4837582Z ##[endgroup] 2025-08-26T20:10:07.7232551Z (node:4751) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-08-26T20:10:07.7233054Z 2025-08-26T20:10:07.7233283Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-08-26T20:10:07.7233891Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-08-26T20:10:07.7234462Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-08-26T20:10:07.8523583Z Found 1 objects with prefix pytorch/pytorch/17248463563/linux-noble-rocm-py3.12-mi300/ 2025-08-26T20:10:07.8524256Z Starting download (1/1): /home/runner/_work/pytorch/pytorch/artifacts.zip 2025-08-26T20:10:25.2397819Z Finished download (1/1): /home/runner/_work/pytorch/pytorch/artifacts.zip 2025-08-26T20:10:25.2402907Z Artifact download has finished successfully 2025-08-26T20:10:25.2800561Z ##[group]Run unzip -o artifacts.zip 2025-08-26T20:10:25.2800721Z unzip -o artifacts.zip 2025-08-26T20:10:25.2808473Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:25.2808620Z env: 2025-08-26T20:10:25.2808713Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:25.2808844Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:25.2809206Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:25.2809367Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:25.2809748Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:25.2810112Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:25.2810222Z AWS_REGION: us-east-1 2025-08-26T20:10:25.2810489Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:25.2812497Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:25.2814596Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:25.2814697Z ##[endgroup] 2025-08-26T20:10:25.2851663Z Archive: artifacts.zip 2025-08-26T20:10:25.2852527Z creating: dist/ 2025-08-26T20:10:28.4091372Z inflating: dist/torch-2.9.0a0+git262640f-cp312-cp312-linux_x86_64.whl 2025-08-26T20:10:28.4176391Z 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2025-08-26T20:10:33.0628725Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:33.0628904Z env: 2025-08-26T20:10:33.0629259Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:33.0629418Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:33.0629616Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:33.0629793Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:33.0630191Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:33.0630744Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:33.0630878Z AWS_REGION: us-east-1 2025-08-26T20:10:33.0631137Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:33.0631442Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:33.0633539Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:33.0633663Z ##[endgroup] 2025-08-26T20:10:33.2667662Z ##[group]Run df -H 2025-08-26T20:10:33.2667864Z df -H 2025-08-26T20:10:33.2678718Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:33.2679000Z env: 2025-08-26T20:10:33.2679144Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:33.2679350Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:33.2679615Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:33.2679864Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:33.2680619Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:33.2681179Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:33.2681356Z AWS_REGION: us-east-1 2025-08-26T20:10:33.2681621Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:33.2681842Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:33.2684994Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:33.2685146Z ##[endgroup] 2025-08-26T20:10:33.2723656Z Filesystem Size Used Avail Use% Mounted on 2025-08-26T20:10:33.2724894Z overlay 2.2T 352G 1.8T 17% / 2025-08-26T20:10:33.2725212Z tmpfs 68M 0 68M 0% /dev 2025-08-26T20:10:33.2725512Z /dev/vda1 2.2T 352G 1.8T 17% /run 2025-08-26T20:10:33.2727420Z shm 68M 4.1k 68M 1% /dev/shm 2025-08-26T20:10:33.2727705Z tmpfs 1.4T 13k 1.4T 1% /run/secrets/kubernetes.io/serviceaccount 2025-08-26T20:10:33.2728608Z tmpfs 675G 0 675G 0% /proc/acpi 2025-08-26T20:10:33.2729335Z tmpfs 675G 0 675G 0% /proc/scsi 2025-08-26T20:10:33.2729513Z tmpfs 675G 0 675G 0% /sys/firmware 2025-08-26T20:10:33.2773875Z Prepare all required actions 2025-08-26T20:10:33.2774158Z Getting action download info 2025-08-26T20:10:33.4508501Z ##[group]Run ./.github/actions/download-td-artifacts 2025-08-26T20:10:33.4508654Z with: 2025-08-26T20:10:33.4508750Z env: 2025-08-26T20:10:33.4508859Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:33.4509008Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:33.4509198Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:33.4509372Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:33.4509763Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:33.4510138Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:33.4510560Z AWS_REGION: us-east-1 2025-08-26T20:10:33.4510743Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:33.4510929Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:33.4512990Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:33.4513106Z ##[endgroup] 2025-08-26T20:10:33.4551900Z ##[group]Run seemethere/download-artifact-s3@v4 2025-08-26T20:10:33.4552032Z with: 2025-08-26T20:10:33.4552118Z name: td_results 2025-08-26T20:10:33.4552217Z s3-bucket: gha-artifacts 2025-08-26T20:10:33.4552320Z region: us-east-1 2025-08-26T20:10:33.4552406Z env: 2025-08-26T20:10:33.4552489Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:33.4552623Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:33.4552792Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:33.4555270Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:33.4555698Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:33.4556075Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:33.4556185Z AWS_REGION: us-east-1 2025-08-26T20:10:33.4556321Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:33.4556463Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:33.4558485Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:33.4558582Z ##[endgroup] 2025-08-26T20:10:33.7717429Z (node:4775) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-08-26T20:10:33.7719588Z 2025-08-26T20:10:33.7719689Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-08-26T20:10:33.7719929Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-08-26T20:10:33.7720169Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-08-26T20:10:33.9085630Z Found 1 objects with prefix pytorch/pytorch/17248463563/td_results/ 2025-08-26T20:10:33.9086580Z Starting download (1/1): /home/runner/_work/pytorch/pytorch/td_results.json 2025-08-26T20:10:34.0489011Z Finished download (1/1): /home/runner/_work/pytorch/pytorch/td_results.json 2025-08-26T20:10:34.0494198Z Artifact download has finished successfully 2025-08-26T20:10:34.0857063Z ##[group]Run mkdir -p .additional_ci_files 2025-08-26T20:10:34.0857228Z mkdir -p .additional_ci_files 2025-08-26T20:10:34.0857393Z mv td_results.json .additional_ci_files/td_results.json || true 2025-08-26T20:10:34.0886455Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:34.0886613Z env: 2025-08-26T20:10:34.0886707Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:34.0886844Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:34.0887019Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:34.0887197Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:34.0887855Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:34.0888378Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:34.0888523Z AWS_REGION: us-east-1 2025-08-26T20:10:34.0888726Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:34.0888891Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:34.0891081Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:34.0891207Z ##[endgroup] 2025-08-26T20:10:34.0999990Z ##[group]Run .github/scripts/parse_ref.py 2025-08-26T20:10:34.1000184Z .github/scripts/parse_ref.py 2025-08-26T20:10:34.1011069Z shell: /usr/bin/bash -e {0} 2025-08-26T20:10:34.1011196Z env: 2025-08-26T20:10:34.1011299Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:34.1011440Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:34.1011617Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:34.1011778Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:34.1012342Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:34.1016443Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:34.1016574Z AWS_REGION: us-east-1 2025-08-26T20:10:34.1016784Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:34.1016972Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:34.1019028Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:34.1019135Z ##[endgroup] 2025-08-26T20:10:34.1204617Z Setting output branch=main 2025-08-26T20:10:34.1273516Z Prepare all required actions 2025-08-26T20:10:34.1273752Z Getting action download info 2025-08-26T20:10:34.2885054Z ##[group]Run ./.github/actions/filter-test-configs 2025-08-26T20:10:34.2885425Z with: 2025-08-26T20:10:34.2885724Z github-token: *** 2025-08-26T20:10:34.2886375Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 2, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 3, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 4, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 5, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 6, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}]} 2025-08-26T20:10:34.2887110Z job-name: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:34.2887375Z env: 2025-08-26T20:10:34.2887505Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:34.2887711Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:34.2892524Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:34.2892690Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:34.2893062Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:34.2893428Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:34.2893542Z AWS_REGION: us-east-1 2025-08-26T20:10:34.2893668Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:34.2893805Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:34.2895848Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:34.2895952Z ##[endgroup] 2025-08-26T20:10:34.2922857Z ##[group]Run nick-fields/retry@v3.0.0 2025-08-26T20:10:34.2922975Z with: 2025-08-26T20:10:34.2923065Z shell: bash 2025-08-26T20:10:34.2923155Z timeout_minutes: 10 2025-08-26T20:10:34.2923246Z max_attempts: 5 2025-08-26T20:10:34.2923337Z retry_wait_seconds: 30 2025-08-26T20:10:34.2923623Z command: set -eux # PyYAML 6.0 doesn't work with MacOS x86 anymore # This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2 python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-08-26T20:10:34.2923926Z polling_interval_seconds: 1 2025-08-26T20:10:34.2926089Z warning_on_retry: true 2025-08-26T20:10:34.2926193Z continue_on_error: false 2025-08-26T20:10:34.2926290Z env: 2025-08-26T20:10:34.2926375Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:34.2926500Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:34.2926670Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:34.2926827Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:34.2927208Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:34.2927568Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:34.2927677Z AWS_REGION: us-east-1 2025-08-26T20:10:34.2927805Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:34.2929908Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:34.2932240Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:34.2932403Z GITHUB_TOKEN: *** 2025-08-26T20:10:34.2932494Z ##[endgroup] 2025-08-26T20:10:34.3503941Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-08-26T20:10:34.4995312Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T20:10:34.6520266Z Collecting requests==2.27.1 2025-08-26T20:10:34.7550330Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-08-26T20:10:34.7891938Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 1.8 MB/s eta 0:00:00 2025-08-26T20:10:34.8539715Z Collecting pyyaml==6.0.2 2025-08-26T20:10:34.8811577Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-08-26T20:10:34.9599484Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 9.7 MB/s eta 0:00:00 2025-08-26T20:10:35.0202754Z Collecting urllib3<1.27,>=1.21.1 2025-08-26T20:10:35.0465331Z Downloading urllib3-1.26.20-py2.py3-none-any.whl (144 kB) 2025-08-26T20:10:35.0519019Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 144.2/144.2 KB 67.6 MB/s eta 0:00:00 2025-08-26T20:10:35.0895345Z Collecting certifi>=2017.4.17 2025-08-26T20:10:35.1154482Z Downloading certifi-2025.8.3-py3-none-any.whl (161 kB) 2025-08-26T20:10:35.1190707Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 161.2/161.2 KB 60.4 MB/s eta 0:00:00 2025-08-26T20:10:35.1580583Z Collecting idna<4,>=2.5 2025-08-26T20:10:35.1852599Z Downloading idna-3.10-py3-none-any.whl (70 kB) 2025-08-26T20:10:35.1962929Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 70.4/70.4 KB 9.4 MB/s eta 0:00:00 2025-08-26T20:10:35.3408706Z Collecting charset-normalizer~=2.0.0 2025-08-26T20:10:35.3666619Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-08-26T20:10:35.4422573Z Installing collected packages: urllib3, pyyaml, idna, charset-normalizer, certifi, requests 2025-08-26T20:10:35.5671862Z WARNING: The script normalizer is installed in '/home/runner/.local/bin' which is not on PATH. 2025-08-26T20:10:35.5672246Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-08-26T20:10:35.5934240Z Successfully installed certifi-2025.8.3 charset-normalizer-2.0.12 idna-3.10 pyyaml-6.0.2 requests-2.27.1 urllib3-1.26.20 2025-08-26T20:10:36.3531183Z Command completed after 1 attempt(s). 2025-08-26T20:10:36.3641215Z ##[group]Run set -x 2025-08-26T20:10:36.3641423Z set -x 2025-08-26T20:10:36.3641563Z  2025-08-26T20:10:36.3641787Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-08-26T20:10:36.3642092Z # in runner workspace 2025-08-26T20:10:36.3642319Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-08-26T20:10:36.3649458Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:36.3649676Z env: 2025-08-26T20:10:36.3649819Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:36.3650013Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:36.3650289Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:36.3650630Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:36.3651193Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:36.3651750Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:36.3651923Z AWS_REGION: us-east-1 2025-08-26T20:10:36.3652177Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:36.3652412Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:36.3655745Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:36.3655909Z ##[endgroup] 2025-08-26T20:10:36.3685936Z + python3 /home/runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-08-26T20:10:36.3791896Z Setting output branch=main 2025-08-26T20:10:36.3829683Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-08-26T20:10:36.3830021Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-08-26T20:10:36.3830156Z echo "Job name: ${JOB_NAME}" 2025-08-26T20:10:36.3830276Z  2025-08-26T20:10:36.3830542Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-08-26T20:10:36.3830721Z # in runner workspace 2025-08-26T20:10:36.3830884Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-08-26T20:10:36.3831070Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-08-26T20:10:36.3831197Z  --job-name "${JOB_NAME}" \ 2025-08-26T20:10:36.3831997Z  --test-matrix "{"include": [{"config": "default", "shard": 1, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 2, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 3, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 4, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 5, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 6, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}]}" \ 2025-08-26T20:10:36.3832640Z  --selected-test-configs "" \ 2025-08-26T20:10:36.3832773Z  --pr-number "${PR_NUMBER}" \ 2025-08-26T20:10:36.3832896Z  --tag "${TAG}" \ 2025-08-26T20:10:36.3833013Z  --event-name "${EVENT_NAME}" \ 2025-08-26T20:10:36.3833135Z  --schedule "${SCHEDULE}" \ 2025-08-26T20:10:36.3833254Z  --branch "${HEAD_BRANCH}" 2025-08-26T20:10:36.3838424Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:36.3838583Z env: 2025-08-26T20:10:36.3838676Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:36.3838813Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:36.3838987Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:36.3839158Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:36.3839539Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:36.3839902Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:36.3840016Z AWS_REGION: us-east-1 2025-08-26T20:10:36.3840182Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:36.3840329Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:36.3844031Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:36.3844245Z GITHUB_TOKEN: *** 2025-08-26T20:10:36.3844504Z JOB_NAME: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:36.3844688Z PR_NUMBER: 2025-08-26T20:10:36.3844811Z TAG: 2025-08-26T20:10:36.3844896Z EVENT_NAME: push 2025-08-26T20:10:36.3844990Z SCHEDULE: 2025-08-26T20:10:36.3845076Z HEAD_BRANCH: main 2025-08-26T20:10:36.3845172Z ##[endgroup] 2025-08-26T20:10:36.3868339Z Workflow: rocm-mi300 2025-08-26T20:10:36.3868559Z Job name: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:36.6285976Z Setting output keep-going=True 2025-08-26T20:10:36.6286180Z Setting output ci-verbose-test-logs=False 2025-08-26T20:10:36.6286404Z Setting output ci-test-showlocals=False 2025-08-26T20:10:36.6286656Z Setting output ci-no-test-timeout=False 2025-08-26T20:10:36.6286816Z Setting output ci-no-td=False 2025-08-26T20:10:36.6287051Z Setting output ci-td-distributed=False 2025-08-26T20:10:36.6287192Z Setting output is-unstable=False 2025-08-26T20:10:36.6287419Z Setting output reenabled-issues= 2025-08-26T20:10:36.6288199Z Setting output test-matrix={"include": [{"config": "default", "shard": 1, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 2, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 3, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 4, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 5, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 6, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}]} 2025-08-26T20:10:36.6289134Z Setting output is-test-matrix-empty=False 2025-08-26T20:10:36.6412460Z ##[group]Run echo "Filtered matrix:" 2025-08-26T20:10:36.6412691Z echo "Filtered matrix:" 2025-08-26T20:10:36.6413811Z echo "{"include": [{"config": "default", "shard": 1, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 2, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 3, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 4, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 5, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}, {"config": "default", "shard": 6, "num_shards": 6, "runner": "linux.rocm.gpu.gfx942.1"}]}" 2025-08-26T20:10:36.6414719Z  2025-08-26T20:10:36.6414847Z echo 2025-08-26T20:10:36.6415011Z echo "Is the current job unstable? False" 2025-08-26T20:10:36.6415204Z  2025-08-26T20:10:36.6415330Z echo 2025-08-26T20:10:36.6415483Z echo "Is keep-going label set? True" 2025-08-26T20:10:36.6423870Z  2025-08-26T20:10:36.6424003Z echo 2025-08-26T20:10:36.6424146Z echo "Reenabled issues? " 2025-08-26T20:10:36.6431605Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:36.6431818Z env: 2025-08-26T20:10:36.6431968Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:36.6432159Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:36.6432410Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:36.6432643Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:36.6433194Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:36.6433745Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:36.6436556Z AWS_REGION: us-east-1 2025-08-26T20:10:36.6436802Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:36.6437008Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:36.6440307Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:36.6440570Z ##[endgroup] 2025-08-26T20:10:36.6469060Z Filtered matrix: 2025-08-26T20:10:36.6470120Z {include: [{config: default, shard: 1, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}, {config: default, shard: 2, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}, {config: default, shard: 3, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}, {config: default, shard: 4, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}, {config: default, shard: 5, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}, {config: default, shard: 6, num_shards: 6, runner: linux.rocm.gpu.gfx942.1}]} 2025-08-26T20:10:36.6471304Z 2025-08-26T20:10:36.6471375Z Is the current job unstable? False 2025-08-26T20:10:36.6471495Z 2025-08-26T20:10:36.6471559Z Is keep-going label set? True 2025-08-26T20:10:36.6471660Z 2025-08-26T20:10:36.6471714Z Reenabled issues? 2025-08-26T20:10:36.6508160Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-08-26T20:10:36.6508440Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-08-26T20:10:36.6516180Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T20:10:36.6516381Z env: 2025-08-26T20:10:36.6516507Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:36.6516691Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:36.6519836Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:36.6520072Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:36.6520850Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:36.6521586Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:36.6521742Z AWS_REGION: us-east-1 2025-08-26T20:10:36.6521959Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:36.6522161Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:36.6525486Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:36.6525625Z JOB_TIMEOUT: 300 2025-08-26T20:10:36.6525751Z ##[endgroup] 2025-08-26T20:10:36.6617986Z ##[group]Run set -x 2025-08-26T20:10:36.6620792Z set -x 2025-08-26T20:10:36.6620922Z  2025-08-26T20:10:36.6621064Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-08-26T20:10:36.6621281Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-08-26T20:10:36.6621496Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-08-26T20:10:36.6621696Z  TEST_COMMAND=.ci/caffe2/test.sh 2025-08-26T20:10:36.6621869Z else 2025-08-26T20:10:36.6622010Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-08-26T20:10:36.6622174Z fi 2025-08-26T20:10:36.6622288Z  2025-08-26T20:10:36.6622469Z # detached container should get cleaned up by teardown_ec2_linux 2025-08-26T20:10:36.6622752Z # TODO: Stop building test binaries as part of the build phase 2025-08-26T20:10:36.6623001Z # Used for GPU_FLAG since that doesn't play nice 2025-08-26T20:10:36.6623232Z # shellcheck disable=SC2086,SC2090 2025-08-26T20:10:36.6623423Z container_name=$(docker run \ 2025-08-26T20:10:36.6623596Z  ${GPU_FLAG:-} \ 2025-08-26T20:10:36.6623753Z  -e BUILD_ENVIRONMENT \ 2025-08-26T20:10:36.6626042Z  -e PR_NUMBER \ 2025-08-26T20:10:36.6626197Z  -e GITHUB_ACTIONS \ 2025-08-26T20:10:36.6626358Z  -e GITHUB_REPOSITORY \ 2025-08-26T20:10:36.6626521Z  -e GITHUB_WORKFLOW \ 2025-08-26T20:10:36.6626686Z  -e GITHUB_JOB \ 2025-08-26T20:10:36.6626834Z  -e GITHUB_RUN_ID \ 2025-08-26T20:10:36.6626988Z  -e GITHUB_RUN_NUMBER \ 2025-08-26T20:10:36.6627152Z  -e GITHUB_RUN_ATTEMPT \ 2025-08-26T20:10:36.6627312Z  -e JOB_ID \ 2025-08-26T20:10:36.6627454Z  -e JOB_NAME \ 2025-08-26T20:10:36.6627598Z  -e BRANCH \ 2025-08-26T20:10:36.6627733Z  -e SHA1 \ 2025-08-26T20:10:36.6627874Z  -e AWS_DEFAULT_REGION \ 2025-08-26T20:10:36.6628037Z  -e IN_WHEEL_TEST \ 2025-08-26T20:10:36.6628187Z  -e SHARD_NUMBER \ 2025-08-26T20:10:36.6628340Z  -e TEST_CONFIG \ 2025-08-26T20:10:36.6628493Z  -e NUM_TEST_SHARDS \ 2025-08-26T20:10:36.6628654Z  -e REENABLED_ISSUES \ 2025-08-26T20:10:36.6628822Z  -e CONTINUE_THROUGH_ERROR \ 2025-08-26T20:10:36.6628992Z  -e VERBOSE_TEST_LOGS \ 2025-08-26T20:10:36.6629154Z  -e TEST_SHOWLOCALS \ 2025-08-26T20:10:36.6631373Z  -e NO_TEST_TIMEOUT \ 2025-08-26T20:10:36.6631528Z  -e NO_TD \ 2025-08-26T20:10:36.6631684Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-08-26T20:10:36.6631880Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-08-26T20:10:36.6632078Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-08-26T20:10:36.6632263Z  -e TESTS_TO_INCLUDE \ 2025-08-26T20:10:36.6632422Z  -e DASHBOARD_TAG \ 2025-08-26T20:10:36.6632625Z  --env-file="${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}" \ 2025-08-26T20:10:36.6632846Z  --ulimit stack=10485760:83886080 \ 2025-08-26T20:10:36.6633017Z  --ulimit core=0 \ 2025-08-26T20:10:36.6633185Z  --security-opt seccomp=unconfined \ 2025-08-26T20:10:36.6635220Z  --cap-add=SYS_PTRACE \ 2025-08-26T20:10:36.6635381Z  --shm-size="8g" \ 2025-08-26T20:10:36.6635526Z  --tty \ 2025-08-26T20:10:36.6635657Z  --detach \ 2025-08-26T20:10:36.6635932Z  --name="${container_name}" \ 2025-08-26T20:10:36.6636103Z  --user jenkins \ 2025-08-26T20:10:36.6636291Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-08-26T20:10:36.6636504Z  -w /var/lib/jenkins/workspace \ 2025-08-26T20:10:36.6636675Z  "${DOCKER_IMAGE}" 2025-08-26T20:10:36.6636816Z ) 2025-08-26T20:10:36.6636951Z # save container name for later step 2025-08-26T20:10:36.6639108Z echo "CONTAINER_NAME=${container_name}" >> "$GITHUB_ENV" 2025-08-26T20:10:36.6639495Z # jenkins user does not have write permission to mounted workspace; work-around by copying within container to jenkins home 2025-08-26T20:10:36.6639993Z docker exec -t "${container_name}" sh -c "cd .. && cp -R workspace pytorch && cd pytorch && pip install dist/*.whl && ${TEST_COMMAND}" 2025-08-26T20:10:36.6644586Z shell: /usr/bin/bash -e {0} 2025-08-26T20:10:36.6644731Z env: 2025-08-26T20:10:36.6644860Z GIT_DEFAULT_BRANCH: main 2025-08-26T20:10:36.6645045Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T20:10:36.6645291Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T20:10:36.6645518Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T20:10:36.6648259Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T20:10:36.6648799Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T20:10:36.6648952Z AWS_REGION: us-east-1 2025-08-26T20:10:36.6649128Z AWS_ACCESS_KEY_ID: *** 2025-08-26T20:10:36.6649329Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T20:10:36.6653001Z AWS_SESSION_TOKEN: *** 2025-08-26T20:10:36.6653175Z BUILD_ENVIRONMENT: linux-noble-rocm-py3.12-mi300 2025-08-26T20:10:36.6653362Z PR_NUMBER: 2025-08-26T20:10:36.6653499Z GITHUB_REPOSITORY: pytorch/pytorch 2025-08-26T20:10:36.6653675Z GITHUB_WORKFLOW: rocm-mi300 2025-08-26T20:10:36.6653823Z GITHUB_JOB: test 2025-08-26T20:10:36.6655955Z GITHUB_RUN_ID: 17248463563 2025-08-26T20:10:36.6656112Z GITHUB_RUN_NUMBER: 8814 2025-08-26T20:10:36.6656257Z GITHUB_RUN_ATTEMPT: 1 2025-08-26T20:10:36.6656391Z JOB_ID: 48946667439 2025-08-26T20:10:36.6656625Z JOB_NAME: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:36.6656881Z BRANCH: main 2025-08-26T20:10:36.6657026Z SHA1: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:36.6657207Z CONTINUE_THROUGH_ERROR: True 2025-08-26T20:10:36.6657361Z VERBOSE_TEST_LOGS: False 2025-08-26T20:10:36.6657507Z TEST_SHOWLOCALS: False 2025-08-26T20:10:36.6657649Z NO_TEST_TIMEOUT: False 2025-08-26T20:10:36.6659631Z NO_TD: False 2025-08-26T20:10:36.6659757Z TEST_CONFIG: default 2025-08-26T20:10:36.6659891Z SHARD_NUMBER: 2 2025-08-26T20:10:36.6660016Z NUM_TEST_SHARDS: 6 2025-08-26T20:10:36.6660148Z REENABLED_ISSUES: 2025-08-26T20:10:36.6660651Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:10:36.6661058Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-08-26T20:10:36.6661231Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-08-26T20:10:36.6661391Z TESTS_TO_INCLUDE: 2025-08-26T20:10:36.6661519Z DASHBOARD_TAG: 2025-08-26T20:10:36.6661643Z ##[endgroup] 2025-08-26T20:10:36.6715939Z + [[ default == \m\u\l\t\i\g\p\u ]] 2025-08-26T20:10:36.6716267Z + [[ linux-noble-rocm-py3.12-mi300 == *onnx* ]] 2025-08-26T20:10:36.6716443Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-08-26T20:10:36.6716598Z +++ nproc --ignore=2 2025-08-26T20:10:36.6718563Z ++ docker run --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e MAX_JOBS=158 -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e TESTS_TO_INCLUDE -e DASHBOARD_TAG --env-file=/home/runner/_work/_temp/github_env_17248463563 --ulimit stack=10485760:83886080 --ulimit core=0 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --shm-size=8g --tty --detach --name= --user jenkins -v /home/runner/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-noble-rocm-n-py3-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T20:10:37.5219342Z + container_name=96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T20:10:37.5220074Z + echo CONTAINER_NAME=96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T20:10:37.5220624Z + docker exec -t 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 sh -c 'cd .. && cp -R workspace pytorch && cd pytorch && pip install dist/*.whl && .ci/pytorch/test.sh' 2025-08-26T20:10:43.5526386Z Processing ./dist/torch-2.9.0a0+git262640f-cp312-cp312-linux_x86_64.whl 2025-08-26T20:10:44.1203986Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (3.19.1) 2025-08-26T20:10:44.1204668Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (4.15.0) 2025-08-26T20:10:44.1210681Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (80.9.0) 2025-08-26T20:10:44.1230455Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (1.13.3) 2025-08-26T20:10:44.1231255Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (2.8.8) 2025-08-26T20:10:44.1231976Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (3.1.6) 2025-08-26T20:10:44.1232695Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from torch==2.9.0a0+git262640f) (2025.7.0) 2025-08-26T20:10:44.1263912Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from sympy>=1.13.3->torch==2.9.0a0+git262640f) (1.3.0) 2025-08-26T20:10:44.1279582Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.12/lib/python3.12/site-packages (from jinja2->torch==2.9.0a0+git262640f) (3.0.2) 2025-08-26T20:10:44.2458993Z Installing collected packages: torch 2025-08-26T20:10:50.3231648Z ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. 2025-08-26T20:10:50.3232061Z helion 0.1.1 requires filecheck, which is not installed. 2025-08-26T20:10:50.3232316Z Successfully installed torch-2.9.0a0+git262640f 2025-08-26T20:10:50.3657304Z + export TERM=vt100 2025-08-26T20:10:50.3657436Z + TERM=vt100 2025-08-26T20:10:50.3662766Z ++ dirname .ci/pytorch/test.sh 2025-08-26T20:10:50.3677330Z + source .ci/pytorch/common.sh 2025-08-26T20:10:50.3694276Z +++ dirname .ci/pytorch/common.sh 2025-08-26T20:10:50.3709387Z ++ source .ci/pytorch/common_utils.sh 2025-08-26T20:10:50.3716674Z +++ declare -f -t trap_add 2025-08-26T20:10:50.3717095Z ++ set -ex -o pipefail 2025-08-26T20:10:50.3717280Z ++ [[ linux-noble-rocm-py3.12-mi300 == *rocm* ]] 2025-08-26T20:10:50.3717445Z ++ unset HIP_PLATFORM 2025-08-26T20:10:50.3718034Z ++ export PYTORCH_TEST_WITH_ROCM=1 2025-08-26T20:10:50.3718169Z ++ PYTORCH_TEST_WITH_ROCM=1 2025-08-26T20:10:50.3718290Z ++ BUILD_TEST_LIBTORCH=0 2025-08-26T20:10:50.3718411Z ++ dirname .ci/pytorch/test.sh 2025-08-26T20:10:50.3733404Z + source .ci/pytorch/common-build.sh 2025-08-26T20:10:50.3733809Z ++ [[ linux-noble-rocm-py3.12-mi300 != *win-* ]] 2025-08-26T20:10:50.3743399Z ++++ dirname .ci/pytorch/common-build.sh 2025-08-26T20:10:50.3763195Z +++ cd .ci/pytorch 2025-08-26T20:10:50.3763527Z +++ pwd -P 2025-08-26T20:10:50.3767909Z ++ script_dir=/var/lib/jenkins/pytorch/.ci/pytorch 2025-08-26T20:10:50.3768223Z ++ [[ linux-noble-rocm-py3.12-mi300 == *-pch* ]] 2025-08-26T20:10:50.3768600Z ++ which sccache 2025-08-26T20:10:50.3999946Z ++ [[ -z '' ]] 2025-08-26T20:10:50.4003916Z ++ unset SCCACHE_BUCKET 2025-08-26T20:10:50.4004381Z ++ unset SCCACHE_REGION 2025-08-26T20:10:50.4004805Z ++ sccache --stop-server 2025-08-26T20:10:50.4240590Z ++ true 2025-08-26T20:10:50.4241454Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-08-26T20:10:50.4296907Z ++ trap_add sccache_epilogue EXIT 2025-08-26T20:10:50.4297522Z ++ trap_add_cmd=sccache_epilogue 2025-08-26T20:10:50.4298139Z ++ shift 2025-08-26T20:10:50.4298675Z ++ for trap_add_name in "$@" 2025-08-26T20:10:50.4310140Z ++++ trap -p EXIT 2025-08-26T20:10:50.4315606Z +++ eval 'extract_trap_cmd ' 2025-08-26T20:10:50.4316795Z ++++ extract_trap_cmd 2025-08-26T20:10:50.4316893Z ++++ printf '%s\n' '' 2025-08-26T20:10:50.4316998Z +++ printf '%s\n' sccache_epilogue 2025-08-26T20:10:50.4317107Z ++ trap -- ' 2025-08-26T20:10:50.4317205Z sccache_epilogue' EXIT 2025-08-26T20:10:50.4318219Z ++ [[ -n '' ]] 2025-08-26T20:10:50.4318777Z ++ [[ linux-noble-rocm-py3.12-mi300 == *rocm* ]] 2025-08-26T20:10:50.4319408Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-08-26T20:10:50.4319962Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-08-26T20:10:50.4320184Z ++ sccache --start-server 2025-08-26T20:10:50.4392163Z sccache: Starting the server... 2025-08-26T20:10:50.5484424Z sccache: Listening on address 127.0.0.1:4226 2025-08-26T20:10:50.5499514Z ++ sccache --zero-stats 2025-08-26T20:10:50.5585838Z Statistics zeroed. 2025-08-26T20:10:50.5588533Z ++ which ccache 2025-08-26T20:10:50.5611054Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T20:10:50.5611340Z + echo 'Environment variables:' 2025-08-26T20:10:50.5612800Z Environment variables: 2025-08-26T20:10:50.5613036Z + env 2025-08-26T20:10:50.5628375Z GITHUB_WORKSPACE=/home/runner/_work/pytorch/pytorch 2025-08-26T20:10:50.5635391Z CONTINUE_THROUGH_ERROR=True 2025-08-26T20:10:50.5635659Z BUILD_ENVIRONMENT=linux-noble-rocm-py3.12-mi300 2025-08-26T20:10:50.5635833Z HOSTNAME=linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln 2025-08-26T20:10:50.5636088Z GITHUB_PATH=/home/runner/_work/_temp/_runner_file_commands/add_path_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.5636300Z GITHUB_ACTION=__self 2025-08-26T20:10:50.5636415Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-08-26T20:10:50.5636541Z GITHUB_RUN_NUMBER=8814 2025-08-26T20:10:50.5636644Z TEST_CONFIG=default 2025-08-26T20:10:50.5636758Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-08-26T20:10:50.5636882Z AWS_DEFAULT_REGION=us-east-1 2025-08-26T20:10:50.5637002Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-08-26T20:10:50.5637127Z GITHUB_REF_TYPE=branch 2025-08-26T20:10:50.5639982Z *** 2025-08-26T20:10:50.5640087Z GITHUB_REPOSITORY_ID=65600975 2025-08-26T20:10:50.5640213Z GITHUB_ACTIONS=true 2025-08-26T20:10:50.5640324Z SHA1=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.5640589Z GITHUB_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.5643022Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/rocm-mi300.yml@refs/heads/main 2025-08-26T20:10:50.5643228Z UCC_HOME=/usr 2025-08-26T20:10:50.5643319Z VERBOSE_TEST_LOGS=False 2025-08-26T20:10:50.5643427Z GITHUB_REF=refs/heads/main 2025-08-26T20:10:50.5643526Z SHARD_NUMBER=2 2025-08-26T20:10:50.5643616Z GITHUB_REF_PROTECTED=true 2025-08-26T20:10:50.5643715Z HOME=/var/lib/jenkins 2025-08-26T20:10:50.5643829Z GITHUB_API_URL=https://api.github.com 2025-08-26T20:10:50.5644248Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-08-26T20:10:50.5644367Z LANG=C.UTF-8 2025-08-26T20:10:50.5644472Z UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6 2025-08-26T20:10:50.5645934Z PYTORCH_TEST_WITH_ROCM=1 2025-08-26T20:10:50.5646038Z NUM_TEST_SHARDS=6 2025-08-26T20:10:50.5646124Z UCX_HOME=/usr 2025-08-26T20:10:50.5646304Z GITHUB_STATE=/home/runner/_work/_temp/_runner_file_commands/save_state_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.5646714Z JOB_NAME=linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:50.5646945Z MAGMA_HOME=/opt/rocm/magma 2025-08-26T20:10:50.5647128Z GITHUB_ENV=/home/runner/_work/_temp/_runner_file_commands/set_env_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.5647358Z GITHUB_EVENT_PATH=/home/runner/_work/_temp/_github_workflow/event.json 2025-08-26T20:10:50.5647508Z GITHUB_EVENT_NAME=push 2025-08-26T20:10:50.5647653Z GITHUB_ACTIONS_RUNNER_EXTRA_USER_AGENT=actions-runner-controller/0.11.0 2025-08-26T20:10:50.5647811Z DASHBOARD_TAG= 2025-08-26T20:10:50.5649169Z GITHUB_RUN_ID=17248463563 2025-08-26T20:10:50.5649369Z GITHUB_STEP_SUMMARY=/home/runner/_work/_temp/_runner_file_commands/step_summary_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.5649584Z GITHUB_ACTOR=pytorchmergebot 2025-08-26T20:10:50.5649688Z PR_NUMBER= 2025-08-26T20:10:50.5649771Z GITHUB_RUN_ATTEMPT=1 2025-08-26T20:10:50.5649869Z ANACONDA_PYTHON_VERSION=3.12 2025-08-26T20:10:50.5650000Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-08-26T20:10:50.5650126Z TERM=vt100 2025-08-26T20:10:50.5650207Z INSTALLED_VISION=yes 2025-08-26T20:10:50.5650296Z BRANCH=main 2025-08-26T20:10:50.5650488Z OPENSSL_ROOT_DIR=/opt/openssl 2025-08-26T20:10:50.5651702Z TESTS_TO_INCLUDE= 2025-08-26T20:10:50.5651857Z GITHUB_ACTION_PATH=/home/runner/_work/pytorch/pytorch/./.github/actions/setup-rocm 2025-08-26T20:10:50.5652043Z GITHUB_SERVER_URL=https://github.com 2025-08-26T20:10:50.5652166Z PYTORCH_ROCM_ARCH=gfx90a;gfx942 2025-08-26T20:10:50.5652296Z UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d 2025-08-26T20:10:50.5652418Z REENABLED_ISSUES= 2025-08-26T20:10:50.5652502Z SHLVL=1 2025-08-26T20:10:50.5652579Z MAX_JOBS=158 2025-08-26T20:10:50.5652664Z GITHUB_ACTOR_ID=97764156 2025-08-26T20:10:50.5652791Z GITHUB_WORKFLOW_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.5652927Z GITHUB_REF_NAME=main 2025-08-26T20:10:50.5654068Z ROCM_PATH=/opt/rocm 2025-08-26T20:10:50.5654157Z GITHUB_JOB=test 2025-08-26T20:10:50.5654244Z NO_TEST_TIMEOUT=False 2025-08-26T20:10:50.5654352Z GITHUB_REPOSITORY=pytorch/pytorch 2025-08-26T20:10:50.5654458Z LC_ALL=C.UTF-8 2025-08-26T20:10:50.5654546Z GITHUB_RETENTION_DAYS=90 2025-08-26T20:10:50.5654649Z OPENSSL_DIR=/opt/openssl 2025-08-26T20:10:50.5654748Z GITHUB_ACTION_REPOSITORY= 2025-08-26T20:10:50.5655094Z PATH=/opt/cache/bin:/opt/rocm/llvm/bin:/opt/rocm/opencl/bin:/opt/rocm/hip/bin:/opt/rocm/hcc/bin:/opt/rocm/bin:/opt/conda/envs/py_3.12/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T20:10:50.5655434Z GITHUB_BASE_REF= 2025-08-26T20:10:50.5655517Z CI=true 2025-08-26T20:10:50.5656593Z GITHUB_REPOSITORY_OWNER=pytorch 2025-08-26T20:10:50.5656698Z JOB_ID=48946667439 2025-08-26T20:10:50.5656784Z GITHUB_HEAD_REF= 2025-08-26T20:10:50.5656870Z GITHUB_ACTION_REF= 2025-08-26T20:10:50.5656958Z TEST_SHOWLOCALS=False 2025-08-26T20:10:50.5657055Z GITHUB_WORKFLOW=rocm-mi300 2025-08-26T20:10:50.5657161Z DEBIAN_FRONTEND=noninteractive 2025-08-26T20:10:50.5657360Z GITHUB_OUTPUT=/home/runner/_work/_temp/_runner_file_commands/set_output_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.5657556Z NO_TD=False 2025-08-26T20:10:50.5657639Z OLDPWD=/var/lib/jenkins 2025-08-26T20:10:50.5657732Z _=/usr/bin/env 2025-08-26T20:10:50.5658859Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-08-26T20:10:50.5820271Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch 2025-08-26T20:10:50.5820581Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T20:10:50.5821172Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib 2025-08-26T20:10:50.5821665Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/test 2025-08-26T20:10:50.5822127Z + BUILD_DIR=build 2025-08-26T20:10:50.5823668Z + BUILD_RENAMED_DIR=build_renamed 2025-08-26T20:10:50.5824960Z + BUILD_BIN_DIR=build/bin 2025-08-26T20:10:50.5825118Z + SHARD_NUMBER=2 2025-08-26T20:10:50.5825578Z + NUM_TEST_SHARDS=6 2025-08-26T20:10:50.5826986Z + export TORCH_SERIALIZATION_DEBUG=1 2025-08-26T20:10:50.5838364Z + TORCH_SERIALIZATION_DEBUG=1 2025-08-26T20:10:50.5839114Z + export VALGRIND=ON 2025-08-26T20:10:50.5839718Z + VALGRIND=ON 2025-08-26T20:10:50.5840313Z + [[ linux-noble-rocm-py3.12-mi300 == *clang9* ]] 2025-08-26T20:10:50.5841039Z + [[ linux-noble-rocm-py3.12-mi300 == *xpu* ]] 2025-08-26T20:10:50.5841670Z + detect_cuda_arch 2025-08-26T20:10:50.5842253Z + [[ linux-noble-rocm-py3.12-mi300 == *cuda* ]] 2025-08-26T20:10:50.5842691Z + [[ linux-noble-rocm-py3.12-mi300 == *s390x* ]] 2025-08-26T20:10:50.5843051Z + [[ 0 == \1 ]] 2025-08-26T20:10:50.5843152Z + [[ True == \1 ]] 2025-08-26T20:10:50.5843270Z + [[ linux-noble-rocm-py3.12-mi300 != *bazel* ]] 2025-08-26T20:10:50.5845187Z ++ realpath build/custom_test_artifacts 2025-08-26T20:10:50.6030905Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/pytorch/build/custom_test_artifacts 2025-08-26T20:10:50.6031113Z + [[ -n '' ]] 2025-08-26T20:10:50.6031503Z + echo 'Environment variables' 2025-08-26T20:10:50.6032318Z Environment variables 2025-08-26T20:10:50.6032453Z + env 2025-08-26T20:10:50.6048447Z GITHUB_WORKSPACE=/home/runner/_work/pytorch/pytorch 2025-08-26T20:10:50.6048811Z CONTINUE_THROUGH_ERROR=True 2025-08-26T20:10:50.6048950Z BUILD_ENVIRONMENT=linux-noble-rocm-py3.12-mi300 2025-08-26T20:10:50.6049119Z HOSTNAME=linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln 2025-08-26T20:10:50.6051876Z GITHUB_PATH=/home/runner/_work/_temp/_runner_file_commands/add_path_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.6052137Z GITHUB_ACTION=__self 2025-08-26T20:10:50.6052277Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-08-26T20:10:50.6052402Z GITHUB_RUN_NUMBER=8814 2025-08-26T20:10:50.6052507Z TEST_CONFIG=default 2025-08-26T20:10:50.6052614Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-08-26T20:10:50.6052743Z AWS_DEFAULT_REGION=us-east-1 2025-08-26T20:10:50.6052861Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-08-26T20:10:50.6052981Z GITHUB_REF_TYPE=branch 2025-08-26T20:10:50.6053100Z *** 2025-08-26T20:10:50.6054805Z GITHUB_REPOSITORY_ID=65600975 2025-08-26T20:10:50.6054946Z GITHUB_ACTIONS=true 2025-08-26T20:10:50.6055053Z SHA1=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.6055208Z GITHUB_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.6055400Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/rocm-mi300.yml@refs/heads/main 2025-08-26T20:10:50.6055572Z UCC_HOME=/usr 2025-08-26T20:10:50.6055663Z TORCH_SERIALIZATION_DEBUG=1 2025-08-26T20:10:50.6055772Z VERBOSE_TEST_LOGS=False 2025-08-26T20:10:50.6055871Z GITHUB_REF=refs/heads/main 2025-08-26T20:10:50.6055971Z SHARD_NUMBER=2 2025-08-26T20:10:50.6056060Z GITHUB_REF_PROTECTED=true 2025-08-26T20:10:50.6056164Z HOME=/var/lib/jenkins 2025-08-26T20:10:50.6056275Z GITHUB_API_URL=https://api.github.com 2025-08-26T20:10:50.6056402Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-08-26T20:10:50.6056518Z LANG=C.UTF-8 2025-08-26T20:10:50.6056625Z UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6 2025-08-26T20:10:50.6056759Z PYTORCH_TEST_WITH_ROCM=1 2025-08-26T20:10:50.6056914Z NUM_TEST_SHARDS=6 2025-08-26T20:10:50.6057001Z UCX_HOME=/usr 2025-08-26T20:10:50.6059830Z GITHUB_STATE=/home/runner/_work/_temp/_runner_file_commands/save_state_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.6060121Z JOB_NAME=linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T20:10:50.6060309Z MAGMA_HOME=/opt/rocm/magma 2025-08-26T20:10:50.6060598Z GITHUB_ENV=/home/runner/_work/_temp/_runner_file_commands/set_env_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.6060933Z GITHUB_EVENT_PATH=/home/runner/_work/_temp/_github_workflow/event.json 2025-08-26T20:10:50.6062070Z GITHUB_EVENT_NAME=push 2025-08-26T20:10:50.6062218Z GITHUB_ACTIONS_RUNNER_EXTRA_USER_AGENT=actions-runner-controller/0.11.0 2025-08-26T20:10:50.6062371Z DASHBOARD_TAG= 2025-08-26T20:10:50.6062460Z GITHUB_RUN_ID=17248463563 2025-08-26T20:10:50.6064459Z GITHUB_STEP_SUMMARY=/home/runner/_work/_temp/_runner_file_commands/step_summary_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.6064808Z GITHUB_ACTOR=pytorchmergebot 2025-08-26T20:10:50.6064916Z PR_NUMBER= 2025-08-26T20:10:50.6065001Z GITHUB_RUN_ATTEMPT=1 2025-08-26T20:10:50.6065092Z VALGRIND=ON 2025-08-26T20:10:50.6065182Z ANACONDA_PYTHON_VERSION=3.12 2025-08-26T20:10:50.6065321Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-08-26T20:10:50.6065448Z TERM=vt100 2025-08-26T20:10:50.6065529Z INSTALLED_VISION=yes 2025-08-26T20:10:50.6065620Z BRANCH=main 2025-08-26T20:10:50.6065712Z OPENSSL_ROOT_DIR=/opt/openssl 2025-08-26T20:10:50.6066994Z TESTS_TO_INCLUDE= 2025-08-26T20:10:50.6067155Z GITHUB_ACTION_PATH=/home/runner/_work/pytorch/pytorch/./.github/actions/setup-rocm 2025-08-26T20:10:50.6067340Z GITHUB_SERVER_URL=https://github.com 2025-08-26T20:10:50.6067463Z PYTORCH_ROCM_ARCH=gfx90a;gfx942 2025-08-26T20:10:50.6067589Z UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d 2025-08-26T20:10:50.6067714Z REENABLED_ISSUES= 2025-08-26T20:10:50.6067799Z SHLVL=1 2025-08-26T20:10:50.6067876Z MAX_JOBS=158 2025-08-26T20:10:50.6067967Z GITHUB_ACTOR_ID=97764156 2025-08-26T20:10:50.6068096Z GITHUB_WORKFLOW_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T20:10:50.6068233Z GITHUB_REF_NAME=main 2025-08-26T20:10:50.6069405Z ROCM_PATH=/opt/rocm 2025-08-26T20:10:50.6069499Z GITHUB_JOB=test 2025-08-26T20:10:50.6069587Z NO_TEST_TIMEOUT=False 2025-08-26T20:10:50.6069692Z GITHUB_REPOSITORY=pytorch/pytorch 2025-08-26T20:10:50.6069801Z LC_ALL=C.UTF-8 2025-08-26T20:10:50.6069889Z GITHUB_RETENTION_DAYS=90 2025-08-26T20:10:50.6069993Z OPENSSL_DIR=/opt/openssl 2025-08-26T20:10:50.6070094Z GITHUB_ACTION_REPOSITORY= 2025-08-26T20:10:50.6070535Z PATH=/opt/cache/bin:/opt/rocm/llvm/bin:/opt/rocm/opencl/bin:/opt/rocm/hip/bin:/opt/rocm/hcc/bin:/opt/rocm/bin:/opt/conda/envs/py_3.12/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T20:10:50.6070877Z GITHUB_BASE_REF= 2025-08-26T20:10:50.6070962Z CI=true 2025-08-26T20:10:50.6072094Z GITHUB_REPOSITORY_OWNER=pytorch 2025-08-26T20:10:50.6072209Z JOB_ID=48946667439 2025-08-26T20:10:50.6072295Z GITHUB_HEAD_REF= 2025-08-26T20:10:50.6072382Z GITHUB_ACTION_REF= 2025-08-26T20:10:50.6072472Z TEST_SHOWLOCALS=False 2025-08-26T20:10:50.6072570Z GITHUB_WORKFLOW=rocm-mi300 2025-08-26T20:10:50.6072676Z DEBIAN_FRONTEND=noninteractive 2025-08-26T20:10:50.6072873Z GITHUB_OUTPUT=/home/runner/_work/_temp/_runner_file_commands/set_output_36b04d47-e281-4e61-9f08-4e9d0ad2ec57 2025-08-26T20:10:50.6073069Z NO_TD=False 2025-08-26T20:10:50.6073153Z OLDPWD=/var/lib/jenkins 2025-08-26T20:10:50.6073250Z _=/usr/bin/env 2025-08-26T20:10:50.6074354Z + echo 'Testing pytorch' 2025-08-26T20:10:50.6074456Z Testing pytorch 2025-08-26T20:10:50.6074546Z + export LANG=C.UTF-8 2025-08-26T20:10:50.6074638Z + LANG=C.UTF-8 2025-08-26T20:10:50.6074719Z + PR_NUMBER= 2025-08-26T20:10:50.6074810Z + [[ default == \d\e\f\a\u\l\t ]] 2025-08-26T20:10:50.6074922Z + export CUDA_VISIBLE_DEVICES=0 2025-08-26T20:10:50.6075028Z + CUDA_VISIBLE_DEVICES=0 2025-08-26T20:10:50.6075129Z + export HIP_VISIBLE_DEVICES=0 2025-08-26T20:10:50.6075238Z + HIP_VISIBLE_DEVICES=0 2025-08-26T20:10:50.6075341Z + [[ default == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-08-26T20:10:50.6076469Z + [[ default == \s\l\o\w ]] 2025-08-26T20:10:50.6076607Z + [[ linux-noble-rocm-py3.12-mi300 == *slow-gradcheck* ]] 2025-08-26T20:10:50.6076759Z + [[ linux-noble-rocm-py3.12-mi300 == *cuda* ]] 2025-08-26T20:10:50.6076895Z + [[ linux-noble-rocm-py3.12-mi300 == *rocm* ]] 2025-08-26T20:10:50.6077028Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-08-26T20:10:50.6077225Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-08-26T20:10:50.6077343Z + [[ default == *crossref* ]] 2025-08-26T20:10:50.6077460Z + [[ linux-noble-rocm-py3.12-mi300 == *rocm* ]] 2025-08-26T20:10:50.6077588Z + export VALGRIND=OFF 2025-08-26T20:10:50.6077680Z + VALGRIND=OFF 2025-08-26T20:10:50.6077764Z + rocminfo 2025-08-26T20:10:50.6355750Z ROCk module version 6.12.12 is loaded 2025-08-26T20:10:50.7726239Z ===================== 2025-08-26T20:10:50.7727800Z HSA System Attributes 2025-08-26T20:10:50.7728775Z ===================== 2025-08-26T20:10:50.7729073Z Runtime Version: 1.15 2025-08-26T20:10:50.7737659Z Runtime Ext Version: 1.7 2025-08-26T20:10:50.7737843Z System Timestamp Freq.: 1000.000000MHz 2025-08-26T20:10:50.7738066Z Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count) 2025-08-26T20:10:50.7738322Z Machine Model: LARGE 2025-08-26T20:10:50.7738529Z System Endianness: LITTLE 2025-08-26T20:10:50.7738744Z Mwaitx: DISABLED 2025-08-26T20:10:50.7738907Z XNACK enabled: NO 2025-08-26T20:10:50.7739053Z DMAbuf Support: YES 2025-08-26T20:10:50.7739190Z VMM Support: YES 2025-08-26T20:10:50.7739262Z 2025-08-26T20:10:50.7739299Z ========== 2025-08-26T20:10:50.7739421Z HSA Agents 2025-08-26T20:10:50.7739558Z ========== 2025-08-26T20:10:50.7739698Z ******* 2025-08-26T20:10:50.7739841Z Agent 1 2025-08-26T20:10:50.7739996Z ******* 2025-08-26T20:10:50.7740155Z Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.7740327Z Uuid: CPU-XX 2025-08-26T20:10:50.7740637Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.7740827Z Vendor Name: CPU 2025-08-26T20:10:50.7741010Z Feature: None specified 2025-08-26T20:10:50.7741180Z Profile: FULL_PROFILE 2025-08-26T20:10:50.7745063Z Float Round Mode: NEAR 2025-08-26T20:10:50.7745257Z Max Queue Number: 0(0x0) 2025-08-26T20:10:50.7745411Z Queue Min Size: 0(0x0) 2025-08-26T20:10:50.7745564Z Queue Max Size: 0(0x0) 2025-08-26T20:10:50.7745780Z Queue Type: MULTI 2025-08-26T20:10:50.7745929Z Node: 0 2025-08-26T20:10:50.7746074Z Device Type: CPU 2025-08-26T20:10:50.7746214Z Cache Info: 2025-08-26T20:10:50.7746332Z L1: 65536(0x10000) KB 2025-08-26T20:10:50.7746489Z Chip ID: 0(0x0) 2025-08-26T20:10:50.7746647Z ASIC Revision: 0(0x0) 2025-08-26T20:10:50.7746795Z Cacheline Size: 64(0x40) 2025-08-26T20:10:50.7746951Z Max Clock Freq. (MHz): 0 2025-08-26T20:10:50.7747133Z BDFID: 0 2025-08-26T20:10:50.7747289Z Internal Node ID: 0 2025-08-26T20:10:50.7747449Z Compute Unit: 80 2025-08-26T20:10:50.7747601Z SIMDs per CU: 0 2025-08-26T20:10:50.7747753Z Shader Engines: 0 2025-08-26T20:10:50.7747908Z Shader Arrs. per Eng.: 0 2025-08-26T20:10:50.7748063Z WatchPts on Addr. Ranges:1 2025-08-26T20:10:50.7748213Z Memory Properties: 2025-08-26T20:10:50.7748639Z Features: None 2025-08-26T20:10:50.7748750Z Pool Info: 2025-08-26T20:10:50.7750955Z Pool 1 2025-08-26T20:10:50.7751087Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:10:50.7751247Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:10:50.7751393Z Allocatable: TRUE 2025-08-26T20:10:50.7751546Z Alloc Granule: 4KB 2025-08-26T20:10:50.7751812Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7751974Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7752127Z Accessible by all: TRUE 2025-08-26T20:10:50.7752263Z Pool 2 2025-08-26T20:10:50.7752391Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:10:50.7752539Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:10:50.7753988Z Allocatable: TRUE 2025-08-26T20:10:50.7754140Z Alloc Granule: 4KB 2025-08-26T20:10:50.7754295Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7754455Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7754607Z Accessible by all: TRUE 2025-08-26T20:10:50.7754744Z Pool 3 2025-08-26T20:10:50.7754870Z Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED 2025-08-26T20:10:50.7755016Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:10:50.7755156Z Allocatable: TRUE 2025-08-26T20:10:50.7755304Z Alloc Granule: 4KB 2025-08-26T20:10:50.7756559Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7756733Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7756898Z Accessible by all: TRUE 2025-08-26T20:10:50.7757033Z Pool 4 2025-08-26T20:10:50.7757157Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:10:50.7757301Z Size: 660245920(0x275a8da0) KB 2025-08-26T20:10:50.7757445Z Allocatable: TRUE 2025-08-26T20:10:50.7757593Z Alloc Granule: 4KB 2025-08-26T20:10:50.7757746Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7757904Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7758123Z Accessible by all: TRUE 2025-08-26T20:10:50.7759461Z ISA Info: 2025-08-26T20:10:50.7759574Z ******* 2025-08-26T20:10:50.7759692Z Agent 2 2025-08-26T20:10:50.7759786Z ******* 2025-08-26T20:10:50.7759903Z Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.7760046Z Uuid: CPU-XX 2025-08-26T20:10:50.7760196Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.7761037Z Vendor Name: CPU 2025-08-26T20:10:50.7761190Z Feature: None specified 2025-08-26T20:10:50.7762928Z Profile: FULL_PROFILE 2025-08-26T20:10:50.7764915Z Float Round Mode: NEAR 2025-08-26T20:10:50.7765074Z Max Queue Number: 0(0x0) 2025-08-26T20:10:50.7765222Z Queue Min Size: 0(0x0) 2025-08-26T20:10:50.7765511Z Queue Max Size: 0(0x0) 2025-08-26T20:10:50.7765653Z Queue Type: MULTI 2025-08-26T20:10:50.7765788Z Node: 1 2025-08-26T20:10:50.7765926Z Device Type: CPU 2025-08-26T20:10:50.7766056Z Cache Info: 2025-08-26T20:10:50.7766173Z L1: 65536(0x10000) KB 2025-08-26T20:10:50.7766368Z Chip ID: 0(0x0) 2025-08-26T20:10:50.7766515Z ASIC Revision: 0(0x0) 2025-08-26T20:10:50.7766664Z Cacheline Size: 64(0x40) 2025-08-26T20:10:50.7766815Z Max Clock Freq. (MHz): 0 2025-08-26T20:10:50.7766962Z BDFID: 0 2025-08-26T20:10:50.7767107Z Internal Node ID: 1 2025-08-26T20:10:50.7767265Z Compute Unit: 80 2025-08-26T20:10:50.7767414Z SIMDs per CU: 0 2025-08-26T20:10:50.7767564Z Shader Engines: 0 2025-08-26T20:10:50.7767713Z Shader Arrs. per Eng.: 0 2025-08-26T20:10:50.7767868Z WatchPts on Addr. Ranges:1 2025-08-26T20:10:50.7769758Z Memory Properties: 2025-08-26T20:10:50.7769872Z Features: None 2025-08-26T20:10:50.7769978Z Pool Info: 2025-08-26T20:10:50.7770080Z Pool 1 2025-08-26T20:10:50.7770210Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:10:50.7770431Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:10:50.7770576Z Allocatable: TRUE 2025-08-26T20:10:50.7770728Z Alloc Granule: 4KB 2025-08-26T20:10:50.7770890Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7771046Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7771202Z Accessible by all: TRUE 2025-08-26T20:10:50.7772432Z Pool 2 2025-08-26T20:10:50.7772578Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:10:50.7772728Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:10:50.7772870Z Allocatable: TRUE 2025-08-26T20:10:50.7773020Z Alloc Granule: 4KB 2025-08-26T20:10:50.7773178Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7773334Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7773487Z Accessible by all: TRUE 2025-08-26T20:10:50.7773620Z Pool 3 2025-08-26T20:10:50.7773747Z Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED 2025-08-26T20:10:50.7773890Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:10:50.7775066Z Allocatable: TRUE 2025-08-26T20:10:50.7775217Z Alloc Granule: 4KB 2025-08-26T20:10:50.7775385Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7775548Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7775701Z Accessible by all: TRUE 2025-08-26T20:10:50.7775834Z Pool 4 2025-08-26T20:10:50.7775957Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:10:50.7776110Z Size: 656328604(0x271ec79c) KB 2025-08-26T20:10:50.7776338Z Allocatable: TRUE 2025-08-26T20:10:50.7776487Z Alloc Granule: 4KB 2025-08-26T20:10:50.7776642Z Alloc Recommended Granule:4KB 2025-08-26T20:10:50.7777848Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7778002Z Accessible by all: TRUE 2025-08-26T20:10:50.7778193Z ISA Info: 2025-08-26T20:10:50.7778293Z ******* 2025-08-26T20:10:50.7778401Z Agent 3 2025-08-26T20:10:50.7778496Z ******* 2025-08-26T20:10:50.7778606Z Name: gfx942 2025-08-26T20:10:50.7778746Z Uuid: GPU-59b2d2c78b3baecf 2025-08-26T20:10:50.7778898Z Marketing Name: AMD Instinct Mi325X VF 2025-08-26T20:10:50.7779051Z Vendor Name: AMD 2025-08-26T20:10:50.7779195Z Feature: KERNEL_DISPATCH 2025-08-26T20:10:50.7780830Z Profile: BASE_PROFILE 2025-08-26T20:10:50.7780980Z Float Round Mode: NEAR 2025-08-26T20:10:50.7781128Z Max Queue Number: 128(0x80) 2025-08-26T20:10:50.7781275Z Queue Min Size: 64(0x40) 2025-08-26T20:10:50.7781420Z Queue Max Size: 131072(0x20000) 2025-08-26T20:10:50.7781566Z Queue Type: MULTI 2025-08-26T20:10:50.7781701Z Node: 2 2025-08-26T20:10:50.7781837Z Device Type: GPU 2025-08-26T20:10:50.7781965Z Cache Info: 2025-08-26T20:10:50.7782075Z L1: 32(0x20) KB 2025-08-26T20:10:50.7782206Z L2: 4096(0x1000) KB 2025-08-26T20:10:50.7783452Z L3: 262144(0x40000) KB 2025-08-26T20:10:50.7783584Z Chip ID: 29881(0x74b9) 2025-08-26T20:10:50.7783726Z ASIC Revision: 1(0x1) 2025-08-26T20:10:50.7783873Z Cacheline Size: 128(0x80) 2025-08-26T20:10:50.7784025Z Max Clock Freq. (MHz): 2100 2025-08-26T20:10:50.7784164Z BDFID: 35584 2025-08-26T20:10:50.7784302Z Internal Node ID: 2 2025-08-26T20:10:50.7784447Z Compute Unit: 304 2025-08-26T20:10:50.7784589Z SIMDs per CU: 4 2025-08-26T20:10:50.7784732Z Shader Engines: 32 2025-08-26T20:10:50.7784885Z Shader Arrs. per Eng.: 1 2025-08-26T20:10:50.7786082Z WatchPts on Addr. Ranges:4 2025-08-26T20:10:50.7786237Z Coherent Host Access: FALSE 2025-08-26T20:10:50.7786374Z Memory Properties: 2025-08-26T20:10:50.7786509Z Features: KERNEL_DISPATCH 2025-08-26T20:10:50.7786649Z Fast F16 Operation: TRUE 2025-08-26T20:10:50.7786801Z Wavefront Size: 64(0x40) 2025-08-26T20:10:50.7786963Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:10:50.7787104Z Workgroup Max Size per Dimension: 2025-08-26T20:10:50.7787225Z x 1024(0x400) 2025-08-26T20:10:50.7787348Z y 1024(0x400) 2025-08-26T20:10:50.7788488Z z 1024(0x400) 2025-08-26T20:10:50.7788712Z Max Waves Per CU: 32(0x20) 2025-08-26T20:10:50.7788862Z Max Work-item Per CU: 2048(0x800) 2025-08-26T20:10:50.7789012Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:10:50.7789143Z Grid Max Size per Dimension: 2025-08-26T20:10:50.7789254Z x 4294967295(0xffffffff) 2025-08-26T20:10:50.7789421Z y 4294967295(0xffffffff) 2025-08-26T20:10:50.7789544Z z 4294967295(0xffffffff) 2025-08-26T20:10:50.7789686Z Max fbarriers/Workgrp: 32 2025-08-26T20:10:50.7789904Z Packet Processor uCode:: 177 2025-08-26T20:10:50.7790060Z SDMA engine uCode:: 24 2025-08-26T20:10:50.7791402Z IOMMU Support:: None 2025-08-26T20:10:50.7791548Z Pool Info: 2025-08-26T20:10:50.7791652Z Pool 1 2025-08-26T20:10:50.7791782Z Segment: GLOBAL; FLAGS: COARSE GRAINED 2025-08-26T20:10:50.7791932Z Size: 268107776(0xffb0000) KB 2025-08-26T20:10:50.7792079Z Allocatable: TRUE 2025-08-26T20:10:50.7792229Z Alloc Granule: 4KB 2025-08-26T20:10:50.7792387Z Alloc Recommended Granule:2048KB 2025-08-26T20:10:50.7792549Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7792711Z Accessible by all: FALSE 2025-08-26T20:10:50.7792843Z Pool 2 2025-08-26T20:10:50.7794119Z Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED 2025-08-26T20:10:50.7794270Z Size: 268107776(0xffb0000) KB 2025-08-26T20:10:50.7794415Z Allocatable: TRUE 2025-08-26T20:10:50.7794564Z Alloc Granule: 4KB 2025-08-26T20:10:50.7794718Z Alloc Recommended Granule:2048KB 2025-08-26T20:10:50.7794873Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7795034Z Accessible by all: FALSE 2025-08-26T20:10:50.7795187Z Pool 3 2025-08-26T20:10:50.7795310Z Segment: GLOBAL; FLAGS: FINE GRAINED 2025-08-26T20:10:50.7795450Z Size: 268107776(0xffb0000) KB 2025-08-26T20:10:50.7795589Z Allocatable: TRUE 2025-08-26T20:10:50.7796796Z Alloc Granule: 4KB 2025-08-26T20:10:50.7796964Z Alloc Recommended Granule:2048KB 2025-08-26T20:10:50.7797127Z Alloc Alignment: 4KB 2025-08-26T20:10:50.7797285Z Accessible by all: FALSE 2025-08-26T20:10:50.7797418Z Pool 4 2025-08-26T20:10:50.7797537Z Segment: GROUP 2025-08-26T20:10:50.7797673Z Size: 64(0x40) KB 2025-08-26T20:10:50.7797813Z Allocatable: FALSE 2025-08-26T20:10:50.7797961Z Alloc Granule: 0KB 2025-08-26T20:10:50.7798114Z Alloc Recommended Granule:0KB 2025-08-26T20:10:50.7798269Z Alloc Alignment: 0KB 2025-08-26T20:10:50.7799458Z Accessible by all: FALSE 2025-08-26T20:10:50.7799594Z ISA Info: 2025-08-26T20:10:50.7799758Z ISA 1 2025-08-26T20:10:50.7799889Z Name: amdgcn-amd-amdhsa--gfx942:sramecc+:xnack- 2025-08-26T20:10:50.7800052Z Machine Models: HSA_MACHINE_MODEL_LARGE 2025-08-26T20:10:50.7800210Z Profiles: HSA_PROFILE_BASE 2025-08-26T20:10:50.7800460Z Default Rounding Mode: NEAR 2025-08-26T20:10:50.7800632Z Default Rounding Mode: NEAR 2025-08-26T20:10:50.7800824Z Fast f16: TRUE 2025-08-26T20:10:50.7800972Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:10:50.7801113Z Workgroup Max Size per Dimension: 2025-08-26T20:10:50.7802335Z x 1024(0x400) 2025-08-26T20:10:50.7802472Z y 1024(0x400) 2025-08-26T20:10:50.7802600Z z 1024(0x400) 2025-08-26T20:10:50.7802742Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:10:50.7802879Z Grid Max Size per Dimension: 2025-08-26T20:10:50.7802999Z x 4294967295(0xffffffff) 2025-08-26T20:10:50.7803126Z y 4294967295(0xffffffff) 2025-08-26T20:10:50.7803250Z z 4294967295(0xffffffff) 2025-08-26T20:10:50.7803393Z FBarrier Max Size: 32 2025-08-26T20:10:50.7803526Z ISA 2 2025-08-26T20:10:50.7803667Z Name: amdgcn-amd-amdhsa--gfx9-4-generic:sramecc+:xnack- 2025-08-26T20:10:50.7804867Z Machine Models: HSA_MACHINE_MODEL_LARGE 2025-08-26T20:10:50.7805026Z Profiles: HSA_PROFILE_BASE 2025-08-26T20:10:50.7805183Z Default Rounding Mode: NEAR 2025-08-26T20:10:50.7805345Z Default Rounding Mode: NEAR 2025-08-26T20:10:50.7805493Z Fast f16: TRUE 2025-08-26T20:10:50.7805640Z Workgroup Max Size: 1024(0x400) 2025-08-26T20:10:50.7805791Z Workgroup Max Size per Dimension: 2025-08-26T20:10:50.7805916Z x 1024(0x400) 2025-08-26T20:10:50.7806043Z y 1024(0x400) 2025-08-26T20:10:50.7806166Z z 1024(0x400) 2025-08-26T20:10:50.7806300Z Grid Max Size: 4294967295(0xffffffff) 2025-08-26T20:10:50.7807478Z Grid Max Size per Dimension: 2025-08-26T20:10:50.7807596Z x 4294967295(0xffffffff) 2025-08-26T20:10:50.7807723Z y 4294967295(0xffffffff) 2025-08-26T20:10:50.7807850Z z 4294967295(0xffffffff) 2025-08-26T20:10:50.7808095Z FBarrier Max Size: 32 2025-08-26T20:10:50.7808338Z *** Done *** 2025-08-26T20:10:50.7827181Z + rocminfo 2025-08-26T20:10:50.7892781Z + grep -E 'Name:.*\sgfx|Marketing' 2025-08-26T20:10:50.9284077Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.9284509Z Marketing Name: AMD EPYC 9575F 64-Core Processor 2025-08-26T20:10:50.9289374Z Name: gfx942 2025-08-26T20:10:50.9289734Z Marketing Name: AMD Instinct Mi325X VF 2025-08-26T20:10:50.9343641Z + MAYBE_ROCM=rocm/ 2025-08-26T20:10:50.9431272Z + [[ linux-noble-rocm-py3.12-mi300 == *xpu* ]] 2025-08-26T20:10:50.9431435Z + [[ linux-noble-rocm-py3.12-mi300 != *-bazel-* ]] 2025-08-26T20:10:50.9431589Z + pip_install ninja==1.10.2 2025-08-26T20:10:50.9431999Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-08-26T20:10:50.9432217Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-08-26T20:10:51.6124051Z Collecting ninja==1.10.2 2025-08-26T20:10:51.6911061Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-08-26T20:10:51.9993698Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-08-26T20:10:52.1635323Z Installing collected packages: ninja 2025-08-26T20:10:52.1636272Z Attempting uninstall: ninja 2025-08-26T20:10:52.1649902Z Found existing installation: ninja 1.11.1.3 2025-08-26T20:10:52.1662706Z Uninstalling ninja-1.11.1.3: 2025-08-26T20:10:52.1868130Z Successfully uninstalled ninja-1.11.1.3 2025-08-26T20:10:52.1992684Z Successfully installed ninja-1.10.2 2025-08-26T20:10:52.2424174Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/opt/rocm/llvm/bin:/opt/rocm/opencl/bin:/opt/rocm/hip/bin:/opt/rocm/hcc/bin:/opt/rocm/bin:/opt/conda/envs/py_3.12/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T20:10:52.2426525Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/opt/rocm/llvm/bin:/opt/rocm/opencl/bin:/opt/rocm/hip/bin:/opt/rocm/hcc/bin:/opt/rocm/bin:/opt/conda/envs/py_3.12/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T20:10:52.2427130Z + [[ linux-noble-rocm-py3.12-mi300 == *aarch64* ]] 2025-08-26T20:10:52.2427353Z + [[ linux-noble-rocm-py3.12-mi300 == *asan* ]] 2025-08-26T20:10:52.2427559Z + [[ linux-noble-rocm-py3.12-mi300 == *-debug* ]] 2025-08-26T20:10:52.2427773Z + [[ linux-noble-rocm-py3.12-mi300 != *-bazel-* ]] 2025-08-26T20:10:52.2428074Z + echo 'We are not in debug mode: linux-noble-rocm-py3.12-mi300. Expect the assertion to pass' 2025-08-26T20:10:52.2434314Z We are not in debug mode: linux-noble-rocm-py3.12-mi300. Expect the assertion to pass 2025-08-26T20:10:52.2434588Z + cd test 2025-08-26T20:10:52.2434796Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-08-26T20:10:53.5391074Z + [[ default == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-08-26T20:10:53.5392216Z + [[ default == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-08-26T20:10:53.5392412Z + [[ default == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-08-26T20:10:53.5393787Z + DYNAMO_BENCHMARK_FLAGS=() 2025-08-26T20:10:53.5394986Z + [[ default == *pr_time_benchmarks* ]] 2025-08-26T20:10:53.5395155Z + [[ default == *dynamo_eager* ]] 2025-08-26T20:10:53.5399689Z + [[ default == *aot_eager* ]] 2025-08-26T20:10:53.5399846Z + [[ default == *aot_inductor* ]] 2025-08-26T20:10:53.5399973Z + [[ default == *max_autotune_inductor* ]] 2025-08-26T20:10:53.5400102Z + [[ default == *inductor* ]] 2025-08-26T20:10:53.5400228Z + [[ default == *dynamic* ]] 2025-08-26T20:10:53.5400451Z + [[ default == *cpu* ]] 2025-08-26T20:10:53.5400597Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-08-26T20:10:53.5409477Z + [[ linux-noble-rocm-py3.12-mi300 == *libtorch* ]] 2025-08-26T20:10:53.5410016Z + [[ linux-noble-rocm-py3.12-mi300 == *-bazel-* ]] 2025-08-26T20:10:53.5414136Z + cd test 2025-08-26T20:10:53.5415650Z + python -c 'import torch; print(torch.__config__.show())' 2025-08-26T20:10:54.4265602Z PyTorch built with: 2025-08-26T20:10:54.4265933Z - GCC 11.4 2025-08-26T20:10:54.4266162Z - C++ Version: 201703 2025-08-26T20:10:54.4266524Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-08-26T20:10:54.4266945Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-08-26T20:10:54.4267271Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-08-26T20:10:54.4274537Z - LAPACK is enabled (usually provided by MKL) 2025-08-26T20:10:54.4274821Z - NNPACK is enabled 2025-08-26T20:10:54.4275066Z - CPU capability usage: AVX512 2025-08-26T20:10:54.4275318Z - HIP Runtime 6.4.43484 2025-08-26T20:10:54.4275542Z - MIOpen 3.4.0 2025-08-26T20:10:54.4275752Z - Magma 2.7.2 2025-08-26T20:10:54.4278627Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=262640fd220236042fbf4443cc163c8838c84c3d, CXX_COMPILER=/opt/cache/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_CUSPARSELT=OFF, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=ON, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 2025-08-26T20:10:54.4281138Z 2025-08-26T20:10:54.8043539Z + cd test 2025-08-26T20:10:54.8050689Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-08-26T20:10:55.7207358Z ATen/Parallel: 2025-08-26T20:10:55.7207585Z at::get_num_threads() : 160 2025-08-26T20:10:55.7209286Z at::get_num_interop_threads() : 160 2025-08-26T20:10:55.7209632Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-08-26T20:10:55.7209891Z omp_get_max_threads() : 160 2025-08-26T20:10:55.7210246Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-08-26T20:10:55.7210647Z mkl_get_max_threads() : 160 2025-08-26T20:10:55.7210870Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-08-26T20:10:55.7211134Z std::thread::hardware_concurrency() : 160 2025-08-26T20:10:55.7218837Z Environment variables: 2025-08-26T20:10:55.7219026Z OMP_NUM_THREADS : [not set] 2025-08-26T20:10:55.7219244Z MKL_NUM_THREADS : [not set] 2025-08-26T20:10:55.7219427Z ATen parallel backend: OpenMP 2025-08-26T20:10:55.7219546Z 2025-08-26T20:10:55.9712941Z + [[ default == *numpy_2* ]] 2025-08-26T20:10:55.9713264Z + [[ linux-noble-rocm-py3.12-mi300 == *aarch64* ]] 2025-08-26T20:10:55.9713486Z + [[ default == *backward* ]] 2025-08-26T20:10:55.9713646Z + [[ default == *xla* ]] 2025-08-26T20:10:55.9713792Z + [[ default == *vllm* ]] 2025-08-26T20:10:55.9713948Z + [[ default == *executorch* ]] 2025-08-26T20:10:55.9719901Z + [[ default == \j\i\t\_\l\e\g\a\c\y ]] 2025-08-26T20:10:55.9720167Z + [[ linux-noble-rocm-py3.12-mi300 == *libtorch* ]] 2025-08-26T20:10:55.9720614Z + [[ default == distributed ]] 2025-08-26T20:10:55.9720779Z + [[ default == *operator_benchmark* ]] 2025-08-26T20:10:55.9720966Z + [[ default == *inductor_distributed* ]] 2025-08-26T20:10:55.9721147Z + [[ default == *inductor-halide* ]] 2025-08-26T20:10:55.9721327Z + [[ default == *inductor-triton-cpu* ]] 2025-08-26T20:10:55.9721533Z + [[ default == *inductor-micro-benchmark* ]] 2025-08-26T20:10:55.9721717Z + [[ default == *huggingface* ]] 2025-08-26T20:10:55.9721875Z + [[ default == *timm* ]] 2025-08-26T20:10:55.9722023Z + [[ default == cachebench ]] 2025-08-26T20:10:55.9724213Z + [[ default == verify_cachebench ]] 2025-08-26T20:10:55.9724402Z + [[ default == *torchbench* ]] 2025-08-26T20:10:55.9724572Z + [[ default == *inductor_cpp_wrapper* ]] 2025-08-26T20:10:55.9724748Z + [[ default == *inductor* ]] 2025-08-26T20:10:55.9724908Z + [[ default == *einops* ]] 2025-08-26T20:10:55.9725064Z + [[ default == *dynamo_wrapped* ]] 2025-08-26T20:10:55.9725248Z + [[ linux-noble-rocm-py3.12-mi300 == *rocm* ]] 2025-08-26T20:10:55.9725433Z + [[ -n '' ]] 2025-08-26T20:10:55.9725554Z + [[ 2 == 1 ]] 2025-08-26T20:10:55.9725673Z + [[ 2 == 2 ]] 2025-08-26T20:10:55.9725791Z + [[ 6 -gt 1 ]] 2025-08-26T20:10:55.9727439Z + install_torchvision 2025-08-26T20:10:55.9727585Z + local orig_preload 2025-08-26T20:10:55.9727718Z + local commit 2025-08-26T20:10:55.9728322Z ++ get_pinned_commit vision 2025-08-26T20:10:55.9728481Z ++ cat .github/ci_commit_pins/vision.txt 2025-08-26T20:10:55.9728670Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:55.9728846Z + orig_preload= 2025-08-26T20:10:55.9728968Z + '[' -n '' ']' 2025-08-26T20:10:55.9729108Z + [[ linux-noble-rocm-py3.12-mi300 == *cuda* ]] 2025-08-26T20:10:55.9729480Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-08-26T20:10:55.9730050Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:55.9732225Z + local wheel_dir=dist/vision 2025-08-26T20:10:55.9732401Z + local found_whl=0 2025-08-26T20:10:55.9732543Z + for file in "${wheel_dir}"/*.whl 2025-08-26T20:10:55.9732710Z + [[ -f dist/vision/*.whl ]] 2025-08-26T20:10:55.9732855Z + '[' 0 == 0 ']' 2025-08-26T20:10:55.9733253Z + python3 -m pip wheel --no-build-isolation --no-deps --no-use-pep517 -w dist/vision git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:56.1443396Z Collecting git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:56.1446902Z Cloning https://github.com/pytorch/vision.git (to revision 966da7e46f65d6d49df3e31214470a4fe5cc8e66) to /tmp/pip-req-build-cojwnfms 2025-08-26T20:10:56.1519760Z Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-cojwnfms 2025-08-26T20:10:57.7768224Z Running command git rev-parse -q --verify 'sha^966da7e46f65d6d49df3e31214470a4fe5cc8e66' 2025-08-26T20:10:57.7815423Z Running command git fetch -q https://github.com/pytorch/vision.git 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:58.0227281Z Running command git checkout -q 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:10:58.3927556Z Resolved https://github.com/pytorch/vision.git to commit 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T20:11:00.2358607Z Preparing metadata (setup.py) ... [?25l- \ | done 2025-08-26T20:11:00.2382520Z [?25hBuilding wheels for collected packages: torchvision 2025-08-26T20:11:00.2441383Z  DEPRECATION: Building 'torchvision' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchvision'. Discussion can be found at https://github.com/pypa/pip/issues/6334 2025-08-26T20:11:32.7350102Z  Building wheel for torchvision (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - done 2025-08-26T20:11:32.7351186Z [?25h Created wheel for torchvision: filename=torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl size=1582708 sha256=20c8a9bf6afa0ed35cc1d9c47f08f1b7034837df6bf9d08e661df2ec4fd26855 2025-08-26T20:11:32.7353856Z Stored in directory: /var/lib/jenkins/.cache/pip/wheels/10/ba/61/eb5228b3631dc6bb4f478b3aa59575551a5473e4596e4c001a 2025-08-26T20:11:32.7357760Z Successfully built torchvision 2025-08-26T20:11:32.8059262Z + for file in "${wheel_dir}"/*.whl 2025-08-26T20:11:32.8059597Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl 2025-08-26T20:11:32.8060066Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl') 2025-08-26T20:11:32.8060329Z + local args 2025-08-26T20:11:32.8060859Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl == *\ * ]] 2025-08-26T20:11:32.8061133Z + for path in "${args[@]}" 2025-08-26T20:11:32.8064986Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl' 2025-08-26T20:11:32.8081842Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl 2025-08-26T20:11:32.8082743Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl 2025-08-26T20:11:32.9574960Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp312-cp312-linux_x86_64.whl 2025-08-26T20:11:32.9597177Z Installing collected packages: torchvision 2025-08-26T20:11:33.2008617Z Successfully installed torchvision-0.22.0a0+966da7e 2025-08-26T20:11:33.2333350Z + '[' -n '' ']' 2025-08-26T20:11:33.2334893Z + test_python_shard 2 2025-08-26T20:11:33.2336243Z + [[ -z 6 ]] 2025-08-26T20:11:33.2343491Z + python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --shard 2 6 --verbose --upload-artifacts-while-running 2025-08-26T20:11:34.9417846Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:11:34.9419434Z import pkg_resources 2025-08-26T20:11:35.3026335Z Excluding test_cuda_nvml_based_avail on ROCm 2025-08-26T20:11:35.7614848Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/pytorch/test/.pytorch-disabled-tests.json 2025-08-26T20:11:35.9461540Z Ignoring disabled issues: [''] 2025-08-26T20:11:35.9519428Z Found test times from artifacts 2025-08-26T20:11:35.9763146Z Found test times from artifacts 2025-08-26T20:11:35.9764110Z Running all tests 2025-08-26T20:11:35.9932996Z Running parallel tests on 1 processes 2025-08-26T20:11:35.9935533Z Name: tests to run (est. time: 148.5min) 2025-08-26T20:11:35.9936690Z Serial tests (94): 2025-08-26T20:11:35.9936971Z inductor/test_flex_attention 2/4 2025-08-26T20:11:35.9937194Z inductor/test_flex_decoding 2/2 2025-08-26T20:11:35.9937414Z inductor/test_torchinductor_opinfo 2/9 2025-08-26T20:11:35.9937648Z inductor/test_torchinductor_opinfo 8/9 2025-08-26T20:11:35.9937938Z inductor/test_inplace_padding 1/1 2025-08-26T20:11:35.9945406Z dynamo/test_fx_graph_runnable 1/1 2025-08-26T20:11:35.9945674Z inductor/test_extension_backend 1/1 2025-08-26T20:11:35.9945885Z inductor/test_pattern_matcher 1/1 2025-08-26T20:11:35.9946096Z dynamo/test_ctx_manager 1/1 2025-08-26T20:11:35.9946291Z inductor/test_mps_basic 1/1 2025-08-26T20:11:35.9946466Z inductor/test_kernel_benchmark 1/1 2025-08-26T20:11:35.9946714Z inductor/test_torchinductor_codegen_dynamic_shapes 3/3 2025-08-26T20:11:35.9946922Z inductor/test_cpu_repro 4/4 2025-08-26T20:11:35.9947084Z inductor/test_compile_subprocess 1/2 2025-08-26T20:11:35.9947260Z inductor/test_loop_ordering 1/1 2025-08-26T20:11:35.9947437Z inductor/test_scatter_optimization 1/1 2025-08-26T20:11:35.9947628Z inductor/test_inductor_freezing 1/1 2025-08-26T20:11:35.9947804Z dynamo/test_unittest 1/1 2025-08-26T20:11:35.9947965Z inductor/test_cutlass_backend 1/1 2025-08-26T20:11:35.9948158Z inductor/test_aot_inductor_custom_ops 1/1 2025-08-26T20:11:35.9948347Z inductor/test_group_batch_fusion 1/1 2025-08-26T20:11:35.9948538Z dynamo/test_activation_checkpointing 1/1 2025-08-26T20:11:35.9948720Z dynamo/test_subclasses 1/1 2025-08-26T20:11:35.9948888Z inductor/test_triton_syntax 1/1 2025-08-26T20:11:35.9949058Z inductor/test_ck_backend 1/1 2025-08-26T20:11:35.9949222Z inductor/test_debug_trace 1/1 2025-08-26T20:11:35.9951493Z inductor/test_distributed_patterns 1/1 2025-08-26T20:11:35.9951691Z inductor/test_external_callables 1/1 2025-08-26T20:11:35.9951861Z inductor/test_utils 1/1 2025-08-26T20:11:35.9952017Z export/test_draft_export 1/1 2025-08-26T20:11:35.9952174Z export/test_passes 1/1 2025-08-26T20:11:35.9952331Z inductor/test_inplacing_pass 1/1 2025-08-26T20:11:35.9952497Z dynamo/test_aot_autograd 1/1 2025-08-26T20:11:35.9952655Z dynamo/test_functions 1/1 2025-08-26T20:11:35.9953176Z inductor/test_fuzzer 1/1 2025-08-26T20:11:35.9953370Z inductor/test_torchinductor_codegen_config_overrides 1/1 2025-08-26T20:11:35.9953578Z export/test_experimental 1/1 2025-08-26T20:11:35.9955139Z export/test_export 1/1 2025-08-26T20:11:35.9955305Z dynamo/test_backward_higher_order_ops 1/1 2025-08-26T20:11:35.9955485Z dynamo/test_compile 1/1 2025-08-26T20:11:35.9955638Z dynamo/test_cudagraphs 1/1 2025-08-26T20:11:35.9955798Z dynamo/test_deque_reconstruct 1/1 2025-08-26T20:11:35.9956145Z dynamo/test_error_messages 1/1 2025-08-26T20:11:35.9956315Z dynamo/test_input_attr_tracking 1/1 2025-08-26T20:11:35.9956489Z dynamo/test_install_free_tensors 1/1 2025-08-26T20:11:35.9956658Z dynamo/test_profiler 1/1 2025-08-26T20:11:35.9956807Z dynamo/test_sets 1/1 2025-08-26T20:11:35.9956952Z dynamo/test_sources 1/1 2025-08-26T20:11:35.9958358Z dynamo/test_torchrec 1/1 2025-08-26T20:11:35.9958507Z dynamo/test_unspec 1/1 2025-08-26T20:11:35.9958654Z export/test_nativert 1/1 2025-08-26T20:11:35.9958819Z inductor/test_block_analysis 1/1 2025-08-26T20:11:35.9958985Z inductor/test_codegen_triton 1/1 2025-08-26T20:11:35.9959150Z inductor/test_combo_kernels 1/1 2025-08-26T20:11:35.9959315Z inductor/test_layout_optim 1/1 2025-08-26T20:11:35.9959482Z inductor/test_op_completeness 1/1 2025-08-26T20:11:35.9959652Z inductor/test_op_dtype_prop 1/1 2025-08-26T20:11:35.9959813Z functorch/test_ops 3/4 2025-08-26T20:11:35.9959956Z test_decomp 5/12 2025-08-26T20:11:35.9961393Z test_decomp 11/12 2025-08-26T20:11:35.9961532Z test_type_hints 1/1 2025-08-26T20:11:35.9961668Z test_modules 1/1 2025-08-26T20:11:35.9961819Z higher_order_ops/test_invoke_subgraph 1/1 2025-08-26T20:11:35.9961988Z test_fx 1/1 2025-08-26T20:11:35.9962108Z test_hub 1/1 2025-08-26T20:11:35.9962312Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 2025-08-26T20:11:35.9962555Z test_extension_utils 1/1 2025-08-26T20:11:35.9962704Z test_native_mha 1/1 2025-08-26T20:11:35.9962838Z test_optim 1/1 2025-08-26T20:11:35.9962969Z test_tensorboard 1/1 2025-08-26T20:11:35.9964307Z test_spectral_ops 1/1 2025-08-26T20:11:35.9964447Z doctests 1/1 2025-08-26T20:11:35.9964571Z test_foreach 1/1 2025-08-26T20:11:35.9964705Z lazy/test_ts_opinfo 1/1 2025-08-26T20:11:35.9964854Z nn/test_load_state_dict 1/1 2025-08-26T20:11:35.9965016Z profiler/test_execution_trace 1/1 2025-08-26T20:11:35.9965187Z profiler/test_record_function 1/1 2025-08-26T20:11:35.9965354Z test_cuda_sanitizer 1/1 2025-08-26T20:11:35.9965496Z test_cuda_trace 1/1 2025-08-26T20:11:35.9965636Z test_fake_tensor 1/1 2025-08-26T20:11:35.9965773Z test_file_check 1/1 2025-08-26T20:11:35.9967093Z test_flop_counter 1/1 2025-08-26T20:11:35.9967238Z test_function_schema 1/1 2025-08-26T20:11:35.9967394Z test_functionalization 1/1 2025-08-26T20:11:35.9967545Z test_fx_passes 1/1 2025-08-26T20:11:35.9967685Z test_fx_reinplace_pass 1/1 2025-08-26T20:11:35.9967840Z test_jit_llga_fuser 1/1 2025-08-26T20:11:35.9968074Z test_meta 2/2 2025-08-26T20:11:35.9968206Z test_autoload_disable 1/1 2025-08-26T20:11:35.9968356Z test_mkldnn_verbose 1/1 2025-08-26T20:11:35.9968506Z test_namedtuple_return_api 1/1 2025-08-26T20:11:35.9968668Z test_native_functions 1/1 2025-08-26T20:11:35.9970026Z test_numa_binding 1/1 2025-08-26T20:11:35.9970171Z test_ops_fwd_gradients 1/1 2025-08-26T20:11:35.9970321Z Parallel tests (0): 2025-08-26T20:11:35.9970567Z Name: excluded (est. time: 0.0min) 2025-08-26T20:11:35.9970726Z Serial tests (0): 2025-08-26T20:11:35.9970859Z Parallel tests (0): 2025-08-26T20:11:35.9971076Z Running inductor/test_flex_attention 2/4 ... [2025-08-26 20:11:35.993800] 2025-08-26T20:11:35.9971320Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:11:35.9971910Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_flex_attention.py', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:35.993979] 2025-08-26T20:20:52.0785395Z 2025-08-26T20:20:52.0794835Z inductor/test_flex_attention 2/4 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_attention_2.4_b99a681a0ad4ce08_.log 2025-08-26T20:20:52.0828983Z Running 179 items in this shard: test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_GQA_causal_mask_cuda, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_aot_eager_gradcheck_score_mod1_cuda, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_aot_eager_gradcheck_score_mod4_cuda, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_aot_eager_gradcheck_score_mod5_cuda, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_block_mask_non_divisible_cuda, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_automatic_dynamic_score_mod1_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_automatic_dynamic_score_mod4_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_automatic_dynamic_score_mod7_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE3_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE3_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE3_cuda_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE_128_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE_128_cuda_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod0_BLOCK_SIZE_256_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod1_BLOCK_SIZE2_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod1_BLOCK_SIZE_128_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod1_BLOCK_SIZE_128_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod1_BLOCK_SIZE_256_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod2_BLOCK_SIZE_128_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod2_BLOCK_SIZE_128_cuda_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod2_BLOCK_SIZE_256_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod3_BLOCK_SIZE2_cuda_float16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod3_BLOCK_SIZE_128_cuda_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod3_BLOCK_SIZE_256_cuda_bfloat16, test/inductor/test_flex_attention.py::TestFlexAttentionCUDA::test_builtin_score_mods_different_block_size_score_mod5_BLOCK_SIZE2_cuda_bfloat16, 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test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_symmetric_bias_batch:2_head:4_seq_len:256_headdim:16_dtype:float16_mode_default_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_symmetric_bias_batch:2_head:4_seq_len:256_headdim:16_dtype:float16_mode_max-autotune-no-cudagraphs_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_symmetric_bias_batch:2_head:4_seq_len:256_headdim:16_dtype:float32_mode_default_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_symmetric_bias_batch:2_head:4_seq_len:37_headdim:16_dtype:float32_mode_default_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_symmetric_bias_batch:2_head:4_seq_len:37_headdim:16_dtype:float32_mode_max-autotune-no-cudagraphs_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_weird_bias_batch:2_head:4_seq_len:256_headdim:16_dtype:float16_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_weird_bias_batch:2_head:4_seq_len:277_headdim:16_dtype:bfloat16_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_weird_bias_batch:2_head:4_seq_len:277_headdim:16_dtype:float16_cuda, test/inductor/test_flex_attention.py::TestLearnableBiasesCUDA::test_weird_bias_batch:2_head:4_seq_len:277_headdim:16_dtype:float32_cuda 2025-08-26T20:20:52.0858794Z 2025-08-26T20:20:52.0858895Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T20:20:52.0859076Z Uploading artifacts took 0.00 seconds 2025-08-26T20:20:52.0859239Z Running inductor/test_flex_decoding 2/2 ... [2025-08-26 20:20:52.078585] 2025-08-26T20:20:52.0859401Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:20:52.0859781Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_flex_decoding.py', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:52.078811] 2025-08-26T20:30:14.8527795Z 2025-08-26T20:30:14.8557870Z inductor/test_flex_decoding 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_decoding_2.2_95278ba7e48b9408_.log 2025-08-26T20:30:14.8611271Z Running 294 items in this shard: test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod1_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod1_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod2_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod2_head_dims2_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod3_head_dims2_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod4_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod4_head_dims2_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod5_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod5_head_dims2_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod6_head_dims2_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod7_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_bfloat16_score_mod7_head_dims1_cuda_bfloat16, 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test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_float32_score_mod7_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_builtin_score_mods_float32_score_mod8_head_dims2_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_bw_decoding_fails_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_captured_buffers_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_captured_reduction_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_captured_scale_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod4_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod7_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_decode_at_different_input_position_float16_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_function_composition_bfloat16_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_function_composition_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod0_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod0_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod1_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod1_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod3_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod3_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod4_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod5_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod6_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod6_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod7_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod8_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod8_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_head_dependent_mask_mod_float16_score_mod8_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims0_score_mod1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims0_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims0_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims0_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims1_score_mod1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims1_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims1_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims2_score_mod1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims2_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims2_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims2_score_mod7_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims0_batch_dims3_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod4_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod7_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims0_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims1_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims1_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims1_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims1_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims1_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims2_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims2_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims2_score_mod4_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims2_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims2_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims3_score_mod4_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims3_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims1_batch_dims3_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims0_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims0_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims0_score_mod7_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims0_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims1_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims1_score_mod1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims1_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims1_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims1_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod6_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod7_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims2_score_mod8_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims3_score_mod2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims3_score_mod3_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims3_score_mod4_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_kv_batch_broadcast_float16_head_dims2_batch_dims3_score_mod5_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_load_from_bias_head_seq_batch_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_load_from_bias_seq_batch_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_logsumexp_correctness_bfloat16_score_mod1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_logsumexp_only_return_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_max_autotune_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_max_autotune_with_captured_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_mixed_dtypes_fails_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_multiple_score_mod_calls_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_njt_causal_bfloat16_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_njt_causal_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_divisible_multi_token_offset_mask_with_captured_buffer_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod0_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod0_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod0_float16_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod1_bfloat16_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod1_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod1_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod1_float32_head_dims0_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod1_float32_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod2_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod2_float16_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod2_float32_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod3_bfloat16_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod3_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod3_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod3_float32_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod4_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod4_float16_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod4_float32_head_dims0_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod5_float16_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod6_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod6_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod6_float32_head_dims0_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod6_float32_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod7_bfloat16_head_dims0_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod7_bfloat16_head_dims1_cuda_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod7_float16_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod7_float16_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod7_float32_head_dims1_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_equal_head_dims_score_mod8_float32_head_dims0_cuda_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_pow_2_headdim_head_dim_17_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_pow_2_headdim_head_dim_94_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_non_sparse_mulitple_block_size_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod0_head_dims0_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod0_head_dims0_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod0_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod0_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod1_head_dims0_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod1_head_dims0_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod1_head_dims1_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod1_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod1_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod2_head_dims0_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod2_head_dims0_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod2_head_dims1_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod2_head_dims1_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod2_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod3_head_dims0_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod3_head_dims0_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod3_head_dims1_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod3_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod4_head_dims0_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod4_head_dims1_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod4_head_dims1_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod4_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod5_head_dims0_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod5_head_dims0_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod5_head_dims1_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod5_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod5_head_dims2_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod6_head_dims0_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod6_head_dims1_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod6_head_dims1_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod6_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod7_head_dims0_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod7_head_dims0_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod7_head_dims1_page_size_64_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod7_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod7_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod8_head_dims1_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod8_head_dims2_page_size_128_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_paged_attention_page_size_float16_score_mod8_head_dims2_page_size_256_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_seq_masking_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_silu_on_score_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_skip_odd_keys_float16_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s0_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s1_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s1_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s1_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s2_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s2_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s0_v_s3_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s1_v_s0_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s1_v_s1_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s1_v_s1_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s1_v_s2_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s1_v_s3_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s2_v_s0_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s2_v_s0_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s2_v_s0_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s2_v_s2_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s0_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s0_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s1_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s2_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s2_head_dims2_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s3_head_dims0_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_strided_inputs_float16_k_s3_v_s3_head_dims1_cuda_float16, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_windowed_full_mask_vs_sdpa_paged_attention_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_windowed_no_mask_vs_sdpa_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_windowed_no_mask_vs_sdpa_paged_attention_cuda, test/inductor/test_flex_decoding.py::TestFlexDecodingCUDA::test_windowed_partial_block_vs_sdpa_cuda 2025-08-26T20:30:14.8662372Z 2025-08-26T20:30:14.8662487Z Running inductor/test_torchinductor_opinfo 2/9 ... [2025-08-26 20:30:14.853208] 2025-08-26T20:30:14.8662684Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:30:14.8663106Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '--shard-id=2', '--num-shards=9', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:30:14.853514] 2025-08-26T20:41:06.4793963Z 2025-08-26T20:41:06.4795015Z inductor/test_torchinductor_opinfo 2/9 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_2.9_bd97e1a8a14d1c1a_.log 2025-08-26T20:41:06.4860615Z Running 407 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___getitem___cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___radd___cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rand___cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rmod___cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rmod___cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rpow___cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rpow___cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rsub___cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__chunk_cat_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__segment_reduce_lengths_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__segment_reduce_offsets_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__unsafe_masked_index_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__unsafe_masked_index_put_accumulate_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__unsafe_masked_index_put_accumulate_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_acosh_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_acosh_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_add_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_addcdiv_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_addcmul_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_addmm_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_addr_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_alias_copy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_amax_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_amin_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_aminmax_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_any_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_any_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_any_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_argmax_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_argwhere_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_argwhere_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_argwhere_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_as_strided_partial_views_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_as_strided_partial_views_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_as_strided_scatter_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_as_strided_scatter_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_as_strided_scatter_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_asin_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_asin_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_asinh_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_atan2_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_atan_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_atanh_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_atanh_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_atleast_2d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_baddbmm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_bfloat16_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_bitwise_and_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_block_diag_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_bool_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_broadcast_shapes_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_broadcast_to_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_broadcast_to_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_broadcast_to_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_byte_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cartesian_prod_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_chalf_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_char_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_chunk_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_clamp_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_clamp_min_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_clamp_min_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_clone_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_column_stack_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_column_stack_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_complex_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_conj_physical_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_constant_pad_nd_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_corrcoef_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_corrcoef_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cos_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cos_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cosh_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_count_nonzero_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_count_nonzero_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cov_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cross_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cummax_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cummax_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cummin_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cumprod_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cumprod_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_cumulative_trapezoid_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_diag_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_diagonal_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_diff_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_digamma_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_digamma_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_div_trunc_rounding_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_dsplit_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_dstack_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_empty_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_empty_like_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_empty_permuted_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_empty_strided_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_eq_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_eq_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_equal_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_equal_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_erf_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_erfc_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_erfinv_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_exp_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_expand_copy_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_expand_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_expand_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_expm1_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_eye_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_eye_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_fft2_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_fft2_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_fft2_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_fft_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_hfft2_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_hfftn_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_ihfft2_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_ihfft2_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_ihfft_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_ihfftn_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_irfft_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_irfft_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_irfftn_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_irfftn_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fft_rfftn_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_flip_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_flipud_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_float_power_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fmin_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_fmin_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_full_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_full_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_geometric_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_grid_sampler_2d_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_gt_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_gt_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_half_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_heaviside_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_histc_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_add_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_add_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_fill_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_put_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_reduce_amin_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_index_select_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_inner_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isclose_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isin_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isnan_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isnan_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isneginf_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isposinf_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isposinf_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_isreal_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_2inputs_2outputs_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_2inputs_2outputs_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_binary_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_binary_return_by_ref_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_binary_return_by_ref_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_jiterator_binary_return_by_ref_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_kron_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_le_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_lgamma_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_cross_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_diagonal_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_diagonal_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_householder_product_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_matrix_rank_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_multi_dot_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linalg_solve_triangular_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_linspace_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_log2_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_log_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_log_softmax_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logical_xor_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logit_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_tensor_overload_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logsumexp_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logsumexp_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_long_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mT_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_amax_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_amin_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_argmin_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_argmin_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_cumprod_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_cumprod_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_cumprod_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_log_softmax_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_norm_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_prod_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_select_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_softmax_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_std_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_sum_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_matrix_exp_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mean_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_median_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_meshgrid_variadic_tensors_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_meshgrid_variadic_tensors_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_min_binary_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_min_reduction_with_dim_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_minimum_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_minimum_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_minimum_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_movedim_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_msort_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_msort_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mvlgamma_mvlgamma_p_5_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nan_to_num_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nan_to_num_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nansum_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nansum_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_narrow_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_narrow_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_native_dropout_backward_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_ne_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_empty_strided_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_empty_strided_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_full_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_adaptive_avg_pool3d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_adaptive_max_pool1d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_alpha_dropout_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_binary_cross_entropy_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_binary_cross_entropy_with_logits_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_conv2d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_conv_transpose3d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_cosine_embedding_loss_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_dropout2d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_dropout3d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_feature_alpha_dropout_without_train_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_feature_alpha_dropout_without_train_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_fractional_max_pool2d_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_gaussian_nll_loss_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_gelu_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardswish_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardtanh_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hinge_embedding_loss_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_area_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_linear_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_nearest-exact_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_nearest_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_nearest_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_l1_loss_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_l1_loss_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_pool2d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_unpool1d_grad_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_unpool2d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_mse_loss_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_multilabel_soft_margin_loss_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_circular_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_circular_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_replicate_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pairwise_distance_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_relu_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softmin_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softplus_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softsign_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softsign_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softsign_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_tanhshrink_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_triplet_margin_loss_cuda_int64, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unfold_copy_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unfold_copy_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_uniform_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unique_consecutive_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unique_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unravel_index_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_copy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_copy_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_var_unbiased_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_view_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_view_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_view_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_vsplit_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_where_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_xlogy_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_zero__cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_zeros_like_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_zeros_like_cuda_uint8 2025-08-26T20:41:06.4923350Z 2025-08-26T20:41:06.4923459Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T20:41:06.4923650Z Uploading artifacts took 0.00 seconds 2025-08-26T20:41:06.4923826Z Running inductor/test_torchinductor_opinfo 8/9 ... [2025-08-26 20:41:06.480317] 2025-08-26T20:41:06.4924006Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:41:06.4924413Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '--shard-id=8', '--num-shards=9', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:41:06.480548] 2025-08-26T20:48:30.1606607Z 2025-08-26T20:48:30.1608421Z inductor/test_torchinductor_opinfo 8/9 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_8.9_619e809011e67bde_.log 2025-08-26T20:48:30.1674448Z Running 397 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_H_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_H_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_H_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_T_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___radd___cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rdiv___cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rmod___cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rmul___cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rmul___cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rsub___cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive___rsub___cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__batch_norm_with_update_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__chunk_cat_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive__native_batch_norm_legit_cuda_float32, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logit_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_tensor_overload_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_tensor_overload_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_tensor_overload_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_logspace_tensor_overload_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_long_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_long_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_lt_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_cumprod_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_cumprod_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_log_softmax_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_logsumexp_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_median_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_masked_prod_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_matmul_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_max_binary_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_max_pool2d_with_indices_backward_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_max_reduction_no_dim_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_max_reduction_with_dim_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_maximum_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mean_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_meshgrid_list_of_tensors_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_min_reduction_no_dim_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_min_reduction_with_dim_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_min_reduction_with_dim_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mm_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_msort_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mv_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mvlgamma_mvlgamma_p_1_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mvlgamma_mvlgamma_p_1_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mvlgamma_mvlgamma_p_1_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_mvlgamma_mvlgamma_p_3_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nansum_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_narrow_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_native_batch_norm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_native_batch_norm_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_native_layer_norm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_neg_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_empty_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_full_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_full_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_new_zeros_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_adaptive_max_pool1d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_adaptive_max_pool2d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_batch_norm_without_cudnn_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_bilinear_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_binary_cross_entropy_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_celu_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_channel_shuffle_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_conv_transpose1d_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_cosine_embedding_loss_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_ctc_loss_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_ctc_loss_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_dropout_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_grid_sample_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardshrink_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardshrink_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardtanh_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hardtanh_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_hinge_embedding_loss_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_huber_loss_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_interpolate_linear_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_layer_norm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_layer_norm_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_linear_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_logsigmoid_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_margin_ranking_loss_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_pool1d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_pool2d_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_unpool1d_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_max_unpool3d_grad_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_multi_head_attention_forward_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_constant_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_replicate_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pad_replicate_negative_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pixel_shuffle_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pixel_unshuffle_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_pixel_unshuffle_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_rms_norm_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_scaled_dot_product_attention_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_scaled_dot_product_attention_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_soft_margin_loss_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softplus_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_softshrink_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_tanhshrink_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_threshold_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_triplet_margin_with_distance_loss_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nn_functional_triplet_margin_with_distance_loss_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nonzero_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nonzero_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_nonzero_static_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_normal_number_mean_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_ones_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_outer_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_outer_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_outer_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_pca_lowrank_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_permute_copy_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_permute_copy_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_pinverse_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_polygamma_polygamma_n_0_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_polygamma_polygamma_n_0_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_polygamma_polygamma_n_1_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_polygamma_polygamma_n_3_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_positive_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_pow_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_pow_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_pow_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_prod_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_rad2deg_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_ravel_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_real_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_real_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_reciprocal_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_reciprocal_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_resize__cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_resize_as__cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_resolve_conj_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_resolve_conj_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_rot90_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_round_decimals_0_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_rsub_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scalar_tensor_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_add_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_reduce_mean_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_reduce_sum_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_reduce_sum_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_scatter_reduce_sum_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_select_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_select_scatter_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_short_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sigmoid_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sign_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_signal_windows_nuttall_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_signbit_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sinc_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sinc_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_slice_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_slice_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_slice_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_slice_scatter_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_softmax_with_dtype_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_softmax_with_dtype_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_airy_ai_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_chebyshev_polynomial_u_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_chebyshev_polynomial_u_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_chebyshev_polynomial_v_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_chebyshev_polynomial_w_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_hermite_polynomial_he_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_hermite_polynomial_he_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_i1_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_i1_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_laguerre_polynomial_l_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_legendre_polynomial_p_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_legendre_polynomial_p_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_ndtr_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_ndtr_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_polygamma_special_polygamma_n_0_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_scaled_modified_bessel_k1_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_v_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_v_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_w_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_special_xlog1py_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_split_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_split_list_args_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_split_with_sizes_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sqrt_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_squeeze_copy_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_squeeze_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_squeeze_multiple_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_squeeze_multiple_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_squeeze_multiple_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_stack_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_stack_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_std_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sub_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sum_to_size_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_sum_to_size_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_t_copy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_tan_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_tensor_split_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_tensor_split_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_to_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_to_sparse_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_to_sparse_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_transpose_copy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_trapz_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_tril_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_triu_indices_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_true_divide_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unbind_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unflatten_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unflatten_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unfold_copy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_uniform_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unique_consecutive_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unique_consecutive_cuda_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsafe_chunk_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsafe_chunk_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_copy_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_unsqueeze_cuda_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_var_mean_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_view_as_cuda_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_view_copy_cuda_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_vsplit_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_vsplit_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_vstack_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_where_cuda_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_where_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_where_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_xlogy_cuda_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_zeros_like_cuda_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCUDA::test_comprehensive_zeros_like_cuda_float64 2025-08-26T20:48:30.1735150Z 2025-08-26T20:48:30.1735253Z Running inductor/test_inplace_padding 1/1 ... [2025-08-26 20:48:30.160925] 2025-08-26T20:48:30.1735428Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:48:30.1735819Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_inplace_padding.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:48:30.161122] 2025-08-26T20:48:48.7179524Z 2025-08-26T20:48:48.7180874Z inductor/test_inplace_padding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplace_padding_1.1_ccf59b63ea42359a_.log 2025-08-26T20:48:48.7184563Z Running 9 items in this shard: test/inductor/test_inplace_padding.py::InplacePaddingTest::test_linear_and_cel, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_linear_and_cel_max_autotune, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_mutating_padding_input, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_mutating_padding_output, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_pad_non_zero, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_pad_non_zero_cpp_wrapper, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_pad_too_large, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_skip_pad_due_to_fusion, test/inductor/test_inplace_padding.py::InplacePaddingTest::test_skip_pad_input 2025-08-26T20:48:48.7187247Z 2025-08-26T20:48:48.7187361Z Running dynamo/test_fx_graph_runnable 1/1 ... [2025-08-26 20:48:48.717844] 2025-08-26T20:48:48.7187562Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:48:48.7188368Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_fx_graph_runnable.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:48:48.718164] 2025-08-26T20:50:27.8720969Z 2025-08-26T20:50:27.8722523Z dynamo/test_fx_graph_runnable 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_graph_runnable_1.1_6b06687019aa7e80_.log 2025-08-26T20:50:27.8726213Z Running 15 items in this shard: test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_all_gather_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_all_reduce_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_basic_tensor_add, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_broadcast_add_dynamic, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_broadcast_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_dtensor_compile_redistribute, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_dynamic_shapes_run, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_reduce_scatter_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_scalar_multiply, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_basic, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_batch_processing, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_dynamic_batch, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_two_inputs_matmul, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_user_defined_triton_kernel, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_user_defined_triton_kernel_autotune 2025-08-26T20:50:27.8729156Z 2025-08-26T20:50:27.8729285Z Running inductor/test_extension_backend 1/1 ... [2025-08-26 20:50:27.868551] 2025-08-26T20:50:27.8735246Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:50:27.8735810Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_extension_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:50:27.868801] 2025-08-26T20:50:45.8947419Z 2025-08-26T20:50:45.8948554Z inductor/test_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_extension_backend_1.1_bdbfae15a274a0fe_.log 2025-08-26T20:50:45.8949819Z Running 1 items in this shard: test/inductor/test_extension_backend.py::ExtensionBackendTests::test_open_device_registration 2025-08-26T20:50:45.8958356Z 2025-08-26T20:50:45.8958538Z Running inductor/test_pattern_matcher 1/1 ... [2025-08-26 20:50:45.894744] 2025-08-26T20:50:45.8958826Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:50:45.8959458Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_pattern_matcher.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:50:45.895017] 2025-08-26T20:51:27.4713160Z 2025-08-26T20:51:27.4713900Z inductor/test_pattern_matcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pattern_matcher_1.1_52ef2a73ae1bc35e_.log 2025-08-26T20:51:27.4720038Z Running 47 items in this shard: test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_addmm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_addmm_broadcasting_bias, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_addmm_dtype_mismatch, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_addmm_symbolic_scalar, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_bmm_to_mm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_cat_addmm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_cat_mm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_cat_slice_cat_cuda, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_cat_splitwithsizes, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_duplicate_search, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_fused_int_mm_mul, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_fused_int_mm_mul_epilogue, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_fused_int_mm_mul_gating, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_fwd_only_generate_original_aten_meta, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_match_equivalent_function_invocations1, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_match_equivalent_function_invocations2, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_match_equivalent_function_invocations3, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_match_with_mutation, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm_bad_cases, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm_cpu, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm_epi_works, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm_exhaustive_dtypes, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mixed_mm_gating, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mm_plus_mm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_multioutput_register_replacement, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_mutation_op_matching, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_original_aten_preserved_split_addmm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_convert, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_cumsum, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_permute_pair, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_permute_pair_3d, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_view_pair, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_pointless_view_pair_dynamic_shapes, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_remove_pointless_clones, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_replace_mul_zero, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_scaled_softmax, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_serialized_patterns_up_to_date, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_splitwithsizes_cat, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_stable_topological_sort, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_successful_partial_reuse_case0, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_successful_partial_reuse_case1, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_successful_partial_reuse_case2, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_symint_pattern_matching, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_unfuse_bias_addmm, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_unsuccessful_partial_reuse_case0, test/inductor/test_pattern_matcher.py::TestPatternMatcher::test_unsuccessful_partial_reuse_case1 2025-08-26T20:51:27.4725982Z 2025-08-26T20:51:27.4731441Z Running dynamo/test_ctx_manager 1/1 ... [2025-08-26 20:51:27.471447] 2025-08-26T20:51:27.4731637Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:51:27.4732026Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_ctx_manager.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:27.471669] 2025-08-26T20:51:43.2415195Z 2025-08-26T20:51:43.2415919Z dynamo/test_ctx_manager 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_ctx_manager_1.1_031b33e298943583_.log 2025-08-26T20:51:43.2435500Z Running 101 items in this shard: test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_arguments_binding, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_cpu, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_cpu_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_cpu_graph_break_2, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_cpu_graph_break_inner_fn, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_decorator, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_device, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_float64, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_graph_break_method, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autocast_sdpa, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autograd_profiler, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_autograd_profiler_enabled, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_context_wrapping_grad_mode_decorator, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_context_wrapping_grad_mode_nested_function_decorator, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_context_wrapping_set_grad_enabled_nested_function, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_amp_autocast, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_device, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_event_across_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_event_created_outside_of_graph, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_event_method, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_event_method_create_stream_outside_of_compile, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_event_reconstruct, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_across_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_compared_with_constant, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_compared_with_stream, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_context_manager1, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_context_manager2, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_cuda_stream_method, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_disable_saved_tensors_hooks, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_disable_saved_tensors_hooks_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_disable_saved_tensors_hooks_prev_disabled, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_disable_saved_tensors_hooks_prev_disabled_nested, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_context_manager_CustomizedCtxManager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_context_manager_customized_ctx_manager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_context_manager_with_graph_break_CustomizedCtxManager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_context_manager_with_graph_break_customized_ctx_manager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_ctx_manager_with_graph_break_CustomizedCtxManagerWithGraphBreak, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_generic_ctx_manager_with_graph_break_customized_ctx_manager_with_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_grad_mode_guard, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_graph_break_inlining_autocast, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_graph_break_inlining_grad, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_inactive_context_graph_break_local, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_inactive_context_graph_break_local_nullctx, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_inactive_context_graph_break_local_nullctx2, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_inactive_context_graph_break_stack, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_inactive_context_graph_break_stack2, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_is_autocast_cpu_enabled, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_nested_generic_context_manager_CustomizedCtxManager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_nested_generic_context_manager_customized_ctx_manager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_nested_generic_context_manager_with_graph_break_CustomizedCtxManager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_nested_generic_context_manager_with_graph_break_customized_ctx_manager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_nested_grad_mode_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_no_grad, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_return_context_manager, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_return_context_manager_with_graph_break, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager1, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager2, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager3, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager_as_decorator, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager_kwargs, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_sdpa_kernel_ctx_manager_set_priority, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_torch_profiler, test/dynamo/test_ctx_manager.py::CtxManagerTests::test_torch_profiler_use_after_with_block, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_WITH_EXCEPT_START, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_advanced_contextmanager_as_argument, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_advanced_contextmanager_as_argument_error, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_0, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_1, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_global_0, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_global_1, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_nonlocal_0, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_change_parent_nonlocal_1, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextlib_nullcontext, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextlib_suppress_name_stderr, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextlib_suppress_name_stdout, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextlib_suppress_name_suppress, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextmanager_as_argument, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextmanager_as_argument_only___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_contextmanager_as_argument_only___exit__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_ctx_basic0, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_ctx_basic1, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_disable___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_disable___exit__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_disable_ctx_manager, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_disable_trace_contextmanager, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_dynamo_disable_ctx, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_globals_change_in_other_file, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_after___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_and_disable___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_before___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_before___enter___and_disable___exit__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_before_and_after___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_in_finally, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_inside___enter__, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_inside_ctx, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_inside_ctx_1, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_inside_ctx_2, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_graph_break_inside_ctx_with_side_effects, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_return_advanced_contextmanager, test/dynamo/test_ctx_manager.py::ContextlibContextManagerTests::test_return_new_contextmanager 2025-08-26T20:51:43.2448587Z 2025-08-26T20:51:43.2449892Z Running inductor/test_mps_basic 1/1 ... [2025-08-26 20:51:43.241760] 2025-08-26T20:51:43.2450241Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:51:43.2450892Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_mps_basic.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:43.242121] 2025-08-26T20:51:49.4563905Z 2025-08-26T20:51:49.4565240Z inductor/test_mps_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_mps_basic_1.1_27649440a6334f8d_.log 2025-08-26T20:51:49.4565532Z 2025-08-26T20:51:49.4577818Z Running inductor/test_kernel_benchmark 1/1 ... [2025-08-26 20:51:49.456537] 2025-08-26T20:51:49.4578485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:51:49.4579973Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_kernel_benchmark.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:49.456930] 2025-08-26T20:53:55.3741021Z 2025-08-26T20:53:55.3741903Z inductor/test_kernel_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_benchmark_1.1_fa47ce1229c38f54_.log 2025-08-26T20:53:55.3745005Z Running 18 items in this shard: test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_fused_layernorm_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_matmul_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_matmul_triton_kernel_benchmark, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_mm_slice_add_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_mm_slice_add_bandwidth_computation_2, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_mm_triton_kernel_benchmark, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_pw_kernel_benchmark, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_reduction_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_remove_inductor_deps, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_remove_inductor_deps_multiple_kernels, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_remove_inductor_deps_scalar, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_remove_inductor_deps_templates, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_slice_add_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_slice_add_cat_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_slice_mm_bandwidth_computation, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_split_scan, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_star_dep, test/inductor/test_kernel_benchmark.py::TestKernelBenchmark::test_unused_input_bandwidth_computation 2025-08-26T20:53:55.3753182Z 2025-08-26T20:53:55.3753314Z Running inductor/test_torchinductor_codegen_dynamic_shapes 3/3 ... [2025-08-26 20:53:55.373987] 2025-08-26T20:53:55.3753520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T20:53:55.3753934Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_torchinductor_codegen_dynamic_shapes.py', '--shard-id=3', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:55.374228] 2025-08-26T21:04:56.1565979Z 2025-08-26T21:04:56.1567592Z inductor/test_torchinductor_codegen_dynamic_shapes 3/3 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_dynamic_shapes_3.3_e71b16332f378a7a_.log 2025-08-26T21:04:56.1675568Z Running 577 items in this shard: test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_AllenaiLongformerBase_repro_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test__dyn_quant_pack_4bit_weight_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test__unsafe_masked_index_put_accumulate_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_abs_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adaptive_avg_pool1d_argmax_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adaptive_avg_pool2d_low_prec_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adaptive_max_pool2d2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adaptive_max_pool2d3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adaptive_pool_errors_with_long_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_add_complex4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_add_const_float_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_add_const_int_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_adding_tensor_offsets_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_addmv_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_allow_reuse_active_if_under_peak_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_any_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_aoti_eager_support_str_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_arange6_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_argmax_argmin1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_argmax_argmin2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_argmax_min_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_as_strided_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_as_strided_scatter_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_assert_alignment_op_name_fail_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_assert_alignment_op_name_pass_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_assert_size_stride_op_name_fail_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_assert_size_stride_op_name_pass_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_avg_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_avg_pool2d2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_avg_pool2d6_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_avg_pool3d_backward3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_avg_pool3d_backward4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bitwise_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bmm1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bmm2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bool_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_broadcast_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_default_kwargs_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int16_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int32_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int64_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int64_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int64_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int8_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int8_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_int8_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_bucketize_int_uint8_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_buffer_batch_norm_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_buffer_use_after_remove_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_builtins_round_float_ndigits_neg_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_builtins_round_int_ndigits_pos_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cat_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cat_extern_kernel_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cat_of_loops_and_extern_kernel_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cat_unbacked_2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cat_unbacked_legacy_empty_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cauchy_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_clamp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_clamp_type_promotion_non_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_clone_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_complex_fallback_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_concat_add_inplace_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_consecutive_split_cumsum_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_constant_pad_1d_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_conv2d_channels_last_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_conv_inference_heuristics_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_convolution2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_convolution3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_convolution4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cumprod_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cumsum_inf_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_cumsum_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_custom_op_3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_custom_op_default_layout_constraint_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_custom_op_fixed_layout_channels_last_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_custom_scan_op_compiled_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_custom_scan_op_multi_input_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dense_mask_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dist_bf16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_div4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_div_prim_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_div_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_bfloat16_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_bfloat16_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_bfloat16_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float16_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float16_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float32_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float32_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float32_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float32_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float64_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_float64_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int16_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int16_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int32_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int64_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int64_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int64_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int8_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int8_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int8_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int8_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_int8_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_uint8_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_uint8_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_uint8_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_uint8_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_dtypeview_uint8_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_embedding_sparse_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_erfc_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_exp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_expand_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fallback_mutable_op_basic_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fallback_mutable_op_list_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fallback_mutable_op_with_return_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fft_real_input_real_output_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_flip_cat_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_float32_to_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_forced_buffer_realize_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fractional_max_pool2d2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_functionalize_rng_wrappers_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_fusing_write_into_disjoint_read_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_gather1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_gather2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_gather_scatter_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_glu_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_graph_partition_arange2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_graph_partition_both_scalars_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_graph_partition_constant_tensor1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_graph_partition_constant_tensor2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_grid_sampler_2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_hardsigmoid_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_hardtanh_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_propagation_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_propagation_floordiv_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_propagation_nested_indirect_indexing_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put_as_masked_fill_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put_fallback2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_put_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_select_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_index_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_indirect_load_broadcast_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_inf_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_inner_fn_str_and_stride_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_inplace_activations_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_inplace_mixed_dtype_ops_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_inplace_resize_as_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_input_mutation2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_input_mutation4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_int8_weight_only_quant_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_isinf_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_large_broadcast_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_large_grid_use_block_ptr_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_large_strided_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_large_tensor_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_leaky_relu_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_lerp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_like_rands2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_linear1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_linear_dynamic_maxautotune_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_linspace4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_log_fp64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_logaddexp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_logcumsumexp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_long_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_low_memory_max_pool_dilation_2_dim_3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_mark_dynamic_with_hint_override_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_masked_fill_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_max_pool2d4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_max_pool2d6_dilation_1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_max_pool2d8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_max_pool2d_with_indices_backward4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_max_pool2d_with_indices_backward6_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_mean_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_min_max_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_mix_device_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_multi_device_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_multilayer_prime_size_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_multilayer_var_lowp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_mutable_custom_op_fixed_layout2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_nan_sort_stable_False_descending_True_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_nan_sort_stable_True_descending_True_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_neg_max_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_new_ones_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_nll_loss_backward_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_one_hot_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pattern_matcher_multi_user_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pixel_shuffle_channels_last_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_bessel_j1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_bessel_y0_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_bessel_y1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_chebyshev_polynomial_v_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_erfc_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_erfcx_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_erfinv_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_gammaincc_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_i0e_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_laguerre_polynomial_l_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_legendre_polynomial_p_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_log1p_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_modified_bessel_i1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_modified_bessel_k1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_scaled_modified_bessel_k0_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_scaled_modified_bessel_k1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pointwise_shifted_chebyshev_polynomial_t_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_polar_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_pow_by_natural_log2_dynamic_shapes_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_prepare_softmax_with_fast_math_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_reduction5_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_reduction_config_limit_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_reflection_pad2d_backward_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_relu_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_remainder_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_remove_no_ops_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_remove_noop_clone_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_remove_noop_view_default_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_remove_noop_view_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_repeat_as_strided_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_repeat_interleave_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_repeat_interleave_Tensor_decomp_int64_nd_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_repeat_interleave_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_resize_as_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_roll_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_round_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_scalar_cpu_tensor_arg_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_scatter_add1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_scatter_reduce2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sdpa_prefer_nd_tiling_False_use_block_ptr_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sdpa_prefer_nd_tiling_True_use_block_ptr_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_searchsorted_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_setitem_with_int_parameter_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sgn_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_shape_prop_torch_ones_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_signbit_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_simplify_loops_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice_mutation1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice_scatter3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice_scatter_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_slice_scatter_reinplace_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_cumprod_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_cumsum_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_cumsum_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_reduction_dynamic_shape_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_reduction_with_int64_size_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_with_list_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_with_sizes_with_unbacked_symints_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_split_with_unbacked_symints_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_squeeze1_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_squeeze2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_squeeze_varargs_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_std_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sum4_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sum5_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_sum_keepdims_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_tensor2_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_tensor3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_tensor_index_slice_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_tmp_not_defined_issue3_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_to_device_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_transpose_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_transposed_propagates_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_unfold_zero_dimension_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_unspec_inputs_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_unspec_inputs_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_upsample_bicubic2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_upsample_nearest2d_backward_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_upsample_nearest2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_var_mean_tile_reduction_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_vdd_clamp_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_view_as_complex_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_view_on_aliased_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_weight_norm_bwd_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_xblock_divides_xnumel_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenCpuTests::test_zeros_dynamic_shapes_cpu, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_AllenaiLongformerBase_repro_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test__dyn_quant_matmul_4bit_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test__dyn_quant_pack_4bit_weight_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test__unsafe_masked_index_put_accumulate_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_adaptive_avg_pool2d2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_adaptive_pool_errors_with_long_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_add_complex4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_add_complex5_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_add_complex6_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_add_complex7_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_add_complex9_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_adding_tensor_offsets_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_addmm_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_angle_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_aoti_eager_override_registration_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_arange3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_arange4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_arange6_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_argmax_argmin1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_as_strided_scatter_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_assert_alignment_op_name_pass_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_assert_size_stride_op_name_fail_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_assert_size_stride_op_name_pass_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d5_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d6_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d_backward2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d_backward4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool2d_backward_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_avg_pool3d_backward4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bernoulli1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bitwise2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bmm1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bmm2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_both_scalars_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_broadcast_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int16_int64_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int16_uint8_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int32_int8_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int8_int32_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int8_int64_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int8_int8_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_int8_uint8_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_uint8_int16_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_uint8_int32_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_bucketize_int_uint8_int8_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_builtins_round_float_ndigits_neg_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_cat_empty_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_cat_unbacked_empty_1d_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_cat_upcasting_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_cauchy_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_clamp_type_promotion_dynamic_shapes_cuda, 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test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_reduction4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_reduction5_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_reduction_config_limit_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_reinterpret_dtypeview_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_remove_no_ops_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_remove_noop_slice_scatter_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_remove_noop_view_default_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_repeat_as_strided_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_repeat_interleave_Tensor_decomp_int32_nd_1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_require_stride_expanded_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_resize_as_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_roi_align_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_round_correctness_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_scaled_dot_product_attention_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_scatter2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_scatter_add1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_scatter_reduce2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_scatter_reduce3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sdpa_prefer_nd_tiling_True_use_block_ptr_True_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_setitem_with_int_parameter_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sgn_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_shape_padding_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sigmoid_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_single_elem_indirect_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_size_asserts_for_multi_output_fallback_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice4_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_mutation1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_mutation2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_mutation3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_scatter2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_scatter3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_scatter5_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_slice_scatter_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_softmax_one_kernel_loop_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sort_bool_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_cumsum_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_failed_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_reduction_dynamic_shape_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_reduction_with_int64_size_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_with_integer_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_split_with_list_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_squeeze1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_squeeze2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_stack_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sum1_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_sum_int_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_tmp_not_defined_issue2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_to_device_constant_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_to_dtype_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_to_memory_format_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_transpose_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_uint4x2_mixed_mm_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_uint_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unbacked_floordiv_simplify_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unbacked_floordiv_simplify_errors_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unbind_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unfold_zero_dimension_tensor_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unroll_small_reduction_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_unsqueeze_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_upsample_bicubic2d_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_upsample_bilinear2d_b_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_upsample_nearest2d_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_var_mean_tile_reduction_False_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_var_mean_tile_reduction_True_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_vdd_clamp_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_vectorized_ops_masked_var_novec_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_view_as_real_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_view_on_aliased_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_views2_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_views3_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_views6_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_views7_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_xblock_divides_xnumel_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_zero_dim_reductions_dynamic_shapes_cuda, test/inductor/test_torchinductor_codegen_dynamic_shapes.py::DynamicShapesCodegenGPUTests::test_zeros_dynamic_shapes_cuda 2025-08-26T21:04:56.1787817Z 2025-08-26T21:04:56.1787927Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T21:04:56.1788113Z Uploading artifacts took 0.00 seconds 2025-08-26T21:04:56.1788287Z Running inductor/test_cpu_repro 4/4 ... [2025-08-26 21:04:56.157205] 2025-08-26T21:04:56.1788454Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:04:56.1820632Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_cpu_repro.py', '--shard-id=4', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:04:56.157401] 2025-08-26T21:25:59.0114505Z 2025-08-26T21:25:59.0116327Z inductor/test_cpu_repro 4/4 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_repro_4.4_4088f8be5b6477d2_.log 2025-08-26T21:25:59.0185491Z Running 183 items in this shard: test/inductor/test_cpu_repro.py::CPUReproTests::test_ModularIndexing_range_issue_103133, test/inductor/test_cpu_repro.py::CPUReproTests::test__adaptive_avg_pool2d, test/inductor/test_cpu_repro.py::CPUReproTests::test_acosh_with_negative_large_input, test/inductor/test_cpu_repro.py::CPUReproTests::test_atomic_add_lowp_fp, test/inductor/test_cpu_repro.py::CPUReproTests::test_auto_zvec_vsx_simd, test/inductor/test_cpu_repro.py::CPUReproTests::test_bf16_zeros, test/inductor/test_cpu_repro.py::CPUReproTests::test_bitwise_logical_op_bool, test/inductor/test_cpu_repro.py::CPUReproTests::test_bool_reduction_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_channel_shuffle_cl_output, test/inductor/test_cpu_repro.py::CPUReproTests::test_consistent_remove_buffers, test/inductor/test_cpu_repro.py::CPUReproTests::test_conv2d_packed, test/inductor/test_cpu_repro.py::CPUReproTests::test_conv_in_channel_1_dynamic_shapes, test/inductor/test_cpu_repro.py::CPUReproTests::test_convert_int64_to_int32_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_decomposed_dequant_relu_quant_int8, test/inductor/test_cpu_repro.py::CPUReproTests::test_dequant_maxpool2d_lowering_uint8, test/inductor/test_cpu_repro.py::CPUReproTests::test_dequant_relu_quant_dequant_relu_quant_lowering_uint8, test/inductor/test_cpu_repro.py::CPUReproTests::test_fp32_load_with_to_lowp_fp, test/inductor/test_cpu_repro.py::CPUReproTests::test_fp8_cast_float16_shape_15,3,13, test/inductor/test_cpu_repro.py::CPUReproTests::test_fp8_cast_float16_shape_4,2048,4096, test/inductor/test_cpu_repro.py::CPUReproTests::test_fused_node, test/inductor/test_cpu_repro.py::CPUReproTests::test_group_norm_large_input, test/inductor/test_cpu_repro.py::CPUReproTests::test_group_norm_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_int32_reduction_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_int64_pointwise_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_int_div_vec, test/inductor/test_cpu_repro.py::CPUReproTests::test_linear_packed, test/inductor/test_cpu_repro.py::CPUReproTests::test_load_inf_bf16, test/inductor/test_cpu_repro.py::CPUReproTests::test_load_same_bool_tensor_twice, test/inductor/test_cpu_repro.py::CPUReproTests::test_lowp_fp_neg_abs, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_change_input_sizes_cpu_unbatched_False_input_size_2_hidden_size_5_num_layers_3_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_2_seq_len_3, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_False_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_False_batch_first_True_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_False_batch_first_True_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_False_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_False_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_False_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_False_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_False_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_True_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_True_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_False_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_1_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_False_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_False_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_True_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_False_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_False_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_False_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_False_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_False_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_False_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_1_bidirectional_True_bias_True_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_False_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_False_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_False_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_1_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_True_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_False_batch_first_False_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_False_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_False_batch_first_True_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_True_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_False_bias_True_empty_state_True_batch_first_True_batch_size_1_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_False_batch_first_False_batch_size_1_seq_len_1, 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test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_True_bias_False_empty_state_True_batch_first_True_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_7_seq_len_1, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_False_batch_size_7_seq_len_7, test/inductor/test_cpu_repro.py::CPUReproTests::test_lstm_packed_unbatched_False_input_size_7_hidden_size_7_num_layers_7_bidirectional_True_bias_True_empty_state_False_batch_first_True_batch_size_7_seq_len_1, 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test/inductor/test_cpu_repro.py::CPUReproTests::test_outer_loop_fusion_buffer_remove, test/inductor/test_cpu_repro.py::CPUReproTests::test_pack_padded_sequence_lstm, test/inductor/test_cpu_repro.py::CPUReproTests::test_parallel_reduction_vectorization, test/inductor/test_cpu_repro.py::CPUReproTests::test_per_channel_fake_quant_module_uint8, test/inductor/test_cpu_repro.py::CPUReproTests::test_select_tiliing_with_index_expr, test/inductor/test_cpu_repro.py::CPUReproTests::test_sign_cpu_only, test/inductor/test_cpu_repro.py::CPUReproTests::test_symbolic_shape_scalar_value_reduction, test/inductor/test_cpu_repro.py::CPUReproTests::test_to_channels_last_lowp_fp, test/inductor/test_cpu_repro.py::CPUReproTests::test_to_dtype_bool_float, test/inductor/test_cpu_repro.py::CPUReproTests::test_to_uint8_rounding_method, test/inductor/test_cpu_repro.py::CPUReproTests::test_transpose_vertical_sum_cpu_only, test/inductor/test_cpu_repro.py::CPUReproTests::test_two_local_buffers_in_outer_loop_fusion, test/inductor/test_cpu_repro.py::CPUReproTests::test_uint8_add, test/inductor/test_cpu_repro.py::CPUReproTests::test_uint8_sub, test/inductor/test_cpu_repro.py::CPUReproTests::test_unrolled_bool_prod_vectorized, test/inductor/test_cpu_repro.py::CPUReproTests::test_unsupported_conv_transpose, test/inductor/test_cpu_repro.py::CPUReproTests::test_vec_randn, test/inductor/test_cpu_repro.py::CPUReproTests::test_vec_remainder 2025-08-26T21:25:59.0261259Z 2025-08-26T21:25:59.0261448Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T21:25:59.0261753Z Uploading artifacts took 0.00 seconds 2025-08-26T21:25:59.0262047Z Running inductor/test_compile_subprocess 1/2 ... [2025-08-26 21:25:59.011855] 2025-08-26T21:25:59.0262340Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:25:59.0262986Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:25:59.012159] 2025-08-26T21:32:43.4659791Z 2025-08-26T21:32:43.4660651Z inductor/test_compile_subprocess 1/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_1.2_b63521f73880522c_.log 2025-08-26T21:32:43.4713143Z Running 416 items in this shard: test/inductor/test_compile_subprocess.py::TestSubprocess::test_progressive, test/inductor/test_compile_subprocess.py::GPUTests::test_AllenaiLongformerBase_repro_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test__dyn_quant_pack_4bit_weight_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test__unsafe_masked_index_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_abs_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_adaptive_avg_pool1d_argmax_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_adaptive_avg_pool2d2_cuda, 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test/inductor/test_compile_subprocess.py::GPUTests::test_shape_padding_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_silu_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_size_asserts_for_multi_output_fallback_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice2_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice4_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice_mutation3_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice_scatter3_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice_scatter4_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice_scatter_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_slice_view_with_graph_break_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_softmax_backward_data_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_softmax_one_kernel_loop_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sort_bool_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sort_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sort_stable_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sort_transpose_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_special_polygamma_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_split_cumprod_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_split_cumsum_low_prec_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_split_failed_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_split_with_list_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_split_with_sizes_with_unbacked_symints_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_std_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_stride_preservation_with_stride_modifying_fx_pass_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_strided_inputs_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sum1_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sum3_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sum_dtype_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sum_int_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_sum_keepdims_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tanh_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tensor1_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tensor2_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tensor3_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tensor_index_put_slice_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tmp_not_defined_issue1_use_block_ptr_True_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tmp_not_defined_issue2_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_tmp_not_defined_issue3_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_to_device_constant_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_to_memory_format_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_topk_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_transpose_add_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_transposed_propagates_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_triton_kernel_bool_param_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_triu_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_uint4x2_mixed_mm_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unbacked_floordiv_simplify_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unbacked_floordiv_simplify_errors_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unroll_small_reduction_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_float32_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_float64_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_int16_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_int32_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_int64_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unspec_inputs_int8_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_unsqueeze_inplace_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_upsample_bilinear2d_a_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_upsample_cat_conv_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_upsample_nearest1d_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_var_correction_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_var_mean_tile_reduction_False_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_vdd_clamp_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_view_as_complex_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_view_as_real_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_view_detach_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_views2_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_views4_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_views5_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_views6_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_weight_norm_bwd_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_where_broadcast_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_where_with_logical_op_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_zero_dim_reductions_cuda, test/inductor/test_compile_subprocess.py::GPUTests::test_zero_element_mutation_cuda 2025-08-26T21:32:43.4763688Z 2025-08-26T21:32:43.4763809Z Running inductor/test_loop_ordering 1/1 ... [2025-08-26 21:32:43.468127] 2025-08-26T21:32:43.4763986Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:32:43.4764380Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_loop_ordering.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:32:43.468376] 2025-08-26T21:33:18.7631865Z 2025-08-26T21:33:18.7633082Z inductor/test_loop_ordering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_loop_ordering_1.1_7e289f5130d7d4be_.log 2025-08-26T21:33:18.7644321Z Running 44 items in this shard: test/inductor/test_loop_ordering.py::ImplDetailTest::test_merge_loops_invalidate_pw_dep_cache, test/inductor/test_loop_ordering.py::ImplDetailTest::test_reorder_and_merge_loops, test/inductor/test_loop_ordering.py::ImplDetailTest::test_reorder_modular_indexing, test/inductor/test_loop_ordering.py::ImplDetailTest::test_reorder_twice, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_apbt_realize, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_different_broadcast_shapes, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_different_reduction_order, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_for_reordering_reindex, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_fp8_cast_and_t, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_fp8_pattern_2, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_fuse_reduction_with_tiled_pw, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_keep_fake_dep, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_pw_outer_red, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_pw_outer_red_2, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_sum_and_t, test/inductor/test_loop_ordering.py::LoopOrderingTest::test_view, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_coalescing, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_induced_fused_tiling, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_inferred_splits_inps0, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_inferred_splits_inps1, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_inferred_splits_inps2, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_inferred_splits_inps3, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_reduction_no_pointwise, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_reduction_pointwise, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_remapped_reads, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_remapped_reads_split, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_solve_for_tiling, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_solve_for_zero, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_tiled_coalesce_analysis_downcast_transposed_v_False, test/inductor/test_loop_ordering.py::MemoryCoalescingTest::test_tiled_coalesce_analysis_downcast_transposed_v_True, test/inductor/test_loop_ordering.py::TestTiling::test_3d_pointwise, test/inductor/test_loop_ordering.py::TestTiling::test_cat, test/inductor/test_loop_ordering.py::TestTiling::test_mutation_deps, test/inductor/test_loop_ordering.py::TestTiling::test_penalized_small_dim, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_NHWC_b_NHWC, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_NHWC_b_T, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_NHWC_b_cont, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_T_b_NHWC, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_T_b_T, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_T_b_cont, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_cont_b_NHWC, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_cont_b_T, test/inductor/test_loop_ordering.py::TestTiling::test_pointwise_a_cont_b_cont, test/inductor/test_loop_ordering.py::TestTiling::test_tiled_reduction 2025-08-26T21:33:18.7649228Z 2025-08-26T21:33:18.7649337Z Running inductor/test_scatter_optimization 1/1 ... [2025-08-26 21:33:18.761120] 2025-08-26T21:33:18.7649527Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:33:18.7650117Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_scatter_optimization.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:33:18.761375] 2025-08-26T21:33:37.3295816Z 2025-08-26T21:33:37.3296627Z inductor/test_scatter_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_scatter_optimization_1.1_2243102b4f0a021d_.log 2025-08-26T21:33:37.3298334Z Running 8 items in this shard: test/inductor/test_scatter_optimization.py::TestScatterOpt::test_3d_tensor, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_can_not_optimize_due_to_dense, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_can_not_optimize_due_to_non_const, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_cross_entropy_loss, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_neg_scatter_dim, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_non_last_dim, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_nonzero_const_tensor, test/inductor/test_scatter_optimization.py::TestScatterOpt::test_shorter_index_tensor 2025-08-26T21:33:37.3299367Z 2025-08-26T21:33:37.3299643Z Running inductor/test_inductor_freezing 1/1 ... [2025-08-26 21:33:37.329492] 2025-08-26T21:33:37.3299923Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:33:37.3300501Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_inductor_freezing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:33:37.329700] 2025-08-26T21:34:29.4282119Z 2025-08-26T21:34:29.4294681Z inductor/test_inductor_freezing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_freezing_1.1_1bcbd4f6f2d4b969_.log 2025-08-26T21:34:29.4302098Z Running 48 items in this shard: test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_aliased_param_return_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_autocast_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_bn_with_multi_bn_share_conv_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_functional_bn_with_multi_bn_share_conv_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_layout_convert_with_view_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_multiple_uses_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_weight_layout_convert_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_conv_with_as_strided_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_cpp_wrapper_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_dont_change_dtype_folding_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_error_on_eager_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_folded_conv_bn_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_folded_conv_bn_hardswish_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_folded_conv_bn_with_module_sharing_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_folded_conv_functional_bn_with_module_sharing_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_mm_concat_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_mutation_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_param_deallocated_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_redundant_clone_for_layout_convert_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_rng_op_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_static_indices_cudagraph_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_symint_not_folded_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_unequal_bias_horizontal_addmm_fusion_cpu, test/inductor/test_inductor_freezing.py::FreezingCpuTests::test_unfolded_bn_cpu, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_aliased_param_return_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_autocast_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_bn_with_multi_bn_share_conv_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_functional_bn_with_multi_bn_share_conv_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_layout_convert_with_view_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_multiple_uses_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_weight_layout_convert_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_conv_with_as_strided_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_cpp_wrapper_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_dont_change_dtype_folding_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_error_on_eager_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_folded_conv_bn_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_folded_conv_bn_hardswish_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_folded_conv_bn_with_module_sharing_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_folded_conv_functional_bn_with_module_sharing_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_mm_concat_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_mutation_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_param_deallocated_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_redundant_clone_for_layout_convert_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_rng_op_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_static_indices_cudagraph_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_symint_not_folded_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_unequal_bias_horizontal_addmm_fusion_cuda, test/inductor/test_inductor_freezing.py::FreezingGpuTests::test_unfolded_bn_cuda 2025-08-26T21:34:29.4308394Z 2025-08-26T21:34:29.4316036Z Running dynamo/test_unittest 1/1 ... [2025-08-26 21:34:29.427951] 2025-08-26T21:34:29.4316427Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:34:29.4319986Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_unittest.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:34:29.428227] 2025-08-26T21:34:32.3467484Z 2025-08-26T21:34:32.3468339Z dynamo/test_unittest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unittest_1.1_ca9f1e59595338d8_.log 2025-08-26T21:34:32.3469079Z Running 1 items in this shard: test/dynamo/test_unittest.py::TestUnittest::test_SkipTest 2025-08-26T21:34:32.3469350Z 2025-08-26T21:34:32.3469676Z Running inductor/test_cutlass_backend 1/1 ... [2025-08-26 21:34:32.346685] 2025-08-26T21:34:32.3470082Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:34:32.3478764Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_cutlass_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:34:32.346920] 2025-08-26T21:34:37.6202843Z 2025-08-26T21:34:37.6204009Z inductor/test_cutlass_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_backend_1.1_464d47dcef59685b_.log 2025-08-26T21:34:37.6230311Z Running 148 items in this shard: test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_aoti_workspace_ptr, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_check_paths, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_compilation_time_use_aoti_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_compilation_time_use_aoti_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_config_number_post_filtering, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_fp8_scaled_mm_fast_accum_filtering, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_integration, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_matmul_nonzero_offset, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_matmul_same_tensor, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_op_allowlist, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_op_denylist, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_shape_coverage_mm, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_subproc_addmm_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_subproc_addmm_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_subproc_bmm, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_backend_subproc_mm, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_key, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_presets_presets_, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_presets_presets_0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_cutlass_presets_presets_0,999, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_diff_matmul_share_same_kernel_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_diff_matmul_share_same_kernel_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_broadcasting_add, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_broadcasting_div, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_broadcasting_mul, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_broadcasting_sub, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_flexible_layout, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_add_shape0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_add_shape1, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_add_shape2, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_add_shape3, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_div_shape0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_div_shape1, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_div_shape2, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_div_shape3, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_mul_shape0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_mul_shape1, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_mul_shape2, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_mul_shape3, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_relu_shape0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_relu_shape1, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_relu_shape2, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_relu_shape3, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_sub_shape0, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_sub_shape1, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_sub_shape2, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_fusions_basic_sub_shape3, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_mixed_dtypes_add, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_mixed_dtypes_div, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_mixed_dtypes_mul, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_mixed_dtypes_relu, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_mixed_dtypes_sub, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_op_add, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_op_div, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_op_mul, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_op_relu, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_op_sub, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_add_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_add_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_div_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_div_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_mul_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_mul_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_relu_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_relu_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_sub_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_multi_output_sub_dynamic_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_return_accumulator, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_reuse_matmul_input_add, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_reuse_matmul_input_div, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_reuse_matmul_input_mul, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_reuse_matmul_input_relu, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_evt_reuse_matmul_input_sub, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_filtered_ops_cache, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_flexible_layout, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_force_cutlass_backend_aoti_cexpr_codegen, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_force_cutlass_backend_aoti_dynamic, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_rowwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_tensorwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_tensorwise_scaling_float8_e4m3fn_shape0_has_bias_False_use_fast_accum_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_tensorwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_fp8_tensorwise_scaling_float8_e4m3fn_shape0_has_bias_True_use_fast_accum_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_gemm_operation_serialization_arch_100_cuda_version_12_4, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_gemm_operation_serialization_arch_100_cuda_version_12_8, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_gemm_operation_serialization_arch_90_cuda_version_12_4, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_gemm_operation_serialization_arch_90_cuda_version_12_8, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_get_max_alignment, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_import_cutlass, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_False_use_aoti_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_False_use_aoti_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_False_use_aoti_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_False_use_aoti_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_True_use_aoti_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_True_use_aoti_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_True_use_aoti_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_addmm_dynamic_True_use_aoti_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_False_bfloat16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_False_bfloat16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_False_float16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_False_float16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_True_bfloat16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_True_bfloat16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_True_float16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_False_use_aoti_True_float16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_False_bfloat16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_False_bfloat16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_False_float16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_False_float16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_True_bfloat16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_True_bfloat16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_True_float16_use_expand_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_bmm_dynamic_True_use_aoti_True_float16_use_expand_True, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_chained_fusion_fp16_fp32acc, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_fp8_scaled_mm_dynamic_False_use_aoti_False_float8_e4m3fn, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_fp8_scaled_mm_dynamic_False_use_aoti_True_float8_e4m3fn, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_fp8_scaled_mm_dynamic_True_use_aoti_False_float8_e4m3fn, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_fp8_scaled_mm_dynamic_True_use_aoti_True_float8_e4m3fn, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_int_mm_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_no_fusion_dtype_mismatch, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_False_use_aoti_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_False_use_aoti_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_False_use_aoti_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_False_use_aoti_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_True_use_aoti_False_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_True_use_aoti_False_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_True_use_aoti_True_bfloat16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_dynamic_True_use_aoti_True_float16, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_regular_mm_streamk, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_relu6_fusion_fp16_fp32acc, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_relu_fusion_fp16_fp32acc, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_shape_dependent_normalization_fusion, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_simple_fusion_fp16_fp32acc, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_backend_sparse_semi_structured_mm_dynamic_False, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_max_autotune_cutlass_threshold, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_maybe_append_choice_caching, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_multiple_mm, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_multiple_mm_with_dynamic_shape, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_number_mm_precompiles, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_standalone_runner, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_streamk_with_dynamic, test/inductor/test_cutlass_backend.py::TestCutlassBackend::test_streamk_with_static 2025-08-26T21:34:37.6258090Z 2025-08-26T21:34:37.6258201Z Running inductor/test_aot_inductor_custom_ops 1/1 ... [2025-08-26 21:34:37.620357] 2025-08-26T21:34:37.6258391Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:34:37.6258877Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_aot_inductor_custom_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:34:37.620549] 2025-08-26T21:36:19.6992126Z 2025-08-26T21:36:19.6994027Z inductor/test_aot_inductor_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_custom_ops_1.1_6af1979acbd84f19_.log 2025-08-26T21:36:19.7003945Z Running 35 items in this shard: test/inductor/test_aot_inductor_custom_ops.py::AOTInductorLoggingTest::test_shape_env_reuse, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_boxed_run_inputs_clearing_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_add_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_add_output_path_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_all_inputs_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_missing_arg_with_default_value_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_out_variant_without_return_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_return_list_of_single_tensor_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_return_single_tensor_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_square_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_with_concat_inputs_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_with_multiple_outputs_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_custom_op_with_reinterpret_view_inputs_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_fn_with_int_output_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_fn_with_optional_tensor_nullopt_output_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_fn_with_optional_tensor_output_2_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_fn_with_optional_tensor_output_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCpu::test_incorrect_custom_op_schema_cpu, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_boxed_run_inputs_clearing_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_add_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_add_output_path_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_all_inputs_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_missing_arg_with_default_value_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_out_variant_without_return_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_return_list_of_single_tensor_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_return_single_tensor_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_square_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_with_concat_inputs_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_with_multiple_outputs_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_custom_op_with_reinterpret_view_inputs_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_fn_with_int_output_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_fn_with_optional_tensor_nullopt_output_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_fn_with_optional_tensor_output_2_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_fn_with_optional_tensor_output_cuda, test/inductor/test_aot_inductor_custom_ops.py::AOTInductorTestABICompatibleCuda::test_incorrect_custom_op_schema_cuda 2025-08-26T21:36:19.7015496Z 2025-08-26T21:36:19.7015593Z Running inductor/test_group_batch_fusion 1/1 ... [2025-08-26 21:36:19.699065] 2025-08-26T21:36:19.7015774Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:36:19.7016174Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_group_batch_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:36:19.699296] 2025-08-26T21:36:52.2711665Z 2025-08-26T21:36:52.2713055Z inductor/test_group_batch_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_group_batch_fusion_1.1_d55b0db3d3f8540b_.log 2025-08-26T21:36:52.2715146Z Running 12 items in this shard: test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_batch_layer_norm_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_batch_linear_lhs_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_batch_linear_pre_grad_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_gate_fusion_post_grad, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_group_linear_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_group_linear_fusion_different_shapes, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_math_op_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_pointwise_op_fusion, test/inductor/test_group_batch_fusion.py::TestGroupBatchFusion::test_pointwise_op_fusion_post_grad, test/inductor/test_group_batch_fusion.py::TestPostGradBatchLinearFusion::test_batch_linear_post_grad_fusion, test/inductor/test_group_batch_fusion.py::TestFindIndependentSubsetGreedy::test_find_independent_subset_greedy, test/inductor/test_group_batch_fusion.py::TestFindIndependentSubsetGreedy::test_find_independent_subset_greedy_fuse 2025-08-26T21:36:52.2717068Z 2025-08-26T21:36:52.2718956Z Running dynamo/test_activation_checkpointing 1/1 ... [2025-08-26 21:36:52.271474] 2025-08-26T21:36:52.2719178Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:36:52.2722083Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_activation_checkpointing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:36:52.271730] 2025-08-26T21:37:10.7287865Z 2025-08-26T21:37:10.7289153Z dynamo/test_activation_checkpointing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_activation_checkpointing_1.1_9f64f61e71242663_.log 2025-08-26T21:37:10.7305610Z Running 31 items in this shard: test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_autocast_flash_attention_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_custom_rule_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_inplace_op_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_invalid_context_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_list_ops_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_must_not_recompute_gemm_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_must_recompute_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_outplace_op_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_parametrization_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_partial_ctx_fn_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_random_op_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_compile_selective_checkpoint_tensor_subclass_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_distributed_utils_checkpoint_wrapper_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_dynamo_does_not_trace_getattr_as_top_frame_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_error_msg_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_fallback_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_kwargs_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_list_inputs_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_pattern_matcher_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_symints_location_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_decomps_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_dropout_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_function_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_function_via_global_checkpoint_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_function_with_kwargs_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_module_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_multiple_checkpoints_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_must_save_tensor_that_has_backward_hook_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_rand_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_recomputed_rand_cuda, test/dynamo/test_activation_checkpointing.py::ActivationCheckpointingViaTagsTestsCUDA::test_tags_sequential_layers_cuda 2025-08-26T21:37:10.7311787Z 2025-08-26T21:37:10.7311875Z Running dynamo/test_subclasses 1/1 ... [2025-08-26 21:37:10.728830] 2025-08-26T21:37:10.7312056Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:37:10.7312459Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_subclasses.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:37:10.729068] 2025-08-26T21:37:42.6061056Z 2025-08-26T21:37:42.6062223Z dynamo/test_subclasses 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_subclasses_1.1_4bb9bdb5234f44e3_.log 2025-08-26T21:37:42.6086458Z Running 125 items in this shard: test/dynamo/test_subclasses.py::SubclassTests::test_as_subclass_attr_mutation, test/dynamo/test_subclasses.py::SubclassTests::test_base_torch_function_tracing, test/dynamo/test_subclasses.py::SubclassTests::test_compile_higher_order_with_functionalization, test/dynamo/test_subclasses.py::SubclassTests::test_compile_with_fake_tensor_automatic_dynamic, test/dynamo/test_subclasses.py::SubclassTests::test_compile_with_fake_tensor_dynamic_dim, test/dynamo/test_subclasses.py::SubclassTests::test_compile_with_functionalization, test/dynamo/test_subclasses.py::SubclassTests::test_disable_all_torch_function, test/dynamo/test_subclasses.py::SubclassTests::test_disable_all_torch_function_restore_values, test/dynamo/test_subclasses.py::SubclassTests::test_disable_all_torch_function_restore_values_graph_break, test/dynamo/test_subclasses.py::SubclassTests::test_has_torch_function, test/dynamo/test_subclasses.py::SubclassTests::test_make_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_mark_static_with_subclass_desugaring_dynamic_False, test/dynamo/test_subclasses.py::SubclassTests::test_mark_static_with_subclass_desugaring_dynamic_True, test/dynamo/test_subclasses.py::SubclassTests::test_newly_constructed_tensor_subclass_attr_mutation, test/dynamo/test_subclasses.py::SubclassTests::test_njt_subclass_from_buffer, test/dynamo/test_subclasses.py::SubclassTests::test_njt_subclass_from_cat, test/dynamo/test_subclasses.py::SubclassTests::test_njt_subclass_simple, test/dynamo/test_subclasses.py::SubclassTests::test_no_call_to_new, test/dynamo/test_subclasses.py::SubclassTests::test_no_torch_function_on_size_bytecode, test/dynamo/test_subclasses.py::SubclassTests::test_no_torch_function_recompiles, test/dynamo/test_subclasses.py::SubclassTests::test_nontraceable_tensor_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_overridden_method_guarding, test/dynamo/test_subclasses.py::SubclassTests::test_parameter_subclass_custom_torch_func_and_dynamic_attr, test/dynamo/test_subclasses.py::SubclassTests::test_parameter_subclass_with_old_torch_function, test/dynamo/test_subclasses.py::SubclassTests::test_recompile_with_symbool_inputs, test/dynamo/test_subclasses.py::SubclassTests::test_recompiles_with_optional_inner_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_return_as_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_return_local_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_return_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_TwoTensor_TwoTensor_TwoTensor, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_TwoTensor_nested_diff_sizes, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_constructor_proxying, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_dont_invoke_torch_function_on_overridden_attr, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_dont_invoke_torch_function_on_overridden_method, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_override_shape_and_to, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_views_dynamic_False, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_views_dynamic_True, test/dynamo/test_subclasses.py::SubclassTests::test_subclass_with_disabled_torch_function, test/dynamo/test_subclasses.py::SubclassTests::test_support_bases, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_automatic_dynamic_shapes, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_clone_view, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_different_shape, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_mark_dynamic_shapes, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_mul, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_nested, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_return_multiple, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_return_shape, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_return_tensor_and_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_simple, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_view, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_TwoTensor_view_mul, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_attr_codegen_tos, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_ctx_custom_guards_error_arg_num, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_ctx_custom_guards_error_not_classmethod, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_ctx_custom_guards_override, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_ctx_guards, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_ctx_recursive_guards, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_custom_attr, test/dynamo/test_subclasses.py::SubclassTests::test_tensor_subclass_with_non_classmethod_torch_function, test/dynamo/test_subclasses.py::SubclassTests::test_torch_dispatch_subclass_guard_recompile, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_call_on_attr, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_call_on_method, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_call_on_method_arg, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_list_args, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_state_graph_break, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_state_guards, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_state_nested, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_state_tracing, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_subclass_survives_into_aot_autograd, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_wrapper_class, test/dynamo/test_subclasses.py::SubclassTests::test_torch_function_wrapper_class_with_kwargs, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_equality_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_equality_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_identity_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_identity_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_isinstance_subclass, test/dynamo/test_subclasses.py::SubclassTests::test_type_check_isinstance_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_user_overridden_attr_unsupported, test/dynamo/test_subclasses.py::SubclassTests::test_user_overridden_method_unsupported, test/dynamo/test_subclasses.py::SubclassTests::test_user_overridden_property_unsupported, test/dynamo/test_subclasses.py::SubclassTests::test_wrapper_subclass_dynamo_attribute_access_on_intermediate, test/dynamo/test_subclasses.py::SubclassTests::test_wrapper_subclass_guards_on_inner_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_wrapper_subclass_with_differently_sized_inner_tensor, test/dynamo/test_subclasses.py::SubclassTests::test_wrapper_subclass_with_same_sized_inner_tensor, test/dynamo/test_subclasses.py::TestNestedTensor::test_basic_autograd, test/dynamo/test_subclasses.py::TestNestedTensor::test_basic_autograd_inductor, test/dynamo/test_subclasses.py::TestNestedTensor::test_binary_does_not_recompile, test/dynamo/test_subclasses.py::TestNestedTensor::test_binary_recompiles, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_input, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_input_2, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_input_4, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_input_5, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_input_6, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_intermediate, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_intermediate_2, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_intermediate_3, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_intermediate_4, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_from_intermediate_5, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_mixed, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_mixed_2, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_construction_mixed_3, test/dynamo/test_subclasses.py::TestNestedTensor::test_in_graph_is_nested_call, test/dynamo/test_subclasses.py::TestNestedTensor::test_inference_tensor, test/dynamo/test_subclasses.py::TestNestedTensor::test_inline_nested_tensor_from_jagged, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_basic, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_leaf_False_False, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_leaf_False_True, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_leaf_True_False, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_leaf_True_True, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_False_obscure, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_basic, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_leaf_False_False, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_leaf_False_True, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_leaf_True_False, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_leaf_True_True, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_base_is_nt_True_obscure, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_dense_subclass_dense_subclass, test/dynamo/test_subclasses.py::TestNestedTensor::test_inputs_to_compiled_fn_are_views_nt_view_name_subclass_dense, test/dynamo/test_subclasses.py::TestNestedTensor::test_param_subclass_isinstance_input, test/dynamo/test_subclasses.py::TestNestedTensor::test_return_shape, test/dynamo/test_subclasses.py::TestNestedTensor::test_subclass_dense_subclass_dense_view, test/dynamo/test_subclasses.py::TestNestedTensor::test_subclass_gives_static_shapes_when_dynamic_false, test/dynamo/test_subclasses.py::TestNestedTensor::test_subclass_with_mutation_in_graph, test/dynamo/test_subclasses.py::TestNestedTensor::test_unary_does_not_recompile, test/dynamo/test_subclasses.py::TestNestedTensor::test_unbind 2025-08-26T21:37:42.6106820Z 2025-08-26T21:37:42.6106916Z Running inductor/test_triton_syntax 1/1 ... [2025-08-26 21:37:42.606142] 2025-08-26T21:37:42.6107089Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:37:42.6107473Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_triton_syntax.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:37:42.606373] 2025-08-26T21:37:58.3502056Z 2025-08-26T21:37:58.3503894Z inductor/test_triton_syntax 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_syntax_1.1_d2b978381f8a27c9_.log 2025-08-26T21:37:58.3505201Z Running 1 items in this shard: test/inductor/test_triton_syntax.py::TestTritonSyntacticallyValid::test_triton_sqrt 2025-08-26T21:37:58.3505499Z 2025-08-26T21:37:58.3505639Z Running inductor/test_ck_backend 1/1 ... [2025-08-26 21:37:58.350007] 2025-08-26T21:37:58.3505913Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:37:58.3506535Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_ck_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:37:58.350274] 2025-08-26T21:38:03.3726560Z 2025-08-26T21:38:03.3727832Z inductor/test_ck_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_ck_backend_1.1_7c5d727460e8f830_.log 2025-08-26T21:38:03.3743602Z Running 34 items in this shard: test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_ATen,Triton,CK_x_shape0, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_ATen,Triton,CK_x_shape1, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_ATen,Triton,CK_x_shape2, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_CK_x_shape0, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_CK_x_shape1, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_addmm_max_autotune_gemm_backends_CK_x_shape2, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_conv2d_max_autotune_conv_backends_ATEN,CK,TRITON, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_conv2d_max_autotune_conv_backends_CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_bmm_max_autotune_gemm_backends_ATen,Triton,CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_bmm_max_autotune_gemm_backends_CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_dynamic_max_autotune_gemm_backends_CK_autotune_in_subproc_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_ATen,Triton,CK_autotune_in_subproc_False_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_ATen,Triton,CK_autotune_in_subproc_False_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_ATen,Triton,CK_autotune_in_subproc_True_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_ATen,Triton,CK_autotune_in_subproc_True_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CKTILE_autotune_in_subproc_False_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CKTILE_autotune_in_subproc_False_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CKTILE_autotune_in_subproc_True_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CKTILE_autotune_in_subproc_True_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CK_autotune_in_subproc_False_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CK_autotune_in_subproc_False_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CK_autotune_in_subproc_True_use_aoti_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_matmul_max_autotune_gemm_backends_CK_autotune_in_subproc_True_use_aoti_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_non_contiguous_max_autotune_gemm_backends_Aten,CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_preselected_max_autotune_gemm_backends_ATen,Triton,CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_precompile_preselected_max_autotune_gemm_backends_CK, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_ATen,Triton,CK_quantize_type_rowwise_has_bias_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_ATen,Triton,CK_quantize_type_rowwise_has_bias_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_ATen,Triton,CK_quantize_type_tensorwise_has_bias_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_ATen,Triton,CK_quantize_type_tensorwise_has_bias_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_CK_quantize_type_rowwise_has_bias_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_CK_quantize_type_rowwise_has_bias_True, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_CK_quantize_type_tensorwise_has_bias_False, test/inductor/test_ck_backend.py::TestCKBackend::test_max_autotune_scaled_mm_max_autotune_gemm_backends_CK_quantize_type_tensorwise_has_bias_True 2025-08-26T21:38:03.3752675Z 2025-08-26T21:38:03.3752774Z Running inductor/test_debug_trace 1/1 ... [2025-08-26 21:38:03.372641] 2025-08-26T21:38:03.3752970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:03.3753417Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_debug_trace.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:03.372854] 2025-08-26T21:38:14.2573356Z 2025-08-26T21:38:14.2574333Z inductor/test_debug_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_debug_trace_1.1_faafb0bacf92e123_.log 2025-08-26T21:38:14.2575229Z Running 3 items in this shard: test/inductor/test_debug_trace.py::TestDebugTrace::test_debug_multi_tempalte, test/inductor/test_debug_trace.py::TestDebugTrace::test_debug_printer_const, test/inductor/test_debug_trace.py::TestDebugTrace::test_debug_trace 2025-08-26T21:38:14.2575810Z 2025-08-26T21:38:14.2575954Z Running inductor/test_distributed_patterns 1/1 ... [2025-08-26 21:38:14.257229] 2025-08-26T21:38:14.2576214Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:14.2578370Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_distributed_patterns.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:14.257443] 2025-08-26T21:38:29.1573047Z 2025-08-26T21:38:29.1574953Z inductor/test_distributed_patterns 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_distributed_patterns_1.1_ed61518a572b1fe5_.log 2025-08-26T21:38:29.1581909Z Running 20 items in this shard: test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_fake_distributed_aot_eager, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_fake_distributed_inductor, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_intermediate_hook_with_closure, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_intermediate_hook_with_nested_closure, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_aot, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_eager, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_inductor, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_multi_layers, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return2, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return3, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return4, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_nonzero_cpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_nonzero_gpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_zero_cpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_zero_gpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_preserve_version_counter1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_preserve_version_counter2, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_set_version_counter1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_set_version_counter2 2025-08-26T21:38:29.1585038Z 2025-08-26T21:38:29.1585148Z Running inductor/test_external_callables 1/1 ... [2025-08-26 21:38:29.157211] 2025-08-26T21:38:29.1585338Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:29.1585743Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_external_callables.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:29.157397] 2025-08-26T21:38:42.4991006Z 2025-08-26T21:38:42.4991808Z inductor/test_external_callables 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_external_callables_1.1_d7d332ece22d64c7_.log 2025-08-26T21:38:42.4992706Z Running 3 items in this shard: test/inductor/test_external_callables.py::TestInductorExternalCallable::test_matmul_cpu, test/inductor/test_external_callables.py::TestInductorExternalCallable::test_matmul_cuda, test/inductor/test_external_callables.py::TestInductorExternalCallable::test_matmul_dup 2025-08-26T21:38:42.4993268Z 2025-08-26T21:38:42.4993381Z Running inductor/test_utils 1/1 ... [2025-08-26 21:38:42.499066] 2025-08-26T21:38:42.4993581Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:42.4997993Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:42.499412] 2025-08-26T21:38:45.1689397Z 2025-08-26T21:38:45.1691611Z inductor/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_utils_1.1_d737d64b50c4f73a_.log 2025-08-26T21:38:45.1700782Z Running 7 items in this shard: test/inductor/test_utils.py::TestUtilsCUDA::testSympySubs_cuda, test/inductor/test_utils.py::TestUtilsCUDA::test_flops_fx_cuda, test/inductor/test_utils.py::TestUtilsCUDA::test_get_device_tflops_cuda_bfloat16, test/inductor/test_utils.py::TestUtilsCUDA::test_get_device_tflops_cuda_float16, test/inductor/test_utils.py::TestUtilsCUDA::test_get_device_tflops_cuda_float32, test/inductor/test_utils.py::TestUtilsCUDA::test_sympy_str_cuda, test/inductor/test_utils.py::TestUtilsCUDA::test_zip_schema_cuda 2025-08-26T21:38:45.1702049Z 2025-08-26T21:38:45.1702153Z Running export/test_draft_export 1/1 ... [2025-08-26 21:38:45.168875] 2025-08-26T21:38:45.1702331Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:45.1702852Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'export/test_draft_export.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:45.169155] 2025-08-26T21:38:55.2557533Z 2025-08-26T21:38:55.2559501Z export/test_draft_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_draft_export_1.1_3fa84eb4cdd2afc3_.log 2025-08-26T21:38:55.2573806Z Running 21 items in this shard: test/export/test_draft_export.py::TestDraftExport::test_complex_data_dependent_expr, test/export/test_draft_export.py::TestDraftExport::test_constantify_unbacked_symbol, test/export/test_draft_export.py::TestDraftExport::test_cuda_memory_usage, test/export/test_draft_export.py::TestDraftExport::test_data_dependent_failure, test/export/test_draft_export.py::TestDraftExport::test_dedup_data_dependent_failure, test/export/test_draft_export.py::TestDraftExport::test_fake_infer_dense_in_memory_check, test/export/test_draft_export.py::TestDraftExport::test_masked_linear, test/export/test_draft_export.py::TestDraftExport::test_missing_meta_kernel_custom_op_basic, test/export/test_draft_export.py::TestDraftExport::test_missing_meta_kernel_custom_op_multiple_profiles, test/export/test_draft_export.py::TestDraftExport::test_missing_meta_kernel_custom_op_update_profile, test/export/test_draft_export.py::TestDraftExport::test_missing_meta_kernel_guard, test/export/test_draft_export.py::TestDraftExport::test_missing_meta_kernel_impl, test/export/test_draft_export.py::TestDraftExport::test_offsets, test/export/test_draft_export.py::TestDraftExport::test_override_incorrectly_aliasing_kernel, test/export/test_draft_export.py::TestDraftExport::test_override_mismatched_fake_kernel_with_unbacked_symbols, test/export/test_draft_export.py::TestDraftExport::test_override_size_and_dtype_mismatched_fake_kernels, test/export/test_draft_export.py::TestDraftExport::test_shape_failure, test/export/test_draft_export.py::TestDraftExport::test_side_effect1, test/export/test_draft_export.py::TestDraftExport::test_side_effect_inps, test/export/test_draft_export.py::TestDraftExport::test_torchbind, test/export/test_draft_export.py::TestDraftExport::test_unbacked_div_mod_replacement 2025-08-26T21:38:55.2576668Z 2025-08-26T21:38:55.2576771Z Running export/test_passes 1/1 ... [2025-08-26 21:38:55.255663] 2025-08-26T21:38:55.2576964Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:38:55.2577400Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'export/test_passes.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:38:55.255886] 2025-08-26T21:39:17.3697444Z 2025-08-26T21:39:17.3698219Z export/test_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_passes_1.1_3aaddae8866959bb_.log 2025-08-26T21:39:17.3701549Z Running 27 items in this shard: test/export/test_passes.py::TestPasses::test_constant_folding_pass, test/export/test_passes.py::TestPasses::test_custom_obj_tuple_out, test/export/test_passes.py::TestPasses::test_fakify_script_objects, test/export/test_passes.py::TestPasses::test_fakify_script_objects_properly_handle_containers, test/export/test_passes.py::TestPasses::test_functionalization_with_view_copy, test/export/test_passes.py::TestPasses::test_inline_, test/export/test_passes.py::TestPasses::test_math_ops, test/export/test_passes.py::TestPasses::test_move_device_submod, test/export/test_passes.py::TestPasses::test_move_device_to, test/export/test_passes.py::TestPasses::test_move_to_device_pass, test/export/test_passes.py::TestPasses::test_predispatch_autocast, test/export/test_passes.py::TestPasses::test_predispatch_autocast_and_set_grad, test/export/test_passes.py::TestPasses::test_predispatch_set_grad, test/export/test_passes.py::TestPasses::test_remove_auto_functionalized_pass, test/export/test_passes.py::TestPasses::test_remove_auto_functionalized_pass_tuple, test/export/test_passes.py::TestPasses::test_remove_effect_token_kwargs, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_cond, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_item, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_nonzero, test/export/test_passes.py::TestPasses::test_runtime_assert_multiple_dims, test/export/test_passes.py::TestPasses::test_runtime_assert_one_dim, test/export/test_passes.py::TestPasses::test_runtime_assert_some_dims_not_specified, test/export/test_passes.py::TestPasses::test_runtime_assert_some_inps_not_used, test/export/test_passes.py::TestPasses::test_sequential_split, test/export/test_passes.py::TestPasses::test_sequential_split_graph, test/export/test_passes.py::TestPasses::test_view_to_view_copy, test/export/test_passes.py::TestPasses::test_views_op_having_view_copy 2025-08-26T21:39:17.3704358Z 2025-08-26T21:39:17.3704459Z Running inductor/test_inplacing_pass 1/1 ... [2025-08-26 21:39:17.369841] 2025-08-26T21:39:17.3704638Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:39:17.3705038Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:39:17.370151] 2025-08-26T21:39:29.5536110Z 2025-08-26T21:39:29.5537950Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_4148436bd7db339f_.log 2025-08-26T21:39:29.5547074Z Running 22 items in this shard: test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_counters_functionalize_old, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_counters_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_dont_modify_input, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_dont_modify_live, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_dont_modify_view_of_live, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_generalized_scatter, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_lists_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_lists_old_functionalize, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_multi_output_intermediate, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_multiple_intermediate, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_multiple_mutations, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_partitioner_recomputes_factory_empty_like_sin_op, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_partitioner_recomputes_factory_empty_like_sin_triton, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_partitioner_recomputes_factory_ones_like_sin_op, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_partitioner_recomputes_factory_ones_like_sin_triton, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_should_modify_inner, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_should_modify_input, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_view_inplaced2_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_view_inplaced_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_views_not_inplaced2_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_views_not_inplaced3_functionalize_v2, test/inductor/test_inplacing_pass.py::TestReinplacingPassCorrectness::test_views_not_inplaced_functionalize_v2 2025-08-26T21:39:29.5552918Z 2025-08-26T21:39:29.5553192Z Running dynamo/test_aot_autograd 1/1 ... [2025-08-26 21:39:29.553631] 2025-08-26T21:39:29.5553451Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:39:29.5553983Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_aot_autograd.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:39:29.553880] 2025-08-26T21:40:07.8157067Z 2025-08-26T21:40:07.8158553Z dynamo/test_aot_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_1.1_3d8f9375338e25ad_.log 2025-08-26T21:40:07.8169812Z Running 48 items in this shard: test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_LSTM, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_alias_inputs, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_autograd_expand_mutation_backwards, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_autograd_expand_mutation_error, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_autograd_expand_mutation_functionalizes, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_autograd_raises_invalid_leaf_set, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_export_joint_simple_repro, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_grad_mode_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_aot_sequence_nr, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_args, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_args_param, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_args_param_non_tensor_arg, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_args_param_non_tensor_arg_list, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_with_global, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_autograd_function_tangent_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_call_fn_with_non_const_inputs_aot_safe, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_call_fn_with_non_const_inputs_aot_unsafe, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_call_fn_with_non_const_inputs_aot_unsafe_control_flow, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_data_ptr_access_copy, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_data_ptr_access_fails_in_backward, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_data_ptr_access_fails_in_forward, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_different_inputs_overlapping_set_with_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer1, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer2, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer3, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer4, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer5, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer6, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph1, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph2, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph3, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph4, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_double_backward_errors, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_eager_sequence_nr, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_grad_inputs_alias_inputs, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_inputs_overlapping_with_mutation_recompile, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_inputs_overlapping_with_mutation_stress, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_multiple_aot_autograd_calls_dupe_args, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_mutation1, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_negative_testing, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_negative_testing_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_nn_parameter_construction, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_no_storage_overlap_guards_no_aliasing, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_no_storage_overlap_guards_no_mutation, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_requires_grad_fake_via_dynamo_recompiles, test/dynamo/test_aot_autograd.py::AotAutogradFallbackTests::test_split_with_sizes_aot_autograd_cleans_up_traceback_meta 2025-08-26T21:40:07.8177634Z 2025-08-26T21:40:07.8177729Z Running dynamo/test_functions 1/1 ... [2025-08-26 21:40:07.815613] 2025-08-26T21:40:07.8177910Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:40:07.8183833Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_functions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:40:07.815895] 2025-08-26T21:40:48.8605853Z 2025-08-26T21:40:48.8607124Z dynamo/test_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_functions_1.1_ca3181f8faa4dccc_.log 2025-08-26T21:40:48.8653369Z Running 465 items in this shard: test/dynamo/test_functions.py::FunctionTests::test_T, test/dynamo/test_functions.py::FunctionTests::test_add, test/dynamo/test_functions.py::FunctionTests::test_add_, test/dynamo/test_functions.py::FunctionTests::test_addcdiv, test/dynamo/test_functions.py::FunctionTests::test_addcdiv_, test/dynamo/test_functions.py::FunctionTests::test_addcmul_, test/dynamo/test_functions.py::FunctionTests::test_are_functorch_transforms_active, test/dynamo/test_functions.py::FunctionTests::test_attrgetter, test/dynamo/test_functions.py::FunctionTests::test_broadcast_foreach_pow, test/dynamo/test_functions.py::FunctionTests::test_build_list_unpack, test/dynamo/test_functions.py::FunctionTests::test_call_dict1, test/dynamo/test_functions.py::FunctionTests::test_call_dict2, test/dynamo/test_functions.py::FunctionTests::test_call_dict3, test/dynamo/test_functions.py::FunctionTests::test_call_dict4, test/dynamo/test_functions.py::FunctionTests::test_call_dict5, test/dynamo/test_functions.py::FunctionTests::test_callable_builtin, test/dynamo/test_functions.py::FunctionTests::test_callable_class, test/dynamo/test_functions.py::FunctionTests::test_callable_lambda, test/dynamo/test_functions.py::FunctionTests::test_callable_list, test/dynamo/test_functions.py::FunctionTests::test_callable_torch, test/dynamo/test_functions.py::FunctionTests::test_chunks1, test/dynamo/test_functions.py::FunctionTests::test_class_dict, test/dynamo/test_functions.py::FunctionTests::test_cls_eq, test/dynamo/test_functions.py::FunctionTests::test_cls_hasattr, test/dynamo/test_functions.py::FunctionTests::test_cls_is, test/dynamo/test_functions.py::FunctionTests::test_compare_constant_and_tensor, test/dynamo/test_functions.py::FunctionTests::test_complex_closure, test/dynamo/test_functions.py::FunctionTests::test_const_tuple_add1, test/dynamo/test_functions.py::FunctionTests::test_const_tuple_add2, test/dynamo/test_functions.py::FunctionTests::test_constant1, test/dynamo/test_functions.py::FunctionTests::test_constant2, test/dynamo/test_functions.py::FunctionTests::test_constant3, test/dynamo/test_functions.py::FunctionTests::test_constant4, test/dynamo/test_functions.py::FunctionTests::test_constant_set, test/dynamo/test_functions.py::FunctionTests::test_context_wrapping_nested_functions_no_closure, test/dynamo/test_functions.py::FunctionTests::test_cublas_allow_tf32, test/dynamo/test_functions.py::FunctionTests::test_custom_dict_kwargs, test/dynamo/test_functions.py::FunctionTests::test_default_dict_closure, test/dynamo/test_functions.py::FunctionTests::test_default_dict_constr, test/dynamo/test_functions.py::FunctionTests::test_default_dict_dict, test/dynamo/test_functions.py::FunctionTests::test_default_dict_lambda, test/dynamo/test_functions.py::FunctionTests::test_default_dict_list, test/dynamo/test_functions.py::FunctionTests::test_default_dict_set, test/dynamo/test_functions.py::FunctionTests::test_default_dict_tuple, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault1, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault2, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault3, test/dynamo/test_functions.py::FunctionTests::test_del, test/dynamo/test_functions.py::FunctionTests::test_deque, test/dynamo/test_functions.py::FunctionTests::test_device, test/dynamo/test_functions.py::FunctionTests::test_device_constant, test/dynamo/test_functions.py::FunctionTests::test_dict_copy, test/dynamo/test_functions.py::FunctionTests::test_dict_fromkeys, test/dynamo/test_functions.py::FunctionTests::test_dict_hasattr, test/dynamo/test_functions.py::FunctionTests::test_dict_id_guard, test/dynamo/test_functions.py::FunctionTests::test_dict_items_sorted, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set1, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set2, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set3, test/dynamo/test_functions.py::FunctionTests::test_dict_keys, test/dynamo/test_functions.py::FunctionTests::test_dict_kwargs, test/dynamo/test_functions.py::FunctionTests::test_dict_mutable_map, test/dynamo/test_functions.py::FunctionTests::test_dict_ops, test/dynamo/test_functions.py::FunctionTests::test_dict_param_keys, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault1, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault2, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault3, test/dynamo/test_functions.py::FunctionTests::test_dict_sorted, test/dynamo/test_functions.py::FunctionTests::test_dict_tuple_lazy_guard, test/dynamo/test_functions.py::FunctionTests::test_dict_update, test/dynamo/test_functions.py::FunctionTests::test_dict_update_kwargs, test/dynamo/test_functions.py::FunctionTests::test_dict_values, test/dynamo/test_functions.py::FunctionTests::test_distributed_is_available, test/dynamo/test_functions.py::FunctionTests::test_distributed_is_initialized, test/dynamo/test_functions.py::FunctionTests::test_dtype, test/dynamo/test_functions.py::FunctionTests::test_dtype_compare, test/dynamo/test_functions.py::FunctionTests::test_elipsis, test/dynamo/test_functions.py::FunctionTests::test_enumerate, test/dynamo/test_functions.py::FunctionTests::test_enumerate_custom, test/dynamo/test_functions.py::FunctionTests::test_enumerate_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter, test/dynamo/test_functions.py::FunctionTests::test_filter_fallback, test/dynamo/test_functions.py::FunctionTests::test_filter_graph_break_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter_infinite_iterator, test/dynamo/test_functions.py::FunctionTests::test_filter_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter_with_graph_break, test/dynamo/test_functions.py::FunctionTests::test_finfo, test/dynamo/test_functions.py::FunctionTests::test_flat_param_same_storage_size, test/dynamo/test_functions.py::FunctionTests::test_float, test/dynamo/test_functions.py::FunctionTests::test_fn_with_self_set, test/dynamo/test_functions.py::FunctionTests::test_foreach_lerp_, test/dynamo/test_functions.py::FunctionTests::test_fstrings1, test/dynamo/test_functions.py::FunctionTests::test_fstrings2, test/dynamo/test_functions.py::FunctionTests::test_fstrings3, test/dynamo/test_functions.py::FunctionTests::test_fstrings4, test/dynamo/test_functions.py::FunctionTests::test_fstrings5, test/dynamo/test_functions.py::FunctionTests::test_fstrings6, test/dynamo/test_functions.py::FunctionTests::test_funcdef_closure, test/dynamo/test_functions.py::FunctionTests::test_functools_cache_guard, test/dynamo/test_functions.py::FunctionTests::test_functools_partial, test/dynamo/test_functions.py::FunctionTests::test_functools_partial_binding, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_hasattr, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_subclass, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_user_methods, test/dynamo/test_functions.py::FunctionTests::test_get_autocast_gpu_dtype, test/dynamo/test_functions.py::FunctionTests::test_get_calculate_correct_fan, test/dynamo/test_functions.py::FunctionTests::test_get_default_dtype, test/dynamo/test_functions.py::FunctionTests::test_get_device_properties_tensor_device, test/dynamo/test_functions.py::FunctionTests::test_get_privateuse1_name, test/dynamo/test_functions.py::FunctionTests::test_getattr, test/dynamo/test_functions.py::FunctionTests::test_getattr_metaclass, test/dynamo/test_functions.py::FunctionTests::test_globalfn, test/dynamo/test_functions.py::FunctionTests::test_globalmodule, test/dynamo/test_functions.py::FunctionTests::test_globalvar, test/dynamo/test_functions.py::FunctionTests::test_import1, test/dynamo/test_functions.py::FunctionTests::test_in_not_in, test/dynamo/test_functions.py::FunctionTests::test_index, test/dynamo/test_functions.py::FunctionTests::test_indexed_range, test/dynamo/test_functions.py::FunctionTests::test_indirect1, test/dynamo/test_functions.py::FunctionTests::test_indirect2, test/dynamo/test_functions.py::FunctionTests::test_indirect3, test/dynamo/test_functions.py::FunctionTests::test_inline_jit__unwrap_optional, test/dynamo/test_functions.py::FunctionTests::test_inline_jit_annotations, test/dynamo/test_functions.py::FunctionTests::test_inline_lru_cache_fn_with_default_args, test/dynamo/test_functions.py::FunctionTests::test_inline_script_if_tracing_fn_with_default_args, test/dynamo/test_functions.py::FunctionTests::test_inline_softmax, test/dynamo/test_functions.py::FunctionTests::test_inline_with_default, test/dynamo/test_functions.py::FunctionTests::test_inner_function, test/dynamo/test_functions.py::FunctionTests::test_is, test/dynamo/test_functions.py::FunctionTests::test_is_any_autocast_enabled, test/dynamo/test_functions.py::FunctionTests::test_is_checkpoint_valid, test/dynamo/test_functions.py::FunctionTests::test_is_complex, test/dynamo/test_functions.py::FunctionTests::test_is_contiguous_frame_counts, test/dynamo/test_functions.py::FunctionTests::test_is_contiguous_memory_format, test/dynamo/test_functions.py::FunctionTests::test_is_floating_point, test/dynamo/test_functions.py::FunctionTests::test_is_fx_tracing, test/dynamo/test_functions.py::FunctionTests::test_is_in_onnx_export, test/dynamo/test_functions.py::FunctionTests::test_is_inference_mode_global_recompilation, test/dynamo/test_functions.py::FunctionTests::test_is_inference_recompilation, test/dynamo/test_functions.py::FunctionTests::test_is_integer, test/dynamo/test_functions.py::FunctionTests::test_is_not, test/dynamo/test_functions.py::FunctionTests::test_is_not_null, test/dynamo/test_functions.py::FunctionTests::test_is_quantized, test/dynamo/test_functions.py::FunctionTests::test_is_sparse, test/dynamo/test_functions.py::FunctionTests::test_isinstance, test/dynamo/test_functions.py::FunctionTests::test_islice_chain, test/dynamo/test_functions.py::FunctionTests::test_itemgetter, test/dynamo/test_functions.py::FunctionTests::test_itertools_chain, test/dynamo/test_functions.py::FunctionTests::test_itertools_chain_from_iterable, test/dynamo/test_functions.py::FunctionTests::test_itertools_combinations, test/dynamo/test_functions.py::FunctionTests::test_itertools_compress, test/dynamo/test_functions.py::FunctionTests::test_itertools_compress_tensors, test/dynamo/test_functions.py::FunctionTests::test_itertools_filterfalse_basic, test/dynamo/test_functions.py::FunctionTests::test_itertools_pairwise, test/dynamo/test_functions.py::FunctionTests::test_itertools_permutations_args, test/dynamo/test_functions.py::FunctionTests::test_itertools_permutations_basic, test/dynamo/test_functions.py::FunctionTests::test_itertools_permutations_various_iterators, test/dynamo/test_functions.py::FunctionTests::test_itertools_product, test/dynamo/test_functions.py::FunctionTests::test_itertools_product_args, test/dynamo/test_functions.py::FunctionTests::test_itertools_product_various_iterators, test/dynamo/test_functions.py::FunctionTests::test_itertools_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_jit_annotate, test/dynamo/test_functions.py::FunctionTests::test_len_constant_dict, test/dynamo/test_functions.py::FunctionTests::test_len_constant_list, test/dynamo/test_functions.py::FunctionTests::test_len_constant_misc_iterables, test/dynamo/test_functions.py::FunctionTests::test_len_tensor, test/dynamo/test_functions.py::FunctionTests::test_list_add, test/dynamo/test_functions.py::FunctionTests::test_list_add_then_mutate, test/dynamo/test_functions.py::FunctionTests::test_list_clear, test/dynamo/test_functions.py::FunctionTests::test_list_compare_polyfill, test/dynamo/test_functions.py::FunctionTests::test_list_compare_polyfill_non_lists, test/dynamo/test_functions.py::FunctionTests::test_list_convert, test/dynamo/test_functions.py::FunctionTests::test_list_expand_lhs, test/dynamo/test_functions.py::FunctionTests::test_list_index_with_constant_tensor, test/dynamo/test_functions.py::FunctionTests::test_list_reversed, test/dynamo/test_functions.py::FunctionTests::test_list_setitem, test/dynamo/test_functions.py::FunctionTests::test_list_setitem_slice, test/dynamo/test_functions.py::FunctionTests::test_list_slice, test/dynamo/test_functions.py::FunctionTests::test_list_slice_assignment, test/dynamo/test_functions.py::FunctionTests::test_list_sorted1, test/dynamo/test_functions.py::FunctionTests::test_list_sorted2, test/dynamo/test_functions.py::FunctionTests::test_list_truth, test/dynamo/test_functions.py::FunctionTests::test_listarg1, test/dynamo/test_functions.py::FunctionTests::test_listarg2, test/dynamo/test_functions.py::FunctionTests::test_listarg3, test/dynamo/test_functions.py::FunctionTests::test_listarg4, test/dynamo/test_functions.py::FunctionTests::test_listarg5, test/dynamo/test_functions.py::FunctionTests::test_load_global_bool, test/dynamo/test_functions.py::FunctionTests::test_lru_cache_warning_issued_during_tracing, test/dynamo/test_functions.py::FunctionTests::test_mT, test/dynamo/test_functions.py::FunctionTests::test_manual_seed, test/dynamo/test_functions.py::FunctionTests::test_map_call_function_ex, test/dynamo/test_functions.py::FunctionTests::test_map_deque_extendleft, test/dynamo/test_functions.py::FunctionTests::test_map_dict_fromkeys, test/dynamo/test_functions.py::FunctionTests::test_map_enumerate, test/dynamo/test_functions.py::FunctionTests::test_map_infinite, test/dynamo/test_functions.py::FunctionTests::test_map_iter, test/dynamo/test_functions.py::FunctionTests::test_map_list, test/dynamo/test_functions.py::FunctionTests::test_map_list_extend, test/dynamo/test_functions.py::FunctionTests::test_map_list_slice_assign, test/dynamo/test_functions.py::FunctionTests::test_map_max, test/dynamo/test_functions.py::FunctionTests::test_map_max_const, test/dynamo/test_functions.py::FunctionTests::test_map_partial_unpack, test/dynamo/test_functions.py::FunctionTests::test_map_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_map_reduce, test/dynamo/test_functions.py::FunctionTests::test_map_return, test/dynamo/test_functions.py::FunctionTests::test_map_set, test/dynamo/test_functions.py::FunctionTests::test_map_sorted, test/dynamo/test_functions.py::FunctionTests::test_map_str_join, test/dynamo/test_functions.py::FunctionTests::test_map_sum, test/dynamo/test_functions.py::FunctionTests::test_map_tuple, test/dynamo/test_functions.py::FunctionTests::test_map_unpack_twice, test/dynamo/test_functions.py::FunctionTests::test_map_unpack_vars, test/dynamo/test_functions.py::FunctionTests::test_map_with_graph_break, test/dynamo/test_functions.py::FunctionTests::test_map_zip_dict, test/dynamo/test_functions.py::FunctionTests::test_math_radians, test/dynamo/test_functions.py::FunctionTests::test_mean_sum_np, test/dynamo/test_functions.py::FunctionTests::test_methodcall1, test/dynamo/test_functions.py::FunctionTests::test_methodcall2, test/dynamo/test_functions.py::FunctionTests::test_methodcall3, test/dynamo/test_functions.py::FunctionTests::test_methodcaller, test/dynamo/test_functions.py::FunctionTests::test_min_max, test/dynamo/test_functions.py::FunctionTests::test_module_constant, test/dynamo/test_functions.py::FunctionTests::test_namedtuple, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_defaults, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_fields, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_hasattr, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_replace, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_subclass, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_user_methods, test/dynamo/test_functions.py::FunctionTests::test_ndarray_builtin_functions, test/dynamo/test_functions.py::FunctionTests::test_ndarray_method, test/dynamo/test_functions.py::FunctionTests::test_ndarray_methods_returning_scalar, test/dynamo/test_functions.py::FunctionTests::test_ndarray_reshape, test/dynamo/test_functions.py::FunctionTests::test_ndarray_transpose, test/dynamo/test_functions.py::FunctionTests::test_ndim, test/dynamo/test_functions.py::FunctionTests::test_no_recompile_inner_function, test/dynamo/test_functions.py::FunctionTests::test_no_recompile_inner_lambda, test/dynamo/test_functions.py::FunctionTests::test_non_inlined_closure, test/dynamo/test_functions.py::FunctionTests::test_not_list, test/dynamo/test_functions.py::FunctionTests::test_np_constant_collections_as_input_int_or_float_float, test/dynamo/test_functions.py::FunctionTests::test_np_constant_collections_as_input_int_or_float_int, test/dynamo/test_functions.py::FunctionTests::test_np_constant_collections_guards_float, test/dynamo/test_functions.py::FunctionTests::test_np_constant_collections_guards_int, test/dynamo/test_functions.py::FunctionTests::test_np_finfo, test/dynamo/test_functions.py::FunctionTests::test_np_iinfo, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_as_integer_ratio_num_type0, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_as_integer_ratio_num_type3, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_bit_length_num_type1, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_conjugate_num_type2, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_conjugate_num_type4, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_hex_num_type5, test/dynamo/test_functions.py::FunctionTests::test_number_method_method_is_integer_num_type6, test/dynamo/test_functions.py::FunctionTests::test_numpy_attributes, test/dynamo/test_functions.py::FunctionTests::test_numpy_dtype_argument_to_function, test/dynamo/test_functions.py::FunctionTests::test_numpy_dtype_call_in_function, test/dynamo/test_functions.py::FunctionTests::test_numpy_fft, test/dynamo/test_functions.py::FunctionTests::test_numpy_linalg, test/dynamo/test_functions.py::FunctionTests::test_numpy_meshgrid, test/dynamo/test_functions.py::FunctionTests::test_numpy_random, test/dynamo/test_functions.py::FunctionTests::test_numpy_size, test/dynamo/test_functions.py::FunctionTests::test_obj_eq, test/dynamo/test_functions.py::FunctionTests::test_obj_is, test/dynamo/test_functions.py::FunctionTests::test_ordered_dict_kwargs, test/dynamo/test_functions.py::FunctionTests::test_partial_across_graph_break_uninvoked, test/dynamo/test_functions.py::FunctionTests::test_partials_as_input_UDF, test/dynamo/test_functions.py::FunctionTests::test_partials_as_input_partials_lambda, test/dynamo/test_functions.py::FunctionTests::test_partials_as_input_partials_mod, test/dynamo/test_functions.py::FunctionTests::test_partials_graph_break_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_partials_graph_break_reconstruct_args_and_kwargs, test/dynamo/test_functions.py::FunctionTests::test_partials_graph_break_reconstruct_mix, test/dynamo/test_functions.py::FunctionTests::test_partials_graph_break_reconstruct_mix_no_source, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___annotations__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___builtins__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___call__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___class__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___closure__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___code__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___defaults__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___delattr__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___dict__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___dir__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___doc__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___eq__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___format__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___ge__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___get__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___getattribute__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___globals__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___gt__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___hash__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___init__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___init_subclass__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___kwdefaults__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___le__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___lt__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___module__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___name__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___ne__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___new__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___qualname__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___reduce__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___reduce_ex__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___repr__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___setattr__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___sizeof__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___str__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr___subclasshook__, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr_args, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr_func, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_attr_keywords, test/dynamo/test_functions.py::FunctionTests::test_partials_hasattr_set_attr, test/dynamo/test_functions.py::FunctionTests::test_partials_lambda, test/dynamo/test_functions.py::FunctionTests::test_partials_recompilation, test/dynamo/test_functions.py::FunctionTests::test_partials_torch_op_arg, test/dynamo/test_functions.py::FunctionTests::test_partials_torch_op_kwarg, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_arg, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg_method, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg_module, test/dynamo/test_functions.py::FunctionTests::test_pop, test/dynamo/test_functions.py::FunctionTests::test_pos, test/dynamo/test_functions.py::FunctionTests::test_pow_int, test/dynamo/test_functions.py::FunctionTests::test_promote_types, test/dynamo/test_functions.py::FunctionTests::test_rand_inlined, test/dynamo/test_functions.py::FunctionTests::test_rand_tensor_partial, test/dynamo/test_functions.py::FunctionTests::test_range1, test/dynamo/test_functions.py::FunctionTests::test_range2, test/dynamo/test_functions.py::FunctionTests::test_range_length, test/dynamo/test_functions.py::FunctionTests::test_range_with_index, test/dynamo/test_functions.py::FunctionTests::test_range_with_slice_index, test/dynamo/test_functions.py::FunctionTests::test_reduce, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_initial, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_none_initial, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_single, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_single_with_initial, test/dynamo/test_functions.py::FunctionTests::test_return_dict, test/dynamo/test_functions.py::FunctionTests::test_return_dict2, test/dynamo/test_functions.py::FunctionTests::test_return_multiple_numpy_ndarray, test/dynamo/test_functions.py::FunctionTests::test_return_numpy_ndarray, test/dynamo/test_functions.py::FunctionTests::test_return_tuple1, test/dynamo/test_functions.py::FunctionTests::test_return_tuple2, test/dynamo/test_functions.py::FunctionTests::test_returning_recursive_func, test/dynamo/test_functions.py::FunctionTests::test_round, test/dynamo/test_functions.py::FunctionTests::test_set_add, test/dynamo/test_functions.py::FunctionTests::test_set_in_frozenset, test/dynamo/test_functions.py::FunctionTests::test_set_keys_view, test/dynamo/test_functions.py::FunctionTests::test_set_update_bytecode, test/dynamo/test_functions.py::FunctionTests::test_set_update_list_with_duplicated_items, test/dynamo/test_functions.py::FunctionTests::test_shape1, test/dynamo/test_functions.py::FunctionTests::test_shape2, test/dynamo/test_functions.py::FunctionTests::test_size_tuple_add, test/dynamo/test_functions.py::FunctionTests::test_slice1, test/dynamo/test_functions.py::FunctionTests::test_slice2, test/dynamo/test_functions.py::FunctionTests::test_slice3, test/dynamo/test_functions.py::FunctionTests::test_slice4, test/dynamo/test_functions.py::FunctionTests::test_slice5, test/dynamo/test_functions.py::FunctionTests::test_slice6, test/dynamo/test_functions.py::FunctionTests::test_slice_eq, test/dynamo/test_functions.py::FunctionTests::test_sliced_range, test/dynamo/test_functions.py::FunctionTests::test_sorted_const_key_non_const_items, test/dynamo/test_functions.py::FunctionTests::test_sourceless_build_method_type, test/dynamo/test_functions.py::FunctionTests::test_startswith, test/dynamo/test_functions.py::FunctionTests::test_sum, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut_with_start_arg, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut_with_start_kwarg, test/dynamo/test_functions.py::FunctionTests::test_sum_with_start_arg, test/dynamo/test_functions.py::FunctionTests::test_sum_with_start_kwarg, test/dynamo/test_functions.py::FunctionTests::test_symbool_to_int, test/dynamo/test_functions.py::FunctionTests::test_tensor_dim, test/dynamo/test_functions.py::FunctionTests::test_tensor_element_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_is_complex, test/dynamo/test_functions.py::FunctionTests::test_tensor_len, test/dynamo/test_functions.py::FunctionTests::test_tensor_new_with_shape, test/dynamo/test_functions.py::FunctionTests::test_tensor_new_with_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_size_indexed_by_symint, test/dynamo/test_functions.py::FunctionTests::test_tensor_type, test/dynamo/test_functions.py::FunctionTests::test_tensor_type2, test/dynamo/test_functions.py::FunctionTests::test_tensor_type3, test/dynamo/test_functions.py::FunctionTests::test_tensor_type4, test/dynamo/test_functions.py::FunctionTests::test_tensor_type5, test/dynamo/test_functions.py::FunctionTests::test_to, test/dynamo/test_functions.py::FunctionTests::test_torch_distributions_functions, test/dynamo/test_functions.py::FunctionTests::test_torch_from_numpy, test/dynamo/test_functions.py::FunctionTests::test_torch_get_device_module, test/dynamo/test_functions.py::FunctionTests::test_torch_size_as_dict_key, test/dynamo/test_functions.py::FunctionTests::test_torch_size_hasattr, test/dynamo/test_functions.py::FunctionTests::test_torch_source, test/dynamo/test_functions.py::FunctionTests::test_transpose_for_scores, test/dynamo/test_functions.py::FunctionTests::test_truth, test/dynamo/test_functions.py::FunctionTests::test_tuple1, test/dynamo/test_functions.py::FunctionTests::test_tuple2, test/dynamo/test_functions.py::FunctionTests::test_tuple_contains, test/dynamo/test_functions.py::FunctionTests::test_tuple_iadd, test/dynamo/test_functions.py::FunctionTests::test_tuple_map, test/dynamo/test_functions.py::FunctionTests::test_tuple_sorted, test/dynamo/test_functions.py::FunctionTests::test_two_point_iter, test/dynamo/test_functions.py::FunctionTests::test_unary_fold_op, test/dynamo/test_functions.py::FunctionTests::test_unary_fold_op_seq, test/dynamo/test_functions.py::FunctionTests::test_unpack1, test/dynamo/test_functions.py::FunctionTests::test_unpack2, test/dynamo/test_functions.py::FunctionTests::test_unpack3, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex1, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex2, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex3, test/dynamo/test_functions.py::FunctionTests::test_unpack_mutable_map, test/dynamo/test_functions.py::FunctionTests::test_unsqueeze_inplace, test/dynamo/test_functions.py::FunctionTests::test_viamethod, test/dynamo/test_functions.py::FunctionTests::test_viatorch, test/dynamo/test_functions.py::FunctionTests::test_zip_longest, test/dynamo/test_functions.py::FunctionTests::test_zip_reconstruct, test/dynamo/test_functions.py::DefaultsTests::test_cast_tensor_single_elem, test/dynamo/test_functions.py::DefaultsTests::test_cuda_current_device, test/dynamo/test_functions.py::DefaultsTests::test_dataclass_factory, test/dynamo/test_functions.py::DefaultsTests::test_dataclass_nested, test/dynamo/test_functions.py::DefaultsTests::test_fn_with_attr, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_construction, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_illegal_call_method, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_copy, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_difference, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_intersection, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_symmetric_difference, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_union, test/dynamo/test_functions.py::DefaultsTests::test_func_attrs, test/dynamo/test_functions.py::DefaultsTests::test_func_default_tensor_args, test/dynamo/test_functions.py::DefaultsTests::test_func_default_torch_args, test/dynamo/test_functions.py::DefaultsTests::test_functional_compile, test/dynamo/test_functions.py::DefaultsTests::test_functools_partial_id, test/dynamo/test_functions.py::DefaultsTests::test_fx_immutable_list_mutation_not_allowed, test/dynamo/test_functions.py::DefaultsTests::test_fx_map_aggregate, test/dynamo/test_functions.py::DefaultsTests::test_in_set_inplace, test/dynamo/test_functions.py::DefaultsTests::test_in_set_would_fail_broadcast, test/dynamo/test_functions.py::DefaultsTests::test_inspect_method_source, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_vmapped_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_vmapped_mutated_tensor_tensor_multi_arg, test/dynamo/test_functions.py::DefaultsTests::test_is_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_mutated_tensor_tensor_across_graph_break, test/dynamo/test_functions.py::DefaultsTests::test_is_not_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_vmapped_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_keyword, test/dynamo/test_functions.py::DefaultsTests::test_listlike_of_tensors_contains_constant, test/dynamo/test_functions.py::DefaultsTests::test_meth_default_tensor_args, test/dynamo/test_functions.py::DefaultsTests::test_pybind_object, test/dynamo/test_functions.py::DefaultsTests::test_reconstructed_name, test/dynamo/test_functions.py::DefaultsTests::test_set_call___init___frozenset, test/dynamo/test_functions.py::DefaultsTests::test_set_call___init___set, test/dynamo/test_functions.py::DefaultsTests::test_set_construction, test/dynamo/test_functions.py::DefaultsTests::test_skip_function_call_very_weird_value, test/dynamo/test_functions.py::DefaultsTests::test_str_handler_for_user_defined_object, test/dynamo/test_functions.py::DefaultsTests::test_sys_recursionlimit, test/dynamo/test_functions.py::DefaultsTests::test_tree_map, test/dynamo/test_functions.py::DefaultsTests::test_udf_list, test/dynamo/test_functions.py::DefaultsTests::test_udf_list_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_udf_list_slice, test/dynamo/test_functions.py::DefaultsTests::test_udf_namedtuple, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_construction, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_construction_custom_new, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_zip_strict 2025-08-26T21:40:48.8702317Z 2025-08-26T21:40:48.8702399Z Running inductor/test_fuzzer 1/1 ... [2025-08-26 21:40:48.861084] 2025-08-26T21:40:48.8702557Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:40:48.8702934Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_fuzzer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:40:48.861314] 2025-08-26T21:40:57.6425764Z 2025-08-26T21:40:57.6426896Z inductor/test_fuzzer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fuzzer_1.1_f46244f676ae757b_.log 2025-08-26T21:40:57.6429873Z Running 11 items in this shard: test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_bisector_boolean, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_bisector_exception, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_dynamo_bisect, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_inductor_bisect, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_inductor_cpu, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_inductor_gpu, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_config_fuzzer_n_tuple, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_fuzzer_inductor_calling_compile, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_fuzzer_running_test, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_sampling_method_random, test/inductor/test_fuzzer.py::TestConfigFuzzer::test_sampling_method_toggle 2025-08-26T21:40:57.6432440Z 2025-08-26T21:40:57.6434017Z Running inductor/test_torchinductor_codegen_config_overrides 1/1 ... [2025-08-26 21:40:57.642432] 2025-08-26T21:40:57.6435382Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:40:57.6435945Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_torchinductor_codegen_config_overrides.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:40:57.642618] 2025-08-26T21:41:06.8738815Z 2025-08-26T21:41:06.8739542Z inductor/test_torchinductor_codegen_config_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_codegen_config_overrides_1.1_102df6963e7124b1_.log 2025-08-26T21:41:06.8740714Z Running 3 items in this shard: test/inductor/test_torchinductor_codegen_config_overrides.py::CodegenInductorTest::test_force_pointwise_cat_force_pointwise_cat_False, test/inductor/test_torchinductor_codegen_config_overrides.py::CodegenInductorTest::test_force_pointwise_cat_force_pointwise_cat_True, test/inductor/test_torchinductor_codegen_config_overrides.py::CodegenInductorTest::test_kernel_fusion_thresholds 2025-08-26T21:41:06.8741307Z 2025-08-26T21:41:06.8741398Z Running export/test_experimental 1/1 ... [2025-08-26 21:41:06.873694] 2025-08-26T21:41:06.8741580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:41:06.8741971Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'export/test_experimental.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:41:06.873878] 2025-08-26T21:41:13.9524460Z 2025-08-26T21:41:13.9531379Z export/test_experimental 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_experimental_1.1_277c48a0608cb163_.log 2025-08-26T21:41:13.9532982Z Running 8 items in this shard: test/export/test_experimental.py::TestExperiment::test_joint_basic, test/export/test_experimental.py::TestExperiment::test_joint_buffer_input_mutations, test/export/test_experimental.py::TestExperiment::test_joint_cifar10_backwards, test/export/test_experimental.py::TestExperiment::test_joint_dynamic, test/export/test_experimental.py::TestExperiment::test_joint_loss_index, test/export/test_experimental.py::TestExperiment::test_sticky_export, test/export/test_experimental.py::TestExperiment::test_sticky_export_dynamic, test/export/test_experimental.py::TestExperiment::test_sticky_export_nested_inp 2025-08-26T21:41:13.9534006Z 2025-08-26T21:41:13.9534100Z Running export/test_export 1/1 ... [2025-08-26 21:41:13.952185] 2025-08-26T21:41:13.9534294Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:41:13.9534740Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'export/test_export.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:41:13.952391] 2025-08-26T21:42:19.3150969Z 2025-08-26T21:42:19.3152795Z export/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_1.1_3d39319e78ce4cfe_.log 2025-08-26T21:42:19.3220887Z Running 438 items in this shard: test/export/test_export.py::TestDynamismExpression::test_export_assume_static_by_default, test/export/test_export.py::TestDynamismExpression::test_export_constraints_error, test/export/test_export.py::TestDynamismExpression::test_export_constraints_error_not_in_range, test/export/test_export.py::TestDynamismExpression::test_export_inline_constraints, test/export/test_export.py::TestDynamismExpression::test_export_slice_maxsize, test/export/test_export.py::TestDynamismExpression::test_export_slice_unbacked_dim1, test/export/test_export.py::TestDynamismExpression::test_export_strict_narrow_unbacked_expr, test/export/test_export.py::TestDynamismExpression::test_no_grad_param_inplace, test/export/test_export.py::TestDynamismExpression::test_reshape_view_backed_size_oblivious, test/export/test_export.py::TestExport::test__scaled_dot_product_flash_attention, test/export/test_export.py::TestExport::test_additional_inputs_constants, test/export/test_export.py::TestExport::test_allow_explicit_guards_as_runtime_asserts, test/export/test_export.py::TestExport::test_args_type_checked, test/export/test_export.py::TestExport::test_aten_lift_fresh_copy, test/export/test_export.py::TestExport::test_attention, test/export/test_export.py::TestExport::test_attr_assignment_extra, test/export/test_export.py::TestExport::test_automatic_constrain_size, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_constant_relation, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_linear_relation, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_simple_equality, test/export/test_export.py::TestExport::test_baddbmm, test/export/test_export.py::TestExport::test_basic, test/export/test_export.py::TestExport::test_basic_non_strict_fake_tensor, test/export/test_export.py::TestExport::test_basic_non_strict_real_tensor, test/export/test_export.py::TestExport::test_bincount, test/export/test_export.py::TestExport::test_buffer_util, test/export/test_export.py::TestExport::test_capture_subclass_constructor, test/export/test_export.py::TestExport::test_capture_subclass_constructor_torch_ir, test/export/test_export.py::TestExport::test_capture_subclass_wrong, test/export/test_export.py::TestExport::test_ccode_python_mod, test/export/test_export.py::TestExport::test_check_specialized_int, test/export/test_export.py::TestExport::test_checks_to_constrain_range, test/export/test_export.py::TestExport::test_cleanup_dynamic_markers, test/export/test_export.py::TestExport::test_colin_unbacked_backed_vr_sub, test/export/test_export.py::TestExport::test_colon_parameter, test/export/test_export.py::TestExport::test_compiling_state, test/export/test_export.py::TestExport::test_cond_access_identical_symint_closure, test/export/test_export.py::TestExport::test_cond_branches_return_constant_int, test/export/test_export.py::TestExport::test_cond_branches_return_same_int, test/export/test_export.py::TestExport::test_cond_buffers, test/export/test_export.py::TestExport::test_cond_contains_unbacked_no_escape, test/export/test_export.py::TestExport::test_cond_int_closure, test/export/test_export.py::TestExport::test_cond_unflatten, test/export/test_export.py::TestExport::test_cond_with_module_stack_export_with, test/export/test_export.py::TestExport::test_cond_with_module_stack_export_with_unflatten, test/export/test_export.py::TestExport::test_constant_aliasing, test/export/test_export.py::TestExport::test_constant_input_naming, test/export/test_export.py::TestExport::test_constant_no_user_inp, test/export/test_export.py::TestExport::test_constant_output, test/export/test_export.py::TestExport::test_constant_output_dup, test/export/test_export.py::TestExport::test_constant_requires_grad_const, test/export/test_export.py::TestExport::test_constant_return, test/export/test_export.py::TestExport::test_constant_tensor_mutation, test/export/test_export.py::TestExport::test_constant_tensor_with_non_functional, test/export/test_export.py::TestExport::test_constant_tensor_with_non_functional_nested, test/export/test_export.py::TestExport::test_constrain_decomp, test/export/test_export.py::TestExport::test_constrain_size_in_eager, test/export/test_export.py::TestExport::test_constrain_size_with_constrain_value, test/export/test_export.py::TestExport::test_constrain_size_with_various_cases, test/export/test_export.py::TestExport::test_conv_dynamic, test/export/test_export.py::TestExport::test_crop_like, test/export/test_export.py::TestExport::test_cse_for_symint, test/export/test_export.py::TestExport::test_custom_op_auto_functionalize, test/export/test_export.py::TestExport::test_custom_op_auto_functionalize_pre_dispatch, test/export/test_export.py::TestExport::test_custom_op_auto_warn_pre_dispatch, test/export/test_export.py::TestExport::test_custom_op_preserve, test/export/test_export.py::TestExport::test_custom_pytree, test/export/test_export.py::TestExport::test_custom_tag_metadata_re_export, test/export/test_export.py::TestExport::test_decomp_batch_norm_functional_predispatch, test/export/test_export.py::TestExport::test_decomp_item_in_prim_after_decomposition, test/export/test_export.py::TestExport::test_decomp_item_in_prim_before_decomposition, test/export/test_export.py::TestExport::test_default_decomposition_core_cia_ops, test/export/test_export.py::TestExport::test_derived_dim_1_2, test/export/test_export.py::TestExport::test_derived_dim_basic, test/export/test_export.py::TestExport::test_derived_dim_integer, test/export/test_export.py::TestExport::test_derived_dim_nested, test/export/test_export.py::TestExport::test_derived_dim_out_of_order, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_repeat_derived, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_simplified, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived, test/export/test_export.py::TestExport::test_derived_dim_repeat_derived, test/export/test_export.py::TestExport::test_detect_leak_strict, test/export/test_export.py::TestExport::test_device_to_dynamic, test/export/test_export.py::TestExport::test_device_to_gpu, test/export/test_export.py::TestExport::test_device_to_mutation, test/export/test_export.py::TestExport::test_device_to_mutation_float, test/export/test_export.py::TestExport::test_device_to_static, test/export/test_export.py::TestExport::test_dim_1_2, test/export/test_export.py::TestExport::test_dim_auto_and_dim, test/export/test_export.py::TestExport::test_dim_dynamic, test/export/test_export.py::TestExport::test_dim_dynamic_divisibility, test/export/test_export.py::TestExport::test_dim_dynamic_specialization, test/export/test_export.py::TestExport::test_dim_hint_range_violations, test/export/test_export.py::TestExport::test_dim_hint_ranges, test/export/test_export.py::TestExport::test_disable_forced_specializations_errors, test/export/test_export.py::TestExport::test_disable_forced_specializations_ok, test/export/test_export.py::TestExport::test_distributed_all_gather, test/export/test_export.py::TestExport::test_distributed_all_gather_into_tensor, test/export/test_export.py::TestExport::test_distributed_all_reduce, test/export/test_export.py::TestExport::test_distributed_all_to_all_single, test/export/test_export.py::TestExport::test_distributed_reduce_scatter_tensor, test/export/test_export.py::TestExport::test_dont_duck_size_for_auto_dynamic, test/export/test_export.py::TestExport::test_double_lifted_constants, test/export/test_export.py::TestExport::test_draft_export_checks_aliasing, test/export/test_export.py::TestExport::test_draft_export_checks_mutation, test/export/test_export.py::TestExport::test_draft_export_checks_mutation_list, test/export/test_export.py::TestExport::test_draft_export_checks_mutation_with_nan, test/export/test_export.py::TestExport::test_draft_export_fake_kernel_inference_errors, test/export/test_export.py::TestExport::test_draft_export_infers_fake_kernel, test/export/test_export.py::TestExport::test_duplicate_modules_with_non_persistent_buffers, test/export/test_export.py::TestExport::test_dynamic_lr_shift, test/export/test_export.py::TestExport::test_dynamic_shapes_bounds, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_basic, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_kwargs, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_pytree, test/export/test_export.py::TestExport::test_dynamic_shapes_dataclass, test/export/test_export.py::TestExport::test_dynamic_shapes_inferred_basic, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_generic, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_user_errors, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_various, test/export/test_export.py::TestExport::test_dynamic_shapes_spec_with_pytree, test/export/test_export.py::TestExport::test_dynamic_sym_round, test/export/test_export.py::TestExport::test_ends_of_bounds_oblivious, test/export/test_export.py::TestExport::test_error_does_not_reference_eager_fallback, test/export/test_export.py::TestExport::test_error_when_passing_mutating_primitive_op, test/export/test_export.py::TestExport::test_exception, test/export/test_export.py::TestExport::test_export_api_with_dynamic_shapes, test/export/test_export.py::TestExport::test_export_as_backend, test/export/test_export.py::TestExport::test_export_associative_scan_lifted_buffers, test/export/test_export.py::TestExport::test_export_associative_scan_symbol_dim, test/export/test_export.py::TestExport::test_export_associative_scan_symbol_scandim, test/export/test_export.py::TestExport::test_export_aten_to_unflatten, test/export/test_export.py::TestExport::test_export_aten_to_unflatten_subclass, test/export/test_export.py::TestExport::test_export_aten_to_unflatten_subclass_pre_dispatch, test/export/test_export.py::TestExport::test_export_cond_preserve_torch_fn_for_subgraphs, test/export/test_export.py::TestExport::test_export_cond_symbool_pred, test/export/test_export.py::TestExport::test_export_cond_warns_constant_pred, test/export/test_export.py::TestExport::test_export_custom_decomp_table_basic_pop, test/export/test_export.py::TestExport::test_export_custom_decomp_table_container_methods, test/export/test_export.py::TestExport::test_export_custom_op_lib, test/export/test_export.py::TestExport::test_export_custom_triton_kernel, test/export/test_export.py::TestExport::test_export_custom_triton_kernel_mutable, test/export/test_export.py::TestExport::test_export_decomp_torture_case_1, test/export/test_export.py::TestExport::test_export_decomp_torture_case_2, test/export/test_export.py::TestExport::test_export_decomps_dynamic, test/export/test_export.py::TestExport::test_export_decomps_simple, test/export/test_export.py::TestExport::test_export_dynamo_config, test/export/test_export.py::TestExport::test_export_for_training_run_decomp, test/export/test_export.py::TestExport::test_export_for_training_with_container_type, test/export/test_export.py::TestExport::test_export_for_training_with_dynamic_shapes, test/export/test_export.py::TestExport::test_export_for_training_with_mutation, test/export/test_export.py::TestExport::test_export_for_training_with_state_dict_hooks, test/export/test_export.py::TestExport::test_export_func_with_default_kwargs, test/export/test_export.py::TestExport::test_export_func_with_keyword_only_args, test/export/test_export.py::TestExport::test_export_func_with_kwargs, test/export/test_export.py::TestExport::test_export_func_with_pytree_kwargs, test/export/test_export.py::TestExport::test_export_func_with_var_keyword_args, test/export/test_export.py::TestExport::test_export_func_with_var_keyword_pytree_args, test/export/test_export.py::TestExport::test_export_func_with_var_postional_args, test/export/test_export.py::TestExport::test_export_function_schema, test/export/test_export.py::TestExport::test_export_graph_with_no_inputs, test/export/test_export.py::TestExport::test_export_input_mutation_bug, test/export/test_export.py::TestExport::test_export_input_mutation_dynamic_shape, test/export/test_export.py::TestExport::test_export_input_mutation_static_shape, test/export/test_export.py::TestExport::test_export_linear_preserve_dynamic_shape, test/export/test_export.py::TestExport::test_export_max_nonstrict, test/export/test_export.py::TestExport::test_export_max_onnx_reported, test/export/test_export.py::TestExport::test_export_method, test/export/test_export.py::TestExport::test_export_mod_constraints, test/export/test_export.py::TestExport::test_export_module, test/export/test_export.py::TestExport::test_export_preserve_linear_at_aot_level, test/export/test_export.py::TestExport::test_export_preserve_linear_but_not_custom_op, test/export/test_export.py::TestExport::test_export_scan_pytree_output, test/export/test_export.py::TestExport::test_export_script_module, test/export/test_export.py::TestExport::test_export_statically_known_true, test/export/test_export.py::TestExport::test_export_then_compile_tensor_ctor, test/export/test_export.py::TestExport::test_export_with_autocast, test/export/test_export.py::TestExport::test_export_with_fake_tensor_inputs, test/export/test_export.py::TestExport::test_export_with_fake_tensor_inputs_on_cuda_devices, test/export/test_export.py::TestExport::test_export_with_inline_constraints, test/export/test_export.py::TestExport::test_export_with_inline_constraints_complex, test/export/test_export.py::TestExport::test_export_with_set_grad_enabled, test/export/test_export.py::TestExport::test_export_with_wrong_inputs, test/export/test_export.py::TestExport::test_external_call_non_strict_real_tensor, test/export/test_export.py::TestExport::test_fake_inputs, test/export/test_export.py::TestExport::test_fake_weights, test/export/test_export.py::TestExport::test_filter_traceback_frames, test/export/test_export.py::TestExport::test_float_conversion, test/export/test_export.py::TestExport::test_float_conversion_from_int, test/export/test_export.py::TestExport::test_fqn, test/export/test_export.py::TestExport::test_from_node_metadata_export, test/export/test_export.py::TestExport::test_full_on_scalar_tensor, test/export/test_export.py::TestExport::test_hints_wrapper, test/export/test_export.py::TestExport::test_hoo_inline_users_issue, test/export/test_export.py::TestExport::test_if_functional, test/export/test_export.py::TestExport::test_if_post_autograd_op_preserved, test/export/test_export.py::TestExport::test_inline_script_class_method, test/export/test_export.py::TestExport::test_inline_script_class_method_recursive, test/export/test_export.py::TestExport::test_inline_script_function, test/export/test_export.py::TestExport::test_inline_script_method, test/export/test_export.py::TestExport::test_int_shape_specialization, test/export/test_export.py::TestExport::test_intermediate_shape_comp, test/export/test_export.py::TestExport::test_is_exporting, test/export/test_export.py::TestExport::test_is_non_negative_check_function, test/export/test_export.py::TestExport::test_is_nonzero, test/export/test_export.py::TestExport::test_isnonzero, test/export/test_export.py::TestExport::test_issue_113041, test/export/test_export.py::TestExport::test_issue_157289, test/export/test_export.py::TestExport::test_istft_op, test/export/test_export.py::TestExport::test_keep_composite_ops_invalid, test/export/test_export.py::TestExport::test_keep_composite_ops_linear_convd, test/export/test_export.py::TestExport::test_keep_composite_ops_linear_convd_for_training_ir, test/export/test_export.py::TestExport::test_kwarg_dynamic_shapes_diff_order, test/export/test_export.py::TestExport::test_kwargs_reorder, test/export/test_export.py::TestExport::test_layer_norm_unbacked_normalized_shape, test/export/test_export.py::TestExport::test_layer_sharing, test/export/test_export.py::TestExport::test_lazy_module_kwargs, test/export/test_export.py::TestExport::test_lifted_constants, test/export/test_export.py::TestExport::test_linear_conv, test/export/test_export.py::TestExport::test_malformed_fqn_from_source_name, test/export/test_export.py::TestExport::test_map, test/export/test_export.py::TestExport::test_map_buffers, test/export/test_export.py::TestExport::test_mask_nonzero_static, test/export/test_export.py::TestExport::test_masked_select_dynamic, test/export/test_export.py::TestExport::test_math_pow, test/export/test_export.py::TestExport::test_mismatched_dynamic_shapes, test/export/test_export.py::TestExport::test_mixed_input, test/export/test_export.py::TestExport::test_module, test/export/test_export.py::TestExport::test_module_dict_key, test/export/test_export.py::TestExport::test_module_input, test/export/test_export.py::TestExport::test_module_input_subclasses_parameterization_nested, test/export/test_export.py::TestExport::test_module_list_slice, test/export/test_export.py::TestExport::test_module_with_dict_container_inp_out, test/export/test_export.py::TestExport::test_modules_access_for_deleted_submodule, test/export/test_export.py::TestExport::test_more_multidimensional_slicing, test/export/test_export.py::TestExport::test_multidimensional_slicing, test/export/test_export.py::TestExport::test_multinomial_dynamic, test/export/test_export.py::TestExport::test_multiple_definitions_same_name_dim, test/export/test_export.py::TestExport::test_nested_dynamic_shapes_spec, test/export/test_export.py::TestExport::test_nested_module, test/export/test_export.py::TestExport::test_nested_module_with_constant_buffer, test/export/test_export.py::TestExport::test_nested_module_with_init_buffer, test/export/test_export.py::TestExport::test_nested_module_with_parameter, test/export/test_export.py::TestExport::test_nn_module_stack, test/export/test_export.py::TestExport::test_nn_module_stack_shared_submodule, test/export/test_export.py::TestExport::test_no_check_is_size_error, test/export/test_export.py::TestExport::test_no_suggested_fixes_for_data_dependent_errors, test/export/test_export.py::TestExport::test_no_tensor_computation, test/export/test_export.py::TestExport::test_no_tensor_computation_2, test/export/test_export.py::TestExport::test_no_tensor_computation_3, test/export/test_export.py::TestExport::test_no_tensor_computation_4, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api_with_container_type, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg, test/export/test_export.py::TestExport::test_non_persistent_buffer, test/export/test_export.py::TestExport::test_non_strict_dynamic_shapes, test/export/test_export.py::TestExport::test_non_strict_dynamic_shapes_suggested_fixes, test/export/test_export.py::TestExport::test_none_buffers, test/export/test_export.py::TestExport::test_nonstrict_retrace_preserves_metadata, test/export/test_export.py::TestExport::test_nonzero_2, test/export/test_export.py::TestExport::test_nonzero_dynamic, test/export/test_export.py::TestExport::test_not_registered_parameter, test/export/test_export.py::TestExport::test_operator_aten_tensor_mode_variant, test/export/test_export.py::TestExport::test_output_node_name, test/export/test_export.py::TestExport::test_pad_sequence, test/export/test_export.py::TestExport::test_param_util, test/export/test_export.py::TestExport::test_partial_patched_forward, test/export/test_export.py::TestExport::test_placeholder_naming_collisions, test/export/test_export.py::TestExport::test_placeholder_naming_collisions_hoo_subgraphs, test/export/test_export.py::TestExport::test_placeholder_naming_order, test/export/test_export.py::TestExport::test_placeholder_naming_order_variadic, test/export/test_export.py::TestExport::test_placeholder_update_preserving, test/export/test_export.py::TestExport::test_predispatch_cond, test/export/test_export.py::TestExport::test_predispatch_grad_wrappers, test/export/test_export.py::TestExport::test_preserve_module_call_signature_unflatten_specialization, test/export/test_export.py::TestExport::test_preserve_requires_grad_placeholders, test/export/test_export.py::TestExport::test_preserve_shape_dynamism_for_unused_inputs, test/export/test_export.py::TestExport::test_profiling_code, test/export/test_export.py::TestExport::test_python_asserts_with_sym_int, test/export/test_export.py::TestExport::test_pytree_register_data_class, test/export/test_export.py::TestExport::test_pytree_register_nested_data_class, test/export/test_export.py::TestExport::test_raise_user_error_when_guard_on_data_dependent_operation, test/export/test_export.py::TestExport::test_range_constraints_with_replacement, test/export/test_export.py::TestExport::test_real_tensor_alias_dtype_mismatch, test/export/test_export.py::TestExport::test_real_tensor_bool_cast, test/export/test_export.py::TestExport::test_real_tensor_errors_on_aliasing_custom_op, test/export/test_export.py::TestExport::test_real_tensor_for_max_op, test/export/test_export.py::TestExport::test_real_tensor_size_mismatch, test/export/test_export.py::TestExport::test_redundant_assert_max_upper_bound, test/export/test_export.py::TestExport::test_redundant_asserts, test/export/test_export.py::TestExport::test_refine_dynamic_shapes_from_suggested_fixes, test/export/test_export.py::TestExport::test_register_constant, test/export/test_export.py::TestExport::test_repeat_interleave, test/export/test_export.py::TestExport::test_replace_unbacked_with_very_large_upperbound, test/export/test_export.py::TestExport::test_replaced_unbacked_bindings, test/export/test_export.py::TestExport::test_reshape_view_helper, test/export/test_export.py::TestExport::test_retracable_ep, test/export/test_export.py::TestExport::test_retrace_pre_autograd, test/export/test_export.py::TestExport::test_run_decomposition_supports_user_input_mutation, test/export/test_export.py::TestExport::test_run_decompositions_keep_metadata, test/export/test_export.py::TestExport::test_run_decompositions_keep_tensor_constant_metadata, test/export/test_export.py::TestExport::test_runtime_assert_for_prim, test/export/test_export.py::TestExport::test_runtime_assert_for_prm_str, test/export/test_export.py::TestExport::test_runtime_assert_with_size, test/export/test_export.py::TestExport::test_sdpa_gqa, test/export/test_export.py::TestExport::test_sequential_slicing, test/export/test_export.py::TestExport::test_set_example_inputs, test/export/test_export.py::TestExport::test_set_grad_as_side_effect, test/export/test_export.py::TestExport::test_set_grad_empty, test/export/test_export.py::TestExport::test_set_grad_unflatten, test/export/test_export.py::TestExport::test_setgrad_lifted_tensor, test/export/test_export.py::TestExport::test_shared_submodule_nn_module_stack, test/export/test_export.py::TestExport::test_simple_export_for_training, test/export/test_export.py::TestExport::test_simple_unbacked_view, test/export/test_export.py::TestExport::test_size_input, test/export/test_export.py::TestExport::test_slice_nn_module_stack, test/export/test_export.py::TestExport::test_solver_unsupported_sympy_function, test/export/test_export.py::TestExport::test_specialize_derived_dim_roots, test/export/test_export.py::TestExport::test_split_const_gm_with_lifted_constants, test/export/test_export.py::TestExport::test_stack_trace, test/export/test_export.py::TestExport::test_stack_trace_make_fx, test/export/test_export.py::TestExport::test_state_primitives, test/export/test_export.py::TestExport::test_state_shape_attribute_assignment, test/export/test_export.py::TestExport::test_state_tensors, test/export/test_export.py::TestExport::test_static_dim_constraints, test/export/test_export.py::TestExport::test_subclass_nested_attr_access, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_complicated_metadata, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_const_metadata, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_const_metadata_not_top_level, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_submodule, test/export/test_export.py::TestExport::test_subclasses_parameterization, test/export/test_export.py::TestExport::test_subclasses_parameterization_nested, test/export/test_export.py::TestExport::test_suggest_torch_checks_with_non_negative_check, test/export/test_export.py::TestExport::test_suggest_torch_checks_with_regular_check, test/export/test_export.py::TestExport::test_suggested_fixes_for_data_dependent_errors_basic, test/export/test_export.py::TestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers, test/export/test_export.py::TestExport::test_suggested_fixes_new_roots, test/export/test_export.py::TestExport::test_sym_float_operators, test/export/test_export.py::TestExport::test_sym_or_sym_and, test/export/test_export.py::TestExport::test_sym_sqrt, test/export/test_export.py::TestExport::test_symbool_item, test/export/test_export.py::TestExport::test_symfloat_item, test/export/test_export.py::TestExport::test_symint_input_additional_inputs, test/export/test_export.py::TestExport::test_symint_input_basic, test/export/test_export.py::TestExport::test_symint_input_ranges, test/export/test_export.py::TestExport::test_symint_input_shapes_collection, test/export/test_export.py::TestExport::test_symint_input_specialization, test/export/test_export.py::TestExport::test_symint_item, test/export/test_export.py::TestExport::test_symint_output, test/export/test_export.py::TestExport::test_symint_tensor_return, test/export/test_export.py::TestExport::test_tensor_attribute_zero_args, test/export/test_export.py::TestExport::test_tensor_constant_aten_to, test/export/test_export.py::TestExport::test_tensor_constant_with_wrapped_method, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer_multiple, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later, test/export/test_export.py::TestExport::test_tolist, test/export/test_export.py::TestExport::test_torch_check_eq_commutativity, test/export/test_export.py::TestExport::test_torch_fn, test/export/test_export.py::TestExport::test_trace_under_fake, test/export/test_export.py::TestExport::test_train_eval_on_exported_preautograd_module, test/export/test_export.py::TestExport::test_unbacked_3d_matmul, test/export/test_export.py::TestExport::test_unbacked_bincount, test/export/test_export.py::TestExport::test_unbacked_bindings_for_divisible_u_symint, test/export/test_export.py::TestExport::test_unbacked_deferred_runtime_retrace, test/export/test_export.py::TestExport::test_unbacked_expand, test/export/test_export.py::TestExport::test_unbacked_infer_size, test/export/test_export.py::TestExport::test_unbacked_kth_value, test/export/test_export.py::TestExport::test_unbacked_linear_layer_norm_input, test/export/test_export.py::TestExport::test_unbacked_noncontig_lin, test/export/test_export.py::TestExport::test_unbacked_pad, test/export/test_export.py::TestExport::test_unbacked_scalar_constructor, test/export/test_export.py::TestExport::test_unbacked_slice, test/export/test_export.py::TestExport::test_unbacked_to_cond, test/export/test_export.py::TestExport::test_unbacked_to_cond_passthrough, test/export/test_export.py::TestExport::test_unbacked_unsqueeze, test/export/test_export.py::TestExport::test_unflatten_asserts, test/export/test_export.py::TestExport::test_unflatten_buffer_update_child2parent_swap, test/export/test_export.py::TestExport::test_unflatten_closure, test/export/test_export.py::TestExport::test_unflatten_isinstance, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_dispatch, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_preserve_signature_no_error, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_shared_submodule, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_state, test/export/test_export.py::TestExport::test_unflatten_no_unroll, test/export/test_export.py::TestExport::test_unflatten_placeholder_update_child2parent_swap, test/export/test_export.py::TestExport::test_unflatten_placeholder_update_grandchild2cousin_swap, test/export/test_export.py::TestExport::test_unflatten_random_dag_5, test/export/test_export.py::TestExport::test_unflatten_random_dag_6, test/export/test_export.py::TestExport::test_unflatten_random_dag_buf_8, test/export/test_export.py::TestExport::test_unflatten_random_dag_const_preserving_3, test/export/test_export.py::TestExport::test_unflatten_random_dag_const_preserving_3_1, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_4, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_6, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_9, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_10, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_4, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_5, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_7, test/export/test_export.py::TestExport::test_unflatten_random_dag_preserving_4, test/export/test_export.py::TestExport::test_unused_aliases, test/export/test_export.py::TestExport::test_unused_constant, test/export/test_export.py::TestExport::test_use_embedding_twice, test/export/test_export.py::TestExport::test_user_input_and_buffer_mutation, test/export/test_export.py::TestExport::test_vmap, test/export/test_export.py::TestExport::test_while_loop_assert_separation, test/export/test_export.py::TestExport::test_while_loop_index_assertions, test/export/test_export.py::TestExport::test_while_loop_simple, test/export/test_export.py::TestExport::test_while_loop_tensor_constant_idx, test/export/test_export.py::TestExport::test_wrapper_module, test/export/test_export.py::TestOneOffModelExportResult::test_assert_tensor_metadata_device_index, test/export/test_export.py::TestOneOffModelExportResult::test_constant_fqn, test/export/test_export.py::TestOneOffModelExportResult::test_constant_name, test/export/test_export.py::TestOneOffModelExportResult::test_duplicated_getitem, test/export/test_export.py::TestOneOffModelExportResult::test_hf_logging_logger, test/export/test_export.py::TestOneOffModelExportResult::test_input_output_no_stacktrace, test/export/test_export.py::TestOneOffModelExportResult::test_int_list_output, test/export/test_export.py::TestOneOffModelExportResult::test_logging_logger, test/export/test_export.py::TestOneOffModelExportResult::test_nested_retrace, test/export/test_export.py::TestOneOffModelExportResult::test_none_input_output, test/export/test_export.py::TestOneOffModelExportResult::test_primitive_constant_output, test/export/test_export.py::TestOneOffModelExportResult::test_print, test/export/test_export.py::TestOneOffModelExportResult::test_print_graph_signature, test/export/test_export.py::TestOneOffModelExportResult::test_scaled_dot_product_attention_cpu, test/export/test_export.py::TestOneOffModelExportResult::test_scaled_dot_product_attention_cuda, test/export/test_export.py::TestOneOffModelExportResult::test_strict_export_with_shared_parameters, test/export/test_export.py::TestOneOffModelExportResult::test_torchrec_jagged_tensor, test/export/test_export.py::TestOneOffModelExportResult::test_unbacked_sdpa, test/export/test_export.py::TestOneOffModelExportResult::test_warning, test/export/test_export.py::TestExportCustomClass::test_export_script_module, test/export/test_export.py::TestExportCustomClass::test_export_unbacked_lt, test/export/test_export.py::TestExportCustomClass::test_int_lift_constant, test/export/test_export.py::TestExportCustomClass::test_lift_custom_obj, test/export/test_export.py::TestExportCustomClass::test_preserve_cia_op, test/export/test_export.py::TestExportCustomClass::test_preserve_non_cia_op, test/export/test_export.py::TestExportCustomClass::test_unbacked_contiguous, test/export/test_export.py::TestExportCustomClass::test_unbacked_select_index 2025-08-26T21:42:19.3292720Z 2025-08-26T21:42:19.3292881Z Running dynamo/test_backward_higher_order_ops 1/1 ... [2025-08-26 21:42:19.315186] 2025-08-26T21:42:19.3293152Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:42:19.3293733Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_backward_higher_order_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:42:19.315440] 2025-08-26T21:42:28.5446092Z 2025-08-26T21:42:28.5447658Z dynamo/test_backward_higher_order_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_backward_higher_order_ops_1.1_684663618e616a38_.log 2025-08-26T21:42:28.5450641Z Running 7 items in this shard: test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_eager, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd_graph_breaks, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd_side_effect, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_make_bw, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_make_fx_forward_contrived 2025-08-26T21:42:28.5452232Z 2025-08-26T21:42:28.5452372Z Running dynamo/test_compile 1/1 ... [2025-08-26 21:42:28.544745] 2025-08-26T21:42:28.5452611Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:42:28.5453157Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_compile.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:42:28.545013] 2025-08-26T21:42:35.5734655Z 2025-08-26T21:42:35.5736433Z dynamo/test_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compile_1.1_31f12787055e7952_.log 2025-08-26T21:42:35.5739923Z Running 17 items in this shard: test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_callback, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_callback_with_graph_break, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_constant_hasattr_fail, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_evnum_hasattr_fail, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_name_error, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_nn_module_invalid_method, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_tensor_invalid_method, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compile_eager_options, test/dynamo/test_compile.py::InPlaceCompilationTests::test_jit_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_list_bad_access, test/dynamo/test_compile.py::InPlaceCompilationTests::test_overwrite_call_impl, test/dynamo/test_compile.py::InPlaceCompilationTests::test_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_state_dict_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_to_sparse_to_dense_with_graph_break, test/dynamo/test_compile.py::InPlaceCompilationTests::test_torch_script_compilation, test/dynamo/test_compile.py::PublicTorchCompilerTests::test_dynamo_signatures 2025-08-26T21:42:35.5742221Z 2025-08-26T21:42:35.5742314Z Running dynamo/test_cudagraphs 1/1 ... [2025-08-26 21:42:35.573291] 2025-08-26T21:42:35.5742495Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:42:35.5742888Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:42:35.573482] 2025-08-26T21:42:39.1956302Z 2025-08-26T21:42:39.1957517Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_2e2ca48ad304d020_.log 2025-08-26T21:42:39.1959536Z Running 8 items in this shard: test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_basic, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_dead_fill, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_dtoh, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_factory, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_htod, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_mutate_constant, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_mutate_input, test/dynamo/test_cudagraphs.py::TestAotCudagraphs::test_mutated_metadata 2025-08-26T21:42:39.1966537Z 2025-08-26T21:42:39.1966682Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-08-26 21:42:39.195484] 2025-08-26T21:42:39.1966904Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:42:39.1967378Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:42:39.195798] 2025-08-26T21:42:41.7153966Z 2025-08-26T21:42:41.7155250Z dynamo/test_deque_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deque_reconstruct_1.1_52dd117003a595b2_.log 2025-08-26T21:42:41.7156089Z Running 3 items in this shard: test/dynamo/test_deque_reconstruct.py::TestDequeReconstruct::test_deque_reconstruct_in_globals, test/dynamo/test_deque_reconstruct.py::TestDequeReconstruct::test_deque_reconstruct_not_in_globals, test/dynamo/test_deque_reconstruct.py::TestDequeReconstruct::test_deque_reconstruct_shallows_globals 2025-08-26T21:42:41.7156583Z 2025-08-26T21:42:41.7156676Z Running dynamo/test_error_messages 1/1 ... [2025-08-26 21:42:41.715291] 2025-08-26T21:42:41.7156843Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:42:41.7163047Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_error_messages.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:42:41.715535] 2025-08-26T21:43:03.6217507Z 2025-08-26T21:43:03.6225390Z dynamo/test_error_messages 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_error_messages_1.1_6779f3e2a09f0693_.log 2025-08-26T21:43:03.6232262Z Running 41 items in this shard: test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_assert_failure_in_generic_ctx_mgr, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_backend_fake_tensor_exc, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_class_property, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_cpp_extension_recommends_custom_ops, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_data_dependent_branching_fullgraph, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_data_dependent_branching_gb, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_data_dependent_operator, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_data_dependent_operator2, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_dict_items_input, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_disable_message, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_dynamic_shape_operator, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_dynamic_shape_operator_no_meta_kernel, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_dynamo_graph_break_fn, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_dynamo_graph_break_fn_with_msg, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_faketensor_nyi, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_generic_ctx_mgr_graph_break, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_graph_break_in_buggy_resume_prologue, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_graph_break_traceback_above_dynamo_shows_user_code, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_graph_break_traceback_collapsed_resume_frames, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_internal_compiler_stacktrace_verbose, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_load_build_class, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_lru_cache_warning_logs_nested_call, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_lru_cache_warning_logs_user_stack_trace, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_nested_compile_user_frames, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_no_internal_compiler_stacktrace, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_observed_exception, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_optree_graph_break_message, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_reconstruction_failure, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_reconstruction_failure_gb, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_skipfile_call, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_skipfile_dynamo_call, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_skipfile_inline, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_slice_with_tensor, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_sort_with_nonconstant_keys, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_super_call_function, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_super_call_method, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_uninitialized_module, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_unsupported_builtin, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_unsupported_bytecode, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_unsupported_context, test/dynamo/test_error_messages.py::GraphBreakMessagesTest::test_warnings 2025-08-26T21:43:03.6237618Z 2025-08-26T21:43:03.6237720Z Running dynamo/test_input_attr_tracking 1/1 ... [2025-08-26 21:43:03.621790] 2025-08-26T21:43:03.6237906Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:43:03.6238303Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_input_attr_tracking.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:43:03.621984] 2025-08-26T21:43:10.4622817Z 2025-08-26T21:43:10.4623764Z dynamo/test_input_attr_tracking 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_input_attr_tracking_1.1_1d687d3c29afb8ab_.log 2025-08-26T21:43:10.4626678Z Running 12 items in this shard: test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_complex_attr_access_with_graph_breaks, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_complex_attr_access_with_inline_reconstruct, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_complex_attr_access_without_graph_breaks, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_const_property_assigned_on_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_const_property_on_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_guards_correctly_property_assigned_on_tensor_type_change, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_guards_correctly_property_assigned_on_tensor_type_change_inductor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_set_data_on_input_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_set_data_on_scoped_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_set_data_on_user_defined_class_input_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_tensor_property_assigned_on_tensor, test/dynamo/test_input_attr_tracking.py::TestInputAttrTracking::test_tensor_property_on_tensor 2025-08-26T21:43:10.4629841Z 2025-08-26T21:43:10.4629970Z Running dynamo/test_install_free_tensors 1/1 ... [2025-08-26 21:43:10.461941] 2025-08-26T21:43:10.4630221Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:43:10.4631092Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_install_free_tensors.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:43:10.462148] 2025-08-26T21:43:52.1655634Z 2025-08-26T21:43:52.1657110Z dynamo/test_install_free_tensors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_install_free_tensors_1.1_cdcbdb0b81754822_.log 2025-08-26T21:43:52.1662211Z Running 25 items in this shard: test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_breadth_linear, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_nested_linear, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_nets_as_input, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_optimizing_buffer_and_param_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_optimizing_buffer_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_optimizing_linear, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_optimizing_params_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_resnet_structure, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_simple_batchnorm, test/dynamo/test_install_free_tensors.py::InstallParamsAsGraphAttrTests::test_transformer, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_dict_of_tensor, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_global_tensor_export, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_list_of_tensor, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_modify_net_state, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_nested_list_of_tensor, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_nonlocal_closure, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_optimizing_buffer_and_param_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_optimizing_buffer_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_optimizing_params_in_input, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_resnet_structure, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_simple_batchnorm, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_simple_linear, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_tensors_as_nn_attr, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_transformer, test/dynamo/test_install_free_tensors.py::InstallParamsWhenExport::test_user_defined_object 2025-08-26T21:43:52.1666714Z 2025-08-26T21:43:52.1666818Z Running dynamo/test_profiler 1/1 ... [2025-08-26 21:43:52.165508] 2025-08-26T21:43:52.1667015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:43:52.1673630Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_profiler.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:43:52.165766] 2025-08-26T21:44:00.9982871Z 2025-08-26T21:44:00.9983617Z dynamo/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_profiler_1.1_a3a2691815b02b89_.log 2025-08-26T21:44:00.9985755Z Running 11 items in this shard: test/dynamo/test_profiler.py::DynamoProfilerTests::test_dynamo_timed_profiling_backend_compile, test/dynamo/test_profiler.py::DynamoProfilerTests::test_dynamo_timed_profiling_isolated, test/dynamo/test_profiler.py::DynamoProfilerTests::test_execution_trace_dynamic_shapes, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_compilation, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_list_compilation, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_runtime, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_cache_lookup, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_cache_lookup_profiler_step, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_dynamo_compiled_region, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_enabled, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_record_function_ignore 2025-08-26T21:44:00.9987147Z 2025-08-26T21:44:00.9992950Z Running dynamo/test_sets 1/1 ... [2025-08-26 21:44:00.997311] 2025-08-26T21:44:00.9993131Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:44:00.9993502Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_sets.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:44:00.997579] 2025-08-26T21:44:06.7313413Z 2025-08-26T21:44:06.7315085Z dynamo/test_sets 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sets_1.1_e975b185baf70e74_.log 2025-08-26T21:44:06.7334410Z Running 124 items in this shard: test/dynamo/test_sets.py::CustomSetTests::test_custom_add, test/dynamo/test_sets.py::CustomSetTests::test_custom_contains, test/dynamo/test_sets.py::MiscTests::test_isdisjoint_with_generator, test/dynamo/test_sets.py::TestSetGuards::test_in_guard, test/dynamo/test_sets.py::TestSetGuards::test_set_guard_on_keys_change, test/dynamo/test_sets.py::TestSetGuards::test_set_multiple_types, test/dynamo/test_sets.py::TestSetGuards::test_set_recompile_on_key_change, test/dynamo/test_sets.py::TestSetGuards::test_set_recompile_on_key_pop, test/dynamo/test_sets.py::TestSetGuards::test_set_with_function, test/dynamo/test_sets.py::TestSetGuards::test_set_with_tensors, test/dynamo/test_sets.py::FrozensetTests::test_binop_and, test/dynamo/test_sets.py::FrozensetTests::test_binop_or, test/dynamo/test_sets.py::FrozensetTests::test_binop_sub, test/dynamo/test_sets.py::FrozensetTests::test_binop_xor, test/dynamo/test_sets.py::FrozensetTests::test_cmp_eq, test/dynamo/test_sets.py::FrozensetTests::test_cmp_greater_than, test/dynamo/test_sets.py::FrozensetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::FrozensetTests::test_cmp_less_than, test/dynamo/test_sets.py::FrozensetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::FrozensetTests::test_cmp_ne, test/dynamo/test_sets.py::FrozensetTests::test_constructor_iterable, test/dynamo/test_sets.py::FrozensetTests::test_contains, test/dynamo/test_sets.py::FrozensetTests::test_copy, test/dynamo/test_sets.py::FrozensetTests::test_difference, test/dynamo/test_sets.py::FrozensetTests::test_equality, test/dynamo/test_sets.py::FrozensetTests::test_in_frozenset, test/dynamo/test_sets.py::FrozensetTests::test_intersection, test/dynamo/test_sets.py::FrozensetTests::test_isdisjoint, test/dynamo/test_sets.py::FrozensetTests::test_issubset, test/dynamo/test_sets.py::FrozensetTests::test_issuperset, test/dynamo/test_sets.py::FrozensetTests::test_symmetric_difference, test/dynamo/test_sets.py::FrozensetTests::test_to_frozenset, test/dynamo/test_sets.py::FrozensetTests::test_to_set, test/dynamo/test_sets.py::FrozensetTests::test_union, test/dynamo/test_sets.py::SetTests::test_add, test/dynamo/test_sets.py::SetTests::test_binop_and, test/dynamo/test_sets.py::SetTests::test_binop_or, test/dynamo/test_sets.py::SetTests::test_binop_sub, test/dynamo/test_sets.py::SetTests::test_binop_xor, test/dynamo/test_sets.py::SetTests::test_clear, test/dynamo/test_sets.py::SetTests::test_cmp_eq, test/dynamo/test_sets.py::SetTests::test_cmp_greater_than, test/dynamo/test_sets.py::SetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::SetTests::test_cmp_less_than, test/dynamo/test_sets.py::SetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::SetTests::test_cmp_ne, test/dynamo/test_sets.py::SetTests::test_constructor_iterable, test/dynamo/test_sets.py::SetTests::test_contains, test/dynamo/test_sets.py::SetTests::test_copy, test/dynamo/test_sets.py::SetTests::test_difference, test/dynamo/test_sets.py::SetTests::test_difference_update, test/dynamo/test_sets.py::SetTests::test_discard, test/dynamo/test_sets.py::SetTests::test_equality, test/dynamo/test_sets.py::SetTests::test_in_frozenset, test/dynamo/test_sets.py::SetTests::test_intersection, test/dynamo/test_sets.py::SetTests::test_intersection_update, test/dynamo/test_sets.py::SetTests::test_isdisjoint, test/dynamo/test_sets.py::SetTests::test_issubset, test/dynamo/test_sets.py::SetTests::test_issuperset, test/dynamo/test_sets.py::SetTests::test_pop, test/dynamo/test_sets.py::SetTests::test_remove, test/dynamo/test_sets.py::SetTests::test_symmetric_difference, test/dynamo/test_sets.py::SetTests::test_symmetric_difference_update, test/dynamo/test_sets.py::SetTests::test_to_frozenset, test/dynamo/test_sets.py::SetTests::test_to_set, test/dynamo/test_sets.py::SetTests::test_union, test/dynamo/test_sets.py::SetTests::test_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_add, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_and, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_or, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_sub, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_xor, test/dynamo/test_sets.py::UserDefinedSetTests::test_clear, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_eq, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_greater_than, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_less_than, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_ne, test/dynamo/test_sets.py::UserDefinedSetTests::test_constructor_iterable, test/dynamo/test_sets.py::UserDefinedSetTests::test_contains, test/dynamo/test_sets.py::UserDefinedSetTests::test_copy, test/dynamo/test_sets.py::UserDefinedSetTests::test_difference, test/dynamo/test_sets.py::UserDefinedSetTests::test_difference_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_discard, test/dynamo/test_sets.py::UserDefinedSetTests::test_equality, test/dynamo/test_sets.py::UserDefinedSetTests::test_in_frozenset, test/dynamo/test_sets.py::UserDefinedSetTests::test_intersection, test/dynamo/test_sets.py::UserDefinedSetTests::test_intersection_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_isdisjoint, test/dynamo/test_sets.py::UserDefinedSetTests::test_issubset, test/dynamo/test_sets.py::UserDefinedSetTests::test_issuperset, test/dynamo/test_sets.py::UserDefinedSetTests::test_pop, test/dynamo/test_sets.py::UserDefinedSetTests::test_remove, test/dynamo/test_sets.py::UserDefinedSetTests::test_symmetric_difference, test/dynamo/test_sets.py::UserDefinedSetTests::test_symmetric_difference_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_to_frozenset, test/dynamo/test_sets.py::UserDefinedSetTests::test_to_set, test/dynamo/test_sets.py::UserDefinedSetTests::test_union, test/dynamo/test_sets.py::UserDefinedSetTests::test_update, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_and, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_or, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_sub, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_xor, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_eq, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_greater_than, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_less_than, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_ne, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_constructor_iterable, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_contains, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_copy, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_difference, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_equality, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_in_frozenset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_intersection, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_isdisjoint, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_issubset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_issuperset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_symmetric_difference, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_to_frozenset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_to_set, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_union 2025-08-26T21:44:06.7351881Z 2025-08-26T21:44:06.7351990Z Running dynamo/test_sources 1/1 ... [2025-08-26 21:44:06.731395] 2025-08-26T21:44:06.7352162Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:44:06.7352540Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_sources.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:44:06.731689] 2025-08-26T21:44:09.2537264Z 2025-08-26T21:44:09.2538757Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_e332bd2bb7586ade_.log 2025-08-26T21:44:09.2540314Z Running 3 items in this shard: test/dynamo/test_sources.py::SourceTests::test_is_local, test/dynamo/test_sources.py::SourceTests::test_property_closure, test/dynamo/test_sources.py::SourceTests::test_supported_nodes 2025-08-26T21:44:09.2541423Z 2025-08-26T21:44:09.2541656Z Running dynamo/test_torchrec 1/1 ... [2025-08-26 21:44:09.253582] 2025-08-26T21:44:09.2542104Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:44:09.2543191Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_torchrec.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:44:09.253820] 2025-08-26T21:44:11.6242150Z 2025-08-26T21:44:11.6243475Z dynamo/test_torchrec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_torchrec_1.1_22935d9216ba0602_.log 2025-08-26T21:44:11.6243874Z Running 0 items in this shard: 2025-08-26T21:44:11.6243961Z 2025-08-26T21:44:11.6244048Z Running dynamo/test_unspec 1/1 ... [2025-08-26 21:44:11.624096] 2025-08-26T21:44:11.6244218Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:44:11.6248646Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'dynamo/test_unspec.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:44:11.624323] 2025-08-26T21:44:40.6111642Z 2025-08-26T21:44:40.6159555Z dynamo/test_unspec 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_unspec_1.1_cd9f4e85cc5a90e8_.log 2025-08-26T21:44:40.6165225Z Running 51 items in this shard: test/dynamo/test_unspec.py::UnspecTests::test_argmin_coerces_symint_to_intlist_spec, test/dynamo/test_unspec.py::UnspecTests::test_bool_tensor_ctor, test/dynamo/test_unspec.py::UnspecTests::test_builtin_getitem, test/dynamo/test_unspec.py::UnspecTests::test_builtin_max_min, test/dynamo/test_unspec.py::UnspecTests::test_compiled_random_calls_are_random, test/dynamo/test_unspec.py::UnspecTests::test_conv1d_symint_padding, test/dynamo/test_unspec.py::UnspecTests::test_data_dependent_evaluate_expr_graph_break, test/dynamo/test_unspec.py::UnspecTests::test_defaults, test/dynamo/test_unspec.py::UnspecTests::test_exponential, test/dynamo/test_unspec.py::UnspecTests::test_feed_random_values_into_graph_only, test/dynamo/test_unspec.py::UnspecTests::test_isinstance_symint, test/dynamo/test_unspec.py::UnspecTests::test_item_max, test/dynamo/test_unspec.py::UnspecTests::test_mark_01_dynamic, test/dynamo/test_unspec.py::UnspecTests::test_mark_static_inside, test/dynamo/test_unspec.py::UnspecTests::test_mark_unbacked, test/dynamo/test_unspec.py::UnspecTests::test_mark_unbacked_channels_last, test/dynamo/test_unspec.py::UnspecTests::test_mark_unbacked_hint_consistency, test/dynamo/test_unspec.py::UnspecTests::test_multiple_consecutive_random_calls_before_graph, test/dynamo/test_unspec.py::UnspecTests::test_no_recompilations, test/dynamo/test_unspec.py::UnspecTests::test_no_recompilations_with_efficient_attention, test/dynamo/test_unspec.py::UnspecTests::test_no_recompiles, test/dynamo/test_unspec.py::UnspecTests::test_no_recompiles_prod_backward, test/dynamo/test_unspec.py::UnspecTests::test_numpy_correctness, test/dynamo/test_unspec.py::UnspecTests::test_propagate_dynamic_dim, test/dynamo/test_unspec.py::UnspecTests::test_prune_torch_check, test/dynamo/test_unspec.py::UnspecTests::test_random_call_with_while_loop, test/dynamo/test_unspec.py::UnspecTests::test_random_object, test/dynamo/test_unspec.py::UnspecTests::test_random_object_methods, test/dynamo/test_unspec.py::UnspecTests::test_random_object_overridden_methods, test/dynamo/test_unspec.py::UnspecTests::test_random_values_with_graph_break, test/dynamo/test_unspec.py::UnspecTests::test_rshift_dynamic, test/dynamo/test_unspec.py::UnspecTests::test_shape_graph_break, test/dynamo/test_unspec.py::UnspecTests::test_specializing_numpy_float_in_control_flow, test/dynamo/test_unspec.py::UnspecTests::test_split_aot_autograd, test/dynamo/test_unspec.py::UnspecTests::test_sum_dimlist_spec, test/dynamo/test_unspec.py::UnspecTests::test_sym_int_conversion, test/dynamo/test_unspec.py::UnspecTests::test_symbol_guard_limit_before_specialize, test/dynamo/test_unspec.py::UnspecTests::test_symfloat_no_replacement, test/dynamo/test_unspec.py::UnspecTests::test_symfloat_to_tensor, test/dynamo/test_unspec.py::UnspecTests::test_tensorfiy_python_scalars_1, test/dynamo/test_unspec.py::UnspecTests::test_tensorfiy_python_scalars_2, test/dynamo/test_unspec.py::UnspecTests::test_tensorfiy_python_scalars_3, test/dynamo/test_unspec.py::UnspecTests::test_to_tensor, test/dynamo/test_unspec.py::UnspecTests::test_unspec_float_input, test/dynamo/test_unspec.py::UnspecTests::test_unspec_float_input_f64, test/dynamo/test_unspec.py::UnspecTests::test_unspec_float_output, test/dynamo/test_unspec.py::UnspecTests::test_unspec_float_precision, test/dynamo/test_unspec.py::UnspecTests::test_unspec_roundtrip_float_input, test/dynamo/test_unspec.py::UnspecTests::test_unspecialized_float_multiply_precision, test/dynamo/test_unspec.py::UnspecTests::test_use_and_specialize, test/dynamo/test_unspec.py::UnspecTestsDeviceCUDA::test_builtin_functions_on_device_cuda 2025-08-26T21:44:40.6170172Z 2025-08-26T21:44:40.6170260Z Running export/test_nativert 1/1 ... [2025-08-26 21:44:40.611312] 2025-08-26T21:44:40.6170532Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:44:40.6170932Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'export/test_nativert.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:44:40.611634] 2025-08-26T21:46:49.9613575Z 2025-08-26T21:46:49.9622743Z export/test_nativert 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_nativert_1.1_4f33d76090dff5be_.log 2025-08-26T21:46:49.9712000Z Running 402 items in this shard: test/export/test_nativert.py::NativeRTTestExport::test__scaled_dot_product_flash_attention_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_additional_inputs_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_allow_explicit_guards_as_runtime_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_args_type_checked_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_aten_lift_fresh_copy_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_attention_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_attr_assignment_extra_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_constrain_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_constant_relation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_linear_relation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_simple_equality_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_baddbmm_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_non_strict_fake_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_non_strict_real_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_bincount_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_buffer_util_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_constructor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_constructor_torch_ir_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_wrong_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_ccode_python_mod_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_check_specialized_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_checks_to_constrain_range_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cleanup_dynamic_markers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_colin_unbacked_backed_vr_sub_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_colon_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_compiling_state_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_access_identical_symint_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_branches_return_constant_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_branches_return_same_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_contains_unbacked_no_escape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_int_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_with_module_stack_export_with_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_with_module_stack_export_with_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_aliasing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_input_naming_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_no_user_inp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_output_dup_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_requires_grad_const_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_return_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_with_non_functional_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_with_non_functional_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_decomp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_in_eager_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_with_constrain_value_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_with_various_cases_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_conv_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_crop_like_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cse_for_symint_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_functionalize_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_functionalize_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_warn_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_preserve_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_tag_metadata_re_export_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_batch_norm_functional_predispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_item_in_prim_after_decomposition_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_item_in_prim_before_decomposition_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_default_decomposition_core_cia_ops_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_1_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_integer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_repeat_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_simplified_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_repeat_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_detect_leak_strict_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_gpu_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_mutation_float_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_static_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_1_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_auto_and_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_divisibility_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_hint_range_violations_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_hint_ranges_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_disable_forced_specializations_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_disable_forced_specializations_ok_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_gather_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_gather_into_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_reduce_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_to_all_single_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_reduce_scatter_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dont_duck_size_for_auto_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_double_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_aliasing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_list_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_with_nan_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_fake_kernel_inference_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_infers_fake_kernel_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_duplicate_modules_with_non_persistent_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_lr_shift_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_bounds_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_dataclass_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_inferred_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_generic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_user_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_various_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_spec_with_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_sym_round_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_ends_of_bounds_oblivious_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_error_does_not_reference_eager_fallback_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_error_when_passing_mutating_primitive_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_exception_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_api_with_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_as_backend_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_lifted_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_symbol_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_symbol_scandim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_subclass_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_subclass_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_preserve_torch_fn_for_subgraphs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_symbool_pred_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_warns_constant_pred_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_decomp_table_basic_pop_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_decomp_table_container_methods_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_op_lib_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_triton_kernel_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_triton_kernel_mutable_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomp_torture_case_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomp_torture_case_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomps_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomps_simple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_dynamo_config_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_run_decomp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_container_type_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_state_dict_hooks_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_default_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_keyword_only_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_pytree_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_keyword_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_keyword_pytree_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_postional_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_function_schema_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_graph_with_no_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_bug_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_dynamic_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_static_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_linear_preserve_dynamic_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_max_nonstrict_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_max_onnx_reported_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_mod_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_preserve_linear_at_aot_level_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_preserve_linear_but_not_custom_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_scan_pytree_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_script_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_statically_known_true_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_then_compile_tensor_ctor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_autocast_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_fake_tensor_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_fake_tensor_inputs_on_cuda_devices_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_inline_constraints_complex_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_inline_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_set_grad_enabled_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_wrong_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_external_call_non_strict_real_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fake_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fake_weights_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_filter_traceback_frames_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_float_conversion_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_float_conversion_from_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fqn_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_from_node_metadata_export_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_full_on_scalar_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_hints_wrapper_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_hoo_inline_users_issue_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_if_functional_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_if_post_autograd_op_preserved_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_class_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_class_method_recursive_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_int_shape_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_intermediate_shape_comp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_exporting_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_non_negative_check_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_nonzero_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_isnonzero_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_issue_113041_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_issue_157289_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_istft_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_invalid_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_linear_convd_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_linear_convd_for_training_ir_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_kwarg_dynamic_shapes_diff_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_kwargs_reorder_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_layer_norm_unbacked_normalized_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_layer_sharing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_lazy_module_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_linear_conv_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_malformed_fqn_from_source_name_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_map_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_map_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mask_nonzero_static_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_masked_select_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_math_pow_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mismatched_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mixed_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_dict_key_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_input_subclasses_parameterization_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_list_slice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_with_dict_container_inp_out_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_modules_access_for_deleted_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_more_multidimensional_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multidimensional_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multinomial_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multiple_definitions_same_name_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_dynamic_shapes_spec_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_constant_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_init_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nn_module_stack_shared_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_check_is_size_error_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_suggested_fixes_for_data_dependent_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_3_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_with_container_type_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_persistent_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_strict_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_strict_dynamic_shapes_suggested_fixes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_none_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonstrict_retrace_preserves_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonzero_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonzero_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_not_registered_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_operator_aten_tensor_mode_variant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_output_node_name_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pad_sequence_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_param_util_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_partial_patched_forward_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_collisions_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_collisions_hoo_subgraphs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_order_variadic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_update_preserving_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_predispatch_cond_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_predispatch_grad_wrappers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_module_call_signature_unflatten_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_requires_grad_placeholders_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_shape_dynamism_for_unused_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_profiling_code_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_python_asserts_with_sym_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pytree_register_data_class_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pytree_register_nested_data_class_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_raise_user_error_when_guard_on_data_dependent_operation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_range_constraints_with_replacement_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_alias_dtype_mismatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_bool_cast_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_errors_on_aliasing_custom_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_for_max_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_size_mismatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_redundant_assert_max_upper_bound_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_redundant_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_refine_dynamic_shapes_from_suggested_fixes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_register_constant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_repeat_interleave_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_replace_unbacked_with_very_large_upperbound_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_replaced_unbacked_bindings_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_reshape_view_helper_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_retracable_ep_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_retrace_pre_autograd_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decomposition_supports_user_input_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decompositions_keep_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decompositions_keep_tensor_constant_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_for_prim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_for_prm_str_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_with_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sdpa_gqa_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sequential_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_example_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_as_side_effect_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_empty_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_setgrad_lifted_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_shared_submodule_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_simple_export_for_training_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_simple_unbacked_view_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_size_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_slice_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_solver_unsupported_sympy_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_specialize_derived_dim_roots_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_split_const_gm_with_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_stack_trace_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_stack_trace_make_fx_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_primitives_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_shape_attribute_assignment_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_tensors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_static_dim_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_complicated_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_const_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_const_metadata_not_top_level_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclasses_parameterization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclasses_parameterization_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggest_torch_checks_with_non_negative_check_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggest_torch_checks_with_regular_check_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_for_data_dependent_errors_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_new_roots_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_float_operators_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_or_sym_and_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_sqrt_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symbool_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symfloat_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_additional_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_ranges_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_shapes_collection_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_tensor_return_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_attribute_zero_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_constant_aten_to_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_constant_with_wrapped_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_multiple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tolist_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_torch_check_eq_commutativity_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_torch_fn_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_trace_under_fake_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_train_eval_on_exported_preautograd_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_3d_matmul_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_bincount_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_bindings_for_divisible_u_symint_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_deferred_runtime_retrace_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_expand_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_infer_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_kth_value_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_linear_layer_norm_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_noncontig_lin_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_pad_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_scalar_constructor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_slice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_to_cond_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_to_cond_passthrough_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_unsqueeze_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_buffer_update_child2parent_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_isinstance_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_preserve_signature_no_error_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_shared_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_state_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_no_unroll_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_placeholder_update_child2parent_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_placeholder_update_grandchild2cousin_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_5_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_6_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_buf_8_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_const_preserving_3_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_const_preserving_3_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_6_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_9_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_10_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_5_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_7_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_preserving_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unused_aliases_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unused_constant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_use_embedding_twice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_user_input_and_buffer_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_vmap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_assert_separation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_index_assertions_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_simple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_tensor_constant_idx_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_wrapper_module_cpp_runtime_nonstrict 2025-08-26T21:46:49.9800038Z 2025-08-26T21:46:49.9800186Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T21:46:49.9800504Z Uploading artifacts took 0.00 seconds 2025-08-26T21:46:49.9800750Z Running inductor/test_block_analysis 1/1 ... [2025-08-26 21:46:49.962025] 2025-08-26T21:46:49.9801003Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:46:49.9801579Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_block_analysis.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:46:49.962314] 2025-08-26T21:46:55.5896576Z 2025-08-26T21:46:55.5898213Z inductor/test_block_analysis 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_block_analysis_1.1_8eb3e626104c4f57_.log 2025-08-26T21:46:55.5906584Z Running 10 items in this shard: test/inductor/test_block_analysis.py::BlockAnalysisTest::test_affine_identity_stride_3_symbol2_expr2, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_affine_identity_stride_4_symbol1_expr1, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_affine_identity_stride_5_symbol0_expr0, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_index_with_dynamic_shapes, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_mod_div_identity_dims0_strides0_symbol0_expr0, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_mod_div_identity_dims1_strides1_symbol1_expr1, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_mod_div_identity_dims2_strides2_symbol2_expr2, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_subexpr_identity_symbol0_expr0_subexpr0, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_subexpr_identity_symbol1_expr1_subexpr1, test/inductor/test_block_analysis.py::BlockAnalysisTest::test_subexpr_identity_symbol2_expr2_subexpr2 2025-08-26T21:46:55.5908276Z 2025-08-26T21:46:55.5908373Z Running inductor/test_codegen_triton 1/1 ... [2025-08-26 21:46:55.587475] 2025-08-26T21:46:55.5908558Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:46:55.5908974Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_codegen_triton.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:46:55.587706] 2025-08-26T21:47:01.7615716Z 2025-08-26T21:47:01.7616444Z inductor/test_codegen_triton 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_codegen_triton_1.1_daef6c744eb30fef_.log 2025-08-26T21:47:01.7617596Z Running 1 items in this shard: test/inductor/test_codegen_triton.py::TestCodegenTriton::test_config_of_sizearg 2025-08-26T21:47:01.7617856Z 2025-08-26T21:47:01.7642366Z Running inductor/test_combo_kernels 1/1 ... [2025-08-26 21:47:01.761529] 2025-08-26T21:47:01.7642850Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:47:01.7643784Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_combo_kernels.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:47:01.761729] 2025-08-26T21:47:45.1364243Z 2025-08-26T21:47:45.1364903Z inductor/test_combo_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_combo_kernels_1.1_f759389fcb77c42c_.log 2025-08-26T21:47:45.1368165Z Running 20 items in this shard: test/inductor/test_combo_kernels.py::ComboKernelTests::test_2d_blocking_partitioning, test/inductor/test_combo_kernels.py::ComboKernelTests::test_activation_functions, test/inductor/test_combo_kernels.py::ComboKernelTests::test_mutated_args, test/inductor/test_combo_kernels.py::ComboKernelTests::test_reduce_functions, test/inductor/test_combo_kernels.py::ComboKernelTests::test_reduce_split, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_2d_blocking_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_activation_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_mutated_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_persistent_reduction_no_x_dim, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_reduce_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_round_robin_dispatch, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_2d_blocking, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_2d_blocking_round_robin, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_activations, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_activations_no_autotune, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_mutated, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_mixed_x_dim_cuda, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_no_x_dim, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_no_x_dim_2, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_reduce 2025-08-26T21:47:45.1371432Z 2025-08-26T21:47:45.1377455Z Running inductor/test_layout_optim 1/1 ... [2025-08-26 21:47:45.136201] 2025-08-26T21:47:45.1378291Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:47:45.1384213Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_layout_optim.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:47:45.136473] 2025-08-26T21:47:50.7011030Z 2025-08-26T21:47:50.7011671Z inductor/test_layout_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_layout_optim_1.1_42648da510de6952_.log 2025-08-26T21:47:50.7012155Z Running 0 items in this shard: 2025-08-26T21:47:50.7012272Z 2025-08-26T21:47:50.7015991Z Running inductor/test_op_completeness 1/1 ... [2025-08-26 21:47:50.701325] 2025-08-26T21:47:50.7017042Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:47:50.7018695Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_op_completeness.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:47:50.701654] 2025-08-26T21:47:53.8742871Z 2025-08-26T21:47:53.8743591Z inductor/test_op_completeness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_op_completeness_1.1_266e46efb06bdc88_.log 2025-08-26T21:47:53.8745176Z Running 5 items in this shard: test/inductor/test_op_completeness.py::TestOpCompleteness::test_cpp_overrides, test/inductor/test_op_completeness.py::TestOpCompleteness::test_cpp_vec_overrides, test/inductor/test_op_completeness.py::TestOpCompleteness::test_halide_overrides, test/inductor/test_op_completeness.py::TestOpCompleteness::test_metal_overrides, test/inductor/test_op_completeness.py::TestOpCompleteness::test_triton_overrides 2025-08-26T21:47:53.8748281Z 2025-08-26T21:47:53.8748434Z Running inductor/test_op_dtype_prop 1/1 ... [2025-08-26 21:47:53.874569] 2025-08-26T21:47:53.8748631Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:47:53.8751126Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'inductor/test_op_dtype_prop.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:47:53.874838] 2025-08-26T21:53:32.4777645Z 2025-08-26T21:53:32.4778789Z inductor/test_op_dtype_prop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_op_dtype_prop_1.1_a6ee3695622cb74e_.log 2025-08-26T21:53:32.4867192Z Running 567 items in this shard: test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_any_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_assoc_scan_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_binary_math_mixed_precision_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_codegen_upcast_to_fp32_upcast_to_fp32_False_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_codegen_upcast_to_fp32_upcast_to_fp32_True_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_constant_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_downcast_div_mod_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_abs_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_abs_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_abs_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_abs_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acos_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acos_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acos_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acos_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acosh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acosh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acosh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_acosh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asin_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asin_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asin_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asin_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asinh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asinh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asinh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_asinh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan2_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan2_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan2_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan2_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atan_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atanh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atanh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atanh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_atanh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_ceil_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_ceil_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_ceil_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_ceil_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_copysign_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_copysign_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_copysign_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_copysign_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cos_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cos_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cos_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cos_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cosh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cosh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cosh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_cosh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erf_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erf_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erf_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erf_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfc_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfc_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfc_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfc_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfinv_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfinv_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfinv_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_erfinv_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp2_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp2_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp2_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp2_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_exp_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_expm1_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_expm1_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_expm1_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_expm1_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_floor_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_floor_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_floor_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_floor_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_fmod_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_fmod_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_fmod_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_fmod_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_hypot_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_hypot_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_hypot_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_hypot_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isinf_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isinf_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isinf_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isinf_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isnan_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isnan_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isnan_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_isnan_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_lgamma_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_lgamma_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_lgamma_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_lgamma_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log10_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log10_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log10_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log10_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log1p_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log1p_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log1p_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log1p_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log2_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log2_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log2_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log2_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_log_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_nextafter_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_nextafter_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_nextafter_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_nextafter_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_pow_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_pow_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_pow_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_pow_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_round_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_round_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_round_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_round_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_rsqrt_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_rsqrt_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_rsqrt_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_rsqrt_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sigmoid_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sigmoid_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sigmoid_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sigmoid_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sin_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sin_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sin_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sin_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sinh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sinh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sinh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sinh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sqrt_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sqrt_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sqrt_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_sqrt_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tan_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tan_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tan_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tan_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tanh_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tanh_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tanh_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_tanh_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_trunc_load_upcast_to_fp32_False_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_trunc_load_upcast_to_fp32_False_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_trunc_load_upcast_to_fp32_True_bfloat16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_dtype_aware_codegen_op_name_trunc_load_upcast_to_fp32_True_float16_cuda, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_abs_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_abs_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_abs_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_abs_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_abs_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acos_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acos_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acos_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acos_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acos_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acosh_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acosh_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acosh_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acosh_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_acosh_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_add_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_add_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_add_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_add_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_add_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_angle_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_angle_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_angle_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_angle_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_angle_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asin_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asin_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asin_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asin_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asin_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asinh_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asinh_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asinh_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asinh_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_asinh_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan2_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan2_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan2_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan2_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan2_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atan_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atanh_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atanh_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atanh_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atanh_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_atanh_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_and_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_and_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_and_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_left_shift_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_left_shift_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_not_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_not_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_not_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_or_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_or_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_or_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_right_shift_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_right_shift_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_xor_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_xor_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_bitwise_xor_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ceil_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ceil_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ceil_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ceil_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_clamp_max_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_clamp_max_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_clamp_max_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_clamp_max_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_clamp_max_cuda_int64, 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test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_mul_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_mul_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_mul_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ne_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ne_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ne_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ne_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_ne_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_neg_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_neg_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_neg_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_neg_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_nextafter_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_nextafter_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_0_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_0_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_0_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_0_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_0_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_1_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_1_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_1_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_1_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_1_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_2_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_2_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_2_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_2_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_2_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_3_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_3_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_3_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_3_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_3_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_4_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_4_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_4_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_4_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_polygamma_polygamma_n_4_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_pow_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_pow_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_pow_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_pow_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_reciprocal_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_reciprocal_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_reciprocal_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_reciprocal_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_reciprocal_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_remainder_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_remainder_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_remainder_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_remainder_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_0_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_0_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_3_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_3_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_neg_3_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_round_decimals_neg_3_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_rsqrt_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_rsqrt_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_rsqrt_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_rsqrt_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_rsqrt_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sigmoid_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sigmoid_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sigmoid_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sigmoid_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sigmoid_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sign_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sign_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sign_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sign_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sign_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_signbit_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_signbit_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_signbit_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_signbit_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_signbit_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sin_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sin_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sin_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sin_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sin_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sinh_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sinh_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sinh_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sinh_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sinh_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sqrt_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sqrt_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sqrt_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sqrt_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sqrt_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_square_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_square_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_square_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_square_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_square_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sub_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sub_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sub_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_sub_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tan_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tan_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tan_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tan_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tan_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tanh_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tanh_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tanh_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tanh_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_tanh_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_true_divide_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_true_divide_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_true_divide_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_true_divide_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_true_divide_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_trunc_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_trunc_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_trunc_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_trunc_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_where_cuda_bool, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_where_cuda_float32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_where_cuda_float64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_where_cuda_int32, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_propagation_where_cuda_int64, test/inductor/test_op_dtype_prop.py::TestCaseCUDA::test_op_dtype_support_cuda 2025-08-26T21:53:32.4942226Z 2025-08-26T21:53:32.4942313Z Running functorch/test_ops 3/4 ... [2025-08-26 21:53:32.478418] 2025-08-26T21:53:32.4942481Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T21:53:32.4942862Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'functorch/test_ops.py', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:53:32.478648] 2025-08-26T22:02:34.6386006Z 2025-08-26T22:02:34.6387224Z functorch/test_ops 3/4 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_3.4_d31fd4a8fee96b15_.log 2025-08-26T22:02:34.6720101Z Running 2555 items in this shard: test/functorch/test_ops.py::TestOperatorsCUDA::test_extremal_numerics_l1_loss_cuda, test/functorch/test_ops.py::TestOperatorsCUDA::test_extremal_numerics_layer_norm_cuda, test/functorch/test_ops.py::TestOperatorsCUDA::test_extremal_numerics_mse_loss_cuda, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad__batch_norm_with_update_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_addbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_addmm_decomposed_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_addr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_all_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_angle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_any_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_arange_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_as_strided_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_as_strided_partial_views_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_as_strided_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_atleast_3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_block_diag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cartesian_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cholesky_inverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_clamp_min_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cosh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cummin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_deg2rad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_diagonal_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_dsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_fft_ifft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_fft_ihfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_fft_ihfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_fft_irfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_fliplr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_floor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_frac_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_geometric_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_grid_sampler_3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_hash_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_hstack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_index_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_index_reduce_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_index_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_isreal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_lerp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_cholesky_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_eigh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_pinv_hermitian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_linalg_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_log10_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_logcumsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_logit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_lt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_mH_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_mT_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_masked_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_masked_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_masked_cumsum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_masked_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_masked_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_max_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_median_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_meshgrid_list_of_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nansum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_native_dropout_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_new_empty_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_new_ones_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_adaptive_avg_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_adaptive_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_adaptive_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_adaptive_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_batch_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_batch_norm_without_cudnn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_binary_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_conv2d_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_conv2d_stride_groups_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_conv2d_stride_padding_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_conv2d_strided_padding_dilation_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_conv_transpose3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_ctc_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_dropout2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_embedding_bag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_embedding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_glu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_group_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_hinge_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_interpolate_area_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_interpolate_linear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_local_response_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_margin_ranking_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_mse_loss_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_multi_head_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_multi_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_multilabel_soft_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_pairwise_distance_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_pixel_unshuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_relu6_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_relu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_rms_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_scaled_dot_product_attention_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_smooth_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_soft_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_softmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_softshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_triplet_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_nonzero_static_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_ones_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_ops_aten_index_put_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_permute_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_polar_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_polygamma_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_polygamma_polygamma_n_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_polygamma_polygamma_n_2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_polygamma_polygamma_n_4_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_ravel_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_renorm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_resize_as__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_resolve_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_rot90_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_round_decimals_neg_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_rsqrt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_scatter_reduce_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_searchsorted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_select_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_short_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_sigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_signal_windows_blackman_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_signal_windows_exponential_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_signal_windows_general_hamming_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_signal_windows_nuttall_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_sin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_sinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_slice_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_bessel_j1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_i1e_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_log_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_modified_bessel_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_modified_bessel_k0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_scaled_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_sqrt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_squeeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_std_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_take_along_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_take_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_torch_ops_aten__safe_softmax_default_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_trapezoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_trapz_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_uniform_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_unsafe_chunk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_grad_var_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_SelectGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp___rmatmul___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp___rmod___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp__batch_norm_with_update_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp__segment_reduce_offsets_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_addbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_addmm_decomposed_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_aminmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_argwhere_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_atan2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_atleast_1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_baddbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_bernoulli_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_bool_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_broadcast_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_byte_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_cdouble_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_char_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_char_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_complex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_constant_pad_nd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_copysign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_corrcoef_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_cos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_cosh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_empty_permuted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_erfc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_fft_fftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_fft_ifftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_fft_ihfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_fft_rfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_float_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_float_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_full_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_gather_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_geometric_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_geqrf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_half_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_half_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_hash_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_heaviside_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_igammac_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_index_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_int_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_isin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_isinf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_isreal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_jiterator_binary_return_by_ref_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_ldexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_cholesky_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_det_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_eigh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_ldl_factor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_ldl_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_ldl_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_lu_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_solve_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linalg_vecdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_linspace_tensor_overload_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_log1p_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logcumsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logical_not_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logical_or_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_logsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_long_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_long_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_lu_unpack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_argmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_softmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_masked_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_maximum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_meshgrid_variadic_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_mm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_mvlgamma_mvlgamma_p_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nanquantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_narrow_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_native_dropout_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_native_layer_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_new_empty_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_new_full_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_new_ones_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_batch_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_conv2d_stride_depthwise_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_conv2d_stride_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_conv2d_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_conv_transpose3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_elu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_gelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_glu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_hardshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_interpolate_linear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_interpolate_trilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_layer_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_leaky_relu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_local_response_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_multi_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_rrelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_scaled_dot_product_attention_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_selu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_triplet_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_ones_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_polar_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_polygamma_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_polygamma_polygamma_n_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_polygamma_polygamma_n_4_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_randn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_resize_as__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_resolve_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_round_decimals_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_rsub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_scatter_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_signal_windows_bartlett_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_sinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_sparse_mm_reduce_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_sparse_sampled_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_hermite_polynomial_h_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_hermite_polynomial_he_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_i0e_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_i1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_log_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_modified_bessel_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_modified_bessel_i1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_special_shifted_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_split_list_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_split_with_sizes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_squeeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_svd_lowrank_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_tile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_torch_ops_aten__efficient_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_trapz_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_trunc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_unbind_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_unsqueeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_where_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_xlogy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_zero__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvp_zeros_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpjvpvmap_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpjvpvmap_SelectGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_H_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_T_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp___getitem___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp___rdiv___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp___rmod___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp__batch_norm_with_update_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp__segment_reduce_lengths_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp__unsafe_masked_index_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_alias_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_all_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_any_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_arange_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_argmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_asin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_bfloat16_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_bfloat16_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_bmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_broadcast_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_clamp_max_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_clone_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_combinations_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_copysign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_cummax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_diagonal_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_empty_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_fft_fft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_fft_hfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_fft_ifftshift_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_flip_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_float_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_fmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_frexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_full_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_grid_sampler_3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_hash_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_index_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_inner_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_isclose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_isinf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_ldexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_cond_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_eigvalsh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_householder_product_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_ldl_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_lstsq_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_multi_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_pinv_hermitian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_vander_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linalg_vecdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_linspace_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_log_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_log_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_log_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logical_xor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logspace_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_logsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_lu_unpack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_mH_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_logsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_median_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_masked_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_matmul_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_max_reduction_no_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_minimum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_mm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_mvlgamma_mvlgamma_p_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_mvlgamma_mvlgamma_p_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nanquantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nansum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_native_batch_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_new_empty_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_new_full_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_adaptive_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_avg_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_avg_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_batch_norm_without_cudnn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_binary_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_channel_shuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_conv2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_conv2d_stride_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_conv2d_strided_padding_dilation_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_cosine_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_dropout3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_fractional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_hardshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_hinge_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_max_unpool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_max_unpool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_pad_reflect_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_pixel_shuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_softshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nn_functional_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_nonzero_static_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_norm_inf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_ones_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_ormqr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_outer_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_pca_lowrank_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_permute_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_pinverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_polygamma_polygamma_n_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_quantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_randint_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_reciprocal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_renorm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_reshape_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_resize_as__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_scatter_reduce_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_short_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_bartlett_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_gaussian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_general_cosine_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_general_hamming_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_hann_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_signal_windows_kaiser_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_sin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_sinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_slice_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_special_bessel_j0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_special_shifted_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_special_shifted_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_squeeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_squeeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_sub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_sum_to_size_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_to_sparse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_torch_ops_aten__efficient_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_transpose_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_triu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_unbind_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_unsqueeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjp_where_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvjpvmap_SortGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmap_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmap_SelectAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmap_SortGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmap_ZeroGradientsGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmapvmap_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmapvmap_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmapvmap_NumpyCubeNotComposableAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmapvmap_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_jvpvmapvmap_ZeroGradientsGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_bool_raises_floor_cuda_bool, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_amax_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_argmax_cuda_complex128, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_argmax_cuda_complex32, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_floor_cuda_complex128, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_floor_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_ge_cuda_complex128, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_ge_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_gt_cuda_complex128, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_le_cuda_complex32, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_lt_cuda_complex128, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_lt_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_minimum_cuda_complex32, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_minimum_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_topk_cuda_complex32, test/functorch/test_ops.py::TestOperatorsCUDA::test_ordered_complex_raises_topk_cuda_complex64, test/functorch/test_ops.py::TestOperatorsCUDA::test_tensor_with_scalar_list_cuda, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_broadcast_to_grad_op_jvp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_list_return_split_grad_op_jvp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_list_return_vsplit_grad_op_jvp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_mH_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_movedim_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_narrow_grad_op_jvp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_narrow_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_positive_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_transpose_grad_op_jvp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_unflatten_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_view_then_inplace_unfold_grad_op_vjp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_NumpyCubeNotComposableAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_NumpySortAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp___getitem___functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp___rdiv___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp___rmul___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp__segment_reduce_offsets_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_addcdiv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_addcmul_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_addmv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_atan2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_atanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_cdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_cdouble_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_chunk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_clamp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_clamp_min_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_combinations_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_count_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_deg2rad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_digamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_empty_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_eq_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_equal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_erfinv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_expand_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_expm1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_eye_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_fft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_fftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_hfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_ifft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_ifftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_ifftshift_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fft_rfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_flatten_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_float_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_float_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_floor_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_frexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_gradient_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_grid_sampler_2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_half_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_heaviside_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_hsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_hstack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_igamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_igammac_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_index_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_index_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_index_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_index_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_int_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_jiterator_2inputs_2outputs_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_jiterator_binary_return_by_ref_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ldexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_det_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_ldl_factor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_ldl_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_lu_factor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_lu_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_vecdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linalg_vector_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_linspace_tensor_overload_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_log_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_logical_and_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_logical_or_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_logsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_long_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_lt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_masked_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_masked_cumsum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_masked_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_masked_softmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_masked_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_max_pool2d_with_indices_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_max_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_meshgrid_list_of_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_min_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_mode_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_multinomial_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_mvlgamma_mvlgamma_p_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nanquantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_native_batch_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ne_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_new_full_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_new_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_adaptive_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_adaptive_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_batch_norm_without_cudnn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_channel_shuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_conv2d_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_conv2d_stride_padding_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_conv2d_stride_padding_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_conv_transpose3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_hardshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_huber_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_kl_div_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_max_unpool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_mse_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_mse_loss_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_pairwise_distance_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_relu6_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_scaled_dot_product_attention_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_selu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_silu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_nn_functional_softplus_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_normal_in_place_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ones_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ones_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ops_aten_index_put_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_outer_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_permute_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_polygamma_polygamma_n_2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_polygamma_polygamma_n_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_rand_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_ravel_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_remainder_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_reshape_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_rsqrt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_scalar_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_scatter_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_scatter_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_searchsorted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_sigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_signal_windows_blackman_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_slice_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_polygamma_special_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_scaled_modified_bessel_k0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_square_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_t_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_tan_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_tile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_trapz_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_unsqueeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjp_view_as_complex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_T_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp___rmod___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp___rpow___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp__chunk_cat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp__segment_reduce_lengths_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp__segment_reduce_offsets_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp__unsafe_masked_index_put_accumulate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_acos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_addbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_addcdiv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_addmv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_all_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_as_strided_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_atanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_atleast_2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_baddbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_bmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_broadcast_shapes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_byte_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_cartesian_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_cauchy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_cdouble_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_char_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_chunk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_complex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_conj_physical_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_copysign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_cummin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_diagonal_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_div_no_rounding_mode_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_double_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_empty_permuted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_empty_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_erf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_expand_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fft_fftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fft_hfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fft_rfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fft_rfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fliplr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_float_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_float_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_float_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_fmod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_frexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_gt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_index_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_index_reduce_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_index_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_isclose_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_lu_factor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_norm_subgradients_at_zero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_pinv_singular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_solve_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_svd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_linalg_vander_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_log10_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_logcumsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_logdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_logical_xor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_lt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_argmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_masked_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_maximum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_min_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_mvlgamma_mvlgamma_p_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_mvlgamma_mvlgamma_p_5_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nan_to_num_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nanquantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_native_batch_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_native_dropout_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_neg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_new_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_adaptive_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_conv2d_strided_padding_dilation_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_conv3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_conv_transpose1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_cosine_similarity_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_embedding_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_gelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_huber_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_interpolate_nearest_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_interpolate_trilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_max_unpool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_mse_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_pad_circular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_pad_constant_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nn_functional_pad_reflect_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_norm_nuc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_pca_lowrank_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_permute_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_pinverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_polar_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_polygamma_polygamma_n_2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_positive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_randint_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_ravel_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_remainder_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_renorm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_reshape_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_resize_as__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_round_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_scatter_reduce_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_short_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_laguerre_polynomial_l_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_log_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_modified_bessel_i1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_modified_bessel_k0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_special_shifted_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_split_with_sizes_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_squeeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_sum_to_size_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_take_along_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_tile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_to_sparse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_transpose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_trunc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_unbind_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_uniform_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_unsqueeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_var_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjp_view_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjpvmap_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvjpvmap_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_MulGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap___getitem___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap___rmul___cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_aminmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_argwhere_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_asin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_atleast_1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_atleast_2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_bernoulli_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_bmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_bucketize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_cat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_ceil_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_cholesky_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_column_stack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_complex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_count_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_deg2rad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_diagflat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_double_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_empty_like_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_inner_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_isclose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_det_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_eigvalsh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_householder_product_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_inv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_lu_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_pinv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_pinv_singular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linalg_slogdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_linspace_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_logdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_logical_and_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_logspace_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_long_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_masked_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_masked_cumsum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_masked_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_masked_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_max_reduction_no_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_max_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_maximum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_meshgrid_list_of_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_meshgrid_variadic_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_mode_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_movedim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_multinomial_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_mv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_mvlgamma_mvlgamma_p_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_mvlgamma_mvlgamma_p_5_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nan_to_num_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nanmedian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_ne_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_new_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_adaptive_avg_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_adaptive_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_adaptive_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_conv2d_stride_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_conv2d_stride_padding_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_cosine_similarity_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_ctc_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_dropout2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_embedding_bag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_fractional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_gaussian_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_gelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_hardsigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_huber_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_instance_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_kl_div_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_max_unpool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_max_unpool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_pad_replicate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_pixel_shuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_prelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_softsign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nn_functional_upsample_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_nonzero_static_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_norm_nuc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_normal_in_place_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_ops_aten_index_put_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_ormqr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_outer_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_pinverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_polygamma_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_randn_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_remainder_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_resolve_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_round_decimals_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_round_decimals_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_rsqrt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_scatter_reduce_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_sgn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_sign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_signal_windows_gaussian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_signal_windows_kaiser_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_signal_windows_nuttall_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_signbit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_sparse_sampled_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_log_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_polygamma_special_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_scaled_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_special_shifted_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_split_list_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_std_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_sub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_svd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_take_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_torch_ops_aten__safe_softmax_default_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_transpose_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_unfold_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_uniform_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_unsqueeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_var_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_vsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_zero__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmap_zeros_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmapvmap_SelectGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vjpvmapvmap_ZeroGradientsGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_H_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_MulGenVmapAutogradFunction_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_NumpyCubeNotComposableAutogradFunction_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ScaleGradGenVmapAutogradFunction_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_SelectAutogradFunction_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_SelectGenVmapAutogradFunction_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_SortGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___getitem___cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___getitem___functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___getitem___functorch_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___rdiv___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___rmul___cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad__unsafe_masked_index_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad__upsample_bilinear2d_aa_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_acosh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_addcdiv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_addmv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_addr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_aminmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_angle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_angle_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_arange_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_argmax_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_as_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_as_strided_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_as_strided_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_as_strided_scatter_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_asin_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_asinh_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_atan2_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_atanh_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_baddbmm_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_bfloat16_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_bool_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_bool_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_broadcast_to_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_byte_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cartesian_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cartesian_prod_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cauchy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cauchy_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cdouble_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_chalf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_char_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_char_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_char_functorch_no_channels_last_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cholesky_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cholesky_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cholesky_inverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cholesky_inverse_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_chunk_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_clamp_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_clamp_max_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_clamp_min_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_clone_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_complex_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_conj_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_conj_physical_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_constant_pad_nd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_copysign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_copysign_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cosh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cosh_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_count_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_count_nonzero_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cov_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cummin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_cumprod_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_diagflat_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_diagonal_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_digamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_div_trunc_rounding_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_double_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_double_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_dstack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_empty_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_empty_strided_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_eq_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_equal_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_erf_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_erfc_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_expand_as_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_fftshift_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_hfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_hfft_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ifft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ifft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ifftshift_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ifftshift_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ihfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ihfft2_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_ihfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_irfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_rfft_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fft_rfftn_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_flip_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_flipud_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_floor_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_frac_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_full_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_full_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_full_like_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ge_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_geqrf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_grid_sampler_2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_grid_sampler_3d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_gt_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_half_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_half_functorch_no_channels_last_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_hash_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_heaviside_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_hstack_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_igamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_igammac_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_add_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_put_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_put_functorch_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_reduce_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_reduce_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_reduce_prod_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_index_select_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_isclose_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_isfinite_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_isneginf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_isposinf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_item_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_item_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_jiterator_binary_return_by_ref_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_le_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_lerp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_lgamma_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_det_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_inv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_ldl_factor_ex_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_lstsq_grad_oriented_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_matrix_norm_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_matrix_rank_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_matrix_rank_hermitian_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_norm_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_pinv_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_pinv_singular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_slogdet_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_solve_ex_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_solve_triangular_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_svd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_vander_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linalg_vander_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linspace_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_linspace_tensor_overload_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_log_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_log_softmax_with_dtype_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_log_softmax_with_dtype_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logcumsumexp_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logdet_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logical_and_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logical_and_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logical_not_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logical_or_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logical_xor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logspace_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_logspace_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_long_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_lu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_lu_solve_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mT_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_argmax_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_fill_functorch_Scalar_only_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_logsumexp_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_median_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_softmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_masked_var_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_matrix_exp_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_max_pool2d_with_indices_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_maximum_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mean_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_meshgrid_list_of_tensors_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_meshgrid_variadic_tensors_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_min_reduction_no_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_min_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mm_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mode_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_movedim_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nanquantile_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_narrow_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_native_dropout_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_native_dropout_backward_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ne_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_neg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_new_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_new_empty_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_new_full_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_new_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_adaptive_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_adaptive_max_pool1d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_adaptive_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_alpha_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_avg_pool1d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_batch_norm_without_cudnn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_bilinear_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_conv1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_conv2d_stride_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_conv2d_stride_padding_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_conv_transpose1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_cosine_embedding_loss_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_dropout2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_dropout2d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_embedding_bag_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_embedding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_embedding_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_feature_alpha_dropout_with_train_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_fractional_max_pool3d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_glu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_glu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_hardsigmoid_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_interpolate_linear_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_leaky_relu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_leaky_relu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_logsigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_logsigmoid_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_margin_ranking_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_pool2d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_unpool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_unpool2d_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_unpool2d_grad_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_unpool3d_grad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_max_unpool3d_grad_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_mse_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_mse_loss_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_mse_loss_functorch_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_nll_loss_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_pad_circular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_pad_circular_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_pad_replicate_negative_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_poisson_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_prelu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_rms_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_rms_norm_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_scaled_dot_product_attention_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_scaled_dot_product_attention_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_selu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_silu_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_smooth_l1_loss_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_softmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_softmin_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_softplus_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_softsign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_triplet_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_triplet_margin_loss_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_nn_functional_upsample_nearest_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_norm_fro_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_norm_inf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_norm_nuc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_norm_nuc_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_normal_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_normal_number_mean_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ones_like_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ops_aten_index_put_functorch_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_outer_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_permute_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_polygamma_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_polygamma_polygamma_n_1_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_polygamma_polygamma_n_2_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_pow_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_pow_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_quantile_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_randn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_randn_like_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_ravel_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_real_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_reciprocal_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_repeat_interleave_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_reshape_as_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_resize__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_resolve_neg_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_rot90_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_round_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_round_decimals_0_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_rsqrt_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scalar_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scatter_add_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scatter_reduce_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scatter_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scatter_reduce_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_scatter_reduce_prod_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_searchsorted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sgn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sgn_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_signal_windows_cosine_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_signal_windows_exponential_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_signal_windows_gaussian_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sparse_mm_reduce_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_bessel_j1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_bessel_y0_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_erfcx_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_hermite_polynomial_h_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_polygamma_special_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_scaled_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_scaled_modified_bessel_k1_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_special_spherical_bessel_j0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_split_with_sizes_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sqrt_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_square_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_squeeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_squeeze_multiple_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_stack_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_std_mean_unbiased_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_sum_to_size_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_svd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_tensor_split_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_to_sparse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_to_sparse_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_topk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_trace_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_transpose_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_transpose_copy_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unbind_copy_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unflatten_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unfold_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_uniform_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unique_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unsafe_split_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_unsqueeze_copy_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_var_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_var_mean_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_var_unbiased_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_view_as_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_where_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_xlogy_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_zeros_cuda_float64, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmap_autograd_grad_zeros_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_H_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_SortGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_T_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall___rmul___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall__unsafe_masked_index_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_addmm_decomposed_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_alias_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_aminmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_argmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_as_strided_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_as_strided_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_as_strided_partial_views_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_atanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_block_diag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_broadcast_shapes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_broadcast_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_cat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_cdouble_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_char_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_cholesky_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_cholesky_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_clamp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_combinations_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_conj_physical_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_cov_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_diagonal_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_digamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_div_floor_rounding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_einsum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_erf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_expand_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule_NumpySortAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule___getitem___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule___getitem___functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule___rmul___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule__native_batch_norm_legit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_has_batch_rule_all_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_int_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_isclose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_isin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_isreal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_item_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_le_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_cholesky_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_eigh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_inv_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_ldl_factor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_ldl_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_pinv_singular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_slogdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_tensorsolve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_linalg_vecdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_log10_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_log_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_logdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_logical_and_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_long_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_mT_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_masked_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_masked_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_masked_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_masked_log_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_masked_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_matrix_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_max_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_min_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_minimum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_movedim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_mv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nanmean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nanmedian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nanquantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_narrow_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_narrow_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_native_dropout_backward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_ne_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_adaptive_avg_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_adaptive_avg_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_conv2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_conv2d_stride_depthwise_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_conv2d_stride_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_conv2d_strided_padding_dilation_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_cosine_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_dropout3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_embedding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_fractional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_gelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_hardshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_interpolate_area_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_interpolate_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_interpolate_linear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_interpolate_nearest-exact_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_max_unpool2d_grad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_multi_head_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_pad_replicate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_pad_replicate_negative_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_pairwise_distance_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_poisson_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_rrelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_selu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_silu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_nn_functional_upsample_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_norm_nuc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_normal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_ones_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_ormqr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_pinverse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_polygamma_polygamma_n_2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_positive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_rad2deg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_remainder_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_reshape_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_roll_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_rot90_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_round_decimals_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_round_decimals_neg_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_scatter_reduce_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_scatter_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_scatter_reduce_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_searchsorted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sgn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_short_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_signal_windows_blackman_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_signal_windows_general_cosine_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_signal_windows_general_hamming_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_signal_windows_hann_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_signbit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_softmax_with_dtype_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_bessel_j1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_hermite_polynomial_h_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_laguerre_polynomial_l_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_log_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_modified_bessel_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_polygamma_special_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_special_shifted_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_split_list_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_split_with_sizes_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_split_with_sizes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_squeeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_stack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_sum_to_size_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_t_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_tanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_tensordot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_topk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_transpose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_triu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_unflatten_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_unfold_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_unsafe_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_unsqueeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_view_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpall_zeros_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_SelectAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_SortGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_T_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp___getitem___functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp__batch_norm_with_update_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp__upsample_bilinear2d_aa_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_acos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_addmv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_alias_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_allclose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_angle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_any_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_as_strided_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_as_strided_partial_views_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_atan_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_atanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_baddbmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_bfloat16_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_bmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_byte_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_cat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_cos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_double_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_dstack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_empty_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_equal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_expand_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fft_fft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fft_ihfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fft_ihfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fft_rfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fft_rfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_fliplr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_floor_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_gather_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_grid_sampler_3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_igamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_index_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_le_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_lerp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_lgamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_det_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_eigh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_lu_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_matrix_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_multi_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_norm_subgradients_at_zero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_pinv_singular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_slogdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_linalg_vecdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_logaddexp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_logaddexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_mH_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_masked_argmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_masked_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_masked_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_max_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_maximum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_meshgrid_list_of_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_mode_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_multinomial_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nanmean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_native_layer_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_adaptive_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_alpha_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_avg_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_batch_norm_without_cudnn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_conv2d_stride_groups_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_conv2d_stride_padding_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_conv2d_stride_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_cosine_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_dropout3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_embedding_bag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_margin_ranking_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_max_unpool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_pad_constant_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_scaled_dot_product_attention_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_smooth_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_softshrink_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_threshold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nn_functional_upsample_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_nonzero_static_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_ormqr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_polar_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_quantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_ravel_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_renorm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_repeat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_resize__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_resize_as__cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_resolve_neg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_rot90_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_round_decimals_neg_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_rsub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_searchsorted_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_signal_windows_bartlett_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_signal_windows_hamming_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_signal_windows_hann_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_signbit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_sort_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_sparse_sampled_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_i0e_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_legendre_polynomial_p_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_modified_bessel_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_modified_bessel_k0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_ndtri_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_polygamma_special_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_shifted_chebyshev_polynomial_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_special_xlog1py_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_split_list_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_split_with_sizes_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_t_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_tan_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_tanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_torch_ops_aten__safe_softmax_default_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_trapezoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_unique_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvjp_unsqueeze_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvmap_NumpyExpMarkDirtyAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvmap_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapjvpvmap_SelectAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_H_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_ScaleGradGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp___rmatmul___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp__unsafe_masked_index_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_alias_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_all_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_angle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_argwhere_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_as_strided_partial_views_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_asin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_asinh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_atanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_bfloat16_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_broadcast_shapes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_broadcast_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_byte_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_chunk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_clamp_max_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_column_stack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_count_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_cumprod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_diagflat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_diagonal_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_dot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_double_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_einsum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_empty_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_erf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_expand_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_eye_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_fft_fft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_fft_hfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_fft_irfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_fft_rfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_floor_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_frexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_gradient_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_gt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_half_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_NumpyMulAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_NumpyTakeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule__chunk_cat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule__segment_reduce_offsets_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule__softmax_backward_data_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule__upsample_bilinear2d_aa_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_addcdiv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_addr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_as_strided_partial_views_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_as_strided_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_asin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_block_diag_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_bool_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_broadcast_shapes_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_broadcast_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_bucketize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_ceil_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_char_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_chunk_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_clamp_max_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_combinations_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_conj_physical_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_cos_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_diagonal_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_div_floor_rounding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_dsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_erf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_erfc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_erfinv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_eye_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_fft_hfft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_fft_hfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_full_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_index_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_index_reduce_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_isclose_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_isinf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_isneginf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_jiterator_unary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_ldexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_lerp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_cholesky_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_cond_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_det_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_eigvalsh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_lstsq_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_norm_subgradients_at_zero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_pinv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_pinv_hermitian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_solve_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_solve_triangular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_linalg_svdvals_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_log10_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_logaddexp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_logical_and_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_logit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_logspace_cuda_float32, 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test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_conv1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_conv2d_stride_padding_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_conv2d_strided_padding_dilation_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_conv2d_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_cosine_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_cosine_similarity_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_dropout3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_embedding_functorch_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_fractional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_grid_sample_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_hardsigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_huber_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_instance_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_interpolate_bicubic_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_interpolate_trilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_linear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_logsigmoid_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_max_unpool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_max_unpool3d_grad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_mish_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_multi_head_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_multi_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_pad_constant_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_pad_reflect_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_pad_replicate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_pairwise_distance_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_rrelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_selu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nn_functional_softplus_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_ormqr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_polygamma_polygamma_n_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_quantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_rad2deg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_randint_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_reciprocal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_round_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_round_decimals_0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_round_decimals_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_rsub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_scatter_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_scatter_reduce_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_select_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_sgn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_sign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_signal_windows_gaussian_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_signal_windows_kaiser_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_signbit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_sparse_sampled_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_bessel_y0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_modified_bessel_i1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_ndtri_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_scaled_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_shifted_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_split_list_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_squeeze_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_stack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_std_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_sum_to_size_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_t_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_take_along_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_tan_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_triangular_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_triu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_trunc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_vstack_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_has_batch_rule_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_hash_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_heaviside_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_histc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_hsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_igamma_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_index_reduce_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_index_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_int_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_isneginf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_jiterator_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_kron_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_eigvals_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_eigvalsh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_householder_product_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_ldl_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_matrix_rank_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linalg_slogdet_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_linspace_tensor_overload_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_logcumsumexp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_logical_not_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_logical_xor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_lt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_lu_solve_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_mT_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_log_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_median_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_masked_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_matmul_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_meshgrid_list_of_tensors_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_min_reduction_with_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_msort_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_multinomial_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_mvlgamma_mvlgamma_p_5_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nan_to_num_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nansum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_narrow_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_adaptive_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_alpha_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_binary_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_conv2d_stride_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_conv2d_strided_padding_dilation_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_conv_transpose2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_embedding_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_fractional_max_pool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_gaussian_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_hinge_embedding_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_interpolate_nearest-exact_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_layer_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_local_response_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_margin_ranking_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_max_pool1d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_max_unpool1d_grad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_pad_replicate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_pixel_shuffle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_rms_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_smooth_l1_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_soft_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_softplus_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_softsign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_nn_functional_upsample_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_norm_fro_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_normal_number_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_pca_lowrank_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_quantile_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_randn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_randn_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_ravel_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_remainder_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_repeat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_repeat_interleave_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_reshape_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_reshape_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_resolve_conj_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_rot90_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_round_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_rsub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_scatter_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_scatter_reduce_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_scatter_reduce_sum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_short_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_sign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_signal_windows_hann_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_slice_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_sort_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_sparse_sampled_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_bessel_j0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_bessel_j1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_legendre_polynomial_p_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_modified_bessel_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_modified_bessel_i1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_shifted_chebyshev_polynomial_u_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_shifted_chebyshev_polynomial_v_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_shifted_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_special_spherical_bessel_j0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_sub_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_svd_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_take_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_tensor_split_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_to_sparse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_torch_ops_aten__efficient_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_true_divide_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_trunc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_unflatten_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_unfold_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_uniform_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_unique_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_var_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_var_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_view_as_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_where_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjp_zeros_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_CubeGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_MulGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_NumpyCubeAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_SelectGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp___getitem___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp___radd___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp___rsub___cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp__unsafe_masked_index_put_accumulate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_acosh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_add_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_addcmul_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_addmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_addmv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_all_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_amax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_amin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_angle_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_any_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_argmin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_atleast_2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_bmm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_bool_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_bool_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_broadcast_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_byte_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_ceil_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_char_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_combinations_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_contiguous_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_corrcoef_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_cov_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_cummin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_deg2rad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_diagflat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_diagonal_copy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_diagonal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_diff_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_div_no_rounding_mode_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_equal_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_erf_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_erfc_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_exp2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_fft_ifft2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_fft_ifft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_fft_ihfft_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_fft_ihfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_fft_rfftn_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_flip_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_float_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_float_power_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_gather_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_ge_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_grid_sampler_3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_half_functorch_no_channels_last_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_heaviside_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_hsplit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_hypot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_i0_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_igammac_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_index_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_index_reduce_mean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_jiterator_4inputs_with_extra_args_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_cholesky_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_cross_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_eigh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_inv_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_inv_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_ldl_factor_ex_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_lstsq_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_lu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_matrix_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_linalg_solve_triangular_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_log10_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_log2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_log_softmax_with_dtype_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_mH_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_fill_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_normalize_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_prod_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_select_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_softmax_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_masked_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_matmul_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_matrix_exp_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_min_binary_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_min_reduction_no_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_minimum_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_mm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_movedim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_mvlgamma_mvlgamma_p_1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nan_to_num_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nanmean_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_ne_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_neg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_new_empty_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_new_full_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nextafter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_adaptive_max_pool3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_binary_cross_entropy_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_conv2d_no_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_conv2d_with_bias_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_dropout2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_dropout3d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_dropout_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_gaussian_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_grid_sample_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_hardtanh_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_interpolate_bilinear_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_layer_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_margin_ranking_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_max_unpool1d_grad_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_max_unpool2d_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_mse_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_multilabel_soft_margin_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_pad_replicate_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_pdist_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_poisson_nll_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_rms_norm_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_rrelu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_selu_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nonzero_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_nonzero_static_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_permute_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_polygamma_polygamma_n_2_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_polygamma_polygamma_n_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_put_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_qr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_rad2deg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_randint_like_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_repeat_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_resolve_neg_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_roll_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_round_decimals_neg_3_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_scalar_tensor_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_select_scatter_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_sign_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_signal_windows_bartlett_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_signal_windows_exponential_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_signbit_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_sin_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_slice_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_softmax_with_dtype_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_sparse_mm_reduce_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_bessel_j1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_entr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_erfcx_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_i1e_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_modified_bessel_k1_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_ndtr_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_shifted_chebyshev_polynomial_w_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_special_xlog1py_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_sqrt_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_square_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_take_along_dim_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_tan_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_to_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_to_sparse_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_torch_ops_aten__efficient_attention_forward_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_trapz_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_unflatten_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_unique_consecutive_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_var_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_var_mean_unbiased_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvjp_vdot_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvmap_ForwardHasDefaultArgsAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvmap_MulGenVmapAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvmap_NumpyCubeNotComposableAutogradFunction_cuda_float32, test/functorch/test_ops.py::TestOperatorsCUDA::test_vmapvjpvmap_ZeroGradientsGenVmapAutogradFunction_cuda_float32 2025-08-26T22:02:34.7029484Z 2025-08-26T22:02:34.7034847Z Running test_decomp 5/12 ... [2025-08-26 22:02:34.640790] 2025-08-26T22:02:34.7035114Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:02:34.7035492Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_decomp.py', '--shard-id=5', '--num-shards=12', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:02:34.640977] 2025-08-26T22:13:23.1695297Z 2025-08-26T22:13:23.1696558Z test_decomp 5/12 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_5.12_d84db3bb4330530a_.log 2025-08-26T22:13:23.1779828Z Running 800 items in this shard: test/test_decomp.py::TestDecompCUDA::test_comprehensive_T_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rand___cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rdiv___cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rdiv___cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rmod___cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rmul___cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rmul___cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rpow___cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rpow___cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rpow___cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive__chunk_cat_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive__segment_reduce_lengths_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive__unsafe_masked_index_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive__unsafe_masked_index_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acos_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acos_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_add_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_add_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addbmm_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addcdiv_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addmm_decomposed_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addr_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addr_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addr_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_alias_copy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_all_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_all_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_amax_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_amax_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_aminmax_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_any_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_any_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_argmin_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_argsort_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_argsort_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_copy_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_partial_views_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_scatter_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_asin_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_asin_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atan2_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atan_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atanh_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atanh_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_1d_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_1d_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_1d_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bincount_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_and_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_and_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_left_shift_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_or_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_or_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_right_shift_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_xor_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_block_diag_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bmm_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bool_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_broadcast_shapes_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_broadcast_to_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_broadcast_to_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_broadcast_to_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_broadcast_to_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_byte_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_byte_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_byte_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cat_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_ceil_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_chalf_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_char_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_char_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_max_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clone_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clone_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clone_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clone_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_column_stack_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_column_stack_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_column_stack_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_combinations_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_combinations_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_combinations_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_conj_physical_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_conj_physical_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_contiguous_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_contiguous_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_copysign_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cos_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cos_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cosh_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cosh_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_count_nonzero_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_count_nonzero_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_count_nonzero_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cov_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cummax_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cummin_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cummin_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumprod_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumprod_cuda_int32, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_fftn_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_fftn_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfftn_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifft_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifftn_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ihfft2_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ihfft_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfft2_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfft_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfftn_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfftn_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_rfft_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_rfftn_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fill_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_flatten_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_flip_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_flip_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fliplr_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fliplr_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_float_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fmax_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_frexp_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_full_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_full_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_full_like_cuda_float16, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_amax_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_amax_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_mean_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_mean_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_prod_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isclose_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isfinite_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isinf_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isinf_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isinf_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isnan_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isneginf_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isreal_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_istft_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_item_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_item_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_4inputs_with_extra_args_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_4inputs_with_extra_args_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_binary_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_binary_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_binary_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_binary_return_by_ref_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_binary_return_by_ref_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_unary_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_jiterator_unary_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_kthvalue_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_kthvalue_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_ldexp_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_le_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_le_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_lerp_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_lgamma_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_cholesky_ex_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_cross_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_diagonal_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_eigh_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_eigh_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_eigvalsh_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_inv_ex_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_ldl_factor_ex_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_lu_factor_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_matrix_rank_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_multi_dot_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_norm_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_norm_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_pinv_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_pinv_singular_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_slogdet_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_solve_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vander_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vander_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vecdot_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vector_norm_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vector_norm_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linspace_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linspace_tensor_overload_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log10_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log1p_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log1p_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logdet_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_or_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_or_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logit_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logspace_tensor_overload_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_long_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_long_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_lt_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_lt_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_mH_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_mH_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_mT_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_mT_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_amax_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_amax_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_argmax_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_argmax_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_cumprod_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_fill_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_logsumexp_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_logsumexp_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_mean_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_prod_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_prod_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_scatter_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_select_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_softmin_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_std_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_sum_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_masked_sum_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_matrix_exp_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_pool2d_with_indices_backward_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_reduction_no_dim_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_reduction_no_dim_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_reduction_no_dim_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_reduction_with_dim_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_max_reduction_with_dim_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_maximum_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_median_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_median_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_meshgrid_variadic_tensors_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_min_binary_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_min_reduction_with_dim_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_minimum_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_minimum_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_mode_cuda_float64, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_narrow_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_narrow_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_narrow_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_neg_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_neg_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_empty_strided_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_full_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_full_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_ones_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_zeros_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_zeros_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_new_zeros_cuda_uint8, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_t_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_v_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_v_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_w_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_entr_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_entr_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_hermite_polynomial_he_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1e_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_legendre_polynomial_p_cuda_int8, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_tanh_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tanh_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tanh_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tensor_split_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tensor_split_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tile_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_sparse_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_sparse_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_sparse_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_sparse_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_torch_ops_aten__safe_softmax_default_cuda_float32, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_unsqueeze_copy_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_unsqueeze_copy_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_var_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_var_mean_unbiased_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_var_unbiased_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_view_as_complex_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_view_as_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_view_as_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_view_copy_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_where_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_zero__cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_zeros_cuda_bool, 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test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_1_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_3_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_nan_to_num_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_nan_to_num_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_narrow_copy_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_native_layer_norm_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_ne_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_new_full_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_new_full_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_binary_cross_entropy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_binary_cross_entropy_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_glu_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_hardshrink_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_hardshrink_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_hardtanh_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_max_unpool3d_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_mish_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_mse_loss_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_pad_constant_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_pad_constant_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_prelu_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_silu_cuda_float32, 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test/test_decomp.py::TestDecompCUDA::test_quick_sinh_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_sinh_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_sinh_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_slice_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_slice_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_slice_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_special_erfcx_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_special_log_ndtr_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_special_log_ndtr_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_special_ndtri_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_special_ndtri_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_special_xlog1py_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_special_xlog1py_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_special_xlog1py_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_special_xlog1py_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_special_zeta_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_split_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_split_list_args_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_copy_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_sqrt_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_sqrt_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_squeeze_multiple_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_std_mean_unbiased_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_sum_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_sum_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_t_copy_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_t_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_t_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_t_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_take_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_take_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_tanh_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_trace_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_transpose_copy_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_triu_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_triu_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_triu_indices_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_trunc_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_copy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_copy_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_copy_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_unfold_copy_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_unfold_copy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_unfold_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_unfold_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_unsafe_split_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_var_mean_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_var_mean_unbiased_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_where_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_xlogy_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_zero__cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_zero__cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_zeros_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_zeros_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_rnn_decomp_module_nn_RNN_train_mode_cuda_float64, test/test_decomp.py::DecompOneOffTestsCUDA::test_contiguous_log_softmax_cuda 2025-08-26T22:13:23.1859879Z 2025-08-26T22:13:23.1859984Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T22:13:23.1860173Z Uploading artifacts took 0.00 seconds 2025-08-26T22:13:23.1860331Z Running test_decomp 11/12 ... [2025-08-26 22:13:23.169868] 2025-08-26T22:13:23.1860591Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:13:23.1860955Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_decomp.py', '--shard-id=11', '--num-shards=12', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:13:23.170123] 2025-08-26T22:23:57.8151067Z 2025-08-26T22:23:57.8152064Z test_decomp 11/12 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_11.12_69a9c896c8860ef3_.log 2025-08-26T22:23:57.8265377Z Running 709 items in this shard: test/test_decomp.py::TestDecompCUDA::test_cat_single_input_cuda, test/test_decomp.py::TestDecompCUDA::test_comprehensive_T_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive___getitem___cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive___radd___cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive___radd___cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rand___cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rdiv___cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rdiv___cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rpow___cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rsub___cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rsub___cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rxor___cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive___rxor___cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive__native_batch_norm_legit_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive__segment_reduce_offsets_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive__unsafe_masked_index_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive__unsafe_masked_index_put_accumulate_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive__unsafe_masked_index_put_accumulate_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_abs_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acos_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acosh_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acosh_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acosh_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_acosh_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_add_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addbmm_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addcmul_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_addr_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_alias_copy_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_argmax_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_argsort_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_as_strided_copy_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_asin_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_asinh_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atan_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atan_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atanh_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atanh_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_1d_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_1d_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_atleast_2d_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bfloat16_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bfloat16_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_xor_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_bitwise_xor_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_block_diag_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cat_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cdist_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cdist_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cfloat_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_char_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_char_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cholesky_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_max_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clamp_min_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_clone_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_conj_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_conj_physical_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_corrcoef_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cos_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cos_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_count_nonzero_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_count_nonzero_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cov_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cummax_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumprod_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumprod_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumsum_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_cumulative_trapezoid_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diag_embed_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diag_embed_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diagflat_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diagonal_copy_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diagonal_copy_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diagonal_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diagonal_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_diff_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_digamma_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_dist_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_div_floor_rounding_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_div_no_rounding_mode_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_double_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_dstack_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_einsum_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_empty_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_empty_permuted_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_empty_permuted_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_eq_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_eq_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_equal_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_erfc_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_erfc_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_erfinv_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_exp2_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_exp2_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_exp2_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_exp_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_exp_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_expand_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_expand_copy_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_expm1_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_expm1_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfft_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfftn_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfftn_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfftn_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_hfftn_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifft2_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifft_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifftn_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifftn_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifftshift_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ifftshift_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ihfft2_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ihfft_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_ihfft_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfft2_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_irfft_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_rfft_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_rfftn_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fft_rfftn_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fill_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fill_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_flip_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_flip_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_fliplr_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_float_cuda_float16, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_copy_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_fill_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_fill_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_fill_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_reduce_amax_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_select_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_select_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_index_select_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_inner_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_int_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isclose_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_isfinite_cuda_bool, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_norm_subgradients_at_zero_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_qr_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_solve_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_solve_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_solve_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_solve_ex_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_svdvals_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_svdvals_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vander_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vecdot_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vector_norm_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linalg_vector_norm_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linspace_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_linspace_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log10_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_log_normal_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logaddexp2_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logaddexp_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_and_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_and_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_not_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_logical_not_cuda_int8, 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test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_layer_norm_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_leaky_relu_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_margin_ranking_loss_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_margin_ranking_loss_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_max_unpool1d_grad_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_max_unpool3d_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_normalize_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pad_circular_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pad_constant_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pad_constant_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pad_replicate_negative_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pairwise_distance_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pdist_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pixel_unshuffle_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_pixel_unshuffle_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_relu6_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_relu_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_relu_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_rms_norm_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_rms_norm_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_rrelu_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_silu_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_soft_margin_loss_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_soft_margin_loss_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_softmin_with_dtype_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_softmin_with_dtype_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_softmin_with_dtype_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_softshrink_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_softsign_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_tanhshrink_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_triplet_margin_loss_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_unfold_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nn_functional_unfold_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nonzero_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nonzero_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_nonzero_static_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_norm_inf_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_norm_nuc_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_norm_nuc_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_normal_in_place_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_normal_number_mean_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_outer_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polar_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_0_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_0_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_1_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_1_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_1_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_2_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_2_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_3_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_4_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_polygamma_polygamma_n_4_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_pow_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_pow_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_pow_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_prod_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_prod_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_qr_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rad2deg_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_randint_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_randn_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_ravel_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_ravel_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_ravel_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_reciprocal_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_repeat_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_repeat_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_repeat_interleave_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_reshape_as_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_reshape_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resize__cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resize__cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resolve_conj_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resolve_conj_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resolve_neg_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_resolve_neg_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rot90_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rsqrt_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rsqrt_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rsqrt_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rsub_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_rsub_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scalar_tensor_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scalar_tensor_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scatter_add_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scatter_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scatter_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scatter_reduce_amin_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_scatter_reduce_sum_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sigmoid_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sign_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_signal_windows_blackman_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_signal_windows_cosine_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_signal_windows_exponential_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_signal_windows_kaiser_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_signbit_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sinc_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sinh_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sinh_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_slice_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_softmax_with_dtype_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sparse_sampled_addmm_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_airy_ai_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_airy_ai_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_bessel_j1_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_bessel_y1_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_t_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_t_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_chebyshev_polynomial_u_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_entr_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_entr_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_erfcx_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_hermite_polynomial_he_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1e_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1e_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_i1e_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_laguerre_polynomial_l_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_log_ndtr_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_modified_bessel_k1_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_ndtr_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_ndtri_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_scaled_modified_bessel_k0_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_scaled_modified_bessel_k1_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_scaled_modified_bessel_k1_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_t_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_u_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_special_shifted_chebyshev_polynomial_w_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_list_args_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_list_args_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_list_args_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_with_sizes_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_with_sizes_copy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_with_sizes_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_split_with_sizes_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_squeeze_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_squeeze_multiple_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_stack_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_stack_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_std_mean_unbiased_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_stft_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sub_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_sum_to_size_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_t_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_t_copy_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_take_along_dim_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_take_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_take_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tan_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tan_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tanh_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tensor_split_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tensordot_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tile_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_to_sparse_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_torch__scaled_mm_cuda_float8_e4m3fn, test/test_decomp.py::TestDecompCUDA::test_comprehensive_trace_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_comprehensive_transpose_copy_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_trapezoid_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_trapezoid_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_comprehensive_triangular_solve_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tril_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_tril_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_comprehensive_true_divide_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_comprehensive_trunc_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_comprehensive_unbind_copy_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_comprehensive_unfold_copy_cuda_int64, 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test/test_decomp.py::TestDecompCUDA::test_quick_expand_copy_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_expand_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_expand_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_expm1_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_expm1_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_expm1_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_eye_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_fft2_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_fft_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_fftn_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft2_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft2_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft2_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfft_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_fft_hfftn_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ifft2_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ifft2_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ifftn_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ihfft2_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ihfft_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ihfft_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_fft_ihfftn_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_irfft2_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_fft_irfft_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_fft_irfftn_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_fft_rfft2_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_fft_rfft_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_fft_rfftn_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_flip_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_floor_divide_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_fmin_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_fmod_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_full_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_ge_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_geometric_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_heaviside_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_igammac_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_index_add_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_index_copy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_index_fill_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_index_fill_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_isin_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_isinf_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_isinf_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_isinf_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_isnan_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_isneginf_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_isneginf_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_isposinf_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_linalg_cross_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_linalg_diagonal_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_linalg_diagonal_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_log2_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_log_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_logical_and_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_logical_or_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_logical_xor_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_logical_xor_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_logit_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_logspace_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_logspace_tensor_overload_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_lt_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_masked_fill_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_masked_fill_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_maximum_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_meshgrid_list_of_tensors_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_meshgrid_variadic_tensors_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_minimum_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_1_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_5_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_5_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_mvlgamma_mvlgamma_p_5_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_nan_to_num_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_nan_to_num_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nan_to_num_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_narrow_copy_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_narrow_copy_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_neg_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_new_empty_strided_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_new_full_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_new_full_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_new_zeros_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nextafter_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nextafter_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_elu_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_gelu_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_hardsigmoid_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_hardtanh_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_huber_loss_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_huber_loss_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_leaky_relu_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_max_unpool2d_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_rrelu_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_silu_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_softplus_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_nn_functional_unfold_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_norm_inf_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_norm_inf_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_normal_number_mean_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_ones_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_permute_copy_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_permute_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_pow_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_pow_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_randn_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_randn_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_randn_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_reciprocal_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_renorm_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_repeat_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_repeat_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_round_decimals_neg_3_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_rsqrt_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_rsqrt_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_select_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_select_scatter_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_sgn_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_sgn_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_sgn_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_sigmoid_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_sigmoid_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_sign_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_signbit_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_sin_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_sinc_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_sinh_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_slice_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_slice_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_softmax_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_special_entr_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_special_entr_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_special_erfcx_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_special_i0e_cuda_int16, test/test_decomp.py::TestDecompCUDA::test_quick_special_i0e_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_special_i1_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_special_i1_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_special_i1e_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_special_i1e_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_special_ndtri_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_split_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_split_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_split_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_split_list_args_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_split_list_args_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_copy_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_copy_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_split_with_sizes_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_sqrt_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_squeeze_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_squeeze_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_squeeze_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_squeeze_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_stack_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_std_mean_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_sub_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_sub_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_sub_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_sum_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_t_copy_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_t_copy_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_t_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_t_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_take_cuda_uint8, test/test_decomp.py::TestDecompCUDA::test_quick_tan_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_tanh_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_trace_cuda_bool, test/test_decomp.py::TestDecompCUDA::test_quick_transpose_copy_cuda_complex64, test/test_decomp.py::TestDecompCUDA::test_quick_transpose_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_tril_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_triu_cuda_complex32, test/test_decomp.py::TestDecompCUDA::test_quick_trunc_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_cuda_int64, test/test_decomp.py::TestDecompCUDA::test_quick_unbind_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_unfold_copy_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_unsqueeze_cuda_int32, test/test_decomp.py::TestDecompCUDA::test_quick_var_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_quick_var_cuda_float64, test/test_decomp.py::TestDecompCUDA::test_quick_var_mean_cuda_complex128, test/test_decomp.py::TestDecompCUDA::test_quick_var_mean_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_view_copy_cuda_float16, test/test_decomp.py::TestDecompCUDA::test_quick_view_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_xlogy_cuda_float32, test/test_decomp.py::TestDecompCUDA::test_quick_xlogy_cuda_int8, test/test_decomp.py::TestDecompCUDA::test_quick_zeros_like_cuda_bfloat16, test/test_decomp.py::TestDecompCUDA::test_rnn_decomp_module_nn_LSTM_eval_mode_cuda_float64, test/test_decomp.py::HasDecompTest::test_aten_core_operators 2025-08-26T22:23:57.8375543Z 2025-08-26T22:23:57.8375649Z Running test_type_hints 1/1 ... [2025-08-26 22:23:57.811692] 2025-08-26T22:23:57.8375867Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:23:57.8376389Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_type_hints.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:23:57.811943] 2025-08-26T22:24:00.7621188Z 2025-08-26T22:24:00.7622204Z test_type_hints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_hints_1.1_d442a8bb9dca508f_.log 2025-08-26T22:24:00.7629022Z Running 1 items in this shard: test/test_type_hints.py::TestTypeHints::test_doc_examples 2025-08-26T22:24:00.7629189Z 2025-08-26T22:24:00.7629288Z Running test_modules 1/1 ... [2025-08-26 22:24:00.758718] 2025-08-26T22:24:00.7629542Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:24:00.7629941Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_modules.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:24:00.758905] 2025-08-26T22:40:21.7881603Z 2025-08-26T22:40:21.7882410Z test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.1_c51a141d77325dd4_.log 2025-08-26T22:40:21.8315250Z Running 3605 items in this shard: test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_check_inplace_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_cpu_gpu_parity_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_device_ctx_init_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_errors_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_factory_kwargs_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_forward_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_forward_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_forward_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_forward_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_grad_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_gradgrad_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GRU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GRU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LSTM_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LSTM_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RNN_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_RNN_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_memory_format_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_multiple_device_transfer_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cuda_float64, 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test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_cuda_float64, 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test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_LazyConv1d_cuda_float64, 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test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ReLU_cuda_float32, 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test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_non_contiguous_tensors_nn_ZeroPad3d_cuda_float64, 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test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_repr_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_repr_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_repr_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_repr_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveAvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AdaptiveMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_AvgPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BCELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BCELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BCEWithLogitsLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BCEWithLogitsLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_BatchNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Bilinear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Bilinear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CTCLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CTCLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CircularPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConstantPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Conv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose1d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose1d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose1d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose2d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose2d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose2d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose3d_cuda_complex128, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose3d_cuda_complex32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose3d_cuda_complex64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CosineEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CosineEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CrossEntropyLoss_cuda_float16, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CrossEntropyLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_CrossEntropyLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Embedding_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Embedding_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_FractionalMaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_FractionalMaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_FractionalMaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_FractionalMaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRUCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRUCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRU_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRU_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRU_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GRU_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GaussianNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GaussianNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GroupNorm_cuda_bfloat16, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GroupNorm_cuda_float16, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GroupNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_GroupNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardswish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardswish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardtanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Hardtanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_HingeEmbeddingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_HingeEmbeddingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_HuberLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_HuberLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm1d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm1d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm1d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm1d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm2d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm2d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm2d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm2d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm3d_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm3d_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm3d_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_InstanceNorm3d_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_KLDivLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_KLDivLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_L1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_L1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LPPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTMCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTMCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTM_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTM_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTM_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LSTM_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LayerNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LayerNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConv3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LazyConvTranspose3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LeakyReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LeakyReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Linear_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Linear_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LocalResponseNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LocalResponseNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LogSigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LogSigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LogSoftmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_LogSoftmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MSELoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MSELoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MarginRankingLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MarginRankingLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MaxPool3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Mish_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Mish_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiLabelMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiLabelMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiLabelSoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiLabelSoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiheadAttention_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiheadAttention_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiheadAttention_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_MultiheadAttention_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_NLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_NLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_PReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_PReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_PoissonNLLLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_PoissonNLLLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RMSNorm_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RMSNorm_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNNCell_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNNCell_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNN_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNN_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNN_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_RNN_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReLU6_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReLU6_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReflectionPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ReplicationPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SELU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SELU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SiLU_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SiLU_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Sigmoid_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Sigmoid_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SmoothL1Loss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SmoothL1Loss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SoftMarginLoss_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_SoftMarginLoss_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmax2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmax2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmax_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmax_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmin_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softmin_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softplus_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softplus_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softsign_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Softsign_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Tanh_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Tanh_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Tanhshrink_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Tanhshrink_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Threshold_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Threshold_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerDecoderLayer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerDecoderLayer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoderLayer_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoderLayer_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoderLayer_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoderLayer_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoder_eval_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoder_eval_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoder_train_mode_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_TransformerEncoder_train_mode_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Transformer_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_Transformer_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad1d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad1d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad2d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad2d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad3d_cuda_float32, test/test_modules.py::TestModuleCUDA::test_save_load_nn_ZeroPad3d_cuda_float64, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveAvgPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AdaptiveMaxPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_AvgPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BCELoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BCELoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BCEWithLogitsLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BCEWithLogitsLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm1d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm1d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm1d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm1d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm2d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm2d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm2d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm2d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm3d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm3d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm3d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_BatchNorm3d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Bilinear_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Bilinear_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CELU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CELU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CTCLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CTCLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CircularPad3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConstantPad3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Conv3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ConvTranspose3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CosineEmbeddingLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CosineEmbeddingLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CrossEntropyLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_CrossEntropyLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ELU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ELU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Embedding_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Embedding_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_FractionalMaxPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_FractionalMaxPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_FractionalMaxPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_FractionalMaxPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GELU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GELU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GLU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GLU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRUCell_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRUCell_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRU_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRU_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRU_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GRU_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GaussianNLLLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GaussianNLLLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GroupNorm_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_GroupNorm_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardshrink_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardshrink_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardswish_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardswish_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardtanh_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Hardtanh_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_HingeEmbeddingLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_HingeEmbeddingLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_HuberLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_HuberLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm1d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm1d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm2d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm2d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm3d_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_InstanceNorm3d_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_KLDivLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_KLDivLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_L1Loss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_L1Loss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LPPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTMCell_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTMCell_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTM_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTM_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTM_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LSTM_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LayerNorm_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LayerNorm_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LeakyReLU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LeakyReLU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Linear_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Linear_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LocalResponseNorm_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LocalResponseNorm_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LogSigmoid_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LogSigmoid_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LogSoftmax_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_LogSoftmax_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MSELoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MSELoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MarginRankingLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MarginRankingLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MaxPool3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Mish_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Mish_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiLabelMarginLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiLabelMarginLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiMarginLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiMarginLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiheadAttention_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiheadAttention_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiheadAttention_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_MultiheadAttention_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_NLLLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_NLLLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_PReLU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_PReLU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_PoissonNLLLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_PoissonNLLLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RMSNorm_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RMSNorm_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNNCell_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNNCell_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNN_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNN_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNN_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_RNN_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReLU6_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReLU6_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReLU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReLU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReflectionPad3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ReplicationPad3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SELU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SELU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SiLU_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SiLU_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Sigmoid_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Sigmoid_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SmoothL1Loss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SmoothL1Loss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SoftMarginLoss_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_SoftMarginLoss_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmax2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmax2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmax_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmax_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmin_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softmin_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softplus_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softplus_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softshrink_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softshrink_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softsign_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Softsign_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Tanh_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Tanh_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Tanhshrink_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Tanhshrink_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Threshold_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Threshold_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerDecoderLayer_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerDecoderLayer_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoder_eval_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoder_eval_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoder_train_mode_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_TransformerEncoder_train_mode_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Transformer_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_Transformer_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad1d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad1d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad2d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad2d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad3d_swap_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_empty_nn_ZeroPad3d_swap_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_AvgPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCELoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCELoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCELoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCELoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Bilinear_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Bilinear_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Bilinear_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Bilinear_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CELU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CELU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CELU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CELU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CTCLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CTCLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CTCLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CTCLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CircularPad3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConstantPad3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Conv3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ConvTranspose3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CrossEntropyLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CrossEntropyLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CrossEntropyLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_CrossEntropyLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ELU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ELU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ELU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ELU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Embedding_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Embedding_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Embedding_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Embedding_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GELU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GELU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GELU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GELU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GLU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GLU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GLU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GLU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRUCell_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRUCell_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRUCell_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRUCell_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GRU_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GaussianNLLLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GaussianNLLLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GaussianNLLLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GaussianNLLLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GroupNorm_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GroupNorm_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GroupNorm_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_GroupNorm_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardshrink_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardshrink_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardshrink_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardshrink_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardswish_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardswish_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardswish_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardswish_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardtanh_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardtanh_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardtanh_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Hardtanh_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HuberLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HuberLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HuberLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_HuberLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_KLDivLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_KLDivLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_KLDivLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_KLDivLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_L1Loss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_L1Loss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_L1Loss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_L1Loss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LPPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTMCell_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTMCell_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTMCell_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTMCell_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LSTM_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LayerNorm_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LayerNorm_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LayerNorm_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LayerNorm_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LeakyReLU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LeakyReLU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LeakyReLU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LeakyReLU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Linear_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Linear_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Linear_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Linear_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LocalResponseNorm_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LocalResponseNorm_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LocalResponseNorm_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LocalResponseNorm_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSigmoid_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSigmoid_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSigmoid_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSigmoid_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSoftmax_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSoftmax_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSoftmax_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_LogSoftmax_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MSELoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MSELoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MSELoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MSELoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MarginRankingLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MarginRankingLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MarginRankingLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MarginRankingLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MaxPool3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Mish_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Mish_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Mish_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Mish_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiMarginLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiMarginLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiMarginLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiMarginLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_NLLLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_NLLLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_NLLLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_NLLLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PReLU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PReLU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PReLU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PReLU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PoissonNLLLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PoissonNLLLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PoissonNLLLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_PoissonNLLLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RMSNorm_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RMSNorm_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RMSNorm_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RMSNorm_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNNCell_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNNCell_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNNCell_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNNCell_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_RNN_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU6_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU6_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU6_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU6_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReLU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReflectionPad3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ReplicationPad3d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SELU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SELU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SELU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SELU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SiLU_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SiLU_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SiLU_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SiLU_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Sigmoid_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Sigmoid_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Sigmoid_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Sigmoid_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SmoothL1Loss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SmoothL1Loss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SmoothL1Loss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SmoothL1Loss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SoftMarginLoss_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SoftMarginLoss_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SoftMarginLoss_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_SoftMarginLoss_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmax_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmin_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmin_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmin_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softmin_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softplus_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softplus_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softplus_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softplus_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softshrink_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softshrink_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softshrink_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softshrink_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softsign_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softsign_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softsign_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Softsign_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanh_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanh_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanh_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanh_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanhshrink_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanhshrink_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanhshrink_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Tanhshrink_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Threshold_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Threshold_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Threshold_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Threshold_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Transformer_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Transformer_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Transformer_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_Transformer_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad1d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad1d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad1d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad1d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad2d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad2d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad2d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad2d_swap_True_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad3d_swap_False_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad3d_swap_False_set_grad_True_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad3d_swap_True_set_grad_False_cuda_float32, test/test_modules.py::TestModuleCUDA::test_to_nn_ZeroPad3d_swap_True_set_grad_True_cuda_float32 2025-08-26T22:40:21.8728576Z 2025-08-26T22:40:21.8734223Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T22:40:21.8734440Z Uploading artifacts took 0.00 seconds 2025-08-26T22:40:21.8734629Z Running higher_order_ops/test_invoke_subgraph 1/1 ... [2025-08-26 22:40:21.792044] 2025-08-26T22:40:21.8734818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:40:21.8735237Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'higher_order_ops/test_invoke_subgraph.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:40:21.792231] 2025-08-26T22:40:58.7654846Z 2025-08-26T22:40:58.7655631Z higher_order_ops/test_invoke_subgraph 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_subgraph_1.1_325244131dded4f5_.log 2025-08-26T22:40:58.7665442Z Running 67 items in this shard: test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_aot_function, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_multiple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_simple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac_rng, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac_rng_cudagraphs, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_auto_functionalize, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_autograd_function, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_buffer_mutation_errors_under_training, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_buffer_mutation_works_under_no_grad, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_bwd_partitioning, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_complex, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_const_tensor, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dce, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dedupe, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_different_strides_in_backward, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_different_symint, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_differing_strides_for_grad_outs, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_div, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dropout_checks_joint_graph, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dropout_checks_joint_graph_inference, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dynamic, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_fail_with_direct_invoke_subgraph, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_fake_tensor_checking, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_gen_schema, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_gen_schema_with_buffer_mutation, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_input_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_inference_mode, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_mutiple_times, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_mutiple_times_fake_tensor_cahche_hit, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_output_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_kwargs_only, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_list, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_mod_attr_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module_forward, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_nonlocal_update, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_normalize_gm, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_output_output_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_preserves_output_strides, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_preserves_strides, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_redundant_compile_region, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_return_none, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_return_none_from_fwd, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_sdpa, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_simple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_simple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_symint_from_fwd_to_bwd, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_triton_kernel_native, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_tuple_of_tuple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_unbacked_symbol, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_view_to_reshape, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_multiple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_simple_func, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_simple_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_multiple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_simple_func, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_simple_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::NegativeTesting::test_graph_break 2025-08-26T22:40:58.7674688Z 2025-08-26T22:40:58.7674751Z Running test_fx 1/1 ... [2025-08-26 22:40:58.765434] 2025-08-26T22:40:58.7674899Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T22:40:58.7675297Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 22:40:58.765618] 2025-08-26T23:15:41.0588511Z 2025-08-26T23:15:41.0590231Z PRINTING LOG FILE of test_fx 1/1 (test/test-reports/test_fx_1.1_de6e6b79f446acef_.log) 2025-08-26T23:15:41.0592213Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:15:41.0594287Z import pkg_resources 2025-08-26T23:15:41.0594789Z Test results will be stored in test-reports/python-pytest/test_fx/test_fx-14bd1d64e1668c09.xml 2025-08-26T23:15:41.0595391Z ============================= test session starts ============================== 2025-08-26T23:15:41.0596026Z platform linux -- Python 3.12.11, pytest-7.3.2, pluggy-1.6.0 -- /opt/conda/envs/py_3.12/bin/python 2025-08-26T23:15:41.0603058Z cachedir: .pytest_cache 2025-08-26T23:15:41.0603337Z hypothesis profile 'pytorch_ci' -> database=None, max_examples=50, derandomize=True, suppress_health_check=[HealthCheck.too_slow] 2025-08-26T23:15:41.0603603Z rootdir: /var/lib/jenkins/pytorch 2025-08-26T23:15:41.0603735Z configfile: pytest.ini 2025-08-26T23:15:41.0603987Z plugins: hypothesis-5.35.1, subtests-0.13.1, cpp-2.3.0, flakefinder-1.1.0, rerunfailures-14.0, xdist-3.3.1, xdoctest-1.1.0, typeguard-4.3.0 2025-08-26T23:15:41.0604271Z collecting ... collected 1269 items 2025-08-26T23:15:41.0604479Z stepcurrent: Cannot find last run test, not skipping 2025-08-26T23:15:41.0761671Z Running 1269 items in this shard: test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cuda, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cuda, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cuda, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cuda, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cuda, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cuda, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cuda, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cuda, test/test_fx.py::TestCSEPass::test_banned_list, test/test_fx.py::TestCSEPass::test_empty, test/test_fx.py::TestCSEPass::test_immutable_list_multiple_entries, test/test_fx.py::TestCSEPass::test_immutable_list_type, test/test_fx.py::TestCSEPass::test_kwarg, test/test_fx.py::TestCSEPass::test_nested_immutable_list_type, test/test_fx.py::TestCSEPass::test_nochange, test/test_fx.py::TestCSEPass::test_rand_like, test/test_fx.py::TestCSEPass::test_rand_n, test/test_fx.py::TestCSEPass::test_random, test/test_fx.py::TestCSEPass::test_simple, test/test_fx.py::TestCSEPass::test_simple_2, test/test_fx.py::TestCSEPass::test_simple_multiple_same_ops, test/test_fx.py::TestCSEPass::test_two_args, test/test_fx.py::TestCSEPass::test_two_args_default, test/test_fx.py::TestDCE::test_dead_chain, test/test_fx.py::TestDCE::test_dead_getattr, test/test_fx.py::TestDCE::test_dead_placeholder, test/test_fx.py::TestDCE::test_dead_placeholder_with_user, test/test_fx.py::TestDCE::test_impure_custom, test/test_fx.py::TestDCE::test_impure_kwargs, test/test_fx.py::TestDCE::test_impure_nodes_args, test/test_fx.py::TestDCE::test_impure_random, test/test_fx.py::TestDCE::test_keep_collectives, test/test_fx.py::TestDCE::test_keep_collectives_no_overload, test/test_fx.py::TestDCE::test_keep_module_with_side_effects, test/test_fx.py::TestDCE::test_keep_setitem, test/test_fx.py::TestDCE::test_keep_torch_assert, test/test_fx.py::TestDCE::test_simple, test/test_fx.py::TestConstFold::test_check_inline_non_const, test/test_fx.py::TestConstFold::test_check_inline_non_const_mult_return, test/test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input, test/test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node, test/test_fx.py::TestConstFold::test_const_fold_module_attr, test/test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs, test/test_fx.py::TestConstFold::test_const_fold_noop, test/test_fx.py::TestConstFold::test_const_fold_submod_hierarchy, test/test_fx.py::TestConstFold::test_const_fold_tensor_meta, test/test_fx.py::TestConstFold::test_const_fold_unused_placeholder, test/test_fx.py::TestConstFold::test_dict_output, test/test_fx.py::TestConstFold::test_fold_module, test/test_fx.py::TestConstFold::test_retain_node_meta, test/test_fx.py::TestConstFold::test_three_outputs, test/test_fx.py::TestConstFold::test_two_outputs, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const, test/test_fx.py::AnnotationsTest::test_annotate, test/test_fx.py::AnnotationsTest::test_annotations, test/test_fx.py::AnnotationsTest::test_broadcasting1, test/test_fx.py::AnnotationsTest::test_broadcasting2, test/test_fx.py::AnnotationsTest::test_broadcasting3, test/test_fx.py::AnnotationsTest::test_consistency, test/test_fx.py::AnnotationsTest::test_precision, test/test_fx.py::TypeCheckerTest::test_flatten_fully_static, test/test_fx.py::TypeCheckerTest::test_resnet50, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2, test/test_fx.py::TypeCheckerTest::test_type_check_add_false, test/test_fx.py::TypeCheckerTest::test_type_check_add_true, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_types, test/test_fx.py::TypeCheckerTest::test_type_check_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_flatten3, test/test_fx.py::TypeCheckerTest::test_type_check_flatten_2, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_true, test/test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_False, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_true, test/test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static, test/test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput, test/test_fx.py::TypeCheckerTest::test_typecheck_basicblock, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_function, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_module, test/test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map, test/test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad, test/test_fx.py::TestMatcher::test_variatic_arg_matching, test/test_fx.py::TestPassManager::test_pass_manager, test/test_fx.py::TestPassManager::test_pass_manager_bad_checks, test/test_fx.py::TestPassManager::test_pass_manager_checks, test/test_fx.py::TestPassManager::test_pass_manager_error, test/test_fx.py::TestPassManager::test_this_before_that_pass_constraint, test/test_fx.py::TestPassManager::test_topological_sort, test/test_fx.py::TestSourceMatcher::test_legalize_slice, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True, test/test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg, test/test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters, test/test_fx.py::TestSubgraphRewriter::test_replaced_nodes, test/test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results, test/test_fx.py::TestFX::test_all_input_nodes, test/test_fx.py::TestFX::test_annotation_with_future, test/test_fx.py::TestFX::test_annotations_empty_tuple, test/test_fx.py::TestFX::test_annotations_with_forward_references, test/test_fx.py::TestFX::test_annotations_with_no_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references, test/test_fx.py::TestFX::test_args_kwargs, test/test_fx.py::TestFX::test_args_kwargs_no_self, test/test_fx.py::TestFX::test_assert, test/test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message, test/test_fx.py::TestFX::test_ast_rewriter_wrap, test/test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly, test/test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_autowrap_functions, test/test_fx.py::TestFX::test_concrete_arg_none_assert, test/test_fx.py::TestFX::test_construct_root_dict, test/test_fx.py::TestFX::test_control_flow_tracing, test/test_fx.py::TestFX::test_copy_it, test/test_fx.py::TestFX::test_copy_no_remap, test/test_fx.py::TestFX::test_ctx_mgr, test/test_fx.py::TestFX::test_custom_codegen, test/test_fx.py::TestFX::test_custom_codegen_with_transformer, test/test_fx.py::TestFX::test_custom_import, test/test_fx.py::TestFX::test_custom_proxy_dynamic_value, test/test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow, test/test_fx.py::TestFX::test_custom_proxy_type, test/test_fx.py::TestFX::test_custom_proxy_type_literal, test/test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule, test/test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls, test/test_fx.py::TestFX::test_deepcopy_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graphmodule_with_transform, test/test_fx.py::TestFX::test_deepcopy_no_recursion, test/test_fx.py::TestFX::test_deepcopy_recursion_depth, test/test_fx.py::TestFX::test_deepcopy_tracer, test/test_fx.py::TestFX::test_deepcopy_with_submods_params, test/test_fx.py::TestFX::test_delete_unused_submodules_leaf, test/test_fx.py::TestFX::test_delete_unused_values, test/test_fx.py::TestFX::test_dict, test/test_fx.py::TestFX::test_direct_param_use, test/test_fx.py::TestFX::test_disallow_override, test/test_fx.py::TestFX::test_ellipsis, test/test_fx.py::TestFX::test_empty_graph_codegen, test/test_fx.py::TestFX::test_enum, test/test_fx.py::TestFX::test_erase_node_error, test/test_fx.py::TestFX::test_example_shape_prop, test/test_fx.py::TestFX::test_find_uses, test/test_fx.py::TestFX::test_fn_type_annotation_empty, test/test_fx.py::TestFX::test_fn_type_annotations, test/test_fx.py::TestFX::test_fx_and_or, test/test_fx.py::TestFX::test_fx_create_arg, test/test_fx.py::TestFX::test_fx_shifts, test/test_fx.py::TestFX::test_fx_stateless, test/test_fx.py::TestFX::test_get_torch_func_signature, test/test_fx.py::TestFX::test_getitem, test/test_fx.py::TestFX::test_getitem_subproc, test/test_fx.py::TestFX::test_graph_edit_with_proxy, test/test_fx.py::TestFX::test_graph_fns, test/test_fx.py::TestFX::test_graph_module, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_dict_init, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_mod_init, test/test_fx.py::TestFX::test_graph_module_replicate_for_dp, test/test_fx.py::TestFX::test_graph_unique_names, test/test_fx.py::TestFX::test_graph_unique_names_manual, test/test_fx.py::TestFX::test_immutable_dict_pytree_ops, test/test_fx.py::TestFX::test_immutable_list_pytree_ops, test/test_fx.py::TestFX::test_imul_code_print, test/test_fx.py::TestFX::test_inf_nan, test/test_fx.py::TestFX::test_inf_nan_kwds, test/test_fx.py::TestFX::test_informative_co_filename, test/test_fx.py::TestFX::test_inline_graph, test/test_fx.py::TestFX::test_insert_arg, test/test_fx.py::TestFX::test_insertion_point, test/test_fx.py::TestFX::test_interpreter, test/test_fx.py::TestFX::test_interpreter_default_args, test/test_fx.py::TestFX::test_interpreter_gc_values, test/test_fx.py::TestFX::test_interpreter_noop_resnet18, test/test_fx.py::TestFX::test_interpreter_not_enough_args, test/test_fx.py::TestFX::test_interpreter_onthefly_swap, test/test_fx.py::TestFX::test_interpreter_other_graph, test/test_fx.py::TestFX::test_interpreter_partial_eval, test/test_fx.py::TestFX::test_interpreter_run_node_override, test/test_fx.py::TestFX::test_interpreter_star_args, test/test_fx.py::TestFX::test_interpreter_with_codegen, test/test_fx.py::TestFX::test_layout, test/test_fx.py::TestFX::test_leaf_module, test/test_fx.py::TestFX::test_lineno_map, test/test_fx.py::TestFX::test_matmul_tracing, test/test_fx.py::TestFX::test_metadata_on_ph, test/test_fx.py::TestFX::test_module_deepcopy_edit_nodes, test/test_fx.py::TestFX::test_move_before, test/test_fx.py::TestFX::test_multi_insert_point, test/test_fx.py::TestFX::test_multiple_default_args, test/test_fx.py::TestFX::test_named_tuple_inlined, test/test_fx.py::TestFX::test_namedtuple_return_qualname, test/test_fx.py::TestFX::test_namedtuple_return_trace, test/test_fx.py::TestFX::test_native_callable, test/test_fx.py::TestFX::test_nn_module_stack, test/test_fx.py::TestFX::test_no_mutation, test/test_fx.py::TestFX::test_node_tagging, test/test_fx.py::TestFX::test_nonetype_annotation, test/test_fx.py::TestFX::test_partial_trace, test/test_fx.py::TestFX::test_pickle_custom_import, test/test_fx.py::TestFX::test_pickle_graphmodule, test/test_fx.py::TestFX::test_pickle_nonetype_annotation, test/test_fx.py::TestFX::test_pickle_torch_custom_ops, test/test_fx.py::TestFX::test_prepend_self, test/test_fx.py::TestFX::test_pretty_print, test/test_fx.py::TestFX::test_pretty_print_graph, test/test_fx.py::TestFX::test_pretty_print_node, test/test_fx.py::TestFX::test_pretty_print_targets, test/test_fx.py::TestFX::test_print_graph, test/test_fx.py::TestFX::test_profiler_ranges_side_effect, test/test_fx.py::TestFX::test_proxy_deepcopy_with_tracer, test/test_fx.py::TestFX::test_proxy_deepcopy_without_tracer, test/test_fx.py::TestFX::test_pytree, test/test_fx.py::TestFX::test_pytree_concrete, test/test_fx.py::TestFX::test_reassign_args_kwargs_uses, test/test_fx.py::TestFX::test_regular_and_default_args, test/test_fx.py::TestFX::test_remove_uses, test/test_fx.py::TestFX::test_remove_uses_with_custom_filter, test/test_fx.py::TestFX::test_replace_input, test/test_fx.py::TestFX::test_replace_uses, test/test_fx.py::TestFX::test_reserved_getattr, test/test_fx.py::TestFX::test_return_tuple, test/test_fx.py::TestFX::test_return_type_exists, test/test_fx.py::TestFX::test_return_type_exists_pre_pep585, test/test_fx.py::TestFX::test_script_method_trace, test/test_fx.py::TestFX::test_script_tensor_constant, test/test_fx.py::TestFX::test_sequential, test/test_fx.py::TestFX::test_shape_prop_aggregate, test/test_fx.py::TestFX::test_shape_prop_layout, test/test_fx.py::TestFX::test_shape_prop_layout_3d, test/test_fx.py::TestFX::test_shape_prop_unbacked_sym, test/test_fx.py::TestFX::test_single_default_arg, test/test_fx.py::TestFX::test_snake_case, test/test_fx.py::TestFX::test_sqrt, test/test_fx.py::TestFX::test_stack_traces, test/test_fx.py::TestFX::test_stack_traces_with_transformer, test/test_fx.py::TestFX::test_string_literal_return, test/test_fx.py::TestFX::test_submodule_manipulation_API, test/test_fx.py::TestFX::test_symbolic_trace_assert, test/test_fx.py::TestFX::test_symbolic_trace_sequential, test/test_fx.py::TestFX::test_tensor_attribute, test/test_fx.py::TestFX::test_tensor_attribute_coalseced, test/test_fx.py::TestFX::test_tensor_constant, test/test_fx.py::TestFX::test_throw_out_variant, test/test_fx.py::TestFX::test_torch_custom_ops, test/test_fx.py::TestFX::test_torch_fx_getattr, test/test_fx.py::TestFX::test_torch_fx_len, test/test_fx.py::TestFX::test_torch_op_overloads, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_dict_int_keys, test/test_fx.py::TestFX::test_trace_dict_proxy_keys, test/test_fx.py::TestFX::test_trace_fn_constant, test/test_fx.py::TestFX::test_trace_function, test/test_fx.py::TestFX::test_trace_multiple_funcs, test/test_fx.py::TestFX::test_trace_return_dataclass, test/test_fx.py::TestFX::test_trace_return_dataclass_nested, test/test_fx.py::TestFX::test_trace_return_namedtuple, test/test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules, test/test_fx.py::TestFX::test_transformer_multi_outputs, test/test_fx.py::TestFX::test_transformer_noop, test/test_fx.py::TestFX::test_transformer_op_swap, test/test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr, test/test_fx.py::TestFX::test_tuple_no_subscript, test/test_fx.py::TestFX::test_typename_print, test/test_fx.py::TestFX::test_typename_print_pre_pep585, test/test_fx.py::TestFX::test_unpack, test/test_fx.py::TestFX::test_unpack_dict_better_error, test/test_fx.py::TestFX::test_unpack_list_better_error, test/test_fx.py::TestFX::test_update_args_api, test/test_fx.py::TestFX::test_update_args_kwargs_yells_at_you, test/test_fx.py::TestFX::test_update_kwargs_api, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_function, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_module, test/test_fx.py::TestFX::test_varargs_concrete, test/test_fx.py::TestFX::test_wrap, test/test_fx.py::TestFX::test_wrap_decorated_function, test/test_fx.py::TestFX::test_wrap_fn_directly, test/test_fx.py::TestFX::test_wrap_with_submodule, test/test_fx.py::TestFX::test_wrapped_method, test/test_fx.py::TestFX::test_wrapped_retrace, test/test_fx.py::TestFX::test_wrapped_via_decorator, test/test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_wrong_target_type, test/test_fx.py::TestFX::test_wrong_topo, test/test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function, test/test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle, test/test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag, test/test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_glu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate, test/test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div, test/test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_linear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_normalize, test/test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pad, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pdist, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_prelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu6, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_silu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmin, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softplus, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_unfold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_H_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_T_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___getitem___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___radd___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rdiv___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmatmul___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmod___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmul___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rpow___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rsub___cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__chunk_cat_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__softmax_backward_data_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_abs_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_acos_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_acosh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_add_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addbmm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addcdiv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addcmul_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmm_decomposed_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_alias_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_all_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_allclose_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_amax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_amin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_aminmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_angle_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_any_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_arange_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argmin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argsort_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argwhere_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_asin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_asinh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atan2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atan_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atanh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_baddbmm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bernoulli_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bfloat16_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_block_diag_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bmm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bool_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_shapes_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_tensors_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_to_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bucketize_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_byte_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cartesian_prod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cat_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cauchy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cdist_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cdouble_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ceil_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cfloat_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_chalf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_char_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cholesky_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cholesky_inverse_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cholesky_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_chunk_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_clamp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_clamp_max_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_clamp_min_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_clone_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_column_stack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_combinations_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_complex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_conj_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_conj_physical_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_constant_pad_nd_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_contiguous_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_copysign_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_corrcoef_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cos_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cosh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_count_nonzero_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cov_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cross_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cummax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cummin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cumprod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cumsum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cumulative_trapezoid_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_deg2rad_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diag_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diag_embed_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diagflat_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diagonal_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diagonal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diagonal_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_diff_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_digamma_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_dist_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_div_floor_rounding_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_div_no_rounding_mode_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_div_trunc_rounding_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_dot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_double_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_dsplit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_dstack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_einsum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_empty_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_empty_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_empty_permuted_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_empty_strided_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_eq_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_equal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_erf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_erfc_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_erfinv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_exp2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_exp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_expand_as_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_expand_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_expand_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_expm1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_exponential_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_eye_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_fft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_fft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_fftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_fftshift_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_hfft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_hfft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_hfftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ifft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ifft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ifftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ifftshift_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ihfft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ihfft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_ihfftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_irfft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_irfft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_irfftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_rfft2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_rfft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fft_rfftn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fill_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_flatten_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_flip_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fliplr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_flipud_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_float_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_float_power_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_floor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_floor_divide_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fmin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_fmod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_frac_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_frexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_full_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_full_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_gather_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ge_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_geometric_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_geqrf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_gradient_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_grid_sampler_2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_grid_sampler_3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_gt_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_half_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hash_tensor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_heaviside_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_histc_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hsplit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hstack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hypot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_i0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_igamma_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_igammac_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_add_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_fill_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_put_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_amax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_amin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_prod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_select_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_inner_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_int_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isclose_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isfinite_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isinf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isnan_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isneginf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isposinf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isreal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_item_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_2inputs_2outputs_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_binary_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_unary_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_kron_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_kthvalue_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ldexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_le_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lerp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lgamma_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cholesky_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cond_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cross_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_det_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_diagonal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eig_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigvals_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_householder_product_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_inv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lstsq_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_qr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_slogdet_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_svd_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_svdvals_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_vander_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_vecdot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_vector_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linspace_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linspace_tensor_overload_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log10_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log1p_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log_normal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log_softmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_log_softmax_with_dtype_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logaddexp2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logaddexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logcumsumexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logdet_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logical_and_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logical_not_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logical_or_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logical_xor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logspace_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logspace_tensor_overload_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_logsumexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_long_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lt_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lu_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lu_unpack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mH_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mT_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_amax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_amin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_argmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_argmin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_cumprod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_cumsum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_fill_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_log_softmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_logaddexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_logsumexp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_median_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_normalize_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_prod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_select_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_softmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_softmin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_std_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_sum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_masked_var_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_matmul_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_matrix_exp_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_max_binary_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_max_pool2d_with_indices_backward_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_max_reduction_no_dim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_max_reduction_with_dim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_maximum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_median_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_meshgrid_list_of_tensors_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_meshgrid_variadic_tensors_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_min_binary_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_min_reduction_no_dim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_min_reduction_with_dim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_minimum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mode_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_movedim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_msort_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mul_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_multinomial_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mv_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_3_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nan_to_num_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nanmean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nanmedian_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nanquantile_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nansum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_narrow_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_narrow_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_native_batch_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_native_dropout_backward_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_native_layer_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ne_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_neg_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_new_empty_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_new_empty_strided_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_new_full_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_new_ones_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_new_zeros_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nextafter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_alpha_dropout_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_without_cudnn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_bilinear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_celu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_channel_shuffle_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_cosine_embedding_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_cosine_similarity_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_cross_entropy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_ctc_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_dropout2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_dropout3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_dropout_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_elu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_embedding_bag_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_embedding_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_gaussian_nll_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_gelu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_glu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_grid_sample_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_group_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_hardshrink_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_hardsigmoid_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_hardswish_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_hardtanh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_hinge_embedding_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_huber_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_instance_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_area_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bicubic_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bilinear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_linear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest-exact_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_trilinear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_kl_div_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_l1_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_layer_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_leaky_relu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_linear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_local_response_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_logsigmoid_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_margin_ranking_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_pool1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_pool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_pool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_grad_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_grad_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_grad_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_mish_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_mse_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_multi_head_attention_forward_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_multi_margin_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_margin_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_soft_margin_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_nll_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_normalize_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pad_circular_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pad_constant_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pad_reflect_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_negative_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pairwise_distance_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pdist_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pixel_shuffle_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_pixel_unshuffle_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_poisson_nll_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_prelu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_relu6_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_relu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_rms_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_rrelu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_scaled_dot_product_attention_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_selu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_silu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_smooth_l1_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_soft_margin_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_softmin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_softmin_with_dtype_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_softplus_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_softshrink_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_softsign_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_tanhshrink_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_threshold_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_unfold_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_upsample_bilinear_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nn_functional_upsample_nearest_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nonzero_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_nonzero_static_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_norm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_norm_fro_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_norm_inf_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_norm_nuc_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_normal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_normal_in_place_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_normal_number_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ones_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ones_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ormqr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_outer_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_pca_lowrank_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_permute_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_permute_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_pinverse_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polar_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_2_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_3_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_4_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_positive_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_pow_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_prod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_put_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_qr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_quantile_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rad2deg_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rand_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_randint_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_randint_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_randn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_randn_like_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ravel_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_real_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_reciprocal_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_remainder_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_renorm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_repeat_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_repeat_interleave_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_reshape_as_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_reshape_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resize__cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resize_as__cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resolve_conj_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resolve_neg_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_roll_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rot90_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_decimals_0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_decimals_3_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_decimals_neg_3_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rsqrt_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rsub_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scalar_tensor_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_add_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_reduce_amax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_reduce_amin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_reduce_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_reduce_prod_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_scatter_reduce_sum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_searchsorted_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_select_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_select_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sgn_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_short_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sigmoid_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sign_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_bartlett_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_blackman_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_cosine_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_exponential_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_gaussian_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_general_cosine_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_general_hamming_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_hamming_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_hann_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_kaiser_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signal_windows_nuttall_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_signbit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sin_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sinc_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sinh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_slice_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_slice_scatter_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_softmax_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_softmax_with_dtype_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sort_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sparse_mm_reduce_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sparse_sampled_addmm_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_airy_ai_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_bessel_j0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_bessel_j1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_bessel_y0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_bessel_y1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_t_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_u_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_v_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_w_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_entr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_erfcx_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_h_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_he_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_i0e_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_i1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_i1e_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_laguerre_polynomial_l_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_legendre_polynomial_p_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_log_ndtr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_modified_bessel_i0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_modified_bessel_i1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_modified_bessel_k0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_modified_bessel_k1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_ndtr_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_ndtri_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_polygamma_special_polygamma_n_0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k1_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_t_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_u_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_v_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_w_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_spherical_bessel_j0_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_xlog1py_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_special_zeta_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_split_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_split_list_args_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_split_with_sizes_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_split_with_sizes_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sqrt_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_square_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_squeeze_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_squeeze_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_squeeze_multiple_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_stack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_std_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_std_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_std_mean_unbiased_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_std_unbiased_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_stft_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sub_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sum_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_sum_to_size_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_svd_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_svd_lowrank_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_t_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_t_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_take_along_dim_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_take_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tan_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tanh_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tensor_split_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tensordot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tile_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_to_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_to_sparse_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_topk_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_torch_ops_aten__efficient_attention_forward_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trace_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_transpose_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_transpose_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trapezoid_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trapz_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_triangular_solve_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tril_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_triu_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_true_divide_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trunc_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unbind_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unbind_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unflatten_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unfold_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unfold_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_uniform_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unique_consecutive_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unique_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsafe_chunk_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsafe_split_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsqueeze_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_mean_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_unbiased_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vdot_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_as_complex_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_as_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_copy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vsplit_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vstack_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_where_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_xlogy_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zero__cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zeros_cuda_float32, test/test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zeros_like_cuda_float32, test/test_fx.py::TestVisionTracing::test_torchvision_models_alexnet, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_base, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_tiny, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet121, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet161, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet169, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet201, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_320_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fcos_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_keypointrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssd300_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssdlite320_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b0, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b1, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b2, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b3, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b4, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b5, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b6, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_l, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_m, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_googlenet, test/test_fx.py::TestVisionTracing::test_torchvision_models_inception_v3, test/test_fx.py::TestVisionTracing::test_torchvision_models_maxvit_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_75, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_3, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_128gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet152, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet18, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet34, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_32x8d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_64x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext50_32x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_lraspp_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x2_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_1, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mc3_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v1_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r2plus1d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r3d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_s3d, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_h_14, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet101_2, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet50_2 2025-08-26T23:15:41.0908408Z 2025-08-26T23:15:41.0908610Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu <- test/fx/test_common_passes.py PASSED [0.0108s] [ 0%] 2025-08-26T23:15:41.0909008Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cuda <- test/fx/test_common_passes.py PASSED [0.1216s] [ 0%] 2025-08-26T23:15:41.0909358Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu <- test/fx/test_common_passes.py PASSED [0.0056s] [ 0%] 2025-08-26T23:15:41.0909715Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cuda <- test/fx/test_common_passes.py PASSED [0.0035s] [ 0%] 2025-08-26T23:15:41.0910083Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu <- test/fx/test_common_passes.py PASSED [0.0044s] [ 0%] 2025-08-26T23:15:41.0910521Z test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cuda <- test/fx/test_common_passes.py PASSED [0.0046s] [ 0%] 2025-08-26T23:15:41.0910876Z test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu <- test/fx/test_common_passes.py PASSED [0.0033s] [ 0%] 2025-08-26T23:15:41.0911204Z test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cuda <- test/fx/test_common_passes.py PASSED [0.0035s] [ 0%] 2025-08-26T23:15:41.0911539Z test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu <- test/fx/test_common_passes.py PASSED [0.0056s] [ 0%] 2025-08-26T23:15:41.0911866Z test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cuda <- test/fx/test_common_passes.py PASSED [0.0043s] [ 0%] 2025-08-26T23:15:41.0912192Z test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu <- test/fx/test_common_passes.py PASSED [0.0028s] [ 0%] 2025-08-26T23:15:41.0912517Z test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cuda <- test/fx/test_common_passes.py PASSED [0.0123s] [ 0%] 2025-08-26T23:15:41.0912871Z test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu <- test/fx/test_common_passes.py PASSED [0.0033s] [ 1%] 2025-08-26T23:15:41.0913249Z test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cuda <- test/fx/test_common_passes.py PASSED [0.0034s] [ 1%] 2025-08-26T23:15:41.0913678Z test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu <- test/fx/test_common_passes.py PASSED [0.0039s] [ 1%] 2025-08-26T23:15:41.0914039Z test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cuda <- test/fx/test_common_passes.py PASSED [0.0036s] [ 1%] 2025-08-26T23:15:41.0914344Z test_fx.py::TestCSEPass::test_banned_list <- test/fx/test_cse_pass.py PASSED [0.0079s] [ 1%] 2025-08-26T23:15:41.0914582Z test_fx.py::TestCSEPass::test_empty <- test/fx/test_cse_pass.py PASSED [0.0021s] [ 1%] 2025-08-26T23:15:41.0914846Z test_fx.py::TestCSEPass::test_immutable_list_multiple_entries <- test/fx/test_cse_pass.py PASSED [0.0054s] [ 1%] 2025-08-26T23:15:41.0915123Z test_fx.py::TestCSEPass::test_immutable_list_type <- test/fx/test_cse_pass.py PASSED [0.0052s] [ 1%] 2025-08-26T23:15:41.0915370Z test_fx.py::TestCSEPass::test_kwarg <- test/fx/test_cse_pass.py PASSED [0.0037s] [ 1%] 2025-08-26T23:15:41.0915623Z test_fx.py::TestCSEPass::test_nested_immutable_list_type <- test/fx/test_cse_pass.py PASSED [0.0045s] [ 1%] 2025-08-26T23:15:41.0915926Z test_fx.py::TestCSEPass::test_nochange <- test/fx/test_cse_pass.py PASSED [0.0041s] [ 1%] 2025-08-26T23:15:41.0916162Z test_fx.py::TestCSEPass::test_rand_like <- test/fx/test_cse_pass.py PASSED [0.0034s] [ 1%] 2025-08-26T23:15:41.0916391Z test_fx.py::TestCSEPass::test_rand_n <- test/fx/test_cse_pass.py PASSED [0.0036s] [ 1%] 2025-08-26T23:15:41.0916617Z test_fx.py::TestCSEPass::test_random <- test/fx/test_cse_pass.py PASSED [2.6066s] [ 2%] 2025-08-26T23:15:41.0916882Z test_fx.py::TestCSEPass::test_simple <- test/fx/test_cse_pass.py PASSED [0.0116s] [ 2%] 2025-08-26T23:15:41.0917109Z test_fx.py::TestCSEPass::test_simple_2 <- test/fx/test_cse_pass.py PASSED [0.0058s] [ 2%] 2025-08-26T23:15:41.0917362Z test_fx.py::TestCSEPass::test_simple_multiple_same_ops <- test/fx/test_cse_pass.py PASSED [0.0043s] [ 2%] 2025-08-26T23:15:41.0917615Z test_fx.py::TestCSEPass::test_two_args <- test/fx/test_cse_pass.py PASSED [0.0048s] [ 2%] 2025-08-26T23:15:41.0917878Z test_fx.py::TestCSEPass::test_two_args_default <- test/fx/test_cse_pass.py PASSED [0.0043s] [ 2%] 2025-08-26T23:15:41.0918120Z test_fx.py::TestDCE::test_dead_chain <- test/fx/test_dce_pass.py PASSED [0.0021s] [ 2%] 2025-08-26T23:15:41.0918347Z test_fx.py::TestDCE::test_dead_getattr <- test/fx/test_dce_pass.py PASSED [0.0017s] [ 2%] 2025-08-26T23:15:41.0918580Z test_fx.py::TestDCE::test_dead_placeholder <- test/fx/test_dce_pass.py PASSED [0.0014s] [ 2%] 2025-08-26T23:15:41.0918836Z test_fx.py::TestDCE::test_dead_placeholder_with_user <- test/fx/test_dce_pass.py PASSED [0.0020s] [ 2%] 2025-08-26T23:15:41.0919088Z test_fx.py::TestDCE::test_impure_custom <- test/fx/test_dce_pass.py PASSED [0.0015s] [ 2%] 2025-08-26T23:15:41.0919326Z test_fx.py::TestDCE::test_impure_kwargs <- test/fx/test_dce_pass.py PASSED [0.0016s] [ 2%] 2025-08-26T23:15:41.0919567Z test_fx.py::TestDCE::test_impure_nodes_args <- test/fx/test_dce_pass.py PASSED [0.0015s] [ 2%] 2025-08-26T23:15:41.0919810Z test_fx.py::TestDCE::test_impure_random <- test/fx/test_dce_pass.py PASSED [0.4145s] [ 3%] 2025-08-26T23:15:41.0920054Z test_fx.py::TestDCE::test_keep_collectives <- test/fx/test_dce_pass.py PASSED [0.0036s] [ 3%] 2025-08-26T23:15:41.0920315Z test_fx.py::TestDCE::test_keep_collectives_no_overload <- test/fx/test_dce_pass.py PASSED [0.0023s] [ 3%] 2025-08-26T23:15:41.0920641Z test_fx.py::TestDCE::test_keep_module_with_side_effects <- test/fx/test_dce_pass.py PASSED [0.0022s] [ 3%] 2025-08-26T23:15:41.0920892Z test_fx.py::TestDCE::test_keep_setitem <- test/fx/test_dce_pass.py PASSED [0.4095s] [ 3%] 2025-08-26T23:15:41.0921134Z test_fx.py::TestDCE::test_keep_torch_assert <- test/fx/test_dce_pass.py PASSED [0.0112s] [ 3%] 2025-08-26T23:15:41.0921370Z test_fx.py::TestDCE::test_simple <- test/fx/test_dce_pass.py PASSED [0.0052s] [ 3%] 2025-08-26T23:15:41.0921629Z test_fx.py::TestConstFold::test_check_inline_non_const <- test/fx/test_fx_const_fold.py PASSED [0.0037s] [ 3%] 2025-08-26T23:15:41.0921932Z test_fx.py::TestConstFold::test_check_inline_non_const_mult_return <- test/fx/test_fx_const_fold.py PASSED [0.0060s] [ 3%] 2025-08-26T23:15:41.0922259Z test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern <- test/fx/test_fx_const_fold.py PASSED [0.0713s] [ 3%] 2025-08-26T23:15:41.0922591Z test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision <- test/fx/test_fx_const_fold.py PASSED [0.0073s] [ 3%] 2025-08-26T23:15:41.0922922Z test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision <- test/fx/test_fx_const_fold.py PASSED [0.0028s] [ 3%] 2025-08-26T23:15:41.0923258Z test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered <- test/fx/test_fx_const_fold.py PASSED [0.0015s] [ 4%] 2025-08-26T23:15:41.0923567Z test_fx.py::TestConstFold::test_const_fold_basic_two_attr <- test/fx/test_fx_const_fold.py PASSED [0.0026s] [ 4%] 2025-08-26T23:15:41.0923873Z test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input <- test/fx/test_fx_const_fold.py PASSED [0.0030s] [ 4%] 2025-08-26T23:15:41.0924198Z test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node <- test/fx/test_fx_const_fold.py PASSED [0.0026s] [ 4%] 2025-08-26T23:15:41.0924531Z test_fx.py::TestConstFold::test_const_fold_module_attr <- test/fx/test_fx_const_fold.py PASSED [0.0028s] [ 4%] 2025-08-26T23:15:41.0924833Z test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs <- test/fx/test_fx_const_fold.py PASSED [0.0036s] [ 4%] 2025-08-26T23:15:41.0925127Z test_fx.py::TestConstFold::test_const_fold_noop <- test/fx/test_fx_const_fold.py PASSED [0.0015s] [ 4%] 2025-08-26T23:15:41.0925454Z test_fx.py::TestConstFold::test_const_fold_submod_hierarchy <- test/fx/test_fx_const_fold.py PASSED [0.0026s] [ 4%] 2025-08-26T23:15:41.0925747Z test_fx.py::TestConstFold::test_const_fold_tensor_meta <- test/fx/test_fx_const_fold.py PASSED [0.0065s] [ 4%] 2025-08-26T23:15:41.0926039Z test_fx.py::TestConstFold::test_const_fold_unused_placeholder <- test/fx/test_fx_const_fold.py PASSED [0.0031s] [ 4%] 2025-08-26T23:15:41.0926342Z test_fx.py::TestConstFold::test_dict_output <- test/fx/test_fx_const_fold.py PASSED [0.0024s] [ 4%] 2025-08-26T23:15:41.0926605Z test_fx.py::TestConstFold::test_fold_module <- test/fx/test_fx_const_fold.py PASSED [0.0025s] [ 4%] 2025-08-26T23:15:41.0926869Z test_fx.py::TestConstFold::test_retain_node_meta <- test/fx/test_fx_const_fold.py PASSED [0.0024s] [ 4%] 2025-08-26T23:15:41.0927137Z test_fx.py::TestConstFold::test_three_outputs <- test/fx/test_fx_const_fold.py PASSED [0.0026s] [ 5%] 2025-08-26T23:15:41.0927398Z test_fx.py::TestConstFold::test_two_outputs <- test/fx/test_fx_const_fold.py PASSED [0.0024s] [ 5%] 2025-08-26T23:15:41.0927714Z test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0029s] [ 5%] 2025-08-26T23:15:41.0928084Z test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0025s] [ 5%] 2025-08-26T23:15:41.0928459Z test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0024s] [ 5%] 2025-08-26T23:15:41.0928835Z test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0029s] [ 5%] 2025-08-26T23:15:41.0929208Z test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0023s] [ 5%] 2025-08-26T23:15:41.0929578Z test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const <- test/fx/test_fx_param_shape_control_flow.py PASSED [0.0023s] [ 5%] 2025-08-26T23:15:41.0929891Z test_fx.py::AnnotationsTest::test_annotate <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 5%] 2025-08-26T23:15:41.0930149Z test_fx.py::AnnotationsTest::test_annotations <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 5%] 2025-08-26T23:15:41.0930465Z test_fx.py::AnnotationsTest::test_broadcasting1 <- test/fx/test_gradual_type.py PASSED [0.0004s] [ 5%] 2025-08-26T23:15:41.0930732Z test_fx.py::AnnotationsTest::test_broadcasting2 <- test/fx/test_gradual_type.py PASSED [0.0004s] [ 5%] 2025-08-26T23:15:41.0930994Z test_fx.py::AnnotationsTest::test_broadcasting3 <- test/fx/test_gradual_type.py PASSED [0.0005s] [ 5%] 2025-08-26T23:15:41.0931257Z test_fx.py::AnnotationsTest::test_consistency <- test/fx/test_gradual_type.py PASSED [0.0004s] [ 6%] 2025-08-26T23:15:41.0931518Z test_fx.py::AnnotationsTest::test_precision <- test/fx/test_gradual_type.py PASSED [0.0006s] [ 6%] 2025-08-26T23:15:41.0931790Z test_fx.py::TypeCheckerTest::test_flatten_fully_static <- test/fx/test_gradual_type.py PASSED [0.0057s] [ 6%] 2025-08-26T23:15:41.0932056Z test_fx.py::TypeCheckerTest::test_resnet50 <- test/fx/test_gradual_type.py PASSED [8.9192s] [ 6%] 2025-08-26T23:15:41.0932331Z test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast <- test/fx/test_gradual_type.py PASSED [0.0030s] [ 6%] 2025-08-26T23:15:41.0932634Z test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2 <- test/fx/test_gradual_type.py PASSED [0.0019s] [ 6%] 2025-08-26T23:15:41.0932961Z test_fx.py::TypeCheckerTest::test_type_check_add_false <- test/fx/test_gradual_type.py PASSED [0.0016s] [ 6%] 2025-08-26T23:15:41.0933240Z test_fx.py::TypeCheckerTest::test_type_check_add_true <- test/fx/test_gradual_type.py PASSED [0.0016s] [ 6%] 2025-08-26T23:15:41.0933526Z test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast <- test/fx/test_gradual_type.py PASSED [0.0014s] [ 6%] 2025-08-26T23:15:41.0933866Z test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 6%] 2025-08-26T23:15:41.0934158Z test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D <- test/fx/test_gradual_type.py PASSED [0.0024s] [ 6%] 2025-08-26T23:15:41.0934460Z test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast <- test/fx/test_gradual_type.py PASSED [0.0030s] [ 6%] 2025-08-26T23:15:41.0934781Z test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false <- test/fx/test_gradual_type.py PASSED [0.0017s] [ 7%] 2025-08-26T23:15:41.0935087Z test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic <- test/fx/test_gradual_type.py PASSED [0.0023s] [ 7%] 2025-08-26T23:15:41.0935377Z test_fx.py::TypeCheckerTest::test_type_check_conv2D <- test/fx/test_gradual_type.py PASSED [0.0017s] [ 7%] 2025-08-26T23:15:41.0935651Z test_fx.py::TypeCheckerTest::test_type_check_conv2D_2 <- test/fx/test_gradual_type.py PASSED [0.0135s] [ 7%] 2025-08-26T23:15:41.0936043Z test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static <- test/fx/test_gradual_type.py [W826 22:41:15.283942934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.0936351Z PASSED [0.2591s] [ 7%] 2025-08-26T23:15:41.0936560Z test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten <- test/fx/test_gradual_type.py PASSED [0.0036s] [ 7%] 2025-08-26T23:15:41.0936866Z test_fx.py::TypeCheckerTest::test_type_check_conv2D_types <- test/fx/test_gradual_type.py PASSED [0.0124s] [ 7%] 2025-08-26T23:15:41.0937150Z test_fx.py::TypeCheckerTest::test_type_check_flatten <- test/fx/test_gradual_type.py PASSED [0.0016s] [ 7%] 2025-08-26T23:15:41.0937425Z test_fx.py::TypeCheckerTest::test_type_check_flatten3 <- test/fx/test_gradual_type.py PASSED [0.0044s] [ 7%] 2025-08-26T23:15:41.0937709Z test_fx.py::TypeCheckerTest::test_type_check_flatten_2 <- test/fx/test_gradual_type.py PASSED [0.0014s] [ 7%] 2025-08-26T23:15:41.0938012Z test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false <- test/fx/test_gradual_type.py PASSED [0.0014s] [ 7%] 2025-08-26T23:15:41.0938324Z test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true <- test/fx/test_gradual_type.py PASSED [0.0014s] [ 7%] 2025-08-26T23:15:41.0938639Z test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 7%] 2025-08-26T23:15:41.0938974Z test_fx.py::TypeCheckerTest::test_type_check_reshape_false <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 8%] 2025-08-26T23:15:41.0939268Z test_fx.py::TypeCheckerTest::test_type_check_reshape_true <- test/fx/test_gradual_type.py PASSED [0.0013s] [ 8%] 2025-08-26T23:15:41.0939595Z test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten <- test/fx/test_gradual_type.py PASSED [0.0079s] [ 8%] 2025-08-26T23:15:41.0939931Z test_fx.py::TypeCheckerTest::test_type_check_transpose_False <- test/fx/test_gradual_type.py PASSED [0.0014s] [ 8%] 2025-08-26T23:15:41.0940228Z test_fx.py::TypeCheckerTest::test_type_check_transpose_true <- test/fx/test_gradual_type.py PASSED [0.0012s] [ 8%] 2025-08-26T23:15:41.0940592Z test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static <- test/fx/test_gradual_type.py PASSED [0.0808s] [ 8%] 2025-08-26T23:15:41.0940907Z test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput <- test/fx/test_gradual_type.py PASSED [0.0015s] [ 8%] 2025-08-26T23:15:41.0941214Z test_fx.py::TypeCheckerTest::test_typecheck_basicblock <- test/fx/test_gradual_type.py PASSED [0.1893s] [ 8%] 2025-08-26T23:15:41.0941538Z test_fx.py::TestMatcher::test_matcher_with_name_node_map_function <- test/fx/test_matcher_utils.py PASSED [3.0707s] [ 8%] 2025-08-26T23:15:41.0941840Z test_fx.py::TestMatcher::test_matcher_with_name_node_map_module <- test/fx/test_matcher_utils.py PASSED [0.5534s] [ 8%] 2025-08-26T23:15:41.0942230Z test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map <- test/fx/test_matcher_utils.py [W826 22:41:19.521934744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.0942633Z [W826 22:41:19.531371651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.0942811Z PASSED [0.0512s] [ 8%] 2025-08-26T23:15:41.0943017Z test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals <- test/fx/test_matcher_utils.py PASSED [0.0086s] [ 8%] 2025-08-26T23:15:41.0943329Z test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes <- test/fx/test_matcher_utils.py PASSED [0.0032s] [ 8%] 2025-08-26T23:15:41.0943678Z test_fx.py::TestMatcher::test_subgraph_matcher_with_list <- test/fx/test_matcher_utils.py PASSED [0.0029s] [ 9%] 2025-08-26T23:15:41.0944143Z test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad <- test/fx/test_matcher_utils.py PASSED [0.0031s] [ 9%] 2025-08-26T23:15:41.0944528Z test_fx.py::TestMatcher::test_variatic_arg_matching <- test/fx/test_matcher_utils.py PASSED [0.0514s] [ 9%] 2025-08-26T23:15:41.0944857Z test_fx.py::TestPassManager::test_pass_manager <- test/fx/test_pass_infra.py PASSED [0.0084s] [ 9%] 2025-08-26T23:15:41.0945165Z test_fx.py::TestPassManager::test_pass_manager_bad_checks <- test/fx/test_pass_infra.py PASSED [0.0005s] [ 9%] 2025-08-26T23:15:41.0945558Z test_fx.py::TestPassManager::test_pass_manager_checks <- test/fx/test_pass_infra.py PASSED [0.0013s] [ 9%] 2025-08-26T23:15:41.0945879Z test_fx.py::TestPassManager::test_pass_manager_error <- test/fx/test_pass_infra.py PASSED [0.0021s] [ 9%] 2025-08-26T23:15:41.0946236Z test_fx.py::TestPassManager::test_this_before_that_pass_constraint <- test/fx/test_pass_infra.py PASSED [0.0004s] [ 9%] 2025-08-26T23:15:41.0946697Z test_fx.py::TestPassManager::test_topological_sort <- test/fx/test_pass_infra.py PASSED [0.0009s] [ 9%] 2025-08-26T23:15:41.0947157Z test_fx.py::TestSourceMatcher::test_legalize_slice <- test/fx/test_source_matcher_utils.py PASSED [0.4734s] [ 9%] 2025-08-26T23:15:41.0947530Z test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool <- test/fx/test_source_matcher_utils.py PASSED [0.6630s] [ 9%] 2025-08-26T23:15:41.0947967Z test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False <- test/fx/test_source_matcher_utils.py PASSED [0.0279s] [ 9%] 2025-08-26T23:15:41.0948451Z test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True <- test/fx/test_source_matcher_utils.py PASSED [0.1462s] [ 10%] 2025-08-26T23:15:41.0948981Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv <- test/fx/test_source_matcher_utils.py [W826 22:41:20.005292619 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.0949347Z PASSED [0.7608s] [ 10%] 2025-08-26T23:15:41.0949688Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False <- test/fx/test_source_matcher_utils.py PASSED [0.0102s] [ 10%] 2025-08-26T23:15:41.0950168Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True <- test/fx/test_source_matcher_utils.py PASSED [0.5960s] [ 10%] 2025-08-26T23:15:41.0950713Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear <- test/fx/test_source_matcher_utils.py PASSED [0.4977s] [ 10%] 2025-08-26T23:15:41.0951187Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False <- test/fx/test_source_matcher_utils.py PASSED [0.0131s] [ 10%] 2025-08-26T23:15:41.0951758Z test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True <- test/fx/test_source_matcher_utils.py PASSED [0.5236s] [ 10%] 2025-08-26T23:15:41.0952238Z test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear <- test/fx/test_source_matcher_utils.py PASSED [0.0419s] [ 10%] 2025-08-26T23:15:41.0952688Z test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False <- test/fx/test_source_matcher_utils.py PASSED [0.0166s] [ 10%] 2025-08-26T23:15:41.0953214Z test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True <- test/fx/test_source_matcher_utils.py PASSED [0.0308s] [ 10%] 2025-08-26T23:15:41.0953727Z test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False <- test/fx/test_source_matcher_utils.py PASSED [0.0107s] [ 10%] 2025-08-26T23:15:41.0954142Z test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True <- test/fx/test_source_matcher_utils.py PASSED [0.4810s] [ 10%] 2025-08-26T23:15:41.0954604Z test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg <- test/fx/test_subgraph_rewriter.py PASSED [0.0041s] [ 10%] 2025-08-26T23:15:41.0954985Z test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments <- test/fx/test_subgraph_rewriter.py PASSED [0.0034s] [ 11%] 2025-08-26T23:15:41.0955418Z test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback <- test/fx/test_subgraph_rewriter.py PASSED [0.0034s] [ 11%] 2025-08-26T23:15:41.0955798Z test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters <- test/fx/test_subgraph_rewriter.py PASSED [0.0069s] [ 11%] 2025-08-26T23:15:41.0956328Z test_fx.py::TestSubgraphRewriter::test_replaced_nodes <- test/fx/test_subgraph_rewriter.py PASSED [0.0030s] [ 11%] 2025-08-26T23:15:41.0956734Z test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs <- test/fx/test_subgraph_rewriter.py PASSED [0.0032s] [ 11%] 2025-08-26T23:15:41.0957186Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int <- test/fx/test_subgraph_rewriter.py PASSED [0.0022s] [ 11%] 2025-08-26T23:15:41.0957604Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method <- test/fx/test_subgraph_rewriter.py PASSED [0.0038s] [ 11%] 2025-08-26T23:15:41.0958131Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement <- test/fx/test_subgraph_rewriter.py PASSED [0.0043s] [ 11%] 2025-08-26T23:15:41.0958545Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order <- test/fx/test_subgraph_rewriter.py PASSED [0.0036s] [ 11%] 2025-08-26T23:15:41.0959014Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched <- test/fx/test_subgraph_rewriter.py PASSED [0.0035s] [ 11%] 2025-08-26T23:15:41.0959459Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert <- test/fx/test_subgraph_rewriter.py PASSED [0.0042s] [ 11%] 2025-08-26T23:15:41.0959861Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match <- test/fx/test_subgraph_rewriter.py PASSED [0.0050s] [ 11%] 2025-08-26T23:15:41.0960289Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs <- test/fx/test_subgraph_rewriter.py PASSED [0.0033s] [ 11%] 2025-08-26T23:15:41.0960775Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph <- test/fx/test_subgraph_rewriter.py PASSED [0.0038s] [ 12%] 2025-08-26T23:15:41.0961297Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched <- test/fx/test_subgraph_rewriter.py PASSED [0.0037s] [ 12%] 2025-08-26T23:15:41.0961779Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching <- test/fx/test_subgraph_rewriter.py PASSED [0.0042s] [ 12%] 2025-08-26T23:15:41.0962214Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic <- test/fx/test_subgraph_rewriter.py PASSED [0.0039s] [ 12%] 2025-08-26T23:15:41.0962700Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules <- test/fx/test_subgraph_rewriter.py PASSED [0.0038s] [ 12%] 2025-08-26T23:15:41.0963133Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs <- test/fx/test_subgraph_rewriter.py PASSED [0.0039s] [ 12%] 2025-08-26T23:15:41.0963566Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs <- test/fx/test_subgraph_rewriter.py PASSED [0.0044s] [ 12%] 2025-08-26T23:15:41.0964060Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules <- test/fx/test_subgraph_rewriter.py PASSED [0.0036s] [ 12%] 2025-08-26T23:15:41.0964561Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match <- test/fx/test_subgraph_rewriter.py PASSED [0.0038s] [ 12%] 2025-08-26T23:15:41.0965121Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable <- test/fx/test_subgraph_rewriter.py PASSED [0.0038s] [ 12%] 2025-08-26T23:15:41.0965558Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern <- test/fx/test_subgraph_rewriter.py PASSED [0.0037s] [ 12%] 2025-08-26T23:15:41.0965984Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches <- test/fx/test_subgraph_rewriter.py PASSED [0.0043s] [ 12%] 2025-08-26T23:15:41.0966509Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement <- test/fx/test_subgraph_rewriter.py PASSED [0.0036s] [ 13%] 2025-08-26T23:15:41.0966966Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args <- test/fx/test_subgraph_rewriter.py PASSED [0.0036s] [ 13%] 2025-08-26T23:15:41.0967353Z test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results <- test/fx/test_subgraph_rewriter.py PASSED [0.0043s] [ 13%] 2025-08-26T23:15:41.0967779Z test_fx.py::TestFX::test_all_input_nodes PASSED [0.0053s] [ 13%] 2025-08-26T23:15:41.0968079Z test_fx.py::TestFX::test_annotation_with_future PASSED [0.0050s] [ 13%] 2025-08-26T23:15:41.0968479Z test_fx.py::TestFX::test_annotations_empty_tuple SKIPPED [0.0002s] (Does not work in 3.11) [ 13%] 2025-08-26T23:15:41.0968946Z test_fx.py::TestFX::test_annotations_with_forward_references PASSED [0.0015s] [ 13%] 2025-08-26T23:15:41.0969290Z test_fx.py::TestFX::test_annotations_with_no_forward_references PASSED [0.0015s] [ 13%] 2025-08-26T23:15:41.0969747Z test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references PASSED [0.0015s] [ 13%] 2025-08-26T23:15:41.0970260Z test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references PASSED [0.0016s] [ 13%] 2025-08-26T23:15:41.0970754Z test_fx.py::TestFX::test_args_kwargs PASSED [0.0015s] [ 13%] 2025-08-26T23:15:41.0971221Z test_fx.py::TestFX::test_args_kwargs_no_self PASSED [0.0007s] [ 13%] 2025-08-26T23:15:41.0971578Z test_fx.py::TestFX::test_assert SKIPPED [0.0001s] (Does not work on Python-3.10) [ 13%] 2025-08-26T23:15:41.0972020Z test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules PASSED [0.0022s] [ 14%] 2025-08-26T23:15:41.0972403Z test_fx.py::TestFX::test_ast_rewriter_rewrites_assert PASSED [0.0018s] [ 14%] 2025-08-26T23:15:41.0972662Z test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message PASSED [0.0018s] [ 14%] 2025-08-26T23:15:41.0972923Z test_fx.py::TestFX::test_ast_rewriter_wrap PASSED [0.0017s] [ 14%] 2025-08-26T23:15:41.0973218Z test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly PASSED [0.0017s] [ 14%] 2025-08-26T23:15:41.0973478Z test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule PASSED [0.0762s] [ 14%] 2025-08-26T23:15:41.0973733Z test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator PASSED [0.0072s] [ 14%] 2025-08-26T23:15:41.0974045Z test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed PASSED [0.0027s] [ 14%] 2025-08-26T23:15:41.0974320Z test_fx.py::TestFX::test_autowrap_functions PASSED [0.0323s] [ 14%] 2025-08-26T23:15:41.0984553Z test_fx.py::TestFX::test_concrete_arg_none_assert PASSED [0.0021s] [ 14%] 2025-08-26T23:15:41.0984775Z test_fx.py::TestFX::test_construct_root_dict PASSED [0.0014s] [ 14%] 2025-08-26T23:15:41.0984974Z test_fx.py::TestFX::test_control_flow_tracing PASSED [0.0012s] [ 14%] 2025-08-26T23:15:41.0985166Z test_fx.py::TestFX::test_copy_it PASSED [0.0008s] [ 14%] 2025-08-26T23:15:41.0985432Z test_fx.py::TestFX::test_copy_no_remap PASSED [0.0016s] [ 15%] 2025-08-26T23:15:41.0985624Z test_fx.py::TestFX::test_ctx_mgr PASSED [0.0016s] [ 15%] 2025-08-26T23:15:41.0985813Z test_fx.py::TestFX::test_custom_codegen PASSED [0.0087s] [ 15%] 2025-08-26T23:15:41.0986008Z test_fx.py::TestFX::test_custom_codegen_with_transformer PASSED [0.0023s] [ 15%] 2025-08-26T23:15:41.0986230Z test_fx.py::TestFX::test_custom_import PASSED [0.0009s] [ 15%] 2025-08-26T23:15:41.0986425Z test_fx.py::TestFX::test_custom_proxy_dynamic_value PASSED [0.0017s] [ 15%] 2025-08-26T23:15:41.0986648Z test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow PASSED [0.0022s] [ 15%] 2025-08-26T23:15:41.0986859Z test_fx.py::TestFX::test_custom_proxy_type PASSED [0.0015s] [ 15%] 2025-08-26T23:15:41.0987052Z test_fx.py::TestFX::test_custom_proxy_type_literal PASSED [0.0016s] [ 15%] 2025-08-26T23:15:41.0987289Z test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule PASSED [0.0023s] [ 15%] 2025-08-26T23:15:41.0987569Z test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule PASSED [0.0020s] [ 15%] 2025-08-26T23:15:41.0987811Z test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls PASSED 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test_fx.py::TestFX::test_move_before PASSED [0.0009s] [ 20%] 2025-08-26T23:15:41.1000450Z test_fx.py::TestFX::test_multi_insert_point PASSED [0.0007s] [ 20%] 2025-08-26T23:15:41.1000696Z test_fx.py::TestFX::test_multiple_default_args PASSED [0.0035s] [ 20%] 2025-08-26T23:15:41.1000894Z test_fx.py::TestFX::test_named_tuple_inlined PASSED [0.0020s] [ 20%] 2025-08-26T23:15:41.1001093Z test_fx.py::TestFX::test_namedtuple_return_qualname PASSED [0.0015s] [ 21%] 2025-08-26T23:15:41.1001287Z test_fx.py::TestFX::test_namedtuple_return_trace PASSED [0.0015s] [ 21%] 2025-08-26T23:15:41.1001501Z test_fx.py::TestFX::test_native_callable PASSED [0.0224s] [ 21%] 2025-08-26T23:15:41.1001694Z test_fx.py::TestFX::test_nn_module_stack PASSED [0.0020s] [ 21%] 2025-08-26T23:15:41.1001880Z test_fx.py::TestFX::test_no_mutation PASSED [0.0006s] [ 21%] 2025-08-26T23:15:41.1002067Z test_fx.py::TestFX::test_node_tagging PASSED [0.0012s] [ 21%] 2025-08-26T23:15:41.1002259Z test_fx.py::TestFX::test_nonetype_annotation PASSED [0.0017s] [ 21%] 2025-08-26T23:15:41.1002452Z test_fx.py::TestFX::test_partial_trace PASSED [0.0033s] [ 21%] 2025-08-26T23:15:41.1002679Z test_fx.py::TestFX::test_pickle_custom_import PASSED [0.0026s] [ 21%] 2025-08-26T23:15:41.1002950Z test_fx.py::TestFX::test_pickle_graphmodule PASSED [0.0039s] [ 21%] 2025-08-26T23:15:41.1003193Z test_fx.py::TestFX::test_pickle_nonetype_annotation PASSED [0.0351s] [ 21%] 2025-08-26T23:15:41.1003440Z test_fx.py::TestFX::test_pickle_torch_custom_ops PASSED [0.0120s] [ 21%] 2025-08-26T23:15:41.1003691Z test_fx.py::TestFX::test_prepend_self PASSED [0.0011s] [ 21%] 2025-08-26T23:15:41.1003923Z test_fx.py::TestFX::test_pretty_print PASSED [0.0021s] [ 22%] 2025-08-26T23:15:41.1004175Z test_fx.py::TestFX::test_pretty_print_graph PASSED [0.0020s] [ 22%] 2025-08-26T23:15:41.1004412Z test_fx.py::TestFX::test_pretty_print_node PASSED [0.0021s] [ 22%] 2025-08-26T23:15:41.1004637Z test_fx.py::TestFX::test_pretty_print_targets PASSED [0.0017s] [ 22%] 2025-08-26T23:15:41.1004902Z test_fx.py::TestFX::test_print_graph PASSED [0.0011s] [ 22%] 2025-08-26T23:15:41.1005141Z test_fx.py::TestFX::test_profiler_ranges_side_effect PASSED [0.0011s] [ 22%] 2025-08-26T23:15:41.1005392Z test_fx.py::TestFX::test_proxy_deepcopy_with_tracer PASSED [0.0019s] [ 22%] 2025-08-26T23:15:41.1005646Z test_fx.py::TestFX::test_proxy_deepcopy_without_tracer PASSED [0.0018s] [ 22%] 2025-08-26T23:15:41.1005887Z test_fx.py::TestFX::test_pytree PASSED [0.0589s] [ 22%] 2025-08-26T23:15:41.1006140Z test_fx.py::TestFX::test_pytree_concrete PASSED [0.0026s] [ 22%] 2025-08-26T23:15:41.1006372Z test_fx.py::TestFX::test_reassign_args_kwargs_uses PASSED [0.0007s] [ 22%] 2025-08-26T23:15:41.1006595Z test_fx.py::TestFX::test_regular_and_default_args PASSED [0.0022s] [ 22%] 2025-08-26T23:15:41.1006845Z test_fx.py::TestFX::test_remove_uses PASSED [0.0006s] [ 23%] 2025-08-26T23:15:41.1007077Z test_fx.py::TestFX::test_remove_uses_with_custom_filter PASSED [0.0005s] [ 23%] 2025-08-26T23:15:41.1007306Z test_fx.py::TestFX::test_replace_input PASSED [0.0010s] [ 23%] 2025-08-26T23:15:41.1007564Z test_fx.py::TestFX::test_replace_uses PASSED [0.1027s] [ 23%] 2025-08-26T23:15:41.1007796Z test_fx.py::TestFX::test_reserved_getattr PASSED [0.0019s] [ 23%] 2025-08-26T23:15:41.1008042Z test_fx.py::TestFX::test_return_tuple PASSED [0.0017s] [ 23%] 2025-08-26T23:15:41.1008278Z test_fx.py::TestFX::test_return_type_exists PASSED [0.0083s] [ 23%] 2025-08-26T23:15:41.1008546Z test_fx.py::TestFX::test_return_type_exists_pre_pep585 PASSED [0.0069s] [ 23%] 2025-08-26T23:15:41.1008797Z test_fx.py::TestFX::test_script_method_trace PASSED [0.0037s] [ 23%] 2025-08-26T23:15:41.1009033Z test_fx.py::TestFX::test_script_tensor_constant PASSED [0.0071s] [ 23%] 2025-08-26T23:15:41.1009266Z test_fx.py::TestFX::test_sequential PASSED [0.0022s] [ 23%] 2025-08-26T23:15:41.1009543Z test_fx.py::TestFX::test_shape_prop_aggregate PASSED [0.0017s] [ 23%] 2025-08-26T23:15:41.1009780Z test_fx.py::TestFX::test_shape_prop_layout PASSED [0.0706s] [ 23%] 2025-08-26T23:15:41.1010113Z test_fx.py::TestFX::test_shape_prop_layout_3d PASSED [0.2294s] [ 24%] 2025-08-26T23:15:41.1010410Z test_fx.py::TestFX::test_shape_prop_unbacked_sym PASSED [0.8260s] [ 24%] 2025-08-26T23:15:41.1010661Z test_fx.py::TestFX::test_single_default_arg PASSED [0.0035s] [ 24%] 2025-08-26T23:15:41.1010899Z test_fx.py::TestFX::test_snake_case PASSED [0.0023s] [ 24%] 2025-08-26T23:15:41.1011131Z test_fx.py::TestFX::test_sqrt PASSED [0.0040s] [ 24%] 2025-08-26T23:15:41.1011346Z test_fx.py::TestFX::test_stack_traces PASSED [0.0017s] [ 24%] 2025-08-26T23:15:41.1011597Z test_fx.py::TestFX::test_stack_traces_with_transformer PASSED [0.0020s] [ 24%] 2025-08-26T23:15:41.1011817Z test_fx.py::TestFX::test_string_literal_return PASSED [0.0014s] [ 24%] 2025-08-26T23:15:41.1012041Z test_fx.py::TestFX::test_submodule_manipulation_API PASSED [0.0089s] [ 24%] 2025-08-26T23:15:41.1012299Z test_fx.py::TestFX::test_symbolic_trace_assert PASSED [0.0050s] [ 24%] 2025-08-26T23:15:41.1012704Z test_fx.py::TestFX::test_symbolic_trace_sequential PASSED [0.0018s] [ 24%] 2025-08-26T23:15:41.1012948Z test_fx.py::TestFX::test_tensor_attribute PASSED [0.0025s] [ 24%] 2025-08-26T23:15:41.1013190Z test_fx.py::TestFX::test_tensor_attribute_coalseced PASSED [0.0023s] [ 24%] 2025-08-26T23:15:41.1013419Z test_fx.py::TestFX::test_tensor_constant PASSED [0.0015s] [ 25%] 2025-08-26T23:15:41.1013667Z test_fx.py::TestFX::test_throw_out_variant PASSED [0.0014s] [ 25%] 2025-08-26T23:15:41.1013890Z test_fx.py::TestFX::test_torch_custom_ops PASSED [0.0017s] [ 25%] 2025-08-26T23:15:41.1014111Z test_fx.py::TestFX::test_torch_fx_getattr PASSED [0.0015s] [ 25%] 2025-08-26T23:15:41.1014368Z test_fx.py::TestFX::test_torch_fx_len PASSED [0.0108s] [ 25%] 2025-08-26T23:15:41.1014589Z test_fx.py::TestFX::test_torch_op_overloads PASSED [0.0016s] [ 25%] 2025-08-26T23:15:41.1014829Z test_fx.py::TestFX::test_torchbind_class_attribute_in_fx PASSED [0.0014s] [ 25%] 2025-08-26T23:15:41.1015088Z test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg PASSED [0.0015s] [ 25%] 2025-08-26T23:15:41.1015367Z test_fx.py::TestFX::test_trace_buffer_slice SKIPPED [0.0001s] (Hotfix for SEV remediation) [ 25%] 2025-08-26T23:15:41.1015647Z test_fx.py::TestFX::test_trace_dict_int_keys PASSED [0.0012s] [ 25%] 2025-08-26T23:15:41.1015871Z test_fx.py::TestFX::test_trace_dict_proxy_keys PASSED [0.0017s] [ 25%] 2025-08-26T23:15:41.1016092Z test_fx.py::TestFX::test_trace_fn_constant PASSED [0.0015s] [ 25%] 2025-08-26T23:15:41.1016334Z test_fx.py::TestFX::test_trace_function PASSED [0.0015s] [ 26%] 2025-08-26T23:15:41.1016561Z test_fx.py::TestFX::test_trace_multiple_funcs PASSED [0.0032s] [ 26%] 2025-08-26T23:15:41.1016801Z test_fx.py::TestFX::test_trace_return_dataclass PASSED [0.0022s] [ 26%] 2025-08-26T23:15:41.1017023Z test_fx.py::TestFX::test_trace_return_dataclass_nested PASSED [0.0020s] [ 26%] 2025-08-26T23:15:41.1017251Z test_fx.py::TestFX::test_trace_return_namedtuple PASSED [0.0022s] [ 26%] 2025-08-26T23:15:41.1017510Z test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules PASSED [0.0068s] [ 26%] 2025-08-26T23:15:41.1017786Z test_fx.py::TestFX::test_transformer_multi_outputs PASSED [0.0021s] [ 26%] 2025-08-26T23:15:41.1018378Z test_fx.py::TestFX::test_transformer_noop PASSED [0.0021s] [ 26%] 2025-08-26T23:15:41.1018624Z test_fx.py::TestFX::test_transformer_op_swap PASSED [0.0018s] [ 26%] 2025-08-26T23:15:41.1018889Z test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr PASSED [0.0018s] [ 26%] 2025-08-26T23:15:41.1019178Z test_fx.py::TestFX::test_tuple_no_subscript PASSED [0.0036s] [ 26%] 2025-08-26T23:15:41.1019420Z test_fx.py::TestFX::test_typename_print PASSED [0.0005s] [ 26%] 2025-08-26T23:15:41.1019655Z test_fx.py::TestFX::test_typename_print_pre_pep585 PASSED [0.0005s] [ 26%] 2025-08-26T23:15:41.1019889Z test_fx.py::TestFX::test_unpack PASSED [0.0016s] [ 27%] 2025-08-26T23:15:41.1020144Z test_fx.py::TestFX::test_unpack_dict_better_error PASSED [0.0012s] [ 27%] 2025-08-26T23:15:41.1020460Z test_fx.py::TestFX::test_unpack_list_better_error PASSED [0.0014s] [ 27%] 2025-08-26T23:15:41.1020706Z test_fx.py::TestFX::test_update_args_api PASSED [0.0011s] [ 27%] 2025-08-26T23:15:41.1020935Z test_fx.py::TestFX::test_update_args_kwargs_yells_at_you PASSED [0.0014s] [ 27%] 2025-08-26T23:15:41.1021160Z test_fx.py::TestFX::test_update_kwargs_api PASSED [0.0011s] [ 27%] 2025-08-26T23:15:41.1021447Z test_fx.py::TestFX::test_user_friendly_call_provenance_with_function PASSED [0.0065s] [ 27%] 2025-08-26T23:15:41.1021715Z test_fx.py::TestFX::test_user_friendly_call_provenance_with_module PASSED [0.0063s] [ 27%] 2025-08-26T23:15:41.1021970Z test_fx.py::TestFX::test_varargs_concrete PASSED [0.0014s] [ 27%] 2025-08-26T23:15:41.1022205Z test_fx.py::TestFX::test_wrap PASSED [0.0015s] [ 27%] 2025-08-26T23:15:41.1022435Z test_fx.py::TestFX::test_wrap_decorated_function PASSED [0.0014s] [ 27%] 2025-08-26T23:15:41.1022661Z test_fx.py::TestFX::test_wrap_fn_directly PASSED [0.0015s] [ 27%] 2025-08-26T23:15:41.1022890Z test_fx.py::TestFX::test_wrap_with_submodule PASSED [0.0595s] [ 27%] 2025-08-26T23:15:41.1023711Z test_fx.py::TestFX::test_wrapped_method PASSED [0.0151s] [ 28%] 2025-08-26T23:15:41.1023953Z test_fx.py::TestFX::test_wrapped_retrace PASSED [0.0037s] [ 28%] 2025-08-26T23:15:41.1024184Z test_fx.py::TestFX::test_wrapped_via_decorator PASSED [0.0018s] [ 28%] 2025-08-26T23:15:41.1024443Z test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed PASSED [0.0021s] [ 28%] 2025-08-26T23:15:41.1024706Z test_fx.py::TestFX::test_wrong_target_type PASSED [0.0006s] [ 28%] 2025-08-26T23:15:41.1024928Z test_fx.py::TestFX::test_wrong_topo PASSED [0.0007s] [ 28%] 2025-08-26T23:15:41.1025217Z test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function PASSED [0.0018s] [ 28%] 2025-08-26T23:15:41.1025532Z test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat PASSED [0.0007s] [ 28%] 2025-08-26T23:15:41.1025838Z test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat PASSED [0.0023s] [ 28%] 2025-08-26T23:15:41.1026169Z test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle PASSED [0.0036s] [ 28%] 2025-08-26T23:15:41.1026476Z test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface PASSED [0.0011s] [ 28%] 2025-08-26T23:15:41.1026803Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d SKIPPED [0.0002s] (Failing on python 3.12+) [ 28%] 2025-08-26T23:15:41.1027183Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 28%] 2025-08-26T23:15:41.1027549Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1027915Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d SKIPPED [0.0002s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1028322Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1028703Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1029134Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1029513Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1029879Z test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1030288Z test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1030705Z test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1031747Z test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1032090Z test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1032428Z test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 29%] 2025-08-26T23:15:41.1032780Z test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1033111Z test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1033639Z test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1034036Z test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1034392Z test_fx.py::TestFunctionalTracing::test_nn_functional_celu SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1034728Z test_fx.py::TestFunctionalTracing::test_nn_functional_celu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1035071Z test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle SKIPPED [0.0008s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1035409Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1035748Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1036072Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1036389Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1036742Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1037092Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 30%] 2025-08-26T23:15:41.1037439Z test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1037814Z test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1038179Z test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity SKIPPED [0.0002s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1038537Z test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1038907Z test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1039237Z test_fx.py::TestFunctionalTracing::test_nn_functional_dropout SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1039577Z test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1039951Z test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1040276Z test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1040687Z test_fx.py::TestFunctionalTracing::test_nn_functional_elu SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1041039Z test_fx.py::TestFunctionalTracing::test_nn_functional_elu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1041387Z test_fx.py::TestFunctionalTracing::test_nn_functional_embedding SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1041730Z test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag SKIPPED [0.0001s] (Failing on python 3.12+) [ 31%] 2025-08-26T23:15:41.1042077Z test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1042445Z test_fx.py::TestFunctionalTracing::test_nn_functional_fold SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1042787Z test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1043180Z test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1043573Z test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1043954Z test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1044343Z test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss SKIPPED [0.0002s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1044676Z test_fx.py::TestFunctionalTracing::test_nn_functional_gelu SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1044990Z test_fx.py::TestFunctionalTracing::test_nn_functional_glu SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1045335Z test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1045671Z test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1046031Z test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax SKIPPED [0.0001s] (Failing on python 3.12+) [ 32%] 2025-08-26T23:15:41.1046377Z test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1046715Z test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1047072Z test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1047408Z test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1047737Z test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1048727Z test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1049081Z test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1049452Z test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1049803Z test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1050137Z test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1050576Z test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1050910Z test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm SKIPPED [0.0002s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1051237Z test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu SKIPPED [0.0001s] (Failing on python 3.12+) [ 33%] 2025-08-26T23:15:41.1051609Z test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1051942Z test_fx.py::TestFunctionalTracing::test_nn_functional_linear SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1052289Z test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1052645Z test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1052985Z test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1053335Z test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1053664Z test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1053995Z test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1057615Z test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1057938Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1058256Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1058574Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1058889Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 34%] 2025-08-26T23:15:41.1059205Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1059522Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1059842Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1060147Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d SKIPPED [0.0002s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1060521Z test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1060819Z test_fx.py::TestFunctionalTracing::test_nn_functional_mish SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1061104Z test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1061423Z test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1061757Z test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1062122Z test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1062460Z test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1062849Z test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle SKIPPED [0.0001s] (Failing on python 3.12+) [ 35%] 2025-08-26T23:15:41.1063160Z test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1063454Z test_fx.py::TestFunctionalTracing::test_nn_functional_normalize SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1063742Z test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1064046Z test_fx.py::TestFunctionalTracing::test_nn_functional_pad SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1064347Z test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1064650Z test_fx.py::TestFunctionalTracing::test_nn_functional_pdist SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1064950Z test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1065260Z test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1065574Z test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss SKIPPED [0.0002s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1065872Z test_fx.py::TestFunctionalTracing::test_nn_functional_prelu SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1066162Z test_fx.py::TestFunctionalTracing::test_nn_functional_relu SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1066443Z test_fx.py::TestFunctionalTracing::test_nn_functional_relu6 SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1066726Z test_fx.py::TestFunctionalTracing::test_nn_functional_relu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 36%] 2025-08-26T23:15:41.1067017Z test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1067305Z test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1067593Z test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1067912Z test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1069561Z test_fx.py::TestFunctionalTracing::test_nn_functional_selu SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1069849Z test_fx.py::TestFunctionalTracing::test_nn_functional_selu_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1070129Z test_fx.py::TestFunctionalTracing::test_nn_functional_silu SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1070517Z test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1070829Z test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss SKIPPED [0.0002s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1071130Z test_fx.py::TestFunctionalTracing::test_nn_functional_softmax SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1071420Z test_fx.py::TestFunctionalTracing::test_nn_functional_softmin SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1071714Z test_fx.py::TestFunctionalTracing::test_nn_functional_softplus SKIPPED [0.0001s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1072042Z test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink SKIPPED [0.0002s] (Failing on python 3.12+) [ 37%] 2025-08-26T23:15:41.1072341Z test_fx.py::TestFunctionalTracing::test_nn_functional_threshold SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1072637Z test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_ SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1078498Z test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1078847Z test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1079172Z test_fx.py::TestFunctionalTracing::test_nn_functional_unfold SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1079486Z test_fx.py::TestFunctionalTracing::test_nn_functional_upsample SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1079798Z test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1080119Z test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest SKIPPED [0.0001s] (Failing on python 3.12+) [ 38%] 2025-08-26T23:15:41.1080541Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_H_cuda_float32 SKIPPED [0.0264s] (Only runs on cpu) [ 38%] 2025-08-26T23:15:41.1080904Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_T_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 38%] 2025-08-26T23:15:41.1081280Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___getitem___cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 38%] 2025-08-26T23:15:41.1081665Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___radd___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 38%] 2025-08-26T23:15:41.1083167Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rdiv___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1083557Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmatmul___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1083942Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmod___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1084316Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rmul___cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1084688Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rpow___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1085067Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive___rsub___cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1085464Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1085865Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__chunk_cat_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1086272Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1086691Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1087108Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1088526Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__softmax_backward_data_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1088939Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 39%] 2025-08-26T23:15:41.1089411Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1089845Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1090237Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_abs_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1090693Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_acos_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1091065Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_acosh_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1091434Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_add_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1091809Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addbmm_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1092184Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addcdiv_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1092558Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addcmul_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1093876Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmm_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1094265Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmm_decomposed_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1094652Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addmv_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1095025Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_addr_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 40%] 2025-08-26T23:15:41.1095399Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_alias_copy_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1095771Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_all_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1096146Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_allclose_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1096517Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_amax_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1096884Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_amin_cuda_float32 SKIPPED [0.0009s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1097257Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_aminmax_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1098522Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_angle_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1098893Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_any_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1099292Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_arange_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1099664Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argmax_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1100035Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argmin_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1100576Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argsort_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 41%] 2025-08-26T23:15:41.1100953Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_argwhere_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1101357Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_copy_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1101747Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1102147Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1102561Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_as_strided_scatter_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1103862Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_asin_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1104234Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_asinh_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1104608Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atan2_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1104978Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atan_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1105344Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atanh_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1105724Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_1d_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1106106Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_2d_cuda_float32 SKIPPED [0.0009s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1106487Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_atleast_3d_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 42%] 2025-08-26T23:15:41.1106866Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_baddbmm_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1107249Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bernoulli_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1107630Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bfloat16_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1108900Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_block_diag_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1109274Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bmm_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1109639Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bool_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1110052Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_shapes_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1110517Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_tensors_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1110915Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_broadcast_to_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1111340Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_bucketize_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1111715Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_byte_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1112098Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cartesian_prod_cuda_float32 SKIPPED [0.0009s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1112496Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cat_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 43%] 2025-08-26T23:15:41.1113840Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cauchy_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1114220Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cdist_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1114591Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cdouble_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1114961Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ceil_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1115333Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_cfloat_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1115704Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_chalf_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 44%] 2025-08-26T23:15:41.1116075Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_char_cuda_float32 SKIPPED [0.0008s] (Only runs on 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test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_grid_sampler_3d_cuda_float32 SKIPPED [0.0001s] (Skipped!) [ 52%] 2025-08-26T23:15:41.1166345Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_gt_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 52%] 2025-08-26T23:15:41.1166708Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_half_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 52%] 2025-08-26T23:15:41.1167086Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hash_tensor_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1167489Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_heaviside_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1167869Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_histc_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1168239Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hsplit_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1169528Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hstack_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1169899Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_hypot_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1170265Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_i0_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1170687Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_igamma_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 53%] 2025-08-26T23:15:41.1171061Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_igammac_cuda_float32 SKIPPED [0.0006s] (Only runs on 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test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_amin_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1174690Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_mean_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1175095Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_reduce_prod_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1175489Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_index_select_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1175868Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_inner_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1176267Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_int_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1176636Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isclose_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1177047Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isfinite_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1177418Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isin_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1177785Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isinf_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 54%] 2025-08-26T23:15:41.1178171Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_isnan_cuda_float32 SKIPPED [0.0007s] (Only runs on 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test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1182023Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_binary_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1182438Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1182854Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_jiterator_unary_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1183234Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_kron_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1183606Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_kthvalue_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1184920Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_ldexp_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1185287Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_le_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 55%] 2025-08-26T23:15:41.1185653Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lerp_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1186021Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_lgamma_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1186404Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cholesky_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1186803Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1187225Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cond_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1187610Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_cross_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1188030Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_det_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1188418Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_diagonal_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1189717Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eig_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1190127Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigh_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1190576Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigvals_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1190968Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 56%] 2025-08-26T23:15:41.1191447Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_householder_product_cuda_float32 SKIPPED [0.0002s] (skipCUDAIfRocm: test doesn't currently work on the ROCm stack) [ 56%] 2025-08-26T23:15:41.1191912Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_inv_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1192300Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1192699Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1193103Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1193653Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cuda_float32 SKIPPED [0.0001s] (skipCUDAIfRocm: test doesn't currently work on the ROCm stack) [ 57%] 2025-08-26T23:15:41.1194104Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lstsq_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1195456Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1195863Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1196251Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1196651Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1197047Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1197443Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1197848Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 57%] 2025-08-26T23:15:41.1198280Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1198695Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1199142Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1199531Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_norm_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1200980Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1201428Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1201829Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1202299Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cuda_float32 SKIPPED [0.0001s] (test is slow; run with PYTORCH_TEST_WITH_SLOW to enable test) [ 58%] 2025-08-26T23:15:41.1202747Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_qr_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1203134Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_slogdet_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1203527Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1203919Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 58%] 2025-08-26T23:15:41.1204324Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 59%] 2025-08-26T23:15:41.1204726Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_svd_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 59%] 2025-08-26T23:15:41.1206049Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_svdvals_cuda_float32 SKIPPED [0.0010s] (Only runs on cpu) [ 59%] 2025-08-26T23:15:41.1206448Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 59%] 2025-08-26T23:15:41.1206856Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 59%] 2025-08-26T23:15:41.1207253Z 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test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resolve_conj_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 79%] 2025-08-26T23:15:41.1343999Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_resolve_neg_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 79%] 2025-08-26T23:15:41.1344390Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_roll_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 79%] 2025-08-26T23:15:41.1346511Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_rot90_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 79%] 2025-08-26T23:15:41.1346894Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 79%] 2025-08-26T23:15:41.1347293Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_round_decimals_0_cuda_float32 SKIPPED 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test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1424573Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trace_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1424753Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_transpose_copy_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1424926Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_transpose_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1425104Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trapezoid_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1425273Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trapz_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 88%] 2025-08-26T23:15:41.1425455Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_triangular_solve_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1425622Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_tril_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1425786Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_triu_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1425960Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_true_divide_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1426126Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_trunc_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1426330Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unbind_copy_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1426497Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unbind_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1427638Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unflatten_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1427814Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unfold_copy_cuda_float32 SKIPPED [0.0009s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1427982Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unfold_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1428163Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_uniform_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1428352Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unique_consecutive_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1428519Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unique_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 89%] 2025-08-26T23:15:41.1428696Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsafe_chunk_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1428873Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsafe_split_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429052Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429226Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_unsqueeze_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429388Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429556Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_mean_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429743Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1429917Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_var_unbiased_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1430083Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vdot_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1430262Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_as_complex_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1430507Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_as_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1430683Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_copy_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 90%] 2025-08-26T23:15:41.1430847Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_view_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1431014Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vsplit_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1431184Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_vstack_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1432281Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_where_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1432447Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_xlogy_cuda_float32 SKIPPED [0.0008s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1432658Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zero__cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1432823Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zeros_cuda_float32 SKIPPED [0.0006s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1432999Z test_fx.py::TestOperatorSignaturesCUDA::test_get_torch_func_signature_exhaustive_zeros_like_cuda_float32 SKIPPED [0.0007s] (Only runs on cpu) [ 91%] 2025-08-26T23:15:41.1433119Z test_fx.py::TestVisionTracing::test_torchvision_models_alexnet PASSED [1.8476s] [ 91%] 2025-08-26T23:15:41.1433229Z test_fx.py::TestVisionTracing::test_torchvision_models_convnext_base PASSED [29.7312s] [ 91%] 2025-08-26T23:15:41.1433336Z test_fx.py::TestVisionTracing::test_torchvision_models_convnext_large PASSED [31.3625s] [ 91%] 2025-08-26T23:15:41.1433524Z test_fx.py::TestVisionTracing::test_torchvision_models_convnext_small PASSED [29.7920s] [ 91%] 2025-08-26T23:15:41.1433630Z test_fx.py::TestVisionTracing::test_torchvision_models_convnext_tiny PASSED [20.0510s] [ 91%] 2025-08-26T23:15:41.1433829Z test_fx.py::TestVisionTracing::test_torchvision_models_densenet121 [W826 22:43:46.585127371 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1433938Z [W826 22:43:46.764529856 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434039Z [W826 22:43:46.940076738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434141Z [W826 22:43:47.108073956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434241Z [W826 22:43:47.273761128 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434340Z [W826 22:43:47.480641032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434437Z [W826 22:43:47.674079662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434537Z [W826 22:43:47.877054867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434634Z [W826 22:43:48.085359678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434732Z [W826 22:43:48.287122701 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1434829Z [W826 22:43:48.457149918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1435841Z [W826 22:43:48.657132598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1435943Z [W826 22:43:48.848537989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436040Z [W826 22:43:48.031264331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436136Z [W826 22:43:49.219074447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436237Z [W826 22:43:49.436070218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436336Z [W826 22:44:01.324843025 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436433Z [W826 22:44:01.498236201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436529Z [W826 22:44:01.682394172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436628Z [W826 22:44:01.873206421 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436745Z [W826 22:44:02.057081087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436842Z [W826 22:44:02.258176280 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1436939Z [W826 22:44:02.449345745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437067Z [W826 22:44:02.653232095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437164Z [W826 22:44:02.857100686 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437262Z [W826 22:44:03.073080651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437359Z [W826 22:44:03.272583809 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437471Z [W826 22:44:03.463201791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437570Z [W826 22:44:03.639076248 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437667Z [W826 22:44:03.845060627 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437764Z [W826 22:44:04.052051980 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1437864Z [W826 22:44:04.247269813 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1438851Z [W826 22:44:15.587060024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1438950Z [W826 22:44:15.775049307 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439046Z [W826 22:44:15.953069482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439147Z [W826 22:44:16.148716467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439245Z [W826 22:44:16.346342363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439342Z [W826 22:44:16.551159099 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439438Z [W826 22:44:16.763039358 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439539Z [W826 22:44:16.955049840 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439635Z [W826 22:44:17.157040929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439732Z [W826 22:44:17.360041792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439829Z [W826 22:44:17.579029873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1439926Z [W826 22:44:17.778219164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440025Z [W826 22:44:17.970710638 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440124Z [W826 22:44:18.165124973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440220Z [W826 22:44:18.371167111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440319Z [W826 22:44:18.585868516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440420Z PASSED [48.1524s] [ 92%] 2025-08-26T23:15:41.1440611Z test_fx.py::TestVisionTracing::test_torchvision_models_densenet161 [W826 22:44:35.541122839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440708Z [W826 22:44:35.781120627 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440808Z [W826 22:44:35.005127991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1440934Z [W826 22:44:36.238176536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1441929Z [W826 22:44:36.453082229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442027Z [W826 22:44:36.688056275 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442164Z [W826 22:44:36.911075972 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442262Z [W826 22:44:37.147114683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442359Z [W826 22:44:37.372131711 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442455Z [W826 22:44:37.592220104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442571Z [W826 22:44:37.830249583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442672Z [W826 22:44:38.069169089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442769Z [W826 22:44:38.297100342 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442865Z [W826 22:44:38.536338784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1442965Z [W826 22:44:38.787175108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443061Z [W826 22:44:38.010091018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443158Z [W826 22:44:39.237112585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443254Z [W826 22:44:39.473166514 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443352Z [W826 22:44:39.687144491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443449Z [W826 22:44:39.903324514 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443546Z [W826 22:44:40.128950312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443642Z [W826 22:44:40.349016556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443745Z [W826 22:44:40.574100063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443841Z [W826 22:44:40.811070999 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1443937Z [W826 22:44:57.967339005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1444033Z [W826 22:44:58.218764599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445023Z [W826 22:44:58.448086632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445122Z [W826 22:44:58.665570285 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445220Z [W826 22:44:58.904219175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445317Z [W826 22:44:59.146095667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445421Z [W826 22:44:59.383241170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445517Z [W826 22:44:59.617161331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445615Z [W826 22:44:59.856143565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445712Z [W826 22:45:00.074209050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445812Z [W826 22:45:00.294157835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1445927Z [W826 22:45:00.520063680 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446024Z [W826 22:45:00.853167709 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446121Z [W826 22:45:01.137152718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446247Z [W826 22:45:01.354071190 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446346Z [W826 22:45:01.552088759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446444Z [W826 22:45:01.778310039 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446540Z [W826 22:45:01.968104953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446652Z [W826 22:45:02.147092904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446751Z [W826 22:45:02.343461658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446848Z [W826 22:45:02.580229707 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1446944Z [W826 22:45:02.809343472 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1447043Z [W826 22:45:03.052219628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448092Z [W826 22:45:03.298120878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448191Z [W826 22:45:23.155773600 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448288Z [W826 22:45:23.379415030 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448392Z [W826 22:45:23.607059938 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448494Z [W826 22:45:23.842184281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448589Z [W826 22:45:24.073122299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448686Z [W826 22:45:24.297231081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448788Z [W826 22:45:24.547052661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448886Z [W826 22:45:24.773041623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1448982Z [W826 22:45:24.006036130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449079Z [W826 22:45:25.230091163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449177Z [W826 22:45:25.471045638 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449274Z [W826 22:45:25.713041906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449370Z [W826 22:45:25.944031393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449467Z [W826 22:45:26.188031542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449568Z [W826 22:45:26.417031189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449665Z [W826 22:45:26.643032882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449761Z [W826 22:45:26.852033534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449859Z [W826 22:45:27.089029159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1449958Z [W826 22:45:27.312064828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1450086Z [W826 22:45:27.536054621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1451525Z [W826 22:45:27.775033156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1451626Z [W826 22:45:27.009032197 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1451766Z [W826 22:45:28.264032438 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1451864Z [W826 22:45:28.492228517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1451902Z PASSED [69.9276s] [ 92%] 2025-08-26T23:15:41.1452096Z test_fx.py::TestVisionTracing::test_torchvision_models_densenet169 [W826 22:45:42.001689504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452220Z [W826 22:45:43.206260924 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452323Z [W826 22:45:43.402079827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452419Z [W826 22:45:43.603240168 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452516Z [W826 22:45:43.814125302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452618Z [W826 22:45:43.022091220 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452715Z [W826 22:45:44.231049173 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452812Z [W826 22:45:44.432119566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1452909Z [W826 22:45:44.634197754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453007Z [W826 22:45:44.846208571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453108Z [W826 22:45:44.043056508 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453204Z [W826 22:45:45.246042452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453301Z [W826 22:45:45.450865298 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453399Z [W826 22:45:45.648192059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453496Z [W826 22:45:45.847626006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1453592Z [W826 22:45:45.046148028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1454748Z [W826 22:45:46.255089141 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1454851Z [W826 22:45:46.471716077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1454949Z [W826 22:45:46.682242817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455046Z [W826 22:45:46.900170883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455143Z [W826 22:45:47.097191447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455244Z [W826 22:45:47.306258319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455341Z [W826 22:45:47.518060438 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455437Z [W826 22:45:47.724206954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455533Z [W826 22:45:47.930079704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455632Z [W826 22:45:48.116023138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455754Z [W826 22:45:48.318160124 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455850Z [W826 22:45:48.529392363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1455947Z [W826 22:45:48.736121310 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456078Z [W826 22:45:48.945053753 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456177Z [W826 22:45:49.161045249 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456273Z [W826 22:45:49.361233495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456371Z [W826 22:46:03.451556064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456484Z [W826 22:46:03.666051783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456586Z [W826 22:46:03.880049949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456684Z [W826 22:46:04.073163373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1456781Z [W826 22:46:04.269053456 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458393Z [W826 22:46:04.465494549 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458503Z [W826 22:46:04.672058189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458601Z [W826 22:46:04.883009562 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458700Z [W826 22:46:05.083191678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458799Z [W826 22:46:05.282323960 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1458902Z [W826 22:46:05.486997878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459002Z [W826 22:46:05.690049102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459104Z [W826 22:46:05.898121278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459203Z [W826 22:46:06.110184754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459301Z [W826 22:46:06.324183730 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459398Z [W826 22:46:06.532093989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459498Z [W826 22:46:06.738057698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459599Z [W826 22:46:06.946475889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459697Z [W826 22:46:07.161047516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459793Z [W826 22:46:07.373121321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459890Z [W826 22:46:07.567048784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1459989Z [W826 22:46:07.776084315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1460088Z [W826 22:46:07.986053213 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1460184Z [W826 22:46:08.184043113 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1461778Z [W826 22:46:08.387044036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1461891Z [W826 22:46:08.600050198 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462025Z [W826 22:46:08.797048204 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462123Z [W826 22:46:08.014048723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462221Z [W826 22:46:09.221057206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462357Z [W826 22:46:09.446053234 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462454Z [W826 22:46:09.654052612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462554Z [W826 22:46:09.866262936 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462650Z [W826 22:46:25.082048119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462775Z [W826 22:46:25.295033320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462875Z [W826 22:46:25.510034221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1462972Z [W826 22:46:25.722027528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463067Z [W826 22:46:25.920035187 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463168Z [W826 22:46:26.131167847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463264Z [W826 22:46:26.350026289 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463361Z [W826 22:46:26.569026688 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463457Z [W826 22:46:26.782261556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463557Z [W826 22:46:26.003132568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463655Z [W826 22:46:27.224695948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463752Z [W826 22:46:27.421057724 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463848Z [W826 22:46:27.640037913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1463951Z [W826 22:46:27.835774527 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464051Z [W826 22:46:27.043057356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464152Z [W826 22:46:28.254236455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464248Z [W826 22:46:28.463170488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464348Z [W826 22:46:28.669135547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464446Z [W826 22:46:28.887078613 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464545Z [W826 22:46:29.096042106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1464641Z [W826 22:46:29.313091065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1465995Z [W826 22:46:29.509043796 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466106Z [W826 22:46:29.727045161 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466205Z [W826 22:46:29.934038364 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466302Z [W826 22:46:30.154098778 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466403Z [W826 22:46:30.364165624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466521Z [W826 22:46:30.573236654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466618Z [W826 22:46:30.774063211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466715Z [W826 22:46:30.979117444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466846Z [W826 22:46:31.191688542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1466943Z [W826 22:46:31.401073219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467040Z [W826 22:46:31.602885281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467079Z PASSED [63.0821s] [ 92%] 2025-08-26T23:15:41.1467299Z test_fx.py::TestVisionTracing::test_torchvision_models_densenet201 [W826 22:46:50.152297698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467399Z [W826 22:46:50.379171558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467496Z [W826 22:46:50.602245565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467592Z [W826 22:46:50.820155961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467695Z [W826 22:46:51.056145302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467794Z [W826 22:46:51.234117768 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467890Z [W826 22:46:51.468457463 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1467986Z [W826 22:46:51.706053809 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469296Z [W826 22:46:51.920183024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469405Z [W826 22:46:52.137589138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469507Z [W826 22:46:52.359121749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469607Z [W826 22:46:52.581270340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469714Z [W826 22:46:52.795316096 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469810Z [W826 22:46:52.015188342 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1469907Z [W826 22:46:53.259127491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470003Z [W826 22:46:53.498155806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470103Z [W826 22:46:53.743143499 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470202Z [W826 22:46:53.985169827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470299Z [W826 22:46:54.227640189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470455Z [W826 22:46:54.441140372 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470556Z [W826 22:46:54.671076276 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470653Z [W826 22:46:54.904233990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470750Z [W826 22:46:55.124101246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470848Z [W826 22:46:55.358918425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1470949Z [W826 22:46:55.592471282 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1471081Z [W826 22:46:55.837061031 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1471179Z [W826 22:46:56.061056305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1471275Z [W826 22:46:56.296117020 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1472616Z [W826 22:46:56.529131926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1472722Z [W826 22:46:56.741836621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1472821Z [W826 22:46:56.970128579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1472920Z [W826 22:46:57.209389410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473041Z [W826 22:47:15.540166922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473140Z [W826 22:47:15.761593745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473237Z [W826 22:47:15.994111919 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473334Z [W826 22:47:16.217050258 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473502Z [W826 22:47:16.446144345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473599Z [W826 22:47:16.693076448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473696Z [W826 22:47:16.921158599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473792Z [W826 22:47:17.153402676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473893Z [W826 22:47:17.387068302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1473991Z [W826 22:47:17.634794644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474090Z [W826 22:47:17.858167857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474189Z [W826 22:47:18.084083751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474291Z [W826 22:47:18.308052305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474388Z [W826 22:47:18.521283252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474485Z [W826 22:47:18.751045999 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1474581Z [W826 22:47:18.982283302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1475888Z [W826 22:47:19.211820131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1475994Z [W826 22:47:19.432069252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476094Z [W826 22:47:19.653066110 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476196Z [W826 22:47:19.901128757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476297Z [W826 22:47:20.119150892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476393Z [W826 22:47:20.348107799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476490Z [W826 22:47:20.586066300 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476587Z [W826 22:47:20.818143411 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476687Z [W826 22:47:21.050164142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476806Z [W826 22:47:21.275095971 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476902Z [W826 22:47:21.513213779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1476998Z [W826 22:47:21.726099831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477124Z [W826 22:47:21.949043391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477221Z [W826 22:47:22.193112518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477321Z [W826 22:47:22.421184309 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477420Z [W826 22:47:22.665700950 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477537Z [W826 22:47:41.735111946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477637Z [W826 22:47:41.929155577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477733Z [W826 22:47:42.149088892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477830Z [W826 22:47:42.389094842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1477928Z [W826 22:47:42.613038586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479217Z [W826 22:47:42.837045379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479321Z [W826 22:47:43.073136558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479420Z [W826 22:47:43.299124431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479521Z [W826 22:47:43.515108668 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479622Z [W826 22:47:43.744071235 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479717Z [W826 22:47:43.977122430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479814Z [W826 22:47:44.202735109 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1479917Z [W826 22:47:44.436045570 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480013Z [W826 22:47:44.661213787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480109Z [W826 22:47:44.900087983 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480206Z [W826 22:47:45.132785163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480304Z [W826 22:47:45.360180735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480463Z [W826 22:47:45.594361263 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480559Z [W826 22:47:45.821682756 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480656Z [W826 22:47:45.026050379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480756Z [W826 22:47:46.244176102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480854Z [W826 22:47:46.458032211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1480952Z [W826 22:47:46.687148807 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1481049Z [W826 22:47:46.921054368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1481146Z [W826 22:47:47.141164911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1482481Z [W826 22:47:47.364082151 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1482586Z [W826 22:47:47.572044370 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1482688Z [W826 22:47:47.788041455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1482833Z [W826 22:47:47.033032718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1482931Z [W826 22:47:48.269031589 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1483027Z [W826 22:47:48.487071583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1483123Z [W826 22:47:48.720175098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1483180Z PASSED [77.1412s] [ 92%] 2025-08-26T23:15:41.1483342Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_320_fpn PASSED [0.0798s] [ 92%] 2025-08-26T23:15:41.1483488Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_fpn PASSED [0.0743s] [ 92%] 2025-08-26T23:15:41.1483619Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn PASSED [0.1677s] [ 92%] 2025-08-26T23:15:41.1483759Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn_v2 PASSED [0.1853s] [ 92%] 2025-08-26T23:15:41.1483881Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_fcos_resnet50_fpn PASSED [0.1616s] [ 92%] 2025-08-26T23:15:41.1484015Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_keypointrcnn_resnet50_fpn PASSED [0.2543s] [ 92%] 2025-08-26T23:15:41.1484144Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn PASSED [0.1836s] [ 92%] 2025-08-26T23:15:41.1484277Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn_v2 PASSED [0.1990s] [ 92%] 2025-08-26T23:15:41.1484403Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn PASSED [0.1625s] [ 92%] 2025-08-26T23:15:41.1484533Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn_v2 PASSED [0.1776s] [ 93%] 2025-08-26T23:15:41.1484741Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssd300_vgg16 [W826 22:47:53.342165822 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1484842Z [W826 22:47:53.384134481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486176Z [W826 22:47:53.408201054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486290Z [W826 22:47:53.448898063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486390Z [W826 22:47:53.469128535 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486430Z PASSED [2.9330s] [ 93%] 2025-08-26T23:15:41.1486660Z test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssdlite320_mobilenet_v3_large [W826 22:47:54.818093870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486759Z [W826 22:47:54.818208178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486860Z [W826 22:47:55.214109730 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1486958Z [W826 22:47:55.214227018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487054Z [W826 22:47:55.620124087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487152Z [W826 22:47:55.620269475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487271Z [W826 22:47:58.133073958 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487369Z [W826 22:47:58.133207856 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487464Z [W826 22:47:58.760788684 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487561Z [W826 22:47:58.761040890 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487694Z [W826 22:47:59.423165142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487796Z [W826 22:47:59.423399028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1487892Z [W826 22:47:59.605683358 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1488008Z [W826 22:47:59.973103864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1488107Z [W826 22:47:59.973206672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1488205Z [W826 22:48:00.165176384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1488301Z [W826 22:48:00.513785277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1489618Z [W826 22:48:00.514034463 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1489729Z [W826 22:48:00.720176609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1489829Z [W826 22:48:01.204289084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1489928Z [W826 22:48:01.305207371 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490030Z [W826 22:48:01.552344222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490128Z [W826 22:48:01.654171986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490225Z [W826 22:48:01.906220011 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490321Z [W826 22:48:01.998156657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490482Z [W826 22:48:02.178480745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490523Z PASSED [8.6959s] [ 93%] 2025-08-26T23:15:41.1490719Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b0 [W826 22:48:02.647298897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490816Z [W826 22:48:02.647465734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1490915Z [W826 22:48:03.343068940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491014Z [W826 22:48:03.343157578 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491111Z [W826 22:48:03.025353759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491207Z [W826 22:48:03.025510906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491305Z [W826 22:48:04.729700280 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491404Z [W826 22:48:04.729821567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491501Z [W826 22:48:05.407757534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1491598Z [W826 22:48:05.407971041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1492895Z [W826 22:48:06.084093556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493033Z [W826 22:48:06.084192164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493132Z [W826 22:48:06.260139849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493230Z [W826 22:48:06.682530444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493327Z [W826 22:48:06.682709392 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493457Z [W826 22:48:06.875251572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493555Z [W826 22:48:07.300167518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493650Z [W826 22:48:07.300298926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493767Z [W826 22:48:07.504568665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493866Z [W826 22:48:07.906832661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1493963Z [W826 22:48:07.906938089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494059Z [W826 22:48:08.541704829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494157Z [W826 22:48:08.541876087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494255Z [W826 22:48:09.198292094 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494354Z [W826 22:48:09.198522080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494453Z [W826 22:48:09.854113901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494554Z [W826 22:48:09.854286988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494653Z [W826 22:48:09.044270248 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494750Z [W826 22:48:10.504944004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494846Z [W826 22:48:10.505087202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1494942Z [W826 22:48:10.691285989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496261Z [W826 22:48:11.132124941 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496366Z [W826 22:48:11.132282849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496465Z [W826 22:48:11.317955854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496568Z [W826 22:48:11.732418772 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496667Z [W826 22:48:11.732525040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496764Z [W826 22:48:11.932596394 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496860Z [W826 22:48:12.382105373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1496956Z [W826 22:48:12.382214221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497053Z [W826 22:48:12.592061784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497151Z [W826 22:48:13.227884249 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497249Z [W826 22:48:13.228006977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497349Z [W826 22:48:13.943396178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497470Z [W826 22:48:13.943560605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497568Z [W826 22:48:14.636106837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497666Z [W826 22:48:14.636228806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497767Z [W826 22:48:15.311088659 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497898Z [W826 22:48:15.311200967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1497995Z [W826 22:48:15.918108066 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1498091Z [W826 22:48:15.918249374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1498204Z [W826 22:48:16.633606255 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1498302Z [W826 22:48:16.633758293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1499614Z [W826 22:48:16.845675335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1499713Z [W826 22:48:17.280748926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1499813Z [W826 22:48:17.280909573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1499917Z [W826 22:48:17.479244404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500015Z [W826 22:48:17.910609722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500113Z [W826 22:48:17.910769119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500212Z [W826 22:48:18.101123793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500311Z [W826 22:48:18.516193770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500471Z [W826 22:48:18.516306038 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500567Z [W826 22:48:19.221084623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500663Z [W826 22:48:19.221220441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500760Z [W826 22:48:19.879075016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500857Z [W826 22:48:19.879169034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1500953Z [W826 22:48:20.590050374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501053Z [W826 22:48:20.590128193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501150Z [W826 22:48:20.787049036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501250Z [W826 22:48:21.204064054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501346Z [W826 22:48:21.204146563 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501444Z [W826 22:48:21.397287363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1501541Z [W826 22:48:21.832104968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1502856Z [W826 22:48:21.832259006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1502967Z [W826 22:48:21.026252192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503066Z [W826 22:48:22.448833395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503196Z [W826 22:48:22.448940384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503293Z [W826 22:48:22.636198874 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503390Z [W826 22:48:22.048540625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503487Z [W826 22:48:22.048620793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503622Z [W826 22:48:23.234044102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503719Z [W826 22:48:24.330162949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503817Z [W826 22:48:24.330335367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1503931Z [W826 22:48:24.017166657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504030Z [W826 22:48:24.017322305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504127Z [W826 22:48:25.682077144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504226Z [W826 22:48:25.682190922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504324Z [W826 22:48:26.402058774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504425Z [W826 22:48:26.402124413 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504521Z [W826 22:48:27.059038223 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504618Z [W826 22:48:27.059088292 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504716Z [W826 22:48:27.767145626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504816Z [W826 22:48:27.767234395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1504911Z [W826 22:48:27.950485497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1505009Z [W826 22:48:28.381057527 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1505106Z [W826 22:48:28.381107107 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1505208Z [W826 22:48:28.573063945 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506493Z [W826 22:48:28.992042883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506598Z [W826 22:48:28.992087803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506700Z [W826 22:48:29.192046538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506802Z [W826 22:48:29.622043397 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506900Z [W826 22:48:29.622105637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1506997Z [W826 22:48:30.331406291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507093Z [W826 22:48:30.331463790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507195Z [W826 22:48:30.000047880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507291Z [W826 22:48:30.000109419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507387Z [W826 22:48:31.696102618 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507485Z [W826 22:48:31.696228256 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507604Z [W826 22:48:31.896037555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507699Z [W826 22:48:32.299055078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507796Z [W826 22:48:32.299123667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1507892Z [W826 22:48:32.504052246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1508033Z [W826 22:48:32.959062959 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1508132Z [W826 22:48:32.959147579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1508232Z [W826 22:48:33.147054080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1508347Z [W826 22:48:33.572051265 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1508447Z [W826 22:48:33.572119694 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1509719Z [W826 22:48:33.765056578 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1509824Z [W826 22:48:34.182187814 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1509922Z [W826 22:48:34.182253793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510026Z [W826 22:48:34.374025484 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510064Z PASSED [32.3932s] [ 93%] 2025-08-26T23:15:41.1510260Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b1 [W826 22:48:35.074974898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510436Z [W826 22:48:35.075167625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510536Z [W826 22:48:35.499593569 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510632Z [W826 22:48:35.499779007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510728Z [W826 22:48:36.195165185 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510824Z [W826 22:48:36.195328142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1510925Z [W826 22:48:36.857813886 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511022Z [W826 22:48:36.857968994 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511122Z [W826 22:48:37.547223727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511220Z [W826 22:48:37.547451863 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511321Z [W826 22:48:38.194060002 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511417Z [W826 22:48:38.194133870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511513Z [W826 22:48:38.862082440 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511608Z [W826 22:48:38.862179209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511707Z [W826 22:48:39.544275002 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1511802Z [W826 22:48:39.544472279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513103Z [W826 22:48:40.208659487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513207Z [W826 22:48:40.208874903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513338Z [W826 22:48:40.399117719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513502Z [W826 22:48:40.806260258 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513600Z [W826 22:48:40.806416516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513695Z [W826 22:48:40.001232431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513829Z [W826 22:48:41.423162904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1513926Z [W826 22:48:41.423344981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514023Z [W826 22:48:41.606520144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514136Z [W826 22:48:41.995486034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514235Z [W826 22:48:41.995707750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514331Z [W826 22:48:42.169165084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514428Z [W826 22:48:42.565289533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514523Z [W826 22:48:42.565423731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514625Z [W826 22:48:43.087084901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514722Z [W826 22:48:43.087174189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514819Z [W826 22:48:43.506306475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1514918Z [W826 22:48:43.506415243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1515019Z [W826 22:48:43.929185423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1515114Z [W826 22:48:43.929324661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516409Z [W826 22:48:44.385117603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516514Z [W826 22:48:44.385253591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516619Z [W826 22:48:44.500063956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516717Z [W826 22:48:44.783461369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516816Z [W826 22:48:44.783556697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1516915Z [W826 22:48:44.920186176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517015Z [W826 22:48:45.176354528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517110Z [W826 22:48:45.176571864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517208Z [W826 22:48:45.307145077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517303Z [W826 22:48:45.596077854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517405Z [W826 22:48:45.596169733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517501Z [W826 22:48:45.734445407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517599Z [W826 22:48:45.027058008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517696Z [W826 22:48:45.027130907 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517815Z [W826 22:48:46.155267146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1517911Z [W826 22:48:46.422187382 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1518009Z [W826 22:48:46.422378359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1518105Z [W826 22:48:46.559073238 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1518238Z [W826 22:48:46.811082953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1518335Z [W826 22:48:46.811227661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1518432Z [W826 22:48:46.937121195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1519738Z [W826 22:48:47.312171669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1519847Z [W826 22:48:47.312288997 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1519946Z [W826 22:48:47.586198886 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520044Z [W826 22:48:47.586325604 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520140Z [W826 22:48:47.034276587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520243Z [W826 22:48:47.034433555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520400Z [W826 22:48:48.488167218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520498Z [W826 22:48:48.488298756 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520598Z [W826 22:48:48.952381381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520696Z [W826 22:48:48.952457370 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520792Z [W826 22:48:49.424095258 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520889Z [W826 22:48:49.424238056 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1520985Z [W826 22:48:49.865232356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521084Z [W826 22:48:49.865369074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521183Z [W826 22:48:50.317096448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521281Z [W826 22:48:50.317216416 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521382Z [W826 22:48:50.737168290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521478Z [W826 22:48:50.737318576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521577Z [W826 22:48:50.864188746 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1521673Z [W826 22:48:51.138104575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1522950Z [W826 22:48:51.138251913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523058Z [W826 22:48:51.263130723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523156Z [W826 22:48:51.541169328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523256Z [W826 22:48:51.541279186 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523355Z [W826 22:48:51.657092625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523485Z [W826 22:48:51.928069779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523582Z [W826 22:48:51.928145908 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523679Z [W826 22:48:51.027794506 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523776Z [W826 22:48:52.303342739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1523908Z [W826 22:48:52.303527966 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524006Z [W826 22:48:52.719144936 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524102Z [W826 22:48:52.719252805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524218Z [W826 22:48:53.187092692 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524317Z [W826 22:48:53.187207410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524414Z [W826 22:48:53.638154287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524513Z [W826 22:48:53.638313404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524613Z [W826 22:48:54.084219957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524715Z [W826 22:48:54.084393726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524812Z [W826 22:48:54.213058957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1524908Z [W826 22:48:54.501115448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526200Z [W826 22:48:54.501259486 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526307Z [W826 22:48:54.627109681 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526406Z [W826 22:48:54.893060281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526504Z [W826 22:48:54.893139000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526602Z [W826 22:48:54.013610088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526703Z [W826 22:48:55.290346624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526799Z [W826 22:48:55.290529921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526896Z [W826 22:48:55.420034509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1526995Z [W826 22:48:55.718131947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527093Z [W826 22:48:55.718273805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527190Z [W826 22:48:55.833435414 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527287Z [W826 22:48:56.124119994 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527386Z [W826 22:48:56.124216423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527482Z [W826 22:48:56.256138364 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527579Z [W826 22:48:56.538074940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527677Z [W826 22:48:56.538196528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527778Z [W826 22:48:56.665072637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1527904Z [W826 22:48:57.513053509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1528000Z [W826 22:48:57.513134978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1528096Z [W826 22:48:57.773037132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1528193Z [W826 22:48:57.773074251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1529517Z [W826 22:48:58.209029898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1529624Z [W826 22:48:58.209064538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1529721Z [W826 22:48:58.669039625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1529841Z [W826 22:48:58.669077496 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1529940Z [W826 22:48:59.129171721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530036Z [W826 22:48:59.129378148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530133Z [W826 22:48:59.636264385 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530230Z [W826 22:48:59.636414012 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530332Z [W826 22:49:00.070340081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530492Z [W826 22:49:00.070555327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530589Z [W826 22:49:00.473146427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530689Z [W826 22:49:00.473255336 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530787Z [W826 22:49:00.916183985 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530884Z [W826 22:49:00.916342384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1530981Z [W826 22:49:00.033056659 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531081Z [W826 22:49:01.296462188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531182Z [W826 22:49:01.296584466 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531279Z [W826 22:49:01.408057633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531377Z [W826 22:49:01.672224582 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531476Z [W826 22:49:01.672399379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1531574Z [W826 22:49:01.795125661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1532928Z [W826 22:49:02.107146944 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533026Z [W826 22:49:02.107323082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533125Z [W826 22:49:02.226079536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533229Z [W826 22:49:02.482197958 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533326Z [W826 22:49:02.482263007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533423Z [W826 22:49:02.929077607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533522Z [W826 22:49:02.929159046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533652Z [W826 22:49:03.404092084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533748Z [W826 22:49:03.404218802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533844Z [W826 22:49:03.838076791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1533940Z [W826 22:49:03.838186240 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534071Z [W826 22:49:04.299060213 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534169Z [W826 22:49:04.299122342 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534266Z [W826 22:49:04.499033699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534388Z [W826 22:49:04.784093556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534490Z [W826 22:49:04.784228214 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534586Z [W826 22:49:04.914109387 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534683Z [W826 22:49:05.201066106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1534779Z [W826 22:49:05.201134894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536106Z [W826 22:49:05.349043460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536213Z [W826 22:49:05.775174028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536313Z [W826 22:49:05.775334465 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536414Z [W826 22:49:05.958107946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536516Z [W826 22:49:06.238211459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536613Z [W826 22:49:06.238378057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536710Z [W826 22:49:06.353102113 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536805Z [W826 22:49:06.621271049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1536908Z [W826 22:49:06.621433747 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537004Z [W826 22:49:06.749048274 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537103Z [W826 22:49:06.024151805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537201Z [W826 22:49:06.024289903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537301Z [W826 22:49:07.149096714 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537339Z PASSED [32.6834s] [ 93%] 2025-08-26T23:15:41.1537537Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b2 [W826 22:49:07.613106509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537638Z [W826 22:49:07.613224568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537738Z [W826 22:49:07.879730020 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537834Z [W826 22:49:07.879856758 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1537931Z [W826 22:49:08.320084089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1538028Z [W826 22:49:08.320182618 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539381Z [W826 22:49:08.760129644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539486Z [W826 22:49:08.760269082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539585Z [W826 22:49:09.194148271 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539684Z [W826 22:49:09.194312538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539815Z [W826 22:49:09.650964497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1539912Z [W826 22:49:09.651139214 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540009Z [W826 22:49:10.104406176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540121Z [W826 22:49:10.104497314 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540221Z [W826 22:49:10.613118804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540317Z [W826 22:49:10.613251712 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540470Z [W826 22:49:11.061107896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540567Z [W826 22:49:11.061234744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540666Z [W826 22:49:11.175096963 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540763Z [W826 22:49:11.444165107 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540865Z [W826 22:49:11.453461203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1540967Z [W826 22:49:11.562286570 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1541071Z [W826 22:49:11.853106299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1541168Z [W826 22:49:11.853245177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1541264Z [W826 22:49:11.973847532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1541360Z [W826 22:49:12.238502733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1542704Z [W826 22:49:12.238594703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1542809Z [W826 22:49:12.363127837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1542908Z [W826 22:49:12.612138099 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543009Z [W826 22:49:12.612271957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543107Z [W826 22:49:13.058143532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543203Z [W826 22:49:13.058296989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543300Z [W826 22:49:13.457120096 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543396Z [W826 22:49:13.457252805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543495Z [W826 22:49:13.885184795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543592Z [W826 22:49:13.885394563 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543689Z [W826 22:49:14.313163125 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543786Z [W826 22:49:14.313303813 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1543914Z [W826 22:49:14.440241061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544010Z [W826 22:49:14.761169198 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544109Z [W826 22:49:14.761346305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544206Z [W826 22:49:14.885201620 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544344Z [W826 22:49:15.155530884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544440Z [W826 22:49:15.155711751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544536Z [W826 22:49:15.282163027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544662Z [W826 22:49:15.539079646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1544763Z [W826 22:49:15.539162736 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546083Z [W826 22:49:15.666402079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546191Z [W826 22:49:15.921585655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546290Z [W826 22:49:15.921759603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546394Z [W826 22:49:15.042228461 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546491Z [W826 22:49:16.313348752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546589Z [W826 22:49:16.313482220 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546688Z [W826 22:49:16.445520610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546787Z [W826 22:49:16.720980045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546883Z [W826 22:49:16.721139152 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1546980Z [W826 22:49:16.842190581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547076Z [W826 22:49:17.268144062 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547174Z [W826 22:49:17.268296990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547270Z [W826 22:49:17.576059478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547367Z [W826 22:49:17.576121117 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547464Z [W826 22:49:18.068221720 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547563Z [W826 22:49:18.068381918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547661Z [W826 22:49:18.596098744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547758Z [W826 22:49:18.596213502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547854Z [W826 22:49:19.092229617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1547952Z [W826 22:49:19.092448783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549287Z [W826 22:49:19.589328804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549395Z [W826 22:49:19.589463882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549502Z [W826 22:49:20.051106533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549637Z [W826 22:49:20.051233431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549734Z [W826 22:49:20.514850384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549831Z [W826 22:49:20.515027951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1549928Z [W826 22:49:20.985184142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550055Z [W826 22:49:20.985392839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550152Z [W826 22:49:21.111070816 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550249Z [W826 22:49:21.389758472 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550428Z [W826 22:49:21.389980229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550527Z [W826 22:49:21.517570906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550625Z [W826 22:49:21.800174091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550721Z [W826 22:49:21.800367418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550819Z [W826 22:49:21.919193851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1550921Z [W826 22:49:22.187646935 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551019Z [W826 22:49:22.187821101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551114Z [W826 22:49:22.320222116 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551214Z [W826 22:49:22.570261992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551312Z [W826 22:49:22.570428398 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551408Z [W826 22:49:22.993131490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551505Z [W826 22:49:22.993315536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551602Z [W826 22:49:23.445132810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551702Z [W826 22:49:23.445321398 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1551799Z [W826 22:49:23.875288727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556323Z [W826 22:49:23.875413145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556429Z [W826 22:49:24.322060327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556529Z [W826 22:49:24.322142576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556626Z [W826 22:49:24.448044060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556722Z [W826 22:49:24.746201046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556820Z [W826 22:49:24.746443093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1556920Z [W826 22:49:24.876477393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557019Z [W826 22:49:25.180300102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557116Z [W826 22:49:25.180629796 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557214Z [W826 22:49:25.310105906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557344Z [W826 22:49:25.600127427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557442Z [W826 22:49:25.600266794 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557538Z [W826 22:49:25.721439101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557635Z [W826 22:49:25.000328203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557773Z [W826 22:49:25.000449952 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557872Z [W826 22:49:26.116267131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1557968Z [W826 22:49:26.392319236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1558085Z [W826 22:49:26.392549404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1558184Z [W826 22:49:26.503298940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1558280Z [W826 22:49:26.785127717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1559824Z [W826 22:49:26.785288954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1559927Z [W826 22:49:26.917090718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560036Z [W826 22:49:28.729534852 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560132Z [W826 22:49:28.729693799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560231Z [W826 22:49:28.001170045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560330Z [W826 22:49:28.001359003 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560498Z [W826 22:49:29.427842775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560595Z [W826 22:49:29.427997913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560692Z [W826 22:49:29.896141275 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560789Z [W826 22:49:29.896310322 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560888Z [W826 22:49:30.373758401 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1560984Z [W826 22:49:30.373969698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561082Z [W826 22:49:30.826151076 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561179Z [W826 22:49:30.826282323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561277Z [W826 22:49:31.270109180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561375Z [W826 22:49:31.270231028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561472Z [W826 22:49:31.746080111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561570Z [W826 22:49:31.746182130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561668Z [W826 22:49:32.228164509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561763Z [W826 22:49:32.228276119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1561860Z [W826 22:49:32.350044226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563149Z [W826 22:49:32.655182974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563285Z [W826 22:49:32.655262383 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563383Z [W826 22:49:32.763094076 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563481Z [W826 22:49:32.017538923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563577Z [W826 22:49:32.017662650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563713Z [W826 22:49:33.153195157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563810Z [W826 22:49:33.424265259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1563906Z [W826 22:49:33.424336838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564018Z [W826 22:49:33.553051189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564117Z [W826 22:49:33.815167709 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564213Z [W826 22:49:33.815357206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564310Z [W826 22:49:34.252625703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564406Z [W826 22:49:34.252785441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564508Z [W826 22:49:34.683100544 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564606Z [W826 22:49:34.683272172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564705Z [W826 22:49:35.095061691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564804Z [W826 22:49:35.095142059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564903Z [W826 22:49:35.514100628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1564999Z [W826 22:49:35.514225596 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1565095Z [W826 22:49:35.632115513 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1565191Z [W826 22:49:35.891958138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566472Z [W826 22:49:35.892100366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566576Z [W826 22:49:35.010393937 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566674Z [W826 22:49:36.278084961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566774Z [W826 22:49:36.278179480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566876Z [W826 22:49:36.408066733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1566971Z [W826 22:49:36.659118093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567068Z [W826 22:49:36.659172012 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567163Z [W826 22:49:36.775186928 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567262Z [W826 22:49:36.023061407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567358Z [W826 22:49:36.023150846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567454Z [W826 22:49:37.133786515 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567552Z [W826 22:49:37.380107627 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567673Z [W826 22:49:37.380235485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567768Z [W826 22:49:37.503039558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567865Z [W826 22:49:37.783092041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1567962Z [W826 22:49:37.783251939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1568100Z [W826 22:49:37.898063034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1568140Z PASSED [30.7492s] [ 93%] 2025-08-26T23:15:41.1568341Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b3 [W826 22:49:38.375511023 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1568453Z [W826 22:49:38.375812119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1569728Z [W826 22:49:38.662335763 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1569834Z [W826 22:49:38.662529311 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1569933Z [W826 22:49:39.123170188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570031Z [W826 22:49:39.123361455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570133Z [W826 22:49:39.569294218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570230Z [W826 22:49:39.569517906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570326Z [W826 22:49:39.009304274 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570494Z [W826 22:49:39.009530630 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570593Z [W826 22:49:40.460640725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570689Z [W826 22:49:40.460896481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570785Z [W826 22:49:40.892121800 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570882Z [W826 22:49:40.892273817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1570979Z [W826 22:49:41.328220385 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571075Z [W826 22:49:41.328372382 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571171Z [W826 22:49:41.780137746 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571269Z [W826 22:49:41.780277934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571369Z [W826 22:49:41.899077368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571468Z [W826 22:49:42.163135908 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571565Z [W826 22:49:42.163292635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571661Z [W826 22:49:42.290792455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1571759Z [W826 22:49:42.554346493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573053Z [W826 22:49:42.554483251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573158Z [W826 22:49:42.667214088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573258Z [W826 22:49:42.934751884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573388Z [W826 22:49:42.934856033 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573485Z [W826 22:49:43.089090921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573581Z [W826 22:49:43.350251286 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573678Z [W826 22:49:43.350481742 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573812Z [W826 22:49:43.466514968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1573910Z [W826 22:49:43.740113492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574006Z [W826 22:49:43.740259719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574121Z [W826 22:49:44.139603759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574220Z [W826 22:49:44.139775477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574317Z [W826 22:49:44.546120699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574414Z [W826 22:49:44.546253727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574513Z [W826 22:49:44.956147615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574615Z [W826 22:49:44.956294883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574712Z [W826 22:49:45.376090229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574809Z [W826 22:49:45.376210487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1574909Z [W826 22:49:45.845158926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1575006Z [W826 22:49:45.845331984 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576294Z [W826 22:49:45.947127358 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576399Z [W826 22:49:46.228260306 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576499Z [W826 22:49:46.228422774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576604Z [W826 22:49:46.340177666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576703Z [W826 22:49:46.605290329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576800Z [W826 22:49:46.605458567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576899Z [W826 22:49:46.723133118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1576999Z [W826 22:49:46.995524879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577095Z [W826 22:49:46.995717786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577192Z [W826 22:49:47.133169463 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577289Z [W826 22:49:47.394056032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577390Z [W826 22:49:47.394145980 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577487Z [W826 22:49:47.525198066 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577584Z [W826 22:49:47.772315087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577682Z [W826 22:49:47.772453604 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577801Z [W826 22:49:47.886226065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577900Z [W826 22:49:48.145266221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1577996Z [W826 22:49:48.145450918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1578094Z [W826 22:49:48.258234195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1578221Z [W826 22:49:48.510129482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1578320Z [W826 22:49:48.510364278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1579610Z [W826 22:49:48.634167684 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1579733Z [W826 22:49:48.038169373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1579834Z [W826 22:49:48.038244772 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1579936Z [W826 22:49:49.321128203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580032Z [W826 22:49:49.321286881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580129Z [W826 22:49:49.765122386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580230Z [W826 22:49:49.765249854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580327Z [W826 22:49:50.191974653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580482Z [W826 22:49:50.192171510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580583Z [W826 22:49:50.636385160 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580682Z [W826 22:49:50.636505259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580779Z [W826 22:49:51.103094844 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580875Z [W826 22:49:51.103217753 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1580972Z [W826 22:49:51.564111716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581072Z [W826 22:49:51.564255314 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581171Z [W826 22:49:51.023088870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581271Z [W826 22:49:51.023192608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581371Z [W826 22:49:52.497557915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581468Z [W826 22:49:52.497826561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581565Z [W826 22:49:52.617115986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1581661Z [W826 22:49:52.907141237 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1582985Z [W826 22:49:52.907298105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583088Z [W826 22:49:52.027188312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583188Z [W826 22:49:53.318403894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583286Z [W826 22:49:53.318588042 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583386Z [W826 22:49:53.448150229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583511Z [W826 22:49:53.740340376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583609Z [W826 22:49:53.740437586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583705Z [W826 22:49:53.856109656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583802Z [W826 22:49:54.148149357 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1583933Z [W826 22:49:54.148333434 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584030Z [W826 22:49:54.259120831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584128Z [W826 22:49:54.531075299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584244Z [W826 22:49:54.531149958 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584345Z [W826 22:49:54.955411954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584446Z [W826 22:49:54.955553403 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584543Z [W826 22:49:55.373215571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584640Z [W826 22:49:55.373454817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584743Z [W826 22:49:55.780260943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584841Z [W826 22:49:55.780468889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1584937Z [W826 22:49:56.204071867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586240Z [W826 22:49:56.204183955 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586347Z [W826 22:49:56.649362060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586447Z [W826 22:49:56.649480079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586545Z [W826 22:49:56.791260249 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586644Z [W826 22:49:57.056119326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586746Z [W826 22:49:57.056278004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586844Z [W826 22:49:57.179116425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1586942Z [W826 22:49:57.441069268 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587042Z [W826 22:49:57.441157087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587140Z [W826 22:49:57.563158260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587237Z [W826 22:49:57.835133749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587333Z [W826 22:49:57.835303676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587430Z [W826 22:49:57.967308587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587527Z [W826 22:49:58.238138163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587627Z [W826 22:49:58.238298930 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587725Z [W826 22:49:58.352084270 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587824Z [W826 22:49:58.612069404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1587942Z [W826 22:49:58.612165072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1588040Z [W826 22:49:58.751102006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1588136Z [W826 22:49:58.008053036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1588233Z [W826 22:49:58.008135614 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1589573Z [W826 22:49:59.121038867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1589677Z [W826 22:49:59.286120449 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1589777Z [W826 22:49:59.286352357 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1589893Z [W826 22:49:59.365122806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1589993Z [W826 22:50:00.153201288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590088Z [W826 22:50:00.153332716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590185Z [W826 22:50:00.356168338 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590281Z [W826 22:50:00.356298946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590521Z [W826 22:50:00.662072845 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590618Z [W826 22:50:00.662185072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590715Z [W826 22:50:00.968131228 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590814Z [W826 22:50:00.968267906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1590916Z [W826 22:50:01.483135940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591014Z [W826 22:50:01.483296878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591113Z [W826 22:50:01.972165702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591209Z [W826 22:50:01.972352508 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591310Z [W826 22:50:02.402128131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591406Z [W826 22:50:02.402276939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591504Z [W826 22:50:02.843837640 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1591603Z [W826 22:50:02.843964147 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1592927Z [W826 22:50:03.268101846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593036Z [W826 22:50:03.268224254 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593135Z [W826 22:50:03.393477359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593233Z [W826 22:50:03.580180498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593337Z [W826 22:50:03.580350236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593484Z [W826 22:50:03.651099718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593582Z [W826 22:50:03.890123842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593682Z [W826 22:50:03.890267751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593814Z [W826 22:50:03.996174631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1593910Z [W826 22:50:04.208110454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594007Z [W826 22:50:04.208235192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594103Z [W826 22:50:04.319092758 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594235Z [W826 22:50:04.585152506 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594332Z [W826 22:50:04.585261565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594431Z [W826 22:50:04.686124854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594550Z [W826 22:50:04.895098311 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594649Z [W826 22:50:04.895215949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594746Z [W826 22:50:05.220100044 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594842Z [W826 22:50:05.220208883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1594939Z [W826 22:50:05.545550260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1595037Z [W826 22:50:05.545707698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596362Z [W826 22:50:05.928562521 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596475Z [W826 22:50:05.928725889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596577Z [W826 22:50:06.344718873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596678Z [W826 22:50:06.344888070 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596775Z [W826 22:50:06.754129968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596872Z [W826 22:50:06.754229467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1596968Z [W826 22:50:06.871061970 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597071Z [W826 22:50:07.123393001 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597167Z [W826 22:50:07.123568178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597264Z [W826 22:50:07.250742272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597363Z [W826 22:50:07.505112121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597460Z [W826 22:50:07.505246339 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597557Z [W826 22:50:07.625083147 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597653Z [W826 22:50:07.896120290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597748Z [W826 22:50:07.896270588 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597848Z [W826 22:50:07.956058808 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1597946Z [W826 22:50:08.122076455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598045Z [W826 22:50:08.122196124 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598144Z [W826 22:50:08.219659555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598267Z [W826 22:50:08.441081891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598363Z [W826 22:50:08.441196759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598461Z [W826 22:50:08.547427636 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1598557Z [W826 22:50:08.734096396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601169Z [W826 22:50:08.734221014 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601273Z [W826 22:50:08.821280005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601372Z [W826 22:50:08.018234287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601489Z [W826 22:50:08.018490103 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601589Z [W826 22:50:09.128150237 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601628Z PASSED [31.2338s] [ 93%] 2025-08-26T23:15:41.1601827Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b4 [W826 22:50:09.655160194 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1601925Z [W826 22:50:09.655291902 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602026Z [W826 22:50:09.880611408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602124Z [W826 22:50:09.880756245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602222Z [W826 22:50:10.295413740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602319Z [W826 22:50:10.295656976 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602416Z [W826 22:50:10.756161346 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602515Z [W826 22:50:10.756324093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602614Z [W826 22:50:11.248335499 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602711Z [W826 22:50:11.248463726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602812Z [W826 22:50:11.704128361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1602908Z [W826 22:50:11.704254169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1603004Z [W826 22:50:12.179099088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1603102Z [W826 22:50:12.179230586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1604564Z [W826 22:50:12.608062382 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1604674Z [W826 22:50:12.608145601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1604772Z [W826 22:50:12.048858805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1604869Z [W826 22:50:13.049036882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1604970Z [W826 22:50:13.453071341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605067Z [W826 22:50:13.453151949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605163Z [W826 22:50:13.902090946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605262Z [W826 22:50:13.902206624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605387Z [W826 22:50:14.310192852 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605485Z [W826 22:50:14.310269671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605581Z [W826 22:50:14.801191333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605678Z [W826 22:50:14.801377940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605816Z [W826 22:50:15.247097217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1605914Z [W826 22:50:15.247217255 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606011Z [W826 22:50:15.693076230 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606126Z [W826 22:50:15.693177158 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606225Z [W826 22:50:16.182218219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606322Z [W826 22:50:16.182396417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606419Z [W826 22:50:16.584084811 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606516Z [W826 22:50:16.584202379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1606615Z [W826 22:50:16.971065121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1607905Z [W826 22:50:16.971177159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608011Z [W826 22:50:17.394114216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608113Z [W826 22:50:17.394270025 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608212Z [W826 22:50:17.824052497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608309Z [W826 22:50:17.824132775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608405Z [W826 22:50:18.277088661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608501Z [W826 22:50:18.277202059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608603Z [W826 22:50:18.708132164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608700Z [W826 22:50:18.712094403 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608797Z [W826 22:50:19.129168780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608897Z [W826 22:50:19.129362287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1608996Z [W826 22:50:19.258840277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609093Z [W826 22:50:19.514950729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609190Z [W826 22:50:19.515138516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609289Z [W826 22:50:19.631211741 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609386Z [W826 22:50:19.884672904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609483Z [W826 22:50:19.884874411 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609578Z [W826 22:50:19.974305936 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609677Z [W826 22:50:20.252218123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1609795Z [W826 22:50:20.252445349 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611117Z [W826 22:50:20.356681637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611226Z [W826 22:50:20.617302820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611326Z [W826 22:50:20.617542546 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611465Z [W826 22:50:20.731600633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611563Z [W826 22:50:20.013143334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611659Z [W826 22:50:20.013340171 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611773Z [W826 22:50:21.142865779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611873Z [W826 22:50:21.409186465 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1611970Z [W826 22:50:21.409370052 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612066Z [W826 22:50:21.531292237 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612164Z [W826 22:50:21.772084515 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612265Z [W826 22:50:21.772201483 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612365Z [W826 22:50:21.882291230 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612461Z [W826 22:50:22.134115278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612561Z [W826 22:50:22.134259576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612657Z [W826 22:50:22.559057865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612754Z [W826 22:50:22.559177243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612850Z [W826 22:50:23.108045855 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1612947Z [W826 22:50:23.108108074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1613048Z [W826 22:50:23.364041159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1613145Z [W826 22:50:23.364089808 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614416Z [W826 22:50:23.815299321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614526Z [W826 22:50:23.815358900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614625Z [W826 22:50:24.257112408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614722Z [W826 22:50:24.257172577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614818Z [W826 22:50:24.749041605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1614916Z [W826 22:50:24.749103924 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615017Z [W826 22:50:25.217054918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615114Z [W826 22:50:25.217106657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615210Z [W826 22:50:25.677767915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615308Z [W826 22:50:25.677900533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615428Z [W826 22:50:26.121052179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615528Z [W826 22:50:26.121121108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615625Z [W826 22:50:26.601656510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615722Z [W826 22:50:26.601745579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615848Z [W826 22:50:27.052162883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1615945Z [W826 22:50:27.052287241 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1616042Z [W826 22:50:27.541292793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1616160Z [W826 22:50:27.541459531 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1616259Z [W826 22:50:27.954268423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1616355Z [W826 22:50:27.954421211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1616451Z [W826 22:50:28.382249924 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1617816Z [W826 22:50:28.382433141 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1617920Z [W826 22:50:28.813242667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618018Z [W826 22:50:28.813472953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618117Z [W826 22:50:29.236058836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618217Z [W826 22:50:29.236152405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618316Z [W826 22:50:29.717411545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618413Z [W826 22:50:29.717622612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618510Z [W826 22:50:30.144154784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618607Z [W826 22:50:30.144334071 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618705Z [W826 22:50:30.611234433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618802Z [W826 22:50:30.611366591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618898Z [W826 22:50:30.031392402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1618999Z [W826 22:50:30.031599389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619096Z [W826 22:50:31.466806188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619193Z [W826 22:50:31.467020825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619289Z [W826 22:50:31.904286941 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619386Z [W826 22:50:31.904488929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619483Z [W826 22:50:32.326130446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619580Z [W826 22:50:32.326287473 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1619675Z [W826 22:50:32.757152419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621025Z [W826 22:50:32.757314847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621165Z [W826 22:50:32.877156544 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621262Z [W826 22:50:33.148075548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621360Z [W826 22:50:33.148210016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621457Z [W826 22:50:33.277098884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621589Z [W826 22:50:33.566216049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621685Z [W826 22:50:33.566293698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621782Z [W826 22:50:33.722085733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1621900Z [W826 22:50:33.991085528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622000Z [W826 22:50:33.991435582 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622096Z [W826 22:50:34.120294631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622195Z [W826 22:50:34.382676656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622291Z [W826 22:50:34.382859303 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622392Z [W826 22:50:34.507197522 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622489Z [W826 22:50:34.759717850 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622587Z [W826 22:50:34.760010134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622685Z [W826 22:50:34.870625404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622784Z [W826 22:50:35.125543584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622880Z [W826 22:50:35.125662872 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1622977Z [W826 22:50:35.248353277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1623073Z [W826 22:50:35.513639977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624418Z [W826 22:50:35.513842674 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624524Z [W826 22:50:35.656536100 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624624Z [W826 22:50:35.943248712 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624724Z [W826 22:50:35.943370950 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624825Z [W826 22:50:36.387135417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1624921Z [W826 22:50:36.387322194 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625019Z [W826 22:50:37.640775052 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625114Z [W826 22:50:37.640902680 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625216Z [W826 22:50:37.906072654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625312Z [W826 22:50:37.906162573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625409Z [W826 22:50:38.373113433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625509Z [W826 22:50:38.373267940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625630Z [W826 22:50:38.807972437 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625726Z [W826 22:50:38.808154304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625823Z [W826 22:50:39.257092501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1625919Z [W826 22:50:39.257213340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1626048Z [W826 22:50:39.701083156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1626145Z [W826 22:50:39.701181683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1626243Z [W826 22:50:40.179414430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1626355Z [W826 22:50:40.179598787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1627671Z [W826 22:50:40.635730185 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1627778Z [W826 22:50:40.635885582 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1627876Z [W826 22:50:41.217323393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1627971Z [W826 22:50:41.217475380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628074Z [W826 22:50:41.917111403 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628170Z [W826 22:50:41.917226471 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628267Z [W826 22:50:42.714125919 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628365Z [W826 22:50:42.714261757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628465Z [W826 22:50:43.275383499 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628560Z [W826 22:50:43.275532727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628656Z [W826 22:50:43.850254881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628752Z [W826 22:50:43.850375859 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628851Z [W826 22:50:44.310453505 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1628949Z [W826 22:50:44.310613233 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629045Z [W826 22:50:44.777221118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629142Z [W826 22:50:44.777335586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629241Z [W826 22:50:45.236289740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629336Z [W826 22:50:45.236474657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629433Z [W826 22:50:45.759068433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629528Z [W826 22:50:45.759171171 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1629626Z [W826 22:50:46.281379942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1630972Z [W826 22:50:46.281579599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631082Z [W826 22:50:46.826205495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631183Z [W826 22:50:46.826349793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631309Z [W826 22:50:47.391032421 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631406Z [W826 22:50:47.391150329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631503Z [W826 22:50:47.982751673 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631598Z [W826 22:50:47.982861671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631731Z [W826 22:50:48.459706410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631828Z [W826 22:50:48.459951626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1631925Z [W826 22:50:48.906094666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632039Z [W826 22:50:48.906219474 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632142Z [W826 22:50:49.049119397 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632239Z [W826 22:50:49.442270812 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632336Z [W826 22:50:49.442367802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632432Z [W826 22:50:49.601235969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632531Z [W826 22:50:49.969287169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632628Z [W826 22:50:49.969440477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632725Z [W826 22:50:50.175121864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632823Z [W826 22:50:50.502266585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1632923Z [W826 22:50:50.502400473 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634327Z [W826 22:50:50.684821898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634437Z [W826 22:50:50.985075612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634536Z [W826 22:50:50.985244509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634638Z [W826 22:50:51.104088052 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634735Z [W826 22:50:51.358068687 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634831Z [W826 22:50:51.358164085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1634930Z [W826 22:50:51.475044378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635030Z [W826 22:50:51.731114391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635127Z [W826 22:50:51.731244199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635224Z [W826 22:50:51.838054217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635321Z [W826 22:50:52.080048167 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635423Z [W826 22:50:52.080118715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635520Z [W826 22:50:52.219275526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635619Z [W826 22:50:52.465100436 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635717Z [W826 22:50:52.465240133 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635837Z [W826 22:50:52.867100975 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635935Z [W826 22:50:52.867333561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1635974Z PASSED [43.8795s] [ 93%] 2025-08-26T23:15:41.1636173Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b5 [W826 22:50:53.551155277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1636306Z [W826 22:50:53.551287515 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1636404Z [W826 22:50:53.734237073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1637704Z [W826 22:50:53.734399280 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1637832Z [W826 22:50:53.989105534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1637934Z [W826 22:50:53.989235022 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638031Z [W826 22:50:54.484275951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638127Z [W826 22:50:54.484395299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638223Z [W826 22:50:54.017171188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638325Z [W826 22:50:54.017354114 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638422Z [W826 22:50:55.459077433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638519Z [W826 22:50:55.459196092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638618Z [W826 22:50:55.869453364 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638715Z [W826 22:50:55.869687340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638812Z [W826 22:50:56.310118328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1638910Z [W826 22:50:56.310258616 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639006Z [W826 22:50:56.756204509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639103Z [W826 22:50:56.756407236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639200Z [W826 22:50:57.175813648 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639297Z [W826 22:50:57.176079124 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639397Z [W826 22:50:57.646168246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639494Z [W826 22:50:57.646352934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639591Z [W826 22:50:58.183910389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1639686Z [W826 22:50:58.184054366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641051Z [W826 22:50:58.662513210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641157Z [W826 22:50:58.662653978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641256Z [W826 22:50:59.131774085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641352Z [W826 22:50:59.132018611 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641452Z [W826 22:50:59.562090969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641575Z [W826 22:50:59.562229927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641673Z [W826 22:50:59.029282106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641769Z [W826 22:50:59.029469103 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641866Z [W826 22:51:00.478954872 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1641990Z [W826 22:51:00.479068170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642088Z [W826 22:51:00.929119651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642185Z [W826 22:51:00.929262538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642303Z [W826 22:51:01.401252061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642404Z [W826 22:51:01.401405310 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642500Z [W826 22:51:01.888077296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642596Z [W826 22:51:01.888191165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642692Z [W826 22:51:02.345234027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642789Z [W826 22:51:02.345350576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642886Z [W826 22:51:02.753617908 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1642981Z [W826 22:51:02.753889434 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644292Z [W826 22:51:03.217403598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644405Z [W826 22:51:03.217545086 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644506Z [W826 22:51:03.688065171 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644602Z [W826 22:51:03.688156791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644700Z [W826 22:51:04.126277224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644802Z [W826 22:51:04.126459201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644899Z [W826 22:51:04.588075204 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1644996Z [W826 22:51:04.588184092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645095Z [W826 22:51:04.046050312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645192Z [W826 22:51:04.046154751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645289Z [W826 22:51:05.471055887 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645386Z [W826 22:51:05.471140466 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645482Z [W826 22:51:05.577057397 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645579Z [W826 22:51:05.854146568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645678Z [W826 22:51:05.854326834 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645774Z [W826 22:51:05.977299684 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645871Z [W826 22:51:06.229988589 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1645989Z [W826 22:51:06.230161587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1646086Z [W826 22:51:06.350203681 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1646181Z [W826 22:51:06.622185039 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1647516Z [W826 22:51:06.622419585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1647656Z [W826 22:51:06.748176602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1647755Z [W826 22:51:06.008296572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1647852Z [W826 22:51:06.008593498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1647964Z [W826 22:51:07.137139281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648062Z [W826 22:51:07.416083293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648159Z [W826 22:51:07.416230791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648255Z [W826 22:51:07.534120167 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648351Z [W826 22:51:07.785055169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648450Z [W826 22:51:07.785146419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648547Z [W826 22:51:07.929088425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648644Z [W826 22:51:08.213049629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648745Z [W826 22:51:08.213145417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648841Z [W826 22:51:08.344080015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1648940Z [W826 22:51:08.600121368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649036Z [W826 22:51:08.600278726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649133Z [W826 22:51:08.733283331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649235Z [W826 22:51:08.992122801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649332Z [W826 22:51:08.992288748 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649427Z [W826 22:51:09.431380017 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1649526Z [W826 22:51:09.431651064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1650893Z [W826 22:51:09.849205393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651000Z [W826 22:51:09.849574717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651099Z [W826 22:51:10.406229928 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651196Z [W826 22:51:10.406413166 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651299Z [W826 22:51:10.681373458 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651395Z [W826 22:51:10.681537566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651492Z [W826 22:51:10.984119624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651590Z [W826 22:51:10.984251902 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651715Z [W826 22:51:11.433113480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651811Z [W826 22:51:11.433301477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1651908Z [W826 22:51:11.843048617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652004Z [W826 22:51:11.843104967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652135Z [W826 22:51:12.331060654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652234Z [W826 22:51:12.331132883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652331Z [W826 22:51:12.836738259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652444Z [W826 22:51:12.836826988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652544Z [W826 22:51:13.290346965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652640Z [W826 22:51:13.290435974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652737Z [W826 22:51:13.736068292 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1652833Z [W826 22:51:13.736135871 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654215Z [W826 22:51:14.177045592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654322Z [W826 22:51:14.177108021 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654423Z [W826 22:51:14.615142916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654522Z [W826 22:51:14.615291234 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654621Z [W826 22:51:15.066233891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654716Z [W826 22:51:15.066456828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654813Z [W826 22:51:15.513149489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1654909Z [W826 22:51:15.513308277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655009Z [W826 22:51:15.965133460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655105Z [W826 22:51:15.965282838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655202Z [W826 22:51:16.380051000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655301Z [W826 22:51:16.380120310 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655398Z [W826 22:51:16.795275326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655496Z [W826 22:51:16.795347695 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655597Z [W826 22:51:17.209244862 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655692Z [W826 22:51:17.209447089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655790Z [W826 22:51:17.634120298 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655886Z [W826 22:51:17.634264927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1655983Z [W826 22:51:18.049080559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1656080Z [W826 22:51:18.049199427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1656203Z [W826 22:51:18.495204609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1656299Z [W826 22:51:18.495355987 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1656395Z [W826 22:51:18.967128873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1657692Z [W826 22:51:18.967356640 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1657839Z [W826 22:51:19.428541279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1657938Z [W826 22:51:19.428667737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658034Z [W826 22:51:19.883079291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658143Z [W826 22:51:19.883193749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658242Z [W826 22:51:20.301086953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658338Z [W826 22:51:20.301212402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658434Z [W826 22:51:20.728073839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658531Z [W826 22:51:20.728176448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658630Z [W826 22:51:21.139028990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658727Z [W826 22:51:21.139216337 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658823Z [W826 22:51:21.533196189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1658923Z [W826 22:51:21.533497945 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659022Z [W826 22:51:21.979119513 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659119Z [W826 22:51:21.979313771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659215Z [W826 22:51:22.099206637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659312Z [W826 22:51:22.357394078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659410Z [W826 22:51:22.357549835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659507Z [W826 22:51:22.481174015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659604Z [W826 22:51:22.737097880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1659704Z [W826 22:51:22.737276137 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661024Z [W826 22:51:22.859076704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661129Z [W826 22:51:23.129089203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661227Z [W826 22:51:23.129217881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661324Z [W826 22:51:23.245029240 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661426Z [W826 22:51:23.508124305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661523Z [W826 22:51:23.508297073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661618Z [W826 22:51:23.626163601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661719Z [W826 22:51:23.869119165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661841Z [W826 22:51:23.869227543 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1661938Z [W826 22:51:23.997088457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662034Z [W826 22:51:24.262126082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662132Z [W826 22:51:24.262320409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662268Z [W826 22:51:24.390122994 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662366Z [W826 22:51:24.655968236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662463Z [W826 22:51:24.656098665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662578Z [W826 22:51:24.773304933 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662677Z [W826 22:51:24.044549332 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662774Z [W826 22:51:24.044749210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662871Z [W826 22:51:25.174192780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1662967Z [W826 22:51:25.444218148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1663066Z [W826 22:51:25.444378926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664351Z [W826 22:51:25.869150444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664450Z [W826 22:51:25.869378490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664550Z [W826 22:51:26.288374608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664650Z [W826 22:51:26.288581245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664747Z [W826 22:51:27.026193330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664843Z [W826 22:51:27.026331528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1664941Z [W826 22:51:28.304165096 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665042Z [W826 22:51:28.304302164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665139Z [W826 22:51:28.587098315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665235Z [W826 22:51:28.587261563 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665335Z [W826 22:51:29.055082100 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665431Z [W826 22:51:29.055178638 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665530Z [W826 22:51:29.475085093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665626Z [W826 22:51:29.475180580 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665723Z [W826 22:51:29.933108480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665820Z [W826 22:51:29.933219789 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1665917Z [W826 22:51:30.398878859 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1666014Z [W826 22:51:30.399013228 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1666112Z [W826 22:51:30.838331042 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1666231Z [W826 22:51:30.838468631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1667484Z [W826 22:51:31.286290085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1667591Z [W826 22:51:31.286399973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1667690Z [W826 22:51:31.737134733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1667823Z [W826 22:51:31.737281661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1667920Z [W826 22:51:32.202290022 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668018Z [W826 22:51:32.202413440 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668129Z [W826 22:51:32.680382751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668229Z [W826 22:51:32.680505679 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668325Z [W826 22:51:33.170123161 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668422Z [W826 22:51:33.170266169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668518Z [W826 22:51:33.650202100 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668619Z [W826 22:51:33.650337978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668717Z [W826 22:51:34.110124038 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668814Z [W826 22:51:34.110261786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1668914Z [W826 22:51:34.564074888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669012Z [W826 22:51:34.564178807 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669108Z [W826 22:51:34.997048272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669206Z [W826 22:51:34.997112711 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669302Z [W826 22:51:35.440039761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669403Z [W826 22:51:35.440086390 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1669499Z [W826 22:51:35.884067453 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1670825Z [W826 22:51:35.884164932 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1670932Z [W826 22:51:36.315142126 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671032Z [W826 22:51:36.315288713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671129Z [W826 22:51:36.763600671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671226Z [W826 22:51:36.763800097 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671323Z [W826 22:51:37.202700129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671424Z [W826 22:51:37.202880606 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671520Z [W826 22:51:37.628080608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671616Z [W826 22:51:37.628185497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671713Z [W826 22:51:38.096087923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671836Z [W826 22:51:38.096205982 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1671932Z [W826 22:51:38.538132756 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672029Z [W826 22:51:38.538293564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672126Z [W826 22:51:38.990098697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672260Z [W826 22:51:38.990236805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672357Z [W826 22:51:39.448609268 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672454Z [W826 22:51:39.448864254 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672567Z [W826 22:51:39.884114942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672667Z [W826 22:51:39.884281359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1672763Z [W826 22:51:39.007196259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674115Z [W826 22:51:40.275755331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674224Z [W826 22:51:40.275928948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674330Z [W826 22:51:40.390550866 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674426Z [W826 22:51:40.666073910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674523Z [W826 22:51:40.666199578 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674623Z [W826 22:51:40.786856213 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674722Z [W826 22:51:41.066474393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674818Z [W826 22:51:41.070031298 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1674914Z [W826 22:51:41.193446242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675010Z [W826 22:51:41.456197691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675110Z [W826 22:51:41.456449597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675206Z [W826 22:51:41.585085199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675304Z [W826 22:51:41.849083990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675402Z [W826 22:51:41.849213268 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675500Z [W826 22:51:41.974194317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675597Z [W826 22:51:42.255304605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675693Z [W826 22:51:42.255503512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675789Z [W826 22:51:42.375326060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675887Z [W826 22:51:42.658909239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1675983Z [W826 22:51:42.659095587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1676081Z [W826 22:51:42.779058332 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677345Z [W826 22:51:43.051147008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677483Z [W826 22:51:43.051334545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677579Z [W826 22:51:43.165187445 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677677Z [W826 22:51:43.443126502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677772Z [W826 22:51:43.443312699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677902Z [W826 22:51:43.903170899 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1677999Z [W826 22:51:43.903444625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678096Z [W826 22:51:44.340611203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678205Z [W826 22:51:44.340823940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678247Z PASSED [51.4609s] [ 93%] 2025-08-26T23:15:41.1678449Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b6 [W826 22:51:45.154145425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678550Z [W826 22:51:45.154310823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678647Z [W826 22:51:45.468070609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678748Z [W826 22:51:45.468165627 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678844Z [W826 22:51:45.782931957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1678942Z [W826 22:51:45.783128294 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1679039Z [W826 22:51:46.249120849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1679140Z [W826 22:51:46.249250487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1679236Z [W826 22:51:46.680164552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1679332Z [W826 22:51:46.680322590 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1679428Z [W826 22:51:47.146131158 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1680804Z [W826 22:51:47.146276846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1680903Z [W826 22:51:47.602135227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681001Z [W826 22:51:47.602291034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681097Z [W826 22:51:48.061943938 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681198Z [W826 22:51:48.062071496 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681295Z [W826 22:51:48.501108734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681391Z [W826 22:51:48.501233632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681487Z [W826 22:51:48.957426709 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681587Z [W826 22:51:48.957552227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681683Z [W826 22:51:49.406154400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681780Z [W826 22:51:49.406336427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1681876Z [W826 22:51:49.861100635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682003Z [W826 22:51:49.861222602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682100Z [W826 22:51:50.332358249 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682197Z [W826 22:51:50.332612435 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682293Z [W826 22:51:50.772127317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682424Z [W826 22:51:50.772284666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682521Z [W826 22:51:51.231078172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682619Z [W826 22:51:51.231188790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1682716Z [W826 22:51:51.681281929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684031Z [W826 22:51:51.681435717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684137Z [W826 22:51:52.108144186 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684235Z [W826 22:51:52.108287184 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684332Z [W826 22:51:52.517431543 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684433Z [W826 22:51:52.517570311 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684530Z [W826 22:51:52.952180329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684626Z [W826 22:51:52.952334957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684723Z [W826 22:51:53.395241227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684826Z [W826 22:51:53.395353355 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1684923Z [W826 22:51:53.836115489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685020Z [W826 22:51:53.836279136 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685117Z [W826 22:51:54.299155039 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685217Z [W826 22:51:54.299354986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685315Z [W826 22:51:54.773259040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685413Z [W826 22:51:54.773426437 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685510Z [W826 22:51:55.214130661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685606Z [W826 22:51:55.214277049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685704Z [W826 22:51:55.636796132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685800Z [W826 22:51:55.636927051 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685896Z [W826 22:51:56.086446869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1685993Z [W826 22:51:56.086719145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687278Z [W826 22:51:56.529159393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687383Z [W826 22:51:56.529252211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687480Z [W826 22:51:56.961073261 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687600Z [W826 22:51:56.961180691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687697Z [W826 22:51:57.385118502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687792Z [W826 22:51:57.385275400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1687889Z [W826 22:51:57.850433068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688011Z [W826 22:51:57.854243509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688109Z [W826 22:51:58.308419667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688205Z [W826 22:51:58.308666493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688301Z [W826 22:51:58.758117292 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688416Z [W826 22:51:58.758273160 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688515Z [W826 22:51:58.882699617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688611Z [W826 22:51:59.150227324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688708Z [W826 22:51:59.150481650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688807Z [W826 22:51:59.274531092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1688903Z [W826 22:51:59.531081898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1689000Z [W826 22:51:59.531228525 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1689097Z [W826 22:51:59.648595571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1689196Z [W826 22:51:59.919351318 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1690545Z [W826 22:51:59.919655523 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1690652Z [W826 22:51:59.041702817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1690751Z [W826 22:52:00.291183481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1690853Z [W826 22:52:00.291471487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1690950Z [W826 22:52:00.405277607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691046Z [W826 22:52:00.671530592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691143Z [W826 22:52:00.671657002 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691246Z [W826 22:52:00.797379968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691343Z [W826 22:52:01.076135392 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691440Z [W826 22:52:01.076409808 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691537Z [W826 22:52:01.194900876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691636Z [W826 22:52:01.444090865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691734Z [W826 22:52:01.444220593 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691831Z [W826 22:52:01.567118363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1691933Z [W826 22:52:01.824412338 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1692061Z [W826 22:52:01.824514166 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1692158Z [W826 22:52:01.945110831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1692254Z [W826 22:52:02.205079324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1692351Z [W826 22:52:02.205223072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1692481Z [W826 22:52:02.323221298 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1693790Z [W826 22:52:02.580155138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1693895Z [W826 22:52:02.580303206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1693994Z [W826 22:52:02.705555040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694124Z [W826 22:52:02.973071927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694221Z [W826 22:52:02.973217074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694319Z [W826 22:52:03.399364222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694416Z [W826 22:52:03.399752216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694519Z [W826 22:52:03.810169556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694616Z [W826 22:52:03.810497150 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694712Z [W826 22:52:04.411223525 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694808Z [W826 22:52:04.411362583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1694910Z [W826 22:52:04.702132922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695006Z [W826 22:52:04.702284340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695107Z [W826 22:52:04.027171244 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695204Z [W826 22:52:04.027328962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695300Z [W826 22:52:05.474146652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695397Z [W826 22:52:05.474309520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695493Z [W826 22:52:05.953762658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695589Z [W826 22:52:05.953914166 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1695689Z [W826 22:52:06.428116915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697000Z [W826 22:52:06.428243242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697108Z [W826 22:52:06.919207664 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697207Z [W826 22:52:06.919366391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697306Z [W826 22:52:07.415233727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697403Z [W826 22:52:07.415455365 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697500Z [W826 22:52:07.884113469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697597Z [W826 22:52:07.884259007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697718Z [W826 22:52:08.334534053 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697815Z [W826 22:52:08.334826429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1697912Z [W826 22:52:08.764562161 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698009Z [W826 22:52:08.764743749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698134Z [W826 22:52:09.226425370 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698230Z [W826 22:52:09.226696696 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698332Z [W826 22:52:09.656830183 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698428Z [W826 22:52:09.657007430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698544Z [W826 22:52:10.122105680 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698641Z [W826 22:52:10.122273917 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698737Z [W826 22:52:10.582334833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698834Z [W826 22:52:10.582549380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1698933Z [W826 22:52:11.056136968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700241Z [W826 22:52:11.056297586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700409Z [W826 22:52:11.467114729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700508Z [W826 22:52:11.467285947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700610Z [W826 22:52:11.884547542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700707Z [W826 22:52:11.884850317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700803Z [W826 22:52:12.324111973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1700899Z [W826 22:52:12.324384489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701001Z [W826 22:52:12.751629540 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701097Z [W826 22:52:12.751882576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701193Z [W826 22:52:13.204123442 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701289Z [W826 22:52:13.204299491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701389Z [W826 22:52:13.661075787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701485Z [W826 22:52:13.661193675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701584Z [W826 22:52:14.092105401 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701680Z [W826 22:52:14.092257407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701778Z [W826 22:52:14.530082306 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701874Z [W826 22:52:14.530207594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1701972Z [W826 22:52:14.962201152 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1702067Z [W826 22:52:14.962288221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1702193Z [W826 22:52:15.419063727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1702291Z [W826 22:52:15.419158697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1703623Z [W826 22:52:15.896053734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1703726Z [W826 22:52:15.896139063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1703868Z [W826 22:52:16.361088114 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1703965Z [W826 22:52:16.361201962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704062Z [W826 22:52:16.815075134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704157Z [W826 22:52:16.815184673 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704278Z [W826 22:52:17.293300921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704374Z [W826 22:52:17.293531317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704471Z [W826 22:52:17.749194721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704567Z [W826 22:52:17.749370870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704667Z [W826 22:52:18.193441671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704763Z [W826 22:52:18.193624049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704864Z [W826 22:52:18.316107565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1704960Z [W826 22:52:18.571169053 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705060Z [W826 22:52:18.571359740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705155Z [W826 22:52:18.701200785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705252Z [W826 22:52:18.968151810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705349Z [W826 22:52:18.968345857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705451Z [W826 22:52:19.095482992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1705547Z [W826 22:52:19.364193841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1706871Z [W826 22:52:19.364500146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1706980Z [W826 22:52:19.481189012 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707084Z [W826 22:52:19.760547707 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707180Z [W826 22:52:19.760749594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707278Z [W826 22:52:19.871126557 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707374Z [W826 22:52:20.140143961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707476Z [W826 22:52:20.140396857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707572Z [W826 22:52:20.243258655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707670Z [W826 22:52:20.501995017 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707766Z [W826 22:52:20.502182834 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707885Z [W826 22:52:20.622225419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1707983Z [W826 22:52:20.895600956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708080Z [W826 22:52:20.895840921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708177Z [W826 22:52:20.015108578 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708302Z [W826 22:52:21.258183610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708399Z [W826 22:52:21.258389987 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708497Z [W826 22:52:21.370210348 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708594Z [W826 22:52:21.631111127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708710Z [W826 22:52:21.631277085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708807Z [W826 22:52:21.751310699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1708904Z [W826 22:52:21.017102132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1711561Z [W826 22:52:21.017266449 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1711669Z [W826 22:52:22.143339981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1711767Z [W826 22:52:22.409358691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1711867Z [W826 22:52:22.409548978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1711963Z [W826 22:52:22.817216310 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712068Z [W826 22:52:22.817579835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712166Z [W826 22:52:23.263560018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712263Z [W826 22:52:23.263840963 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712360Z [W826 22:52:25.354091485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712462Z [W826 22:52:25.354214873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712559Z [W826 22:52:25.614055498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712656Z [W826 22:52:25.614118917 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712755Z [W826 22:52:25.917039650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712858Z [W826 22:52:25.917085490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1712955Z [W826 22:52:26.332045610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1713055Z [W826 22:52:26.332090089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1713151Z [W826 22:52:26.710043847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1713249Z [W826 22:52:26.710083857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1713345Z [W826 22:52:27.133048923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1713489Z [W826 22:52:27.133095433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715053Z [W826 22:52:27.547034478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715202Z [W826 22:52:27.547069077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715302Z [W826 22:52:27.977046017 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715397Z [W826 22:52:27.977091196 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715495Z [W826 22:52:28.403181075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715638Z [W826 22:52:28.403347343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715735Z [W826 22:52:28.824792123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715832Z [W826 22:52:28.825020000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1715929Z [W826 22:52:29.240107867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716046Z [W826 22:52:29.240227836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716144Z [W826 22:52:29.673277288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716241Z [W826 22:52:29.673410086 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716341Z [W826 22:52:30.102192923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716439Z [W826 22:52:30.102327741 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716536Z [W826 22:52:30.512081461 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716634Z [W826 22:52:30.512189089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716731Z [W826 22:52:30.950057987 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716829Z [W826 22:52:30.950129195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1716926Z [W826 22:52:31.430113676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1717022Z [W826 22:52:31.430235194 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1717119Z [W826 22:52:32.057056536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718452Z [W826 22:52:32.057148245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718557Z [W826 22:52:32.679198911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718656Z [W826 22:52:32.679393538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718753Z [W826 22:52:33.304086013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718855Z [W826 22:52:33.304201762 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1718953Z [W826 22:52:33.749288848 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719050Z [W826 22:52:33.749436366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719147Z [W826 22:52:34.364047716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719248Z [W826 22:52:34.364111795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719346Z [W826 22:52:34.031474904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719445Z [W826 22:52:34.031534283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719542Z [W826 22:52:35.720037937 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719663Z [W826 22:52:35.720085516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719759Z [W826 22:52:36.369431433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719856Z [W826 22:52:36.369540282 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1719953Z [W826 22:52:36.806444864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1720082Z [W826 22:52:36.806641251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1720180Z [W826 22:52:37.352064115 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1720277Z [W826 22:52:37.352152654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1720444Z [W826 22:52:37.044089835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1720564Z [W826 22:52:37.044149444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722020Z [W826 22:52:38.727951691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722127Z [W826 22:52:38.728103048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722225Z [W826 22:52:39.438529985 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722328Z [W826 22:52:39.438710922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722425Z [W826 22:52:40.169191491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722522Z [W826 22:52:40.169405698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722619Z [W826 22:52:40.653098361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722721Z [W826 22:52:40.653230779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722818Z [W826 22:52:41.242121954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1722914Z [W826 22:52:41.242532739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723012Z [W826 22:52:41.450070157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723109Z [W826 22:52:41.840129571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723206Z [W826 22:52:41.840660342 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723304Z [W826 22:52:41.016098045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723401Z [W826 22:52:42.411413477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723499Z [W826 22:52:42.411595654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723595Z [W826 22:52:42.594103598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723691Z [W826 22:52:42.976069615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723788Z [W826 22:52:42.976180984 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723885Z [W826 22:52:43.178081839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1723983Z [W826 22:52:43.572882739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1724080Z [W826 22:52:43.573090806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725341Z [W826 22:52:43.740072508 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725481Z [W826 22:52:44.126104073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725580Z [W826 22:52:44.126251081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725676Z [W826 22:52:44.300168157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725772Z [W826 22:52:44.569098353 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1725905Z [W826 22:52:44.569232111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726001Z [W826 22:52:44.677059012 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726098Z [W826 22:52:44.951739839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726194Z [W826 22:52:44.951899467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726307Z [W826 22:52:45.143393543 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726403Z [W826 22:52:45.553141043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726502Z [W826 22:52:45.553292521 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726598Z [W826 22:52:45.746102466 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726698Z [W826 22:52:46.169178841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726794Z [W826 22:52:46.169454976 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726891Z [W826 22:52:46.355435108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1726987Z [W826 22:52:46.745090246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1727089Z [W826 22:52:46.745259914 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1727186Z [W826 22:52:46.917197790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1727283Z [W826 22:52:47.294074156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1727379Z [W826 22:52:47.294195334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1728627Z [W826 22:52:47.008051468 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1728732Z [W826 22:52:47.008216765 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1728831Z [W826 22:52:48.641132134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1728927Z [W826 22:52:48.641374150 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1728972Z PASSED [64.3702s] [ 93%] 2025-08-26T23:15:41.1729173Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7 [W826 22:52:49.795203631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729271Z [W826 22:52:49.795387138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729367Z [W826 22:52:50.199111110 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729469Z [W826 22:52:50.199512854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729565Z [W826 22:52:50.662066662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729662Z [W826 22:52:50.662160120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729760Z [W826 22:52:51.143066397 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729881Z [W826 22:52:51.143149675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1729977Z [W826 22:52:51.823505125 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730074Z [W826 22:52:51.823677272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730170Z [W826 22:52:52.460133767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730296Z [W826 22:52:52.460272194 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730479Z [W826 22:52:53.130116475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730578Z [W826 22:52:53.130230614 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1730675Z [W826 22:52:53.862251399 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1731945Z [W826 22:52:53.862323688 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732051Z [W826 22:52:54.413539723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732153Z [W826 22:52:54.413691271 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732249Z [W826 22:52:54.910092918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732352Z [W826 22:52:54.910226236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732448Z [W826 22:52:55.390044599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732545Z [W826 22:52:55.390112828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732641Z [W826 22:52:55.821715222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732745Z [W826 22:52:55.821899888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732841Z [W826 22:52:56.249328177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1732937Z [W826 22:52:56.249535644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733034Z [W826 22:52:56.709798288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733133Z [W826 22:52:56.709995154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733231Z [W826 22:52:57.167059637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733330Z [W826 22:52:57.167148216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733426Z [W826 22:52:57.638172104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733526Z [W826 22:52:57.638335971 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733623Z [W826 22:52:58.125111587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733720Z [W826 22:52:58.125251444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733816Z [W826 22:52:58.555330433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1733914Z [W826 22:52:58.555531889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735145Z [W826 22:52:58.002895011 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735250Z [W826 22:52:58.002990699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735348Z [W826 22:52:59.470334014 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735474Z [W826 22:52:59.470428913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735571Z [W826 22:52:59.901630013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735666Z [W826 22:52:59.901744780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735763Z [W826 22:53:00.319178693 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735896Z [W826 22:53:00.319365990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1735993Z [W826 22:53:00.759830098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736090Z [W826 22:53:00.760145422 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736186Z [W826 22:53:01.195796224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736300Z [W826 22:53:01.195914333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736399Z [W826 22:53:01.618415637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736496Z [W826 22:53:01.618594654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736592Z [W826 22:53:02.060226953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736694Z [W826 22:53:02.060476170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736790Z [W826 22:53:02.477699405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736887Z [W826 22:53:02.477837073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1736983Z [W826 22:53:02.919177908 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1737084Z [W826 22:53:02.919335405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738345Z [W826 22:53:03.348345089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738454Z [W826 22:53:03.348544166 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738552Z [W826 22:53:03.776346388 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738653Z [W826 22:53:03.776509405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738750Z [W826 22:53:04.230408477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738847Z [W826 22:53:04.230530855 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1738944Z [W826 22:53:04.711114207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739045Z [W826 22:53:04.711256904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739142Z [W826 22:53:05.196137438 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739239Z [W826 22:53:05.196320256 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739335Z [W826 22:53:05.615371333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739435Z [W826 22:53:05.615599389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739532Z [W826 22:53:06.069177566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739630Z [W826 22:53:06.069299774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739727Z [W826 22:53:06.545717049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739846Z [W826 22:53:06.545840427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1739943Z [W826 22:53:06.023076260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1740039Z [W826 22:53:06.023215427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1740136Z [W826 22:53:07.461324592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1740261Z [W826 22:53:07.461564818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1740441Z [W826 22:53:07.896167356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1741691Z [W826 22:53:07.896362242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1741795Z [W826 22:53:07.008507229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1741922Z [W826 22:53:08.276110914 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742019Z [W826 22:53:08.276323480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742115Z [W826 22:53:08.387498301 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742213Z [W826 22:53:08.670080247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742314Z [W826 22:53:08.670262154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742410Z [W826 22:53:08.793122885 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742506Z [W826 22:53:09.069246450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742603Z [W826 22:53:09.069487326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742704Z [W826 22:53:09.196969556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742800Z [W826 22:53:09.455055108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742897Z [W826 22:53:09.455162546 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1742995Z [W826 22:53:09.577404567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743096Z [W826 22:53:09.827129407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743193Z [W826 22:53:09.827304685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743289Z [W826 22:53:09.953650672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743386Z [W826 22:53:10.214208786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743485Z [W826 22:53:10.214477492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743581Z [W826 22:53:10.346612260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1743677Z [W826 22:53:10.616440901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1744938Z [W826 22:53:10.616725877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745042Z [W826 22:53:10.747201081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745142Z [W826 22:53:10.012216836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745238Z [W826 22:53:10.012456323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745335Z [W826 22:53:11.139311762 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745462Z [W826 22:53:11.428217831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745560Z [W826 22:53:11.428434047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745656Z [W826 22:53:11.562965808 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745752Z [W826 22:53:11.856524315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745884Z [W826 22:53:11.856746141 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1745981Z [W826 22:53:11.979278027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746078Z [W826 22:53:12.263197662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746176Z [W826 22:53:12.263413689 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746293Z [W826 22:53:12.394168418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746390Z [W826 22:53:12.669241979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746486Z [W826 22:53:12.669444956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746582Z [W826 22:53:12.802245494 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746681Z [W826 22:53:13.083114996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746778Z [W826 22:53:13.083304653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1746873Z [W826 22:53:13.530735284 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748133Z [W826 22:53:13.530949970 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748244Z [W826 22:53:13.956547046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748343Z [W826 22:53:13.956861772 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748440Z [W826 22:53:14.385143047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748539Z [W826 22:53:14.385385964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748642Z [W826 22:53:14.012106227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748739Z [W826 22:53:14.012227105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748836Z [W826 22:53:15.328438584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1748932Z [W826 22:53:15.328557022 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749031Z [W826 22:53:15.681098761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749128Z [W826 22:53:15.681209330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749225Z [W826 22:53:15.992384715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749322Z [W826 22:53:15.992599452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749421Z [W826 22:53:16.423194172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749518Z [W826 22:53:16.423403719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749616Z [W826 22:53:16.831254738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749712Z [W826 22:53:16.831421776 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749831Z [W826 22:53:17.251116583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1749928Z [W826 22:53:17.251241461 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1750024Z [W826 22:53:17.724699831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1750121Z [W826 22:53:17.724895528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1751546Z [W826 22:53:18.208128948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1751653Z [W826 22:53:18.208275206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1751751Z [W826 22:53:18.652934269 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1751847Z [W826 22:53:18.653068757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1751968Z [W826 22:53:19.078617294 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752065Z [W826 22:53:19.078771371 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752162Z [W826 22:53:19.523990656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752259Z [W826 22:53:19.524254612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752361Z [W826 22:53:19.948212774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752458Z [W826 22:53:19.948419731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752557Z [W826 22:53:20.381066469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752653Z [W826 22:53:20.381157007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752757Z [W826 22:53:20.811087617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752856Z [W826 22:53:20.811228725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1752953Z [W826 22:53:21.255484165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1753050Z [W826 22:53:21.255687371 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1753150Z [W826 22:53:21.689104857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1753246Z [W826 22:53:21.689223585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1753344Z [W826 22:53:22.123210282 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1753510Z [W826 22:53:22.123347000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1754814Z [W826 22:53:22.566341510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1754920Z [W826 22:53:22.566527247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755019Z [W826 22:53:22.969077048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755116Z [W826 22:53:22.969213576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755218Z [W826 22:53:23.354460843 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755314Z [W826 22:53:23.354548090 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755411Z [W826 22:53:23.759064021 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755507Z [W826 22:53:23.759153530 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755639Z [W826 22:53:24.174056361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755736Z [W826 22:53:24.174134800 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755833Z [W826 22:53:24.573510799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1755930Z [W826 22:53:24.573644127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756065Z [W826 22:53:24.968593685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756163Z [W826 22:53:24.968678953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756262Z [W826 22:53:25.390052884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756358Z [W826 22:53:25.390119753 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756474Z [W826 22:53:25.803057064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756571Z [W826 22:53:25.803137703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756670Z [W826 22:53:26.173048986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1756767Z [W826 22:53:26.173116974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758046Z [W826 22:53:26.592291749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758154Z [W826 22:53:26.592352799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758253Z [W826 22:53:26.991344334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758350Z [W826 22:53:26.991440783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758453Z [W826 22:53:27.421167996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758549Z [W826 22:53:27.421366443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758646Z [W826 22:53:27.846123912 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758743Z [W826 22:53:27.846312949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758844Z [W826 22:53:28.267158229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1758941Z [W826 22:53:28.267235607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759038Z [W826 22:53:28.704090130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759134Z [W826 22:53:28.704282287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759236Z [W826 22:53:29.160127460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759335Z [W826 22:53:29.160231727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759434Z [W826 22:53:29.600258502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759530Z [W826 22:53:29.600423119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759629Z [W826 22:53:29.029172818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759725Z [W826 22:53:29.029380764 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759823Z [W826 22:53:30.468141768 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1759919Z [W826 22:53:30.468275986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1760040Z [W826 22:53:30.894126369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761389Z [W826 22:53:30.894265617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761499Z [W826 22:53:30.026107599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761599Z [W826 22:53:31.278165744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761752Z [W826 22:53:31.278398060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761850Z [W826 22:53:31.388182443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1761946Z [W826 22:53:31.637098785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762043Z [W826 22:53:31.637264293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762160Z [W826 22:53:31.755110330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762256Z [W826 22:53:31.010179059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762353Z [W826 22:53:31.010291367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762450Z [W826 22:53:32.118376996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762550Z [W826 22:53:32.352093632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762649Z [W826 22:53:32.352238000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762750Z [W826 22:53:32.464087210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762848Z [W826 22:53:32.725051129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1762950Z [W826 22:53:32.725139607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1763046Z [W826 22:53:32.842030559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1763144Z [W826 22:53:33.094277931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1763240Z [W826 22:53:33.094528628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1763340Z [W826 22:53:33.212175188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1763437Z [W826 22:53:33.472079193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1764747Z [W826 22:53:33.472205731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1764846Z [W826 22:53:33.587186242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1764946Z [W826 22:53:33.861165460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765043Z [W826 22:53:33.861406027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765140Z [W826 22:53:33.978660083 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765236Z [W826 22:53:34.235743841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765339Z [W826 22:53:34.235942698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765435Z [W826 22:53:34.346164663 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765532Z [W826 22:53:34.594406786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765629Z [W826 22:53:34.594742521 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765758Z [W826 22:53:34.705183923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765855Z [W826 22:53:34.963125338 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1765955Z [W826 22:53:34.963300775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766053Z [W826 22:53:35.072114342 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766178Z [W826 22:53:35.339919533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766275Z [W826 22:53:35.340032562 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766373Z [W826 22:53:35.469076048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766469Z [W826 22:53:35.739188786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1766583Z [W826 22:53:35.739272313 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1767878Z [W826 22:53:36.177052673 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1767985Z [W826 22:53:36.177219181 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768085Z [W826 22:53:36.595496140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768188Z [W826 22:53:36.595837334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768287Z [W826 22:53:36.036512140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768384Z [W826 22:53:36.036715945 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768481Z [W826 22:53:39.221122092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768583Z [W826 22:53:39.221290529 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768681Z [W826 22:53:39.504055211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768777Z [W826 22:53:39.504121440 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768875Z [W826 22:53:39.806055238 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1768975Z [W826 22:53:39.806108647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769074Z [W826 22:53:40.094050610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769172Z [W826 22:53:40.094108829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769271Z [W826 22:53:40.516056022 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769371Z [W826 22:53:40.516116471 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769468Z [W826 22:53:40.920128299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769565Z [W826 22:53:40.920264177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769662Z [W826 22:53:41.352423953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769760Z [W826 22:53:41.352607880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1769858Z [W826 22:53:41.750094849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771213Z [W826 22:53:41.750208147 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771319Z [W826 22:53:42.214072984 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771448Z [W826 22:53:42.214151983 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771546Z [W826 22:53:42.617101057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771642Z [W826 22:53:42.617242135 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771739Z [W826 22:53:42.043084608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771871Z [W826 22:53:42.043199516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1771969Z [W826 22:53:43.418074893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772066Z [W826 22:53:43.418173691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772162Z [W826 22:53:43.809267558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772285Z [W826 22:53:43.809449486 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772382Z [W826 22:53:44.232086597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772481Z [W826 22:53:44.232190727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772577Z [W826 22:53:44.658441283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772677Z [W826 22:53:44.658548521 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772774Z [W826 22:53:45.107144154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772870Z [W826 22:53:45.107310341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1772967Z [W826 22:53:45.568205883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1773069Z [W826 22:53:45.568329451 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1773165Z [W826 22:53:45.025097788 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1773261Z [W826 22:53:45.025238846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1774589Z [W826 22:53:46.451136008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1774699Z [W826 22:53:46.451313605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1774799Z [W826 22:53:46.873268127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1774896Z [W826 22:53:46.873447374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1774994Z [W826 22:53:47.313079545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775096Z [W826 22:53:47.313185503 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775194Z [W826 22:53:47.774130456 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775290Z [W826 22:53:47.774274304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775386Z [W826 22:53:48.222405535 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775488Z [W826 22:53:48.222529093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775585Z [W826 22:53:48.654270754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775684Z [W826 22:53:48.654482631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775783Z [W826 22:53:49.076441443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1775904Z [W826 22:53:49.076556832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776001Z [W826 22:53:49.526185569 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776097Z [W826 22:53:49.526417255 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776194Z [W826 22:53:49.963172770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776318Z [W826 22:53:49.963321008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776416Z [W826 22:53:50.400158281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1776511Z [W826 22:53:50.400305339 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1777804Z [W826 22:53:50.842086317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1777930Z [W826 22:53:50.842197355 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778033Z [W826 22:53:51.299081520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778130Z [W826 22:53:51.303571501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778226Z [W826 22:53:51.746820466 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778327Z [W826 22:53:51.746957134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778424Z [W826 22:53:52.201111682 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778520Z [W826 22:53:52.201297229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778617Z [W826 22:53:52.641115426 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778718Z [W826 22:53:52.641290993 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778814Z [W826 22:53:53.095062617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1778910Z [W826 22:53:53.095164685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779008Z [W826 22:53:53.559059703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779111Z [W826 22:53:53.559167761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779208Z [W826 22:53:53.006129810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779304Z [W826 22:53:53.006323116 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779401Z [W826 22:53:54.418224583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779501Z [W826 22:53:54.418356501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779598Z [W826 22:53:54.864873006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779695Z [W826 22:53:54.865033554 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1779792Z [W826 22:53:55.326066805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781165Z [W826 22:53:55.326150534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781271Z [W826 22:53:55.453269059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781371Z [W826 22:53:55.735121415 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781468Z [W826 22:53:55.735373231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781598Z [W826 22:53:55.864077692 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781695Z [W826 22:53:56.143079923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781793Z [W826 22:53:56.143218781 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1781889Z [W826 22:53:56.266075032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782023Z [W826 22:53:56.525064371 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782120Z [W826 22:53:56.525212148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782217Z [W826 22:53:56.651758172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782313Z [W826 22:53:56.927068989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782434Z [W826 22:53:56.927213747 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782531Z [W826 22:53:56.048312915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782628Z [W826 22:53:57.310832979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782724Z [W826 22:53:57.310936077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782826Z [W826 22:53:57.432285221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1782922Z [W826 22:53:57.704049263 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1783019Z [W826 22:53:57.704145652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1783116Z [W826 22:53:57.838850471 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784419Z [W826 22:53:58.167798792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784526Z [W826 22:53:58.168031480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784624Z [W826 22:53:58.293309103 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784720Z [W826 22:53:58.576112785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784823Z [W826 22:53:58.576273402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1784919Z [W826 22:53:58.709144480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785016Z [W826 22:53:58.958257070 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785112Z [W826 22:53:58.958494496 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785214Z [W826 22:53:59.088078743 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785310Z [W826 22:53:59.365046795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785407Z [W826 22:53:59.365147603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785504Z [W826 22:53:59.485045491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785601Z [W826 22:53:59.741038224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785699Z [W826 22:53:59.741127763 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785797Z [W826 22:53:59.870044110 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1785894Z [W826 22:54:00.142190316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1786014Z [W826 22:54:00.142393904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1786111Z [W826 22:54:00.270910068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1786208Z [W826 22:54:00.529059728 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1786304Z [W826 22:54:00.529148737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1786429Z [W826 22:54:00.952241142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1787738Z [W826 22:54:00.952646935 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1787845Z [W826 22:54:01.388311757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1787944Z [W826 22:54:01.388531404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788064Z [W826 22:54:01.820132188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788160Z [W826 22:54:01.820415093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788200Z PASSED [73.1343s] [ 93%] 2025-08-26T23:15:41.1788401Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_l [W826 22:54:07.889327803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788505Z [W826 22:54:07.889613189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788602Z [W826 22:54:08.312284480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788700Z [W826 22:54:08.312489917 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788796Z [W826 22:54:08.766505706 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788899Z [W826 22:54:08.766719353 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1788998Z [W826 22:54:09.247248395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789095Z [W826 22:54:09.247439202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789192Z [W826 22:54:09.723086769 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789290Z [W826 22:54:09.723238876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789386Z [W826 22:54:10.172950602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789484Z [W826 22:54:10.173102360 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789580Z [W826 22:54:10.641138213 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789679Z [W826 22:54:10.641293731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1789775Z [W826 22:54:11.094135159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791175Z [W826 22:54:11.094299857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791279Z [W826 22:54:11.566135282 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791382Z [W826 22:54:11.566293169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791479Z [W826 22:54:11.043176207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791577Z [W826 22:54:11.043398544 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791675Z [W826 22:54:12.507780864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791803Z [W826 22:54:12.507924102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791899Z [W826 22:54:12.963105573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1791997Z [W826 22:54:12.963247431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792093Z [W826 22:54:13.422800565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792233Z [W826 22:54:13.422976043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792330Z [W826 22:54:13.899111102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792430Z [W826 22:54:13.899274939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792528Z [W826 22:54:14.377050634 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792646Z [W826 22:54:14.377139572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792742Z [W826 22:54:14.836015397 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792840Z [W826 22:54:14.836241283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1792937Z [W826 22:54:15.302068931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1793036Z [W826 22:54:15.302189989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1793132Z [W826 22:54:15.761548666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1794522Z [W826 22:54:15.761708335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1794630Z [W826 22:54:16.227816118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1794740Z [W826 22:54:16.227994525 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1794837Z [W826 22:54:16.685238905 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1794934Z [W826 22:54:16.685358603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795031Z [W826 22:54:17.119104704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795133Z [W826 22:54:17.119235452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795230Z [W826 22:54:17.553120541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795328Z [W826 22:54:17.553270988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795425Z [W826 22:54:17.985184058 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795526Z [W826 22:54:17.985306746 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795623Z [W826 22:54:18.419059538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795720Z [W826 22:54:18.419143425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795818Z [W826 22:54:18.854070738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1795917Z [W826 22:54:18.854171567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796013Z [W826 22:54:19.293164747 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796110Z [W826 22:54:19.293279196 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796207Z [W826 22:54:19.736118868 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796328Z [W826 22:54:19.736271714 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796424Z [W826 22:54:20.214976105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1796521Z [W826 22:54:20.215229991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1797834Z [W826 22:54:20.683108108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1797974Z [W826 22:54:20.683275405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798075Z [W826 22:54:21.131500803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798172Z [W826 22:54:21.131645790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798270Z [W826 22:54:21.254063509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798381Z [W826 22:54:21.501442635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798479Z [W826 22:54:21.501575253 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798576Z [W826 22:54:21.626130448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798673Z [W826 22:54:21.894238825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798776Z [W826 22:54:21.894513331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798873Z [W826 22:54:21.031495705 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1798970Z [W826 22:54:22.306060374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799069Z [W826 22:54:22.306165842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799170Z [W826 22:54:22.441112907 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799267Z [W826 22:54:22.724382212 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799363Z [W826 22:54:22.724640368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799460Z [W826 22:54:22.840217911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799558Z [W826 22:54:23.118096519 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799655Z [W826 22:54:23.118266416 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1799751Z [W826 22:54:23.246233579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801127Z [W826 22:54:23.485127115 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801242Z [W826 22:54:23.485328032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801341Z [W826 22:54:23.599134033 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801438Z [W826 22:54:23.850071865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801535Z [W826 22:54:23.850215942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801637Z [W826 22:54:23.965118326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801734Z [W826 22:54:24.219051871 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801831Z [W826 22:54:24.219162120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1801928Z [W826 22:54:24.344108548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802053Z [W826 22:54:24.600068973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802150Z [W826 22:54:24.600232971 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802247Z [W826 22:54:24.719091773 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802344Z [W826 22:54:24.980609353 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802479Z [W826 22:54:24.980764699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802578Z [W826 22:54:25.104102024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802677Z [W826 22:54:25.364050086 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802773Z [W826 22:54:25.364186075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802892Z [W826 22:54:25.478683124 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1802988Z [W826 22:54:25.736127366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1803085Z [W826 22:54:25.736327003 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804398Z [W826 22:54:25.864262236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804510Z [W826 22:54:26.112578278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804610Z [W826 22:54:26.112871704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804706Z [W826 22:54:26.232524593 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804804Z [W826 22:54:26.489299106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1804906Z [W826 22:54:26.489569432 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805003Z [W826 22:54:26.615240340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805099Z [W826 22:54:26.889114389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805195Z [W826 22:54:26.889283036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805294Z [W826 22:54:26.008577182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805391Z [W826 22:54:27.268136142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805487Z [W826 22:54:27.268314968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805584Z [W826 22:54:27.386248135 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805685Z [W826 22:54:27.651236321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805782Z [W826 22:54:27.651423498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805878Z [W826 22:54:27.766861683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1805975Z [W826 22:54:27.034170893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1806072Z [W826 22:54:27.034457108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1806169Z [W826 22:54:28.161146201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1806266Z [W826 22:54:28.411137028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1806364Z [W826 22:54:28.411364924 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1807697Z [W826 22:54:28.532448103 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1807805Z [W826 22:54:28.773095502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1807902Z [W826 22:54:28.773270169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808000Z [W826 22:54:28.895150485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808130Z [W826 22:54:29.137116346 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808227Z [W826 22:54:29.137307532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808323Z [W826 22:54:29.239227725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808420Z [W826 22:54:29.499132989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808533Z [W826 22:54:29.499347916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808631Z [W826 22:54:29.627132851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808727Z [W826 22:54:29.891960389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808823Z [W826 22:54:29.892160886 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1808925Z [W826 22:54:29.009120109 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809024Z [W826 22:54:30.257234334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809120Z [W826 22:54:30.257374311 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809217Z [W826 22:54:30.378140394 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809319Z [W826 22:54:30.630160030 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809416Z [W826 22:54:30.630459385 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809512Z [W826 22:54:30.043180349 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1809611Z [W826 22:54:30.043471545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811013Z [W826 22:54:31.456207909 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811123Z [W826 22:54:31.456516054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811224Z [W826 22:54:31.860246866 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811320Z [W826 22:54:31.860560502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811421Z [W826 22:54:32.233196552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811518Z [W826 22:54:32.233429900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811614Z [W826 22:54:32.642173655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811711Z [W826 22:54:32.642495630 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811813Z [W826 22:54:33.079304334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1811909Z [W826 22:54:33.079640739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812006Z [W826 22:54:38.065211715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812102Z [W826 22:54:38.065504391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812230Z [W826 22:54:38.644304001 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812326Z [W826 22:54:38.644712665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812423Z [W826 22:54:39.077564980 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812519Z [W826 22:54:39.077871935 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812661Z [W826 22:54:39.539280221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812757Z [W826 22:54:39.539587106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812856Z [W826 22:54:39.991918541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1812953Z [W826 22:54:39.992257806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1813070Z [W826 22:54:40.430262922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814396Z [W826 22:54:40.430679485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814501Z [W826 22:54:40.860285620 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814599Z [W826 22:54:40.860573195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814702Z [W826 22:54:41.302397622 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814798Z [W826 22:54:41.302708408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814895Z [W826 22:54:41.761508253 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1814991Z [W826 22:54:41.761961026 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815093Z [W826 22:54:42.162197163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815189Z [W826 22:54:42.162457068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815286Z [W826 22:54:42.620850641 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815382Z [W826 22:54:42.621292654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815483Z [W826 22:54:42.037507685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815580Z [W826 22:54:42.037994538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815689Z [W826 22:54:43.457315860 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815786Z [W826 22:54:43.457680455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815887Z [W826 22:54:43.869374575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1815983Z [W826 22:54:43.869719770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1816081Z [W826 22:54:44.214264892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1816177Z [W826 22:54:44.214647467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1816275Z [W826 22:54:44.667237608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1817599Z [W826 22:54:44.667604651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1817708Z [W826 22:54:45.106266098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1817806Z [W826 22:54:45.106660232 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1817927Z [W826 22:54:45.510596361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818023Z [W826 22:54:45.510987885 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818121Z [W826 22:54:45.904263328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818216Z [W826 22:54:45.904565603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818339Z [W826 22:54:46.254322226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818435Z [W826 22:54:46.254656962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818533Z [W826 22:54:46.658290235 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818629Z [W826 22:54:46.658710599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818744Z [W826 22:54:47.105230223 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818842Z [W826 22:54:47.105665906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1818942Z [W826 22:54:47.481251462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819039Z [W826 22:54:47.481582047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819140Z [W826 22:54:47.948749383 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819237Z [W826 22:54:47.949250267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819333Z [W826 22:54:48.397659121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819429Z [W826 22:54:48.402321050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819529Z [W826 22:54:48.846415533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1819625Z [W826 22:54:48.846788617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821033Z [W826 22:54:49.289209324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821138Z [W826 22:54:49.289533529 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821242Z [W826 22:54:49.773154283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821339Z [W826 22:54:49.773429749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821436Z [W826 22:54:50.211255548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821533Z [W826 22:54:50.211601332 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821635Z [W826 22:54:50.625892673 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821732Z [W826 22:54:50.626410585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821829Z [W826 22:54:50.731357360 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1821925Z [W826 22:54:50.946322386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822025Z [W826 22:54:50.946748740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822121Z [W826 22:54:51.056591470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822226Z [W826 22:54:51.322324065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822322Z [W826 22:54:51.322747989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822448Z [W826 22:54:51.437329217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822544Z [W826 22:54:51.677735780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822641Z [W826 22:54:51.678160223 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822738Z [W826 22:54:51.801260662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822872Z [W826 22:54:51.000299171 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1822969Z [W826 22:54:51.000621376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1823068Z [W826 22:54:52.058271790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1824484Z [W826 22:54:52.342670208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1824614Z [W826 22:54:52.343066931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1824718Z [W826 22:54:52.464259188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1824815Z [W826 22:54:52.695165818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1824912Z [W826 22:54:52.695469422 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825015Z [W826 22:54:52.827622711 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825112Z [W826 22:54:53.071503452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825209Z [W826 22:54:53.071944275 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825308Z [W826 22:54:53.150284841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825410Z [W826 22:54:53.434411541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825508Z [W826 22:54:53.434861545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825604Z [W826 22:54:53.556279658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825700Z [W826 22:54:53.801277660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825800Z [W826 22:54:53.801714894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825899Z [W826 22:54:53.916526108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1825996Z [W826 22:54:54.169213074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826094Z [W826 22:54:54.169570008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826194Z [W826 22:54:54.292291462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826292Z [W826 22:54:54.580332943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826388Z [W826 22:54:54.580598819 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826487Z [W826 22:54:54.716351252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826585Z [W826 22:54:54.002462832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1826682Z [W826 22:54:54.002830457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1827949Z [W826 22:54:55.120564576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828057Z [W826 22:54:55.391594589 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828181Z [W826 22:54:55.392256759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828278Z [W826 22:54:55.521777518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828375Z [W826 22:54:55.785200208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828471Z [W826 22:54:55.785523843 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828596Z [W826 22:54:55.918448179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828693Z [W826 22:54:56.194428206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828791Z [W826 22:54:56.194690392 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1828887Z [W826 22:54:56.334255176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829002Z [W826 22:54:56.638371880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829099Z [W826 22:54:56.639039501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829200Z [W826 22:54:56.759570897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829299Z [W826 22:54:56.038175893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829398Z [W826 22:54:56.038505599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829495Z [W826 22:54:57.156177149 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829594Z [W826 22:54:57.418209110 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829690Z [W826 22:54:57.418519376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829792Z [W826 22:54:57.532160638 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829889Z [W826 22:54:57.769365231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1829986Z [W826 22:54:57.769639387 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831311Z [W826 22:54:57.882275565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831422Z [W826 22:54:58.139236244 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831521Z [W826 22:54:58.139506550 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831619Z [W826 22:54:58.257690903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831715Z [W826 22:54:58.503200928 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831817Z [W826 22:54:58.503521723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1831914Z [W826 22:54:58.625189003 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832011Z [W826 22:54:58.884191661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832108Z [W826 22:54:58.884527665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832210Z [W826 22:54:58.011337416 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832307Z [W826 22:54:59.276791365 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832404Z [W826 22:54:59.277083049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832503Z [W826 22:54:59.402324775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832634Z [W826 22:54:59.679528242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832731Z [W826 22:54:59.679988965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832829Z [W826 22:54:59.816236840 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1832926Z [W826 22:55:00.104193403 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1833058Z [W826 22:55:00.104456499 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1833155Z [W826 22:55:00.467283420 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1833254Z [W826 22:55:00.467950490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1833350Z [W826 22:55:00.822205504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1834690Z [W826 22:55:00.822594428 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1834793Z [W826 22:55:01.173174967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1834893Z [W826 22:55:01.173560821 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1834989Z [W826 22:55:01.602542475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835091Z [W826 22:55:01.603171816 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835188Z [W826 22:55:01.025193717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835285Z [W826 22:55:01.025613000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835381Z [W826 22:55:02.384237627 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835483Z [W826 22:55:02.384754209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835579Z [W826 22:55:08.914087909 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835677Z [W826 22:55:08.914239507 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835773Z [W826 22:55:09.094044512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835877Z [W826 22:55:09.094102042 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1835973Z [W826 22:55:09.267049123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836070Z [W826 22:55:09.267103252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836166Z [W826 22:55:09.635144293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836265Z [W826 22:55:09.635304410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836361Z [W826 22:55:10.091076583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836458Z [W826 22:55:10.091184552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1836554Z [W826 22:55:10.543161352 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1837806Z [W826 22:55:10.543304760 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1837912Z [W826 22:55:10.976072526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838012Z [W826 22:55:10.976179125 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838109Z [W826 22:55:11.444045321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838229Z [W826 22:55:11.444100431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838325Z [W826 22:55:11.913335686 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838423Z [W826 22:55:11.913392325 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838519Z [W826 22:55:12.380107319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838643Z [W826 22:55:12.380240617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838740Z [W826 22:55:12.806414844 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838837Z [W826 22:55:12.806660450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1838934Z [W826 22:55:13.222430948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839050Z [W826 22:55:13.222578216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839147Z [W826 22:55:13.702129093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839245Z [W826 22:55:13.702308660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839341Z [W826 22:55:13.962077577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839441Z [W826 22:55:13.962200095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839538Z [W826 22:55:14.182055594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839637Z [W826 22:55:14.182134042 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839733Z [W826 22:55:14.351079055 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1839832Z [W826 22:55:14.351136244 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841163Z [W826 22:55:14.597048164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841267Z [W826 22:55:14.597117762 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841368Z [W826 22:55:14.022347144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841471Z [W826 22:55:14.022460713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841569Z [W826 22:55:15.443908842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841665Z [W826 22:55:15.444185138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841762Z [W826 22:55:15.911066540 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841864Z [W826 22:55:15.911250727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1841960Z [W826 22:55:16.293192615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842056Z [W826 22:55:16.293395752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842153Z [W826 22:55:16.726252697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842251Z [W826 22:55:16.726447454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842351Z [W826 22:55:17.183102442 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842446Z [W826 22:55:17.183232780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842543Z [W826 22:55:17.655077425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842672Z [W826 22:55:17.655180744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842769Z [W826 22:55:18.108492845 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842865Z [W826 22:55:18.108693291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1842962Z [W826 22:55:18.528122343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1843095Z [W826 22:55:18.528257391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844377Z [W826 22:55:18.949148139 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844485Z [W826 22:55:18.949267507 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844585Z [W826 22:55:19.402086505 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844708Z [W826 22:55:19.402225943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844806Z [W826 22:55:19.858269532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1844903Z [W826 22:55:19.858504888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845000Z [W826 22:55:20.289278564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845102Z [W826 22:55:20.289494951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845201Z [W826 22:55:20.416149974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845298Z [W826 22:55:20.677218480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845396Z [W826 22:55:20.677393847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845493Z [W826 22:55:20.808116678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845590Z [W826 22:55:21.087086398 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845687Z [W826 22:55:21.087241816 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845783Z [W826 22:55:21.222194431 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845883Z [W826 22:55:21.522915427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1845984Z [W826 22:55:21.523163203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1846083Z [W826 22:55:21.637111841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1846183Z [W826 22:55:21.915505791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1846282Z [W826 22:55:21.915703018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1847588Z [W826 22:55:21.032975834 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1847695Z [W826 22:55:22.308269832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1847795Z [W826 22:55:22.308428830 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1847895Z [W826 22:55:22.434902965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1847998Z [W826 22:55:22.694428965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848093Z [W826 22:55:22.694599862 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848190Z [W826 22:55:22.819100698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848312Z [W826 22:55:23.075710382 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848409Z [W826 22:55:23.075960429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848506Z [W826 22:55:23.192125833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848602Z [W826 22:55:23.476087067 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848726Z [W826 22:55:23.476256975 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848823Z [W826 22:55:23.593572470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1848919Z [W826 22:55:23.857074619 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849016Z [W826 22:55:23.857208957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849141Z [W826 22:55:23.980570501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849240Z [W826 22:55:24.236421887 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849339Z [W826 22:55:24.236607144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849438Z [W826 22:55:24.360186964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849540Z [W826 22:55:24.628078895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1849638Z [W826 22:55:24.628193613 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1850994Z [W826 22:55:24.751507647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851101Z [W826 22:55:24.004257501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851206Z [W826 22:55:24.004517067 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851309Z [W826 22:55:25.117165745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851405Z [W826 22:55:25.375097949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851504Z [W826 22:55:25.375257467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851605Z [W826 22:55:25.499061423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851703Z [W826 22:55:25.748093364 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851799Z [W826 22:55:25.748237492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851896Z [W826 22:55:25.875155820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1851995Z [W826 22:55:26.147098210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852093Z [W826 22:55:26.147266317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852188Z [W826 22:55:26.269066295 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852286Z [W826 22:55:26.519981487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852384Z [W826 22:55:26.520173894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852485Z [W826 22:55:26.635249505 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852584Z [W826 22:55:26.889197760 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852681Z [W826 22:55:26.889343568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852809Z [W826 22:55:26.018057479 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1852907Z [W826 22:55:27.284061788 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1853003Z [W826 22:55:27.284178956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854322Z [W826 22:55:27.398044386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854468Z [W826 22:55:27.656217677 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854569Z [W826 22:55:27.656555631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854666Z [W826 22:55:27.776130644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854763Z [W826 22:55:28.050096771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854884Z [W826 22:55:28.050299477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1854981Z [W826 22:55:28.161150423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855077Z [W826 22:55:28.433171730 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855173Z [W826 22:55:28.433451037 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855273Z [W826 22:55:28.549143018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855370Z [W826 22:55:28.803282071 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855467Z [W826 22:55:28.803474837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855564Z [W826 22:55:28.934080939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855665Z [W826 22:55:29.194098092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855764Z [W826 22:55:29.194245429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855863Z [W826 22:55:29.316071296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1855962Z [W826 22:55:29.571067315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1856061Z [W826 22:55:29.571195733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1856158Z [W826 22:55:29.693259007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1856254Z [W826 22:55:29.958072265 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1857555Z [W826 22:55:29.958211163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1857669Z [W826 22:55:30.390065653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1857768Z [W826 22:55:30.390271251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1857868Z [W826 22:55:30.822237409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1857966Z [W826 22:55:30.822511284 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858066Z [W826 22:55:31.223126765 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858162Z [W826 22:55:31.223370222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858260Z [W826 22:55:31.663064621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858357Z [W826 22:55:31.663288987 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858476Z [W826 22:55:32.096083973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858573Z [W826 22:55:32.096318219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858669Z [W826 22:55:32.534057589 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858765Z [W826 22:55:32.534215557 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1858805Z PASSED [90.7086s] [ 93%] 2025-08-26T23:15:41.1859037Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_m [W826 22:55:37.248737380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859141Z [W826 22:55:37.248924867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859237Z [W826 22:55:37.695197457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859356Z [W826 22:55:37.695340843 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859453Z [W826 22:55:38.090109974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859552Z [W826 22:55:38.090287571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1859649Z [W826 22:55:38.517277497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861028Z [W826 22:55:38.517418944 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861132Z [W826 22:55:38.918209522 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861231Z [W826 22:55:38.918333910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861330Z [W826 22:55:39.343252827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861435Z [W826 22:55:39.343475384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861531Z [W826 22:55:39.816153876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861628Z [W826 22:55:39.816314934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861724Z [W826 22:55:40.281319894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861822Z [W826 22:55:40.281558380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1861918Z [W826 22:55:40.871086216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862016Z [W826 22:55:40.871206214 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862112Z [W826 22:55:41.404166970 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862212Z [W826 22:55:41.404334737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862307Z [W826 22:55:41.868489361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862407Z [W826 22:55:41.868688318 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862505Z [W826 22:55:42.380498649 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862606Z [W826 22:55:42.380669176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862703Z [W826 22:55:42.840222630 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862800Z [W826 22:55:42.840484906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1862896Z [W826 22:55:43.317091928 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864218Z [W826 22:55:43.317475003 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864324Z [W826 22:55:43.839869101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864427Z [W826 22:55:43.840030218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864523Z [W826 22:55:44.278154632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864667Z [W826 22:55:44.278337340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864763Z [W826 22:55:44.747250790 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864861Z [W826 22:55:44.747459117 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1864956Z [W826 22:55:45.211082748 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865075Z [W826 22:55:45.211221286 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865171Z [W826 22:55:45.739768750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865268Z [W826 22:55:45.740021015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865365Z [W826 22:55:46.244294142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865465Z [W826 22:55:46.244521190 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865561Z [W826 22:55:46.732343118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865661Z [W826 22:55:46.732566655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865759Z [W826 22:55:47.394113824 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865864Z [W826 22:55:47.394551677 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1865960Z [W826 22:55:47.568216827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1866057Z [W826 22:55:47.940128489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1866152Z [W826 22:55:47.940320686 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867471Z [W826 22:55:48.064194962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867578Z [W826 22:55:48.329074559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867678Z [W826 22:55:48.329454443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867774Z [W826 22:55:48.450484192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867879Z [W826 22:55:48.764115130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1867975Z [W826 22:55:48.764287757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868072Z [W826 22:55:48.881593213 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868168Z [W826 22:55:49.153336316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868269Z [W826 22:55:49.153524203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868366Z [W826 22:55:49.286277152 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868464Z [W826 22:55:49.553206778 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868560Z [W826 22:55:49.553326216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868681Z [W826 22:55:49.666390167 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868778Z [W826 22:55:49.915114443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868878Z [W826 22:55:49.915244132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1868977Z [W826 22:55:49.038107402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1869117Z [W826 22:55:50.301058869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1869215Z [W826 22:55:50.301162727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1869313Z [W826 22:55:50.428893534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1869409Z [W826 22:55:50.696044476 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1870790Z [W826 22:55:50.696137925 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1870899Z [W826 22:55:50.815808584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1870998Z [W826 22:55:51.119834900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871096Z [W826 22:55:51.119979218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871201Z [W826 22:55:51.235312115 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871298Z [W826 22:55:51.481049447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871394Z [W826 22:55:51.481142675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871492Z [W826 22:55:51.600211605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871593Z [W826 22:55:51.861315230 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871690Z [W826 22:55:51.861459878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871786Z [W826 22:55:51.996332304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871884Z [W826 22:55:52.262140968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1871981Z [W826 22:55:52.262322594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872078Z [W826 22:55:52.383122877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872177Z [W826 22:55:52.661065083 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872277Z [W826 22:55:52.661184222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872379Z [W826 22:55:52.773427647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872477Z [W826 22:55:53.061126772 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872574Z [W826 22:55:53.061311200 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872671Z [W826 22:55:53.194261676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1872768Z [W826 22:55:53.459076374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874130Z [W826 22:55:53.459204022 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874234Z [W826 22:55:53.582352598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874334Z [W826 22:55:53.866069156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874464Z [W826 22:55:53.866186174 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874562Z [W826 22:55:53.987759035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874658Z [W826 22:55:54.256069511 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874755Z [W826 22:55:54.256191758 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874887Z [W826 22:55:54.390380695 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1874985Z [W826 22:55:54.650987838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875084Z [W826 22:55:54.651201835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875180Z [W826 22:55:55.064376492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875297Z [W826 22:55:55.064827576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875394Z [W826 22:55:55.527508922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875490Z [W826 22:55:55.527725119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875590Z [W826 22:55:56.120168850 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875691Z [W826 22:55:56.120397216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875788Z [W826 22:55:56.552153198 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875884Z [W826 22:55:56.552647760 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1875981Z [W826 22:56:00.892095111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1876080Z [W826 22:56:00.892222609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877384Z [W826 22:56:01.306051146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877492Z [W826 22:56:01.306127296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877591Z [W826 22:56:01.727058233 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877696Z [W826 22:56:01.727140392 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877795Z [W826 22:56:02.126223056 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877891Z [W826 22:56:02.126350274 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1877989Z [W826 22:56:02.554116448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878091Z [W826 22:56:02.554213175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878189Z [W826 22:56:02.976384035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878286Z [W826 22:56:02.976614772 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878383Z [W826 22:56:03.381683603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878481Z [W826 22:56:03.381918869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878578Z [W826 22:56:03.823123006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878675Z [W826 22:56:03.823283314 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878772Z [W826 22:56:04.266407060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878892Z [W826 22:56:04.266648946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1878993Z [W826 22:56:04.730090812 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1879092Z [W826 22:56:04.730222849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1879189Z [W826 22:56:05.186093730 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1879314Z [W826 22:56:05.186240418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1879412Z [W826 22:56:05.651297628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1880801Z [W826 22:56:05.651577313 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1880915Z [W826 22:56:06.120206368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881046Z [W826 22:56:06.120440725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881148Z [W826 22:56:06.580145846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881246Z [W826 22:56:06.580294504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881345Z [W826 22:56:07.072101222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881449Z [W826 22:56:07.072231280 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881546Z [W826 22:56:07.536072419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881642Z [W826 22:56:07.536168828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881739Z [W826 22:56:07.019797471 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881840Z [W826 22:56:07.019897910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1881937Z [W826 22:56:08.476195855 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882033Z [W826 22:56:08.476399081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882130Z [W826 22:56:08.952282265 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882227Z [W826 22:56:08.952444252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882326Z [W826 22:56:09.421102007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882425Z [W826 22:56:09.421242864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882522Z [W826 22:56:09.851151914 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882621Z [W826 22:56:09.851323302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882718Z [W826 22:56:10.266323961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1882814Z [W826 22:56:10.266481509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884147Z [W826 22:56:10.383351552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884247Z [W826 22:56:10.649964962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884345Z [W826 22:56:10.650080871 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884444Z [W826 22:56:10.764088048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884541Z [W826 22:56:10.031694154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884668Z [W826 22:56:10.031879591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884764Z [W826 22:56:11.144235823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884860Z [W826 22:56:11.416476077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1884958Z [W826 22:56:11.416636454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885089Z [W826 22:56:11.528218009 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885186Z [W826 22:56:11.786445509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885283Z [W826 22:56:11.786747075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885381Z [W826 22:56:11.908226386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885497Z [W826 22:56:12.185207598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885596Z [W826 22:56:12.185402345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885694Z [W826 22:56:12.320120644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885791Z [W826 22:56:12.599088445 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885892Z [W826 22:56:12.599278732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1885989Z [W826 22:56:12.721150048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1886085Z [W826 22:56:12.000116999 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887389Z [W826 22:56:12.000299736 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887506Z [W826 22:56:13.127090767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887606Z [W826 22:56:13.408717877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887706Z [W826 22:56:13.408883714 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887802Z [W826 22:56:13.531120634 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1887904Z [W826 22:56:13.805240030 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888000Z [W826 22:56:13.805444917 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888097Z [W826 22:56:13.943234788 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888194Z [W826 22:56:14.196193739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888296Z [W826 22:56:14.196400715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888393Z [W826 22:56:14.327123626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888491Z [W826 22:56:14.604797766 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888589Z [W826 22:56:14.605070142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888688Z [W826 22:56:14.727098156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888787Z [W826 22:56:14.998153668 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888886Z [W826 22:56:14.998337065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1888983Z [W826 22:56:15.128263108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1889103Z [W826 22:56:15.398241296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1889200Z [W826 22:56:15.398541433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1889298Z [W826 22:56:15.530141880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1889394Z [W826 22:56:15.784141774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1890802Z [W826 22:56:15.784320852 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1890907Z [W826 22:56:15.905315191 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891008Z [W826 22:56:16.151084502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891107Z [W826 22:56:16.151213430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891227Z [W826 22:56:16.266144552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891324Z [W826 22:56:16.517371511 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891422Z [W826 22:56:16.517611557 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891517Z [W826 22:56:16.632324863 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891619Z [W826 22:56:16.881104498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891715Z [W826 22:56:16.881275315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891813Z [W826 22:56:16.016105353 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1891909Z [W826 22:56:17.249201729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892009Z [W826 22:56:17.249383295 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892106Z [W826 22:56:17.674072886 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892204Z [W826 22:56:17.674257323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892302Z [W826 22:56:18.114361316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892408Z [W826 22:56:18.114520665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892506Z [W826 22:56:18.533058969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892602Z [W826 22:56:18.533215667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1892699Z [W826 22:56:18.953166750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894024Z [W826 22:56:18.953465295 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894129Z [W826 22:56:23.041124051 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894229Z [W826 22:56:23.041254739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894329Z [W826 22:56:24.490270366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894433Z [W826 22:56:24.490477532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894529Z [W826 22:56:24.928631716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894626Z [W826 22:56:24.928778004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894722Z [W826 22:56:25.370065558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894850Z [W826 22:56:25.370159648 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1894947Z [W826 22:56:25.808070814 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895044Z [W826 22:56:25.808186532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895140Z [W826 22:56:26.273066345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895267Z [W826 22:56:26.273163893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895366Z [W826 22:56:26.685105320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895467Z [W826 22:56:26.685161339 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895568Z [W826 22:56:27.117319745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895683Z [W826 22:56:27.117498512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895779Z [W826 22:56:27.571833737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895876Z [W826 22:56:27.571991454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1895973Z [W826 22:56:27.025070578 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897294Z [W826 22:56:27.025171836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897403Z [W826 22:56:28.484766420 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897505Z [W826 22:56:28.485026206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897604Z [W826 22:56:28.918075387 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897711Z [W826 22:56:28.918185636 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897808Z [W826 22:56:29.390220219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1897906Z [W826 22:56:29.390355946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898003Z [W826 22:56:29.842044212 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898104Z [W826 22:56:29.842106451 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898201Z [W826 22:56:30.301288651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898298Z [W826 22:56:30.301459748 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898395Z [W826 22:56:30.764080165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898499Z [W826 22:56:30.764172164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898595Z [W826 22:56:31.196455137 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898695Z [W826 22:56:31.196648164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898794Z [W826 22:56:31.642078666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898894Z [W826 22:56:31.642230534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1898991Z [W826 22:56:32.090065817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1899089Z [W826 22:56:32.090153867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1899185Z [W826 22:56:32.557430032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1899306Z [W826 22:56:32.557703498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1900680Z [W826 22:56:32.970077518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1900790Z [W826 22:56:32.970193246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1900888Z [W826 22:56:33.436780983 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901033Z [W826 22:56:33.436956529 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901130Z [W826 22:56:33.569072518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901228Z [W826 22:56:33.851522765 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901325Z [W826 22:56:33.851731612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901443Z [W826 22:56:33.978846748 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901541Z [W826 22:56:34.249070674 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901640Z [W826 22:56:34.249193441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901736Z [W826 22:56:34.372292919 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901837Z [W826 22:56:34.634978109 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1901934Z [W826 22:56:34.635252316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902032Z [W826 22:56:34.762307102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902131Z [W826 22:56:34.034301941 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902239Z [W826 22:56:34.034458927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902336Z [W826 22:56:35.158620319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902434Z [W826 22:56:35.437082517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902531Z [W826 22:56:35.437241114 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1902632Z [W826 22:56:35.569053368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1903957Z [W826 22:56:35.837171865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904065Z [W826 22:56:35.837361473 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904166Z [W826 22:56:35.961067071 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904267Z [W826 22:56:36.207273156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904367Z [W826 22:56:36.207424183 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904463Z [W826 22:56:36.341261295 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904560Z [W826 22:56:36.595092043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904663Z [W826 22:56:36.595240940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904761Z [W826 22:56:36.713100538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904857Z [W826 22:56:36.984094542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1904954Z [W826 22:56:36.984234560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905093Z [W826 22:56:37.104053518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905190Z [W826 22:56:37.366472043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905286Z [W826 22:56:37.366613991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905386Z [W826 22:56:37.489341394 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905515Z [W826 22:56:37.756089262 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905614Z [W826 22:56:37.756205031 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905711Z [W826 22:56:37.881049591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905808Z [W826 22:56:38.160051691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1905921Z [W826 22:56:38.160128741 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1906018Z [W826 22:56:38.281041081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907326Z [W826 22:56:38.556049452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907434Z [W826 22:56:38.556125761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907538Z [W826 22:56:38.682917145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907638Z [W826 22:56:38.951100176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907737Z [W826 22:56:38.951270624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907834Z [W826 22:56:39.069073028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1907938Z [W826 22:56:39.330824579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908035Z [W826 22:56:39.331213763 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908131Z [W826 22:56:39.451227723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908228Z [W826 22:56:39.717838909 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908329Z [W826 22:56:39.717912668 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908427Z [W826 22:56:39.845050257 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908523Z [W826 22:56:40.106293826 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908621Z [W826 22:56:40.106450104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908719Z [W826 22:56:40.230097767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908818Z [W826 22:56:40.501291082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1908917Z [W826 22:56:40.501409820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1909015Z [W826 22:56:40.972179824 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1909114Z [W826 22:56:40.972309893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1909211Z [W826 22:56:41.394383705 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1909307Z [W826 22:56:41.394561212 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1910704Z [W826 22:56:41.826109948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1910852Z [W826 22:56:41.826355024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1910955Z [W826 22:56:42.258097887 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911054Z [W826 22:56:42.258309563 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911094Z PASSED [69.7358s] [ 94%] 2025-08-26T23:15:41.1911332Z test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_s [W826 22:56:45.524861803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911430Z [W826 22:56:45.525005660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911526Z [W826 22:56:45.941168737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911623Z [W826 22:56:45.941312634 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911743Z [W826 22:56:46.385093689 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911839Z [W826 22:56:46.385236316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1911935Z [W826 22:56:46.809833591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912036Z [W826 22:56:46.809955799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912137Z [W826 22:56:47.246105343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912234Z [W826 22:56:47.246215091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912331Z [W826 22:56:47.686137656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912428Z [W826 22:56:47.686251175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912529Z [W826 22:56:48.100674477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912626Z [W826 22:56:48.100887964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1912722Z [W826 22:56:48.556137160 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914118Z [W826 22:56:48.556330927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914229Z [W826 22:56:48.964116892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914332Z [W826 22:56:48.964208542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914429Z [W826 22:56:49.422085216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914528Z [W826 22:56:49.422197855 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914629Z [W826 22:56:49.862164819 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914726Z [W826 22:56:49.862380866 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914822Z [W826 22:56:50.290069862 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1914919Z [W826 22:56:50.290190980 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915020Z [W826 22:56:50.743084932 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915117Z [W826 22:56:50.743211330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915214Z [W826 22:56:51.182337179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915311Z [W826 22:56:51.182530225 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915430Z [W826 22:56:51.590161333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915526Z [W826 22:56:51.590270242 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915625Z [W826 22:56:51.017051861 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915724Z [W826 22:56:51.017142120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915851Z [W826 22:56:52.178057362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1915949Z [W826 22:56:52.446056136 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1916047Z [W826 22:56:52.446153675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1916144Z [W826 22:56:52.568096895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917483Z [W826 22:56:52.844542487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917589Z [W826 22:56:52.844627126 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917690Z [W826 22:56:52.949090488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917789Z [W826 22:56:53.212302016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917893Z [W826 22:56:53.212386326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1917989Z [W826 22:56:53.337086062 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918087Z [W826 22:56:53.601078478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918184Z [W826 22:56:53.601150667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918288Z [W826 22:56:53.730325904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918384Z [W826 22:56:53.012060645 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918481Z [W826 22:56:53.012162583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918577Z [W826 22:56:54.127097492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918677Z [W826 22:56:54.407065230 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918773Z [W826 22:56:54.407156108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918872Z [W826 22:56:54.520209836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1918972Z [W826 22:56:54.777121232 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1919073Z [W826 22:56:54.777232490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1919169Z [W826 22:56:54.896086218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1919266Z [W826 22:56:55.159352967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1919362Z [W826 22:56:55.159436455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1920736Z [W826 22:56:55.288082501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1920848Z [W826 22:56:55.554297942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1920950Z [W826 22:56:55.554372891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921047Z [W826 22:56:55.679084788 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921184Z [W826 22:56:55.927904581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921281Z [W826 22:56:55.927986649 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921378Z [W826 22:56:56.060078661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921474Z [W826 22:56:56.326064577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921608Z [W826 22:56:56.326161255 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921705Z [W826 22:56:56.441089715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921802Z [W826 22:56:56.701071073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1921899Z [W826 22:56:56.701188111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922017Z [W826 22:56:56.856389484 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922115Z [W826 22:56:57.137182477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922218Z [W826 22:56:57.137375774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922314Z [W826 22:56:57.233374439 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922416Z [W826 22:56:57.503263613 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922513Z [W826 22:56:57.503380731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922610Z [W826 22:56:57.616427690 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1922706Z [W826 22:57:00.580079769 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924024Z [W826 22:57:00.580203047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924129Z [W826 22:57:00.991112125 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924229Z [W826 22:57:00.991259092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924327Z [W826 22:57:01.410032357 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924430Z [W826 22:57:01.410128026 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924526Z [W826 22:57:01.823187789 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924623Z [W826 22:57:01.823410396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924719Z [W826 22:57:02.266079889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924821Z [W826 22:57:02.266202587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1924917Z [W826 22:57:02.680166806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925014Z [W826 22:57:02.680360283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925110Z [W826 22:57:03.122111170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925209Z [W826 22:57:03.122264738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925306Z [W826 22:57:03.561055341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925409Z [W826 22:57:03.561140149 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925507Z [W826 22:57:03.979389012 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925628Z [W826 22:57:03.979653557 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925724Z [W826 22:57:04.380121118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925822Z [W826 22:57:04.380305425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1925918Z [W826 22:57:04.793071323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1926043Z [W826 22:57:04.793167482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927355Z [W826 22:57:05.226572628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927463Z [W826 22:57:05.226915613 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927561Z [W826 22:57:05.651070944 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927691Z [W826 22:57:05.651203492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927787Z [W826 22:57:06.083062453 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927886Z [W826 22:57:06.083167091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1927981Z [W826 22:57:06.531054362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928083Z [W826 22:57:06.531150740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928179Z [W826 22:57:06.959066053 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928276Z [W826 22:57:06.959163621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928375Z [W826 22:57:07.081257679 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928476Z [W826 22:57:07.349180394 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928573Z [W826 22:57:07.349329902 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928671Z [W826 22:57:07.468089291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928768Z [W826 22:57:07.723331044 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928869Z [W826 22:57:07.723569531 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1928970Z [W826 22:57:07.853155261 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1929068Z [W826 22:57:08.127566525 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1929165Z [W826 22:57:08.127931370 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1929268Z [W826 22:57:08.243868283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1929364Z [W826 22:57:08.493423445 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1930773Z [W826 22:57:08.493706400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1930872Z [W826 22:57:08.610284353 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1930975Z [W826 22:57:08.891488073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931073Z [W826 22:57:08.891666879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931170Z [W826 22:57:08.011148208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931265Z [W826 22:57:09.264983623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931397Z [W826 22:57:09.265094641 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931494Z [W826 22:57:09.390084172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931591Z [W826 22:57:09.663055479 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931687Z [W826 22:57:09.663134818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931820Z [W826 22:57:09.780067267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1931916Z [W826 22:57:10.063060457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932014Z [W826 22:57:10.063156896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932114Z [W826 22:57:10.185068116 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932237Z [W826 22:57:10.457135986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932334Z [W826 22:57:10.457295304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932431Z [W826 22:57:10.593113047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932528Z [W826 22:57:10.855351132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1932628Z [W826 22:57:10.855450599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1933971Z [W826 22:57:10.986074524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934079Z [W826 22:57:11.241054781 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934178Z [W826 22:57:11.241148329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934282Z [W826 22:57:11.358240086 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934382Z [W826 22:57:11.621142468 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934478Z [W826 22:57:11.621325296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934578Z [W826 22:57:11.741245088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934680Z [W826 22:57:11.995102802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934778Z [W826 22:57:11.995259910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934875Z [W826 22:57:12.138267621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1934972Z [W826 22:57:12.405097873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935075Z [W826 22:57:12.405267621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935172Z [W826 22:57:12.536931239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935268Z [W826 22:57:16.694231831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935366Z [W826 22:57:16.694345309 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935465Z [W826 22:57:17.146578823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935564Z [W826 22:57:17.146725820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935660Z [W826 22:57:17.606324649 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935757Z [W826 22:57:17.606514066 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935876Z [W826 22:57:18.049116139 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1935973Z [W826 22:57:18.049270447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937309Z [W826 22:57:18.487084215 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937419Z [W826 22:57:18.487177542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937560Z [W826 22:57:18.912126111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937660Z [W826 22:57:18.912250119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937759Z [W826 22:57:19.318170434 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937856Z [W826 22:57:19.318311763 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1937970Z [W826 22:57:19.770347179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938067Z [W826 22:57:19.770476197 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938164Z [W826 22:57:20.188926426 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938262Z [W826 22:57:20.188995805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938363Z [W826 22:57:20.629040479 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938460Z [W826 22:57:20.629098038 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938557Z [W826 22:57:21.058071294 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1938654Z [W826 22:57:21.058164913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1940312Z [W826 22:57:21.454073044 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1940484Z [W826 22:57:21.454176202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1940582Z [W826 22:57:21.846052795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1940680Z [W826 22:57:21.846114544 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1940779Z [W826 22:57:22.277579722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942469Z [W826 22:57:22.277765379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942575Z [W826 22:57:22.717091103 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942676Z [W826 22:57:22.717212341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942778Z [W826 22:57:23.164128218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942902Z [W826 22:57:23.164201666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1942999Z [W826 22:57:23.278034153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943097Z [W826 22:57:23.543353158 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943196Z [W826 22:57:23.543432828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943294Z [W826 22:57:23.670581726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943391Z [W826 22:57:23.929138117 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943489Z [W826 22:57:23.929288154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943640Z [W826 22:57:23.048102153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943740Z [W826 22:57:24.281061464 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943838Z [W826 22:57:24.281136492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1943937Z [W826 22:57:24.416053930 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1944059Z [W826 22:57:24.694752367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1944159Z [W826 22:57:24.694881335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1944255Z [W826 22:57:24.827129884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1944352Z [W826 22:57:25.152114841 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1944469Z [W826 22:57:25.152255259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1945936Z [W826 22:57:25.281761011 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946045Z [W826 22:57:25.517192452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946148Z [W826 22:57:25.517336720 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946250Z [W826 22:57:25.640268324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946349Z [W826 22:57:25.038068576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946445Z [W826 22:57:25.038159684 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946541Z [W826 22:57:26.163079278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946643Z [W826 22:57:26.416584148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946818Z [W826 22:57:26.416722406 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1946915Z [W826 22:57:26.525067228 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947013Z [W826 22:57:26.754072959 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947110Z [W826 22:57:26.754163168 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947207Z [W826 22:57:26.856062430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947303Z [W826 22:57:27.105213437 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947402Z [W826 22:57:27.105395666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947501Z [W826 22:57:27.223115751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947599Z [W826 22:57:27.461226260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947695Z [W826 22:57:27.461460597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947792Z [W826 22:57:27.576453345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947890Z [W826 22:57:27.804817807 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1947989Z [W826 22:57:27.804969645 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948085Z [W826 22:57:27.913064180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948182Z [W826 22:57:28.161039356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948300Z [W826 22:57:28.161210573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948399Z [W826 22:57:28.284050029 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948496Z [W826 22:57:28.507052074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1948598Z [W826 22:57:28.507124313 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1949971Z [W826 22:57:28.605049598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950020Z PASSED [46.1369s] [ 94%] 2025-08-26T23:15:41.1950219Z test_fx.py::TestVisionTracing::test_torchvision_models_googlenet [W826 22:57:33.229142716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950317Z [W826 22:57:34.520274097 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950489Z [W826 22:57:34.739076348 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950589Z [W826 22:57:35.348116297 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950686Z [W826 22:57:35.012073732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950783Z [W826 22:57:36.624980041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950882Z [W826 22:57:37.266106702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1950978Z [W826 22:57:37.704327143 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951075Z [W826 22:57:37.878249163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951172Z [W826 22:57:38.279158266 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951273Z [W826 22:57:38.424052099 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951400Z [W826 22:57:39.455112503 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951499Z [W826 22:57:40.542224564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951595Z [W826 22:57:40.753486222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951694Z [W826 22:57:41.411073185 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951790Z [W826 22:57:41.995096545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951887Z [W826 22:57:42.613055956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1951983Z [W826 22:57:43.220051898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1953270Z [W826 22:57:43.616121157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1953378Z [W826 22:57:43.766074650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1953546Z [W826 22:57:44.154065784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1953645Z [W826 22:57:44.348045312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1953685Z PASSED [16.1717s] [ 94%] 2025-08-26T23:15:41.1953795Z test_fx.py::TestVisionTracing::test_torchvision_models_inception_v3 PASSED [29.8633s] [ 94%] 2025-08-26T23:15:41.1953980Z test_fx.py::TestVisionTracing::test_torchvision_models_maxvit_t [W826 22:58:15.690200991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954078Z [W826 22:58:15.690416299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954179Z [W826 22:58:17.112159595 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954305Z [W826 22:58:17.112337542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954403Z [W826 22:58:18.676182205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954499Z [W826 22:58:18.676349702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954614Z [W826 22:58:20.139122769 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954711Z [W826 22:58:20.139546592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954810Z [W826 22:58:21.765347550 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1954908Z [W826 22:58:21.765539077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1955029Z [W826 22:58:23.275374610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1955132Z [W826 22:58:23.275587097 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1955229Z [W826 22:58:24.733299023 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1955325Z [W826 22:58:24.733469480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1955425Z [W826 22:58:26.294093243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1956706Z [W826 22:58:26.294226671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1956813Z [W826 22:58:27.790171901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1956911Z [W826 22:58:27.790346968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957014Z [W826 22:58:29.205454939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957131Z [W826 22:58:29.630235879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957229Z [W826 22:58:29.630415536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957326Z [W826 22:58:30.876833575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957426Z [W826 22:58:30.877012232 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957522Z [W826 22:58:32.131492755 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957619Z [W826 22:58:32.131654203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957715Z [W826 22:58:33.607150682 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957813Z [W826 22:58:33.607294829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1957911Z [W826 22:58:35.131124715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958009Z [W826 22:58:35.131294723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958107Z [W826 22:58:36.556804811 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958208Z [W826 22:58:36.556960168 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958305Z [W826 22:58:38.089147444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958403Z [W826 22:58:38.089318231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958499Z [W826 22:58:39.535770192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958596Z [W826 22:58:39.535948581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1958710Z [W826 22:58:40.963292699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1959989Z [W826 22:58:40.963404718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960092Z [W826 22:58:43.052104992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960213Z [W826 22:58:43.052244290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960312Z [W826 22:58:44.526102934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960477Z [W826 22:58:44.526229552 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960574Z [W826 22:58:45.860907235 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960693Z [W826 22:58:46.151198302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960795Z [W826 22:58:46.151529327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960892Z [W826 22:58:47.112101770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1960988Z [W826 22:58:47.112294127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961087Z [W826 22:58:49.761260010 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961183Z [W826 22:58:49.761503866 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961281Z [W826 22:58:51.261158879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961377Z [W826 22:58:51.261316227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961480Z [W826 22:58:52.888141217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961597Z [W826 22:58:52.888295815 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961695Z [W826 22:58:54.422098656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961790Z [W826 22:58:54.422210174 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961889Z [W826 22:58:55.965163232 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1961986Z [W826 22:58:55.965374819 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963262Z [W826 22:58:57.498099106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963370Z [W826 22:58:57.498220534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963473Z [W826 22:58:58.910704915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963575Z [W826 22:58:58.910805623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963673Z [W826 22:59:00.460077312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963769Z [W826 22:59:00.460209650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963870Z [W826 22:59:01.878830896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1963967Z [W826 22:59:01.878980754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964065Z [W826 22:59:03.136081585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964161Z [W826 22:59:03.407101462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964259Z [W826 22:59:03.407253510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964386Z [W826 22:59:04.387071453 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964484Z [W826 22:59:04.387214830 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964520Z PASSED [50.3714s] [ 94%] 2025-08-26T23:15:41.1964732Z test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_5 [W826 22:59:06.765151787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964831Z [W826 22:59:07.081473339 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1964929Z [W826 22:59:07.373147035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1965026Z [W826 22:59:07.610129121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1965138Z [W826 22:59:07.916220812 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1965238Z [W826 22:59:08.052059106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1965340Z [W826 22:59:08.397440554 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1966603Z [W826 22:59:08.688236303 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1966710Z [W826 22:59:08.872137277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1966809Z [W826 22:59:08.921862182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1966907Z [W826 22:59:09.064080446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967006Z [W826 22:59:09.331141605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967105Z [W826 22:59:09.604100952 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967223Z [W826 22:59:09.900106719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967319Z [W826 22:59:11.555061702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967416Z [W826 22:59:11.005452964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967515Z [W826 22:59:12.426844978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967613Z [W826 22:59:12.882104765 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967710Z [W826 22:59:13.370125170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967808Z [W826 22:59:13.892939804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1967905Z [W826 22:59:14.413440894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968007Z [W826 22:59:14.891552723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968105Z [W826 22:59:15.188512616 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968204Z [W826 22:59:15.290469407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968302Z [W826 22:59:15.677383158 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968400Z [W826 22:59:15.900126068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1968498Z [W826 22:59:15.043084340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1969767Z [W826 22:59:16.195285839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1969876Z [W826 22:59:17.899576123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970001Z [W826 22:59:18.128065502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970099Z [W826 22:59:18.257040803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970196Z [W826 22:59:18.382013335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970307Z [W826 22:59:18.654059376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970479Z [W826 22:59:18.968108373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970575Z [W826 22:59:19.274437169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970673Z [W826 22:59:19.424062219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970791Z [W826 22:59:19.496035196 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970891Z [W826 22:59:19.520023333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1970988Z [W826 22:59:19.817910831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971086Z [W826 22:59:20.072547944 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971184Z [W826 22:59:20.300099058 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971281Z [W826 22:59:20.560075977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971320Z PASSED [15.5001s] [ 94%] 2025-08-26T23:15:41.1971509Z test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_75 [W826 22:59:23.344104386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971609Z [W826 22:59:23.623338596 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971726Z [W826 22:59:23.949096269 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1971824Z [W826 22:59:24.210054143 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973113Z [W826 22:59:24.508076210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973220Z [W826 22:59:24.791466824 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973319Z [W826 22:59:25.101361585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973417Z [W826 22:59:25.407215259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973514Z [W826 22:59:25.712108469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973612Z [W826 22:59:25.019045486 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973713Z [W826 22:59:28.709091979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973809Z [W826 22:59:28.021106478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1973906Z [W826 22:59:29.346221652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974004Z [W826 22:59:29.672059135 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974101Z [W826 22:59:29.966321520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974197Z [W826 22:59:30.263113876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974294Z [W826 22:59:30.578207916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974391Z [W826 22:59:30.895338304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974530Z [W826 22:59:31.180737677 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974628Z [W826 22:59:31.511191828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974727Z [W826 22:59:34.478039979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974844Z [W826 22:59:34.781081847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1974941Z [W826 22:59:35.116051467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1975038Z [W826 22:59:35.429136389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1975135Z [W826 22:59:35.737229849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976426Z [W826 22:59:36.076842457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976538Z [W826 22:59:36.377121637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976636Z [W826 22:59:36.677197272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976737Z [W826 22:59:36.987480837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976835Z [W826 22:59:37.304220742 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1976872Z PASSED [16.7395s] [ 94%] 2025-08-26T23:15:41.1977055Z test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_0 [W826 22:59:40.094100391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977153Z [W826 22:59:40.411245719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977251Z [W826 22:59:40.708070614 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977371Z [W826 22:59:40.014053345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977469Z [W826 22:59:41.338059036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977566Z [W826 22:59:41.603112777 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977664Z [W826 22:59:41.917391490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977764Z [W826 22:59:42.249085581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977863Z [W826 22:59:42.572095548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1977960Z [W826 22:59:42.880042660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1978058Z [W826 22:59:45.807068581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1978157Z [W826 22:59:46.103876356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1978252Z [W826 22:59:46.391124911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1978349Z [W826 22:59:46.684101635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1978446Z [W826 22:59:46.954136518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1979730Z [W826 22:59:47.263065253 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1979827Z [W826 22:59:47.552275207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1979927Z [W826 22:59:47.880201717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980023Z [W826 22:59:48.181379005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980142Z [W826 22:59:48.482033590 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980239Z [W826 22:59:51.636056774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980336Z [W826 22:59:51.915084007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980534Z [W826 22:59:52.220726335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980631Z [W826 22:59:52.543774121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980729Z [W826 22:59:52.860192520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980826Z [W826 22:59:53.150044484 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1980942Z [W826 22:59:53.468406654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981042Z [W826 22:59:53.767244367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981138Z [W826 22:59:54.061204496 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981240Z [W826 22:59:54.377059085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981277Z PASSED [17.0726s] [ 94%] 2025-08-26T23:15:41.1981462Z test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_3 [W826 22:59:57.330371966 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981558Z [W826 22:59:57.636337869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981654Z [W826 22:59:57.952934296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1981753Z [W826 22:59:58.973315566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983050Z [W826 22:59:59.283116669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983158Z [W826 22:59:59.609205658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983257Z [W826 22:59:59.921079618 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983358Z [W826 23:00:00.218318617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983454Z [W826 23:00:02.026391471 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983551Z [W826 23:00:03.315232450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983647Z [W826 23:00:03.634993658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983748Z [W826 23:00:04.576518267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983847Z [W826 23:00:04.891131194 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1983944Z [W826 23:00:05.205191990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984040Z [W826 23:00:05.512069238 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984139Z [W826 23:00:05.820083609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984234Z [W826 23:00:08.680136792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984331Z [W826 23:00:08.999206271 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984429Z [W826 23:00:09.302076211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984528Z [W826 23:00:10.388416314 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984647Z [W826 23:00:10.692190331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984744Z [W826 23:00:10.962075095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984839Z [W826 23:00:11.278063292 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984951Z [W826 23:00:11.573032145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1984987Z PASSED [17.1748s] [ 94%] 2025-08-26T23:15:41.1986353Z test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v2 [W826 23:00:14.561051516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986460Z [W826 23:00:14.933119269 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986581Z [W826 23:00:15.290889895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986685Z [W826 23:00:15.649243950 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986783Z [W826 23:00:15.009072033 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986880Z [W826 23:00:16.377203398 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1986980Z [W826 23:00:16.728637651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987076Z [W826 23:00:16.023434148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987173Z [W826 23:00:17.377215076 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987269Z [W826 23:00:17.781158401 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987366Z [W826 23:00:18.126214724 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987489Z [W826 23:00:20.952069363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987587Z [W826 23:00:21.284090209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987686Z [W826 23:00:21.642081001 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987786Z [W826 23:00:21.011056211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987883Z [W826 23:00:22.353042993 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1987980Z [W826 23:00:22.690064561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1988077Z [W826 23:00:22.036554062 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1988176Z [W826 23:00:23.349198261 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1988275Z [W826 23:00:23.757109095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1989531Z [W826 23:00:24.109079010 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1989639Z [W826 23:00:24.474660184 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1989741Z [W826 23:00:26.848254259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1989840Z [W826 23:00:27.079096222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1989940Z [W826 23:00:27.320082637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990036Z [W826 23:00:27.587276774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990135Z [W826 23:00:27.791064868 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990255Z [W826 23:00:27.977096000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990424Z [W826 23:00:28.270050095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990521Z [W826 23:00:28.424032016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990642Z [W826 23:00:28.662083647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990739Z [W826 23:00:28.947111165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990837Z [W826 23:00:29.202029533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1990873Z PASSED [17.6503s] [ 94%] 2025-08-26T23:15:41.1991074Z test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_large [W826 23:00:30.291127792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991196Z [W826 23:00:30.291264910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991295Z [W826 23:00:30.543079376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991391Z [W826 23:00:30.543203084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991490Z [W826 23:00:30.901223896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991587Z [W826 23:00:30.901422253 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1991684Z [W826 23:00:31.401131136 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1992962Z [W826 23:00:31.811320415 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993074Z [W826 23:00:32.269759561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993198Z [W826 23:00:32.663155802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993300Z [W826 23:00:32.022104209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993396Z [W826 23:00:32.022250016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993550Z [W826 23:00:33.537125904 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993647Z [W826 23:00:33.537321490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993744Z [W826 23:00:33.017214203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993840Z [W826 23:00:33.017401120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1993941Z [W826 23:00:34.088444043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994041Z [W826 23:00:34.345140953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994138Z [W826 23:00:34.345381649 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994235Z [W826 23:00:34.423090389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994335Z [W826 23:00:34.584132159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994434Z [W826 23:00:34.584359996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994533Z [W826 23:00:34.697159568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994629Z [W826 23:00:36.402102783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994729Z [W826 23:00:36.402248320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994850Z [W826 23:00:36.855390849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1994947Z [W826 23:00:36.855560487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996233Z [W826 23:00:37.329241245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996355Z [W826 23:00:37.329477301 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996455Z [W826 23:00:37.972095279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996555Z [W826 23:00:38.420177937 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996654Z [W826 23:00:38.677654915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996770Z [W826 23:00:38.849227921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996872Z [W826 23:00:39.072141617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1996968Z [W826 23:00:39.072345134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997064Z [W826 23:00:39.312078459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997162Z [W826 23:00:39.312218567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997259Z [W826 23:00:39.635089196 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997355Z [W826 23:00:39.635253594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997453Z [W826 23:00:39.686037812 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997551Z [W826 23:00:39.852317771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997664Z [W826 23:00:39.852586927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997763Z [W826 23:00:39.956137323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997863Z [W826 23:00:40.166127962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1997960Z [W826 23:00:40.166379718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1998058Z [W826 23:00:40.229083381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1998156Z [W826 23:00:41.475169354 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1998252Z [W826 23:00:41.475336041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1999552Z [W826 23:00:41.750100580 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1999661Z [W826 23:00:41.750234657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1999758Z [W826 23:00:41.962115127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1999857Z [W826 23:00:41.962244035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.1999955Z [W826 23:00:42.345145688 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000052Z [W826 23:00:42.587156797 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000148Z [W826 23:00:42.850077101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000245Z [W826 23:00:43.125092075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000406Z [W826 23:00:43.347114675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000531Z [W826 23:00:43.347338403 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000627Z [W826 23:00:43.640235018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000724Z [W826 23:00:43.640431175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000837Z [W826 23:00:43.978081524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2000936Z [W826 23:00:43.978219092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001034Z [W826 23:00:44.102035193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001134Z [W826 23:00:44.322090864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001252Z [W826 23:00:44.322211612 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001353Z [W826 23:00:44.381100204 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001448Z [W826 23:00:44.548105882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001547Z [W826 23:00:44.548284469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2001647Z [W826 23:00:44.665226227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2002890Z PASSED [15.4374s] [ 94%] 2025-08-26T23:15:41.2003091Z test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_small [W826 23:00:44.919160540 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003193Z [W826 23:00:44.919332288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003293Z [W826 23:00:45.246601008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003419Z [W826 23:00:45.485235320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003517Z [W826 23:00:45.624347072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003614Z [W826 23:00:45.624469580 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003713Z [W826 23:00:45.624556509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003811Z [W826 23:00:45.687272231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2003907Z [W826 23:00:45.917089751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004005Z [W826 23:00:45.917198629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004104Z [W826 23:00:45.011148136 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004206Z [W826 23:00:46.186098210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004304Z [W826 23:00:46.186173048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004405Z [W826 23:00:46.311258539 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004503Z [W826 23:00:46.444260316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004600Z [W826 23:00:46.444378025 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004696Z [W826 23:00:46.528080180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004793Z [W826 23:00:46.610148652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2004892Z [W826 23:00:46.610222130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006191Z [W826 23:00:46.686912035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006299Z [W826 23:00:46.877678323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006400Z [W826 23:00:46.877788541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006521Z [W826 23:00:46.877867330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006619Z [W826 23:00:46.936396468 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006715Z [W826 23:00:47.084468140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006812Z [W826 23:00:47.084695347 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2006930Z [W826 23:00:47.184178167 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007032Z [W826 23:00:47.345102059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007129Z [W826 23:00:47.345383745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007226Z [W826 23:00:47.444160546 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007324Z [W826 23:00:47.684485142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007420Z [W826 23:00:47.684698887 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007518Z [W826 23:00:48.115102492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007616Z [W826 23:00:48.399115296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007715Z [W826 23:00:48.594455602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007827Z [W826 23:00:48.594685768 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2007924Z [W826 23:00:48.594816896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2008020Z [W826 23:00:48.641072876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2008119Z [W826 23:00:48.891110340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2008216Z [W826 23:00:48.891256098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2009494Z [W826 23:00:48.035075886 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2009602Z [W826 23:00:49.284076957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2009705Z [W826 23:00:49.284156705 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2009806Z [W826 23:00:49.385062263 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2009904Z [W826 23:00:49.544119915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010002Z [W826 23:00:49.544176064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010101Z [W826 23:00:49.635790057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010197Z [W826 23:00:49.791124705 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010293Z [W826 23:00:49.791181784 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010460Z [W826 23:00:49.893054357 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010559Z [W826 23:00:50.076116475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010695Z [W826 23:00:50.076190344 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010791Z [W826 23:00:50.076256173 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2010888Z [W826 23:00:50.134059013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011004Z [W826 23:00:50.289984803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011105Z [W826 23:00:50.290135421 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011206Z [W826 23:00:50.385119130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011303Z [W826 23:00:50.538231845 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011418Z [W826 23:00:50.538317893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2011520Z [W826 23:00:50.631139667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2012829Z [W826 23:00:51.223301460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2012937Z [W826 23:00:51.223482217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013040Z [W826 23:00:51.650053691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013139Z [W826 23:00:51.920188710 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013238Z [W826 23:00:52.126891560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013334Z [W826 23:00:52.127073597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013434Z [W826 23:00:52.127177735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013555Z [W826 23:00:52.183097654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013653Z [W826 23:00:52.456432565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013749Z [W826 23:00:52.456851469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013848Z [W826 23:00:52.585089021 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2013945Z [W826 23:00:52.849263514 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014041Z [W826 23:00:52.849443081 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014137Z [W826 23:00:52.969096858 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014240Z [W826 23:00:53.141223055 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014339Z [W826 23:00:53.141353542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014436Z [W826 23:00:53.237288138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014532Z [W826 23:00:53.403100595 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014630Z [W826 23:00:53.403172783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2014727Z [W826 23:00:53.502052683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016023Z [W826 23:00:53.720465209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016128Z [W826 23:00:53.720642927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016230Z [W826 23:00:53.720718745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016352Z [W826 23:00:53.782221217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016450Z [W826 23:00:53.947398604 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016546Z [W826 23:00:53.947636770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016659Z [W826 23:00:54.055629567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016755Z [W826 23:00:54.226372566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016851Z [W826 23:00:54.226587773 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016947Z [W826 23:00:54.332525882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2016999Z PASSED [9.6237s] [ 94%] 2025-08-26T23:15:41.2017108Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_16gf PASSED [26.2234s] [ 94%] 2025-08-26T23:15:41.2017220Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_1_6gf PASSED [20.5221s] [ 95%] 2025-08-26T23:15:41.2017324Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_32gf PASSED [31.0430s] [ 95%] 2025-08-26T23:15:41.2017431Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_3_2gf PASSED [29.7213s] [ 95%] 2025-08-26T23:15:41.2017623Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_400mf [W826 23:02:44.268101488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2017723Z [W826 23:02:44.291101170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2017820Z [W826 23:02:44.359209158 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2017922Z [W826 23:02:44.383146776 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2018037Z [W826 23:02:44.452079811 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2018134Z [W826 23:02:44.474112498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019431Z [W826 23:02:44.534068884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019535Z [W826 23:02:44.559096234 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019635Z [W826 23:02:44.647077072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019736Z [W826 23:02:44.696109609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019832Z [W826 23:02:44.864075522 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2019931Z [W826 23:02:44.921768633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020031Z [W826 23:02:44.986065101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020127Z [W826 23:02:44.011101861 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020224Z [W826 23:02:45.072067881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020321Z [W826 23:02:45.100098964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020493Z [W826 23:02:45.163069823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020591Z [W826 23:02:45.190073462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020687Z [W826 23:02:45.253067080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020786Z [W826 23:02:45.276066642 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2020922Z [W826 23:02:45.336069007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2021023Z [W826 23:02:45.358074894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2021122Z [W826 23:02:45.428070154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2021219Z [W826 23:02:47.971170708 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2021334Z [W826 23:02:47.032316705 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2021432Z [W826 23:02:48.192588558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2022731Z [W826 23:02:48.258304703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2022861Z [W826 23:02:48.454251860 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2022963Z [W826 23:02:48.544424175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023065Z [W826 23:02:48.731140876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023162Z [W826 23:02:48.782219019 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023259Z [W826 23:02:48.907093854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023358Z [W826 23:02:48.951522652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023454Z [W826 23:02:49.106559336 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023551Z [W826 23:02:49.168760606 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023651Z [W826 23:02:49.328603826 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023769Z [W826 23:02:49.368104571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023867Z [W826 23:02:49.444083017 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2023963Z [W826 23:02:49.477360458 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024062Z [W826 23:02:49.542085810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024161Z [W826 23:02:49.570709803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024263Z [W826 23:02:49.636069065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024362Z [W826 23:02:49.664086958 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024461Z [W826 23:02:49.735093092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024558Z [W826 23:02:49.756087965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2024654Z [W826 23:02:49.823061132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2025958Z [W826 23:02:53.483098091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026065Z [W826 23:02:53.504077825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026167Z [W826 23:02:53.612282678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026265Z [W826 23:02:53.657430815 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026365Z [W826 23:02:53.764223810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026464Z [W826 23:02:53.804101409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026583Z [W826 23:02:53.910110228 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026679Z [W826 23:02:53.963370428 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026777Z [W826 23:02:53.046541032 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026874Z [W826 23:02:54.091129036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2026990Z [W826 23:02:54.222428781 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027087Z [W826 23:02:54.280113802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027185Z [W826 23:02:54.384052962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027297Z [W826 23:02:54.426052078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027400Z [W826 23:02:54.538408157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027499Z [W826 23:02:54.567058791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027597Z [W826 23:02:54.674114823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027693Z [W826 23:02:54.715088205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027790Z [W826 23:02:54.835772804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027888Z [W826 23:02:54.872406073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2027985Z [W826 23:02:54.977150701 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2029283Z [W826 23:02:54.035831787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2029407Z [W826 23:02:55.136100024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2029446Z PASSED [13.2766s] [ 95%] 2025-08-26T23:15:41.2029558Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_800mf PASSED [21.6246s] [ 95%] 2025-08-26T23:15:41.2029663Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_8gf PASSED [15.0843s] [ 95%] 2025-08-26T23:15:41.2029855Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_128gf [W826 23:03:35.249072096 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2029952Z [W826 23:03:35.249186054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030050Z [W826 23:03:35.434054025 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030150Z [W826 23:03:35.434154643 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030250Z [W826 23:03:35.641035339 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030418Z [W826 23:03:35.641132797 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030515Z [W826 23:03:35.818042741 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030612Z [W826 23:03:35.818163279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030710Z [W826 23:03:35.997039402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030807Z [W826 23:03:35.997154640 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2030904Z [W826 23:03:36.177039327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2031001Z [W826 23:03:36.177137326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2031129Z [W826 23:03:36.348034883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2031227Z [W826 23:03:36.348117082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2031323Z [W826 23:03:36.535974254 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2032639Z [W826 23:03:36.536074582 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2032770Z [W826 23:03:36.715036833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2032868Z [W826 23:03:36.715139843 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2032967Z [W826 23:03:36.965936444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033082Z [W826 23:03:36.966143741 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033184Z [W826 23:03:37.150048646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033280Z [W826 23:03:37.150460129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033379Z [W826 23:03:37.312036851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033528Z [W826 23:03:37.312475284 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033628Z [W826 23:03:37.484037922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033725Z [W826 23:03:37.484393825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033823Z [W826 23:03:37.650035895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2033921Z [W826 23:03:37.650445109 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034040Z [W826 23:03:37.809029498 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034136Z [W826 23:03:37.809408252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034234Z [W826 23:03:38.059139831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034332Z [W826 23:03:38.059718981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034434Z [W826 23:03:38.244071539 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034534Z [W826 23:03:38.244418474 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034631Z [W826 23:03:38.421058391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2034729Z [W826 23:03:38.421499164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036048Z [W826 23:03:38.580110323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036151Z [W826 23:03:38.580670084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036252Z [W826 23:03:38.760116018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036350Z [W826 23:03:38.760689369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036450Z [W826 23:03:38.934114597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036548Z [W826 23:03:38.934689888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036645Z [W826 23:03:39.102095159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036744Z [W826 23:03:39.102661290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036863Z [W826 23:03:39.255087635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2036960Z [W826 23:03:39.255583717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037057Z [W826 23:03:39.428093739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037153Z [W826 23:03:39.428642331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037267Z [W826 23:03:39.582099660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037365Z [W826 23:03:39.582648221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037466Z [W826 23:03:39.756091239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037582Z [W826 23:03:39.756617561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037682Z [W826 23:03:39.984116456 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037779Z [W826 23:03:39.989138568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037876Z [W826 23:03:40.255069094 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2037972Z [W826 23:03:40.255175902 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039257Z [W826 23:03:40.418046885 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039365Z [W826 23:03:40.418135512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039465Z [W826 23:03:40.624046305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039567Z [W826 23:03:40.624131333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039686Z [W826 23:03:40.790033328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039784Z [W826 23:03:40.790124586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039881Z [W826 23:03:40.955031137 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2039979Z [W826 23:03:40.955121676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040079Z [W826 23:03:41.132022009 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040174Z [W826 23:03:41.132115098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040272Z [W826 23:03:41.301992450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040434Z [W826 23:03:41.302079799 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040534Z [W826 23:03:41.466005735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040630Z [W826 23:03:41.466097934 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040728Z [W826 23:03:41.638032605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040826Z [W826 23:03:41.638130203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2040924Z [W826 23:03:41.854039878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2041022Z [W826 23:03:41.854230175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2041119Z [W826 23:03:41.021033267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2041218Z [W826 23:03:41.021395151 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2041340Z [W826 23:03:42.204051835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2042642Z [W826 23:03:42.204504768 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2042754Z [W826 23:03:42.368054849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2042854Z [W826 23:03:42.368438153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2042975Z [W826 23:03:42.538052561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043073Z [W826 23:03:42.538474134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043169Z [W826 23:03:42.718049316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043286Z [W826 23:03:42.718444829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043387Z [W826 23:03:42.888045807 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043484Z [W826 23:03:42.888433061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043580Z [W826 23:03:43.074049569 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043677Z [W826 23:03:43.074582700 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043775Z [W826 23:03:43.277051196 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043873Z [W826 23:03:43.277337780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2043968Z [W826 23:03:43.485046504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044070Z [W826 23:03:43.485358270 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044186Z [W826 23:03:43.693757363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044284Z [W826 23:03:43.694100217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044380Z [W826 23:03:43.876046482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044479Z [W826 23:03:43.876382067 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2044577Z [W826 23:03:44.073174121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2045865Z [W826 23:03:44.073488286 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2045974Z [W826 23:03:44.252054993 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046079Z [W826 23:03:44.252350999 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046179Z [W826 23:03:44.431051494 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046279Z [W826 23:03:44.431385929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046375Z [W826 23:03:44.612150312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046472Z [W826 23:03:44.612578655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046570Z [W826 23:03:44.799089510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046667Z [W826 23:03:44.799487273 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046763Z [W826 23:03:45.060164202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046862Z [W826 23:03:45.061382722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2046992Z [W826 23:03:46.181137685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047089Z [W826 23:03:46.181275572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047186Z [W826 23:03:46.425097383 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047284Z [W826 23:03:46.425226021 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047403Z [W826 23:03:46.701067973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047505Z [W826 23:03:46.701181801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047601Z [W826 23:03:46.880049534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047715Z [W826 23:03:46.880153042 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2047816Z [W826 23:03:47.056049201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049114Z [W826 23:03:47.056148400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049219Z [W826 23:03:47.400310348 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049320Z [W826 23:03:47.400640273 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049420Z [W826 23:03:47.793129537 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049517Z [W826 23:03:47.793396953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049614Z [W826 23:03:48.112107646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049714Z [W826 23:03:48.112299154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049830Z [W826 23:03:48.296093469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2049928Z [W826 23:03:48.296196918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050023Z [W826 23:03:48.506065678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050120Z [W826 23:03:48.506257145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050216Z [W826 23:03:48.682048186 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050313Z [W826 23:03:48.682441259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050485Z [W826 23:03:48.856054874 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050585Z [W826 23:03:48.856364430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050686Z [W826 23:03:48.034061020 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050786Z [W826 23:03:48.034503184 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050882Z [W826 23:03:49.198059675 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2050978Z [W826 23:03:49.198480009 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2051075Z [W826 23:03:49.373060838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2051173Z [W826 23:03:49.373503751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2052476Z [W826 23:03:49.548064542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2052587Z [W826 23:03:49.548494575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2052715Z [W826 23:03:49.718058143 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2052815Z [W826 23:03:49.718340238 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2052912Z [W826 23:03:49.899087092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053009Z [W826 23:03:49.899569584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053125Z [W826 23:03:50.081081596 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053223Z [W826 23:03:50.081617098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053318Z [W826 23:03:50.240086778 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053433Z [W826 23:03:50.240661969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053534Z [W826 23:03:50.430124598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053631Z [W826 23:03:50.430629380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053727Z [W826 23:03:50.599064825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053824Z [W826 23:03:50.599509968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2053921Z [W826 23:03:50.766054332 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054021Z [W826 23:03:50.766448346 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054119Z [W826 23:03:50.949325417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054220Z [W826 23:03:50.949783870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054360Z [W826 23:03:51.132113829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054458Z [W826 23:03:51.132723459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2054555Z [W826 23:03:51.311081751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2055895Z [W826 23:03:51.311584632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2055996Z [W826 23:03:51.549089402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056095Z [W826 23:03:51.549819470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056133Z PASSED [19.7245s] [ 95%] 2025-08-26T23:15:41.2056321Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_16gf [W826 23:03:52.208173962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056424Z [W826 23:03:52.208269680 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056521Z [W826 23:03:52.392133725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056617Z [W826 23:03:52.392253054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056714Z [W826 23:03:52.626090220 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056813Z [W826 23:03:52.626220968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2056911Z [W826 23:03:52.790090554 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057007Z [W826 23:03:52.790226112 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057106Z [W826 23:03:52.970133539 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057229Z [W826 23:03:52.970331316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057329Z [W826 23:03:53.142057330 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057425Z [W826 23:03:53.142156698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057523Z [W826 23:03:53.339060391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057636Z [W826 23:03:53.339178139 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057733Z [W826 23:03:53.527058561 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2057829Z [W826 23:03:53.527275858 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059153Z [W826 23:03:53.703049669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059263Z [W826 23:03:53.703200626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059361Z [W826 23:03:53.879040837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059462Z [W826 23:03:53.879171255 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059558Z [W826 23:03:54.053046865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059657Z [W826 23:03:54.053182153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059754Z [W826 23:03:54.224048531 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059851Z [W826 23:03:54.224184129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2059951Z [W826 23:03:54.396043511 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060067Z [W826 23:03:54.396181968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060164Z [W826 23:03:54.582041983 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060262Z [W826 23:03:54.582194121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060428Z [W826 23:03:54.772476735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060526Z [W826 23:03:54.772632743 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060626Z [W826 23:03:54.964107269 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060726Z [W826 23:03:54.964366395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060824Z [W826 23:03:55.126040386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2060922Z [W826 23:03:55.126187363 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2061018Z [W826 23:03:55.355047467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2061114Z [W826 23:03:55.355247235 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062441Z [W826 23:03:55.615050227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062548Z [W826 23:03:55.615107315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062646Z [W826 23:03:55.786280898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062745Z [W826 23:03:55.786445205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062844Z [W826 23:03:55.994052341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2062980Z [W826 23:03:55.994126459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063077Z [W826 23:03:56.156047676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063175Z [W826 23:03:56.156124065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063272Z [W826 23:03:56.324075778 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063383Z [W826 23:03:56.324150467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063480Z [W826 23:03:56.501047041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063577Z [W826 23:03:56.501132750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063690Z [W826 23:03:56.707077900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063792Z [W826 23:03:56.707189588 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063891Z [W826 23:03:56.878053836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2063989Z [W826 23:03:56.878304712 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2064086Z [W826 23:03:57.056056893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2064185Z [W826 23:03:57.056275119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2064282Z [W826 23:03:57.233059915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2064378Z [W826 23:03:57.233268321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2064475Z [W826 23:03:57.399048228 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2065799Z [W826 23:03:57.399217906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2065903Z [W826 23:03:57.565053351 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066002Z [W826 23:03:57.565234089 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066100Z [W826 23:03:57.735049882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066200Z [W826 23:03:57.735242250 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066297Z [W826 23:03:57.894052925 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066394Z [W826 23:03:57.894259392 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066493Z [W826 23:03:58.060055068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066593Z [W826 23:03:58.060286095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066689Z [W826 23:03:58.237050591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066786Z [W826 23:03:58.237244718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066882Z [W826 23:03:58.403049734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2066980Z [W826 23:03:58.403273600 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067076Z [W826 23:03:58.610048559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067177Z [W826 23:03:58.610281715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067275Z [W826 23:03:59.428075233 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067391Z [W826 23:03:59.428165531 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067487Z [W826 23:03:59.596045564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067584Z [W826 23:03:59.596099775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2067680Z [W826 23:03:59.815078162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2068988Z [W826 23:03:59.815154541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069096Z [W826 23:03:59.974034375 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069197Z [W826 23:03:59.974076024 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069314Z [W826 23:04:00.148041084 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069416Z [W826 23:04:00.148099893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069512Z [W826 23:04:00.331034672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069609Z [W826 23:04:00.331081321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069705Z [W826 23:04:00.550072219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069802Z [W826 23:04:00.550193777 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069899Z [W826 23:04:00.733046888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2069996Z [W826 23:04:00.733192006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070093Z [W826 23:04:00.930044898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070207Z [W826 23:04:00.930168607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070303Z [W826 23:04:01.106046726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070465Z [W826 23:04:01.106199984 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070564Z [W826 23:04:01.292044528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070663Z [W826 23:04:01.292170576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070760Z [W826 23:04:01.469087049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070857Z [W826 23:04:01.469271266 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2070954Z [W826 23:04:01.630047671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2071052Z [W826 23:04:01.630164760 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072364Z [W826 23:04:01.798048873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072469Z [W826 23:04:01.798175722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072567Z [W826 23:04:01.963037293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072667Z [W826 23:04:01.963160060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072764Z [W826 23:04:02.130036610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072862Z [W826 23:04:02.130149649 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2072963Z [W826 23:04:02.295043969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073087Z [W826 23:04:02.295201757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073185Z [W826 23:04:02.516036566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073281Z [W826 23:04:02.516211333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073319Z PASSED [10.9521s] [ 95%] 2025-08-26T23:15:41.2073573Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_1_6gf [W826 23:04:02.850047021 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073672Z [W826 23:04:02.850197579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073770Z [W826 23:04:02.030074476 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073889Z [W826 23:04:02.030183145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2073990Z [W826 23:04:03.253078131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2074087Z [W826 23:04:03.253170920 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2074184Z [W826 23:04:03.426063726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2074284Z [W826 23:04:03.426153015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2074381Z [W826 23:04:03.604050393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2075680Z [W826 23:04:03.604126002 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2075787Z [W826 23:04:03.770031756 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2075889Z [W826 23:04:03.776452536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076012Z [W826 23:04:03.982762602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076110Z [W826 23:04:03.982881189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076207Z [W826 23:04:04.159044015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076303Z [W826 23:04:04.159101114 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076403Z [W826 23:04:04.380011272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076500Z [W826 23:04:04.380093761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076596Z [W826 23:04:04.554046160 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076695Z [W826 23:04:04.554121059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076794Z [W826 23:04:04.718044004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076891Z [W826 23:04:04.718117023 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2076987Z [W826 23:04:04.885041633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077084Z [W826 23:04:04.885092322 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077183Z [W826 23:04:05.064036913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077285Z [W826 23:04:05.064100402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077381Z [W826 23:04:05.237049267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077480Z [W826 23:04:05.237110297 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2077597Z [W826 23:04:05.415043304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2078897Z [W826 23:04:05.415102323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079003Z [W826 23:04:05.597041178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079102Z [W826 23:04:05.597092317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079220Z [W826 23:04:05.775037424 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079318Z [W826 23:04:05.775082875 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079414Z [W826 23:04:05.939033109 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079523Z [W826 23:04:05.939085718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079626Z [W826 23:04:06.102043029 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079724Z [W826 23:04:06.102104828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079820Z [W826 23:04:06.269045617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2079917Z [W826 23:04:06.269097176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080015Z [W826 23:04:06.445034134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080112Z [W826 23:04:06.445082864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080207Z [W826 23:04:06.610042513 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080311Z [W826 23:04:06.610099923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080530Z [W826 23:04:06.782038244 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080630Z [W826 23:04:06.782094323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080727Z [W826 23:04:06.944034229 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080824Z [W826 23:04:06.944089199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2080923Z [W826 23:04:07.100049129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2081021Z [W826 23:04:07.100107698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082349Z [W826 23:04:07.307044644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082458Z [W826 23:04:07.307105432 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082558Z [W826 23:04:07.466043046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082657Z [W826 23:04:07.466143074 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082754Z [W826 23:04:07.711035178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082850Z [W826 23:04:07.711080077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2082949Z [W826 23:04:07.861035740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083046Z [W826 23:04:07.861074640 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083142Z [W826 23:04:08.051041340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083242Z [W826 23:04:08.051083440 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083366Z [W826 23:04:08.208035553 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083463Z [W826 23:04:08.208073273 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083564Z [W826 23:04:08.374049417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083664Z [W826 23:04:08.374085777 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083787Z [W826 23:04:08.527036683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083886Z [W826 23:04:08.527073883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2083982Z [W826 23:04:08.682038408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2084110Z [W826 23:04:08.682074107 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2084211Z [W826 23:04:08.844034354 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2084308Z [W826 23:04:08.844074663 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2084407Z [W826 23:04:08.043036594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2085725Z [W826 23:04:08.043080362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2085827Z [W826 23:04:09.207030598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2085929Z [W826 23:04:09.207075147 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086027Z [W826 23:04:09.365030056 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086127Z [W826 23:04:09.365074635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086246Z [W826 23:04:09.525052163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086344Z [W826 23:04:09.525094071 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086440Z [W826 23:04:09.662036688 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086537Z [W826 23:04:09.662089967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086636Z [W826 23:04:09.821036210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086736Z [W826 23:04:09.821074170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086832Z [W826 23:04:09.981030718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2086930Z [W826 23:04:09.981075586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087027Z [W826 23:04:10.134034153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087129Z [W826 23:04:10.134081193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087226Z [W826 23:04:10.285033151 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087324Z [W826 23:04:10.285070630 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087420Z [W826 23:04:10.456038045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2087517Z [W826 23:04:10.456094895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2088861Z [W826 23:04:10.624037048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2088967Z [W826 23:04:10.624085347 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089090Z [W826 23:04:10.784033305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089188Z [W826 23:04:10.784085634 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089285Z [W826 23:04:10.951037892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089381Z [W826 23:04:10.951095542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089494Z [W826 23:04:11.117034577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089592Z [W826 23:04:11.117079976 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089689Z [W826 23:04:11.287033207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089801Z [W826 23:04:11.287074556 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089902Z [W826 23:04:11.451035682 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2089998Z [W826 23:04:11.451089091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090096Z [W826 23:04:11.629436352 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090192Z [W826 23:04:11.629474631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090291Z [W826 23:04:11.844028788 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090473Z [W826 23:04:11.844074388 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090570Z [W826 23:04:11.021035040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090669Z [W826 23:04:11.021118729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090790Z [W826 23:04:13.113059055 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090888Z [W826 23:04:13.113140274 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2090984Z [W826 23:04:13.290035997 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092305Z [W826 23:04:13.290075946 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092415Z [W826 23:04:13.505029887 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092513Z [W826 23:04:13.505064896 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092613Z [W826 23:04:13.686085785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092712Z [W826 23:04:13.686183064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092815Z [W826 23:04:13.865064396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2092911Z [W826 23:04:13.865145495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093008Z [W826 23:04:13.027051642 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093104Z [W826 23:04:13.027113521 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093205Z [W826 23:04:14.204050865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093303Z [W826 23:04:14.204106894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093400Z [W826 23:04:14.369054914 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093497Z [W826 23:04:14.369119043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093623Z [W826 23:04:14.580059616 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093722Z [W826 23:04:14.580132225 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093823Z [W826 23:04:14.743050836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2093919Z [W826 23:04:14.743121555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2094040Z [W826 23:04:14.922043948 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2094137Z [W826 23:04:14.922099876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2094235Z [W826 23:04:15.082038144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2094353Z [W826 23:04:15.082081013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2095670Z [W826 23:04:15.241040176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2095773Z [W826 23:04:15.241086345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2095872Z [W826 23:04:15.406042935 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2095971Z [W826 23:04:15.406086494 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096075Z [W826 23:04:15.570039080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096171Z [W826 23:04:15.570091629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096268Z [W826 23:04:15.738035562 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096366Z [W826 23:04:15.738074802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096482Z [W826 23:04:15.896039820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096579Z [W826 23:04:15.896073819 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096675Z [W826 23:04:16.060040455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096771Z [W826 23:04:16.060084304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096871Z [W826 23:04:16.224032700 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2096967Z [W826 23:04:16.224068279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097066Z [W826 23:04:16.387035549 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097167Z [W826 23:04:16.387073149 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097266Z [W826 23:04:16.556035276 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097363Z [W826 23:04:16.556074106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097460Z [W826 23:04:16.726033547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2097556Z [W826 23:04:16.726070037 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2098864Z [W826 23:04:16.888036553 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2098972Z [W826 23:04:16.888072962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099070Z [W826 23:04:17.050022939 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099169Z [W826 23:04:17.050064618 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099290Z [W826 23:04:17.230035324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099386Z [W826 23:04:17.230067374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099483Z [W826 23:04:17.444038439 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099579Z [W826 23:04:17.444083418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099693Z [W826 23:04:17.625038519 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099790Z [W826 23:04:17.625123177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2099828Z PASSED [15.1110s] [ 95%] 2025-08-26T23:15:41.2100016Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_32gf [W826 23:04:18.554066573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100131Z [W826 23:04:18.554173822 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100228Z [W826 23:04:18.725040670 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100327Z [W826 23:04:18.725097129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100511Z [W826 23:04:18.928038226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100611Z [W826 23:04:18.928090825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100707Z [W826 23:04:19.087044738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100806Z [W826 23:04:19.087123907 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2100905Z [W826 23:04:19.250034669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2101031Z [W826 23:04:19.250097088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102362Z [W826 23:04:19.428042155 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102465Z [W826 23:04:19.428111863 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102567Z [W826 23:04:19.587038618 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102667Z [W826 23:04:19.587114267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102766Z [W826 23:04:19.795038877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102862Z [W826 23:04:19.795153015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2102962Z [W826 23:04:19.963044579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103062Z [W826 23:04:19.963196966 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103160Z [W826 23:04:20.129039222 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103256Z [W826 23:04:20.129188350 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103353Z [W826 23:04:20.297035164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103449Z [W826 23:04:20.297167182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103547Z [W826 23:04:20.480030533 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103643Z [W826 23:04:20.480151011 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103742Z [W826 23:04:20.648032585 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103870Z [W826 23:04:20.648144943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2103968Z [W826 23:04:20.825043617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2104065Z [W826 23:04:20.825192485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2104162Z [W826 23:04:20.995039508 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2104291Z [W826 23:04:20.995186915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2105622Z [W826 23:04:21.173035954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2105728Z [W826 23:04:21.173186162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2105850Z [W826 23:04:21.345031734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2105952Z [W826 23:04:21.345168532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106049Z [W826 23:04:21.521032972 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106148Z [W826 23:04:21.521165940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106245Z [W826 23:04:21.691028343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106344Z [W826 23:04:21.691163271 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106442Z [W826 23:04:21.886046554 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106538Z [W826 23:04:21.886322880 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106636Z [W826 23:04:22.131036727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106749Z [W826 23:04:22.131084597 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106848Z [W826 23:04:22.302030922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2106944Z [W826 23:04:22.302075652 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107045Z [W826 23:04:22.511100864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107144Z [W826 23:04:22.511243813 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107243Z [W826 23:04:22.680179901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107339Z [W826 23:04:22.680315868 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107439Z [W826 23:04:22.848059735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107537Z [W826 23:04:22.848156703 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2107634Z [W826 23:04:22.016048547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2108945Z [W826 23:04:22.016134646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109054Z [W826 23:04:23.182042051 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109153Z [W826 23:04:23.182143249 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109254Z [W826 23:04:23.385060367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109351Z [W826 23:04:23.385183285 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109451Z [W826 23:04:23.554042793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109571Z [W826 23:04:23.554205422 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109668Z [W826 23:04:23.724042165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109764Z [W826 23:04:23.724206942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109861Z [W826 23:04:23.884043631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2109972Z [W826 23:04:23.884202240 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110071Z [W826 23:04:23.046040247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110167Z [W826 23:04:23.046191166 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110282Z [W826 23:04:24.205043690 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110505Z [W826 23:04:24.205181138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110604Z [W826 23:04:24.389041814 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110700Z [W826 23:04:24.389204800 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110797Z [W826 23:04:24.554071622 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110895Z [W826 23:04:24.554287139 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2110992Z [W826 23:04:24.718872603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2111088Z [W826 23:04:24.719051660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2112477Z [W826 23:04:24.880045102 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2112611Z [W826 23:04:24.880207029 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2112713Z [W826 23:04:24.043037733 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2112809Z [W826 23:04:24.043184601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2112906Z [W826 23:04:25.204039223 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113004Z [W826 23:04:25.204186461 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113101Z [W826 23:04:25.407044151 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113197Z [W826 23:04:25.407302807 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113297Z [W826 23:04:26.308055221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113397Z [W826 23:04:26.308141130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113559Z [W826 23:04:26.477036078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113656Z [W826 23:04:26.477093177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113754Z [W826 23:04:26.690039689 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113852Z [W826 23:04:26.690103699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2113951Z [W826 23:04:26.860043060 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2114046Z [W826 23:04:26.860130239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2114146Z [W826 23:04:26.025034879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2114265Z [W826 23:04:26.025100328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2114362Z [W826 23:04:27.195032491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2114459Z [W826 23:04:27.195088550 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2115775Z [W826 23:04:27.351031320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2115907Z [W826 23:04:27.351096539 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116010Z [W826 23:04:27.552034728 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116108Z [W826 23:04:27.552125746 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116225Z [W826 23:04:27.721038974 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116327Z [W826 23:04:27.721193352 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116425Z [W826 23:04:27.940088511 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116522Z [W826 23:04:27.940326407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116620Z [W826 23:04:28.114055560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116717Z [W826 23:04:28.114220448 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116815Z [W826 23:04:28.288052809 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2116911Z [W826 23:04:28.288212827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117011Z [W826 23:04:28.452061644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117124Z [W826 23:04:28.452210182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117226Z [W826 23:04:28.607041018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117324Z [W826 23:04:28.607194876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117421Z [W826 23:04:28.774033927 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117520Z [W826 23:04:28.774189564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117618Z [W826 23:04:28.940040770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117715Z [W826 23:04:28.940201257 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2117815Z [W826 23:04:29.104034035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119133Z [W826 23:04:29.104185492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119237Z [W826 23:04:29.324112325 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119337Z [W826 23:04:29.324338162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119435Z [W826 23:04:29.522034132 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119535Z [W826 23:04:29.522177710 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119632Z [W826 23:04:29.742034423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119731Z [W826 23:04:29.742268839 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2119771Z PASSED [12.1110s] [ 95%] 2025-08-26T23:15:41.2119960Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_3_2gf [W826 23:04:30.105068876 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120078Z [W826 23:04:30.105179375 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120175Z [W826 23:04:30.265048104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120271Z [W826 23:04:30.265113233 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120448Z [W826 23:04:30.467049316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120547Z [W826 23:04:30.467119915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120647Z [W826 23:04:30.622039751 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120763Z [W826 23:04:30.622103710 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120863Z [W826 23:04:30.925044819 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2120959Z [W826 23:04:30.925115938 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2121056Z [W826 23:04:31.092022528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2121151Z [W826 23:04:31.092075047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2122475Z [W826 23:04:31.260039610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2122583Z [W826 23:04:31.260097409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2122683Z [W826 23:04:31.468088918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2122785Z [W826 23:04:31.468149367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2122909Z [W826 23:04:31.634044583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123006Z [W826 23:04:31.634123111 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123103Z [W826 23:04:31.803041349 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123201Z [W826 23:04:31.803113308 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123300Z [W826 23:04:31.958037454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123396Z [W826 23:04:31.958109713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123494Z [W826 23:04:32.138031489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123591Z [W826 23:04:32.138091178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123692Z [W826 23:04:32.297043391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123787Z [W826 23:04:32.297113180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123886Z [W826 23:04:32.479033245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2123984Z [W826 23:04:32.479089964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2124081Z [W826 23:04:32.658026316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2124179Z [W826 23:04:32.658079435 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2124276Z [W826 23:04:32.820035243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2124374Z [W826 23:04:32.820097372 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2124498Z [W826 23:04:32.979036345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2125816Z [W826 23:04:32.979097324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2125927Z [W826 23:04:33.146031752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126024Z [W826 23:04:33.146097611 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126142Z [W826 23:04:33.314029735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126239Z [W826 23:04:33.314088594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126336Z [W826 23:04:33.484039336 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126446Z [W826 23:04:33.484102795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126548Z [W826 23:04:33.686044028 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126643Z [W826 23:04:33.686139737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126741Z [W826 23:04:33.936047423 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126837Z [W826 23:04:33.936102442 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2126934Z [W826 23:04:34.105041420 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127031Z [W826 23:04:34.105086679 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127127Z [W826 23:04:34.309038341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127227Z [W826 23:04:34.309087770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127340Z [W826 23:04:34.480040346 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127436Z [W826 23:04:34.480083116 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127534Z [W826 23:04:34.651035692 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127630Z [W826 23:04:34.651077241 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127730Z [W826 23:04:34.817034666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2127827Z [W826 23:04:34.817081225 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129137Z [W826 23:04:34.989038765 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129241Z [W826 23:04:34.989090564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129343Z [W826 23:04:35.198034248 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129441Z [W826 23:04:35.198082108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129538Z [W826 23:04:35.360958580 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129635Z [W826 23:04:35.361048378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129734Z [W826 23:04:35.525033083 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129830Z [W826 23:04:35.525091092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2129927Z [W826 23:04:35.692035721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130025Z [W826 23:04:35.692100750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130146Z [W826 23:04:35.865034305 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130243Z [W826 23:04:35.865100004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130407Z [W826 23:04:35.027031491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130505Z [W826 23:04:35.027089740 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130630Z [W826 23:04:36.239159426 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130729Z [W826 23:04:36.239322844 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130826Z [W826 23:04:36.432042130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2130940Z [W826 23:04:36.432120369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2131040Z [W826 23:04:36.604992526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2131139Z [W826 23:04:36.605073154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132456Z [W826 23:04:36.763045593 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132567Z [W826 23:04:36.763126771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132668Z [W826 23:04:36.940034445 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132768Z [W826 23:04:36.940106224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132864Z [W826 23:04:37.106114877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2132964Z [W826 23:04:37.106290324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133084Z [W826 23:04:37.275045615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133182Z [W826 23:04:37.275133524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133277Z [W826 23:04:37.475041169 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133374Z [W826 23:04:37.475149277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133471Z [W826 23:04:38.366079885 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133569Z [W826 23:04:38.366200493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133665Z [W826 23:04:38.544043942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133764Z [W826 23:04:38.544092381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133864Z [W826 23:04:38.750053991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2133964Z [W826 23:04:38.750120500 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2134062Z [W826 23:04:38.911039193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2134159Z [W826 23:04:38.911094982 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2134255Z [W826 23:04:39.082044319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2134353Z [W826 23:04:39.082082188 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2134449Z [W826 23:04:39.250038121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2135764Z [W826 23:04:39.250068721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2135908Z [W826 23:04:39.421061335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136006Z [W826 23:04:39.421106046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136104Z [W826 23:04:39.631106323 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136201Z [W826 23:04:39.631231181 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136314Z [W826 23:04:39.825059141 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136411Z [W826 23:04:39.825170299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136508Z [W826 23:04:39.007060495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136619Z [W826 23:04:39.007154933 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136718Z [W826 23:04:40.166058967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136817Z [W826 23:04:40.166147586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2136912Z [W826 23:04:40.338048007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137011Z [W826 23:04:40.338132646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137111Z [W826 23:04:40.502039572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137213Z [W826 23:04:40.502103411 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137309Z [W826 23:04:40.669043409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137409Z [W826 23:04:40.669102148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137521Z [W826 23:04:40.832047150 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137619Z [W826 23:04:40.832119869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2137715Z [W826 23:04:40.007042123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139029Z [W826 23:04:40.007104512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139135Z [W826 23:04:41.168033085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139235Z [W826 23:04:41.168092704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139333Z [W826 23:04:41.398031251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139434Z [W826 23:04:41.398088441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139534Z [W826 23:04:41.565032919 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139632Z [W826 23:04:41.565079758 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139728Z [W826 23:04:41.725034726 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139824Z [W826 23:04:41.725089674 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2139923Z [W826 23:04:41.937038653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140023Z [W826 23:04:41.937128041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140059Z PASSED [12.1894s] [ 95%] 2025-08-26T23:15:41.2140252Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_400mf [W826 23:04:42.228050088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140436Z [W826 23:04:42.228115027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140538Z [W826 23:04:42.425076878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140636Z [W826 23:04:42.425144757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140733Z [W826 23:04:42.592040146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140851Z [W826 23:04:42.592092485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2140948Z [W826 23:04:42.746030387 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2141045Z [W826 23:04:42.746068616 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142375Z [W826 23:04:42.958117632 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142503Z [W826 23:04:42.958164501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142603Z [W826 23:04:43.119032795 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142700Z [W826 23:04:43.119077524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142797Z [W826 23:04:43.282038984 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142896Z [W826 23:04:43.282087064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2142993Z [W826 23:04:43.493966432 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143090Z [W826 23:04:43.494171209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143188Z [W826 23:04:43.711023870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143313Z [W826 23:04:43.711082829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143411Z [W826 23:04:43.881044851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143507Z [W826 23:04:43.881108650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143605Z [W826 23:04:44.068131425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143705Z [W826 23:04:44.068205444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143809Z [W826 23:04:44.191089929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2143905Z [W826 23:04:44.191175628 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2144002Z [W826 23:04:44.302065810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2144102Z [W826 23:04:44.302118900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2144199Z [W826 23:04:44.421110195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2144295Z [W826 23:04:44.421178754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2145610Z [W826 23:04:44.536093844 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2145715Z [W826 23:04:44.536159793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2145816Z [W826 23:04:44.655075770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2145915Z [W826 23:04:44.655129549 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146013Z [W826 23:04:44.887283272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146139Z [W826 23:04:44.887336080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146238Z [W826 23:04:45.159080127 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146337Z [W826 23:04:45.159219555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146439Z [W826 23:04:45.331042647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146550Z [W826 23:04:45.331102156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146648Z [W826 23:04:45.495046951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146744Z [W826 23:04:45.495103441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146842Z [W826 23:04:45.712056130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2146956Z [W826 23:04:45.712114329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147056Z [W826 23:04:45.875053071 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147155Z [W826 23:04:45.875117630 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147255Z [W826 23:04:45.036052252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147353Z [W826 23:04:45.036123591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147451Z [W826 23:04:46.203048400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2147547Z [W826 23:04:46.203113059 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2148859Z [W826 23:04:46.379015548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2148985Z [W826 23:04:46.379080656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149084Z [W826 23:04:46.557049903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149186Z [W826 23:04:46.557115462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149282Z [W826 23:04:46.748082937 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149383Z [W826 23:04:46.748134336 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149480Z [W826 23:04:46.861102026 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149578Z [W826 23:04:46.861183744 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149674Z [W826 23:04:46.977072509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149775Z [W826 23:04:46.977145797 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149872Z [W826 23:04:47.093412686 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2149969Z [W826 23:04:47.093625523 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150065Z [W826 23:04:47.220107502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150163Z [W826 23:04:47.220190280 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150263Z [W826 23:04:47.336549128 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150411Z [W826 23:04:47.336749834 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150508Z [W826 23:04:48.094088004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150634Z [W826 23:04:48.094205412 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150731Z [W826 23:04:48.297994367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150828Z [W826 23:04:48.298056136 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2150924Z [W826 23:04:48.469291378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152258Z [W826 23:04:48.469318947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152364Z [W826 23:04:48.643034850 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152466Z [W826 23:04:48.643073469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152562Z [W826 23:04:48.866040955 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152688Z [W826 23:04:48.866087095 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152784Z [W826 23:04:49.056039624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152881Z [W826 23:04:49.056086224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2152977Z [W826 23:04:49.241036913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153076Z [W826 23:04:49.241070192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153172Z [W826 23:04:49.426031159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153269Z [W826 23:04:49.426065779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153365Z [W826 23:04:49.613038995 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153579Z [W826 23:04:49.613072625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153678Z [W826 23:04:49.796033014 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153777Z [W826 23:04:49.796063833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153873Z [W826 23:04:49.992058810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2153973Z [W826 23:04:49.992091579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2154071Z [W826 23:04:50.146208738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2154167Z [W826 23:04:50.146377755 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2154264Z [W826 23:04:50.265089976 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2155600Z [W826 23:04:50.265150115 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2155711Z [W826 23:04:50.400087861 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2155814Z [W826 23:04:50.400158931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2155914Z [W826 23:04:50.530073837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156016Z [W826 23:04:50.530123996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156112Z [W826 23:04:50.649081402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156208Z [W826 23:04:50.649404027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156246Z PASSED [8.6858s] [ 95%] 2025-08-26T23:15:41.2156441Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_800mf [W826 23:04:50.926092376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156563Z [W826 23:04:50.926251713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156660Z [W826 23:04:51.137076528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156756Z [W826 23:04:51.137183317 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156873Z [W826 23:04:51.293059708 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2156970Z [W826 23:04:51.293149296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157069Z [W826 23:04:51.447150997 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157168Z [W826 23:04:51.447308554 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157289Z [W826 23:04:51.751632402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157385Z [W826 23:04:51.751796690 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157482Z [W826 23:04:51.955061833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157579Z [W826 23:04:51.955157061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2157677Z [W826 23:04:52.121056306 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2158998Z [W826 23:04:52.121133785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159106Z [W826 23:04:52.290054163 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159206Z [W826 23:04:52.290128321 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159334Z [W826 23:04:52.458053075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159431Z [W826 23:04:52.458131774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159529Z [W826 23:04:52.638041510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159625Z [W826 23:04:52.638107120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159724Z [W826 23:04:52.808049581 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159820Z [W826 23:04:52.808120050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2159917Z [W826 23:04:52.978046172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160014Z [W826 23:04:52.978108182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160117Z [W826 23:04:53.194045307 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160214Z [W826 23:04:53.194121696 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160311Z [W826 23:04:53.366065416 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160465Z [W826 23:04:53.366186734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160565Z [W826 23:04:53.642059926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160662Z [W826 23:04:53.642116395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160759Z [W826 23:04:53.878055268 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160856Z [W826 23:04:53.878120367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2160989Z [W826 23:04:53.044044862 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162310Z [W826 23:04:53.044099732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162417Z [W826 23:04:54.203049985 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162516Z [W826 23:04:54.203105654 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162639Z [W826 23:04:54.418045345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162739Z [W826 23:04:54.418107794 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162835Z [W826 23:04:54.592044343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2162932Z [W826 23:04:54.592103133 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163059Z [W826 23:04:54.758046047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163157Z [W826 23:04:54.758099006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163255Z [W826 23:04:54.925044525 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163352Z [W826 23:04:54.925102564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163449Z [W826 23:04:55.098049899 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163547Z [W826 23:04:55.098113178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163643Z [W826 23:04:55.274117605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163743Z [W826 23:04:55.274266723 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163867Z [W826 23:04:55.444090767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2163965Z [W826 23:04:55.444236225 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2164062Z [W826 23:04:55.613079994 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2164159Z [W826 23:04:55.613184942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2164259Z [W826 23:04:55.822072997 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2164358Z [W826 23:04:55.822201455 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2165687Z [W826 23:04:55.990078199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2165795Z [W826 23:04:55.990254147 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2165901Z [W826 23:04:56.723115497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2165999Z [W826 23:04:56.723233325 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166096Z [W826 23:04:56.923052752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166193Z [W826 23:04:56.923115291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166293Z [W826 23:04:57.105045206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166391Z [W826 23:04:57.105097625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166487Z [W826 23:04:57.276040622 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166584Z [W826 23:04:57.276083461 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166706Z [W826 23:04:57.479046878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166804Z [W826 23:04:57.479084998 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2166902Z [W826 23:04:57.635366362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167001Z [W826 23:04:57.635404973 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167116Z [W826 23:04:57.798026248 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167213Z [W826 23:04:57.798065208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167310Z [W826 23:04:57.960036134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167407Z [W826 23:04:57.960078093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167522Z [W826 23:04:58.125035243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167620Z [W826 23:04:58.125073832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2167716Z [W826 23:04:58.301039700 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169029Z [W826 23:04:58.301090429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169134Z [W826 23:04:58.471039582 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169238Z [W826 23:04:58.471088031 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169336Z [W826 23:04:58.633029717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169433Z [W826 23:04:58.633067027 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169553Z [W826 23:04:58.845036094 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169650Z [W826 23:04:58.845080803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169746Z [W826 23:04:58.007036999 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169843Z [W826 23:04:58.007100428 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2169880Z PASSED [8.3755s] [ 95%] 2025-08-26T23:15:41.2170072Z test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_8gf [W826 23:04:59.452070405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170170Z [W826 23:04:59.452176673 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170267Z [W826 23:04:59.618049399 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170443Z [W826 23:04:59.618130957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170544Z [W826 23:04:59.823047724 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170639Z [W826 23:04:59.823124104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170736Z [W826 23:04:59.993047016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170832Z [W826 23:04:59.993116865 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2170930Z [W826 23:05:00.160039594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2171026Z [W826 23:05:00.160111433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172349Z [W826 23:05:00.324040128 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172481Z [W826 23:05:00.324102527 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172585Z [W826 23:05:00.534050696 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172681Z [W826 23:05:00.534120195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172778Z [W826 23:05:00.705046522 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172896Z [W826 23:05:00.705147180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2172994Z [W826 23:05:00.879036100 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173091Z [W826 23:05:00.879125259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173188Z [W826 23:05:01.056042262 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173305Z [W826 23:05:01.056143201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173404Z [W826 23:05:01.255040091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173500Z [W826 23:05:01.255141610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173597Z [W826 23:05:01.432040094 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173696Z [W826 23:05:01.432139752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173798Z [W826 23:05:01.613079093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173894Z [W826 23:05:01.613188061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2173991Z [W826 23:05:01.787036282 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2174093Z [W826 23:05:01.787128481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2174206Z [W826 23:05:01.964047854 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2174302Z [W826 23:05:01.964180362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2175617Z [W826 23:05:02.139073146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2175720Z [W826 23:05:02.139170535 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2175821Z [W826 23:05:02.357218877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2175917Z [W826 23:05:02.357383235 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176014Z [W826 23:05:02.720095843 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176117Z [W826 23:05:02.720211901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176215Z [W826 23:05:02.899052524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176311Z [W826 23:05:02.899133893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176407Z [W826 23:05:03.118056663 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176504Z [W826 23:05:03.118136350 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176602Z [W826 23:05:03.292050151 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176698Z [W826 23:05:03.292124990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176796Z [W826 23:05:03.467050324 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2176914Z [W826 23:05:03.467125443 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177014Z [W826 23:05:03.633030178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177110Z [W826 23:05:03.633099837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177207Z [W826 23:05:03.851051201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177321Z [W826 23:05:03.851130220 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177419Z [W826 23:05:03.025045129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2177515Z [W826 23:05:03.025151437 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2178817Z [W826 23:05:04.205063615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2178947Z [W826 23:05:04.205154073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179046Z [W826 23:05:04.381133261 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179146Z [W826 23:05:04.381381447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179243Z [W826 23:05:04.551049764 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179344Z [W826 23:05:04.551151992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179443Z [W826 23:05:04.724064407 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179542Z [W826 23:05:04.724182005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179639Z [W826 23:05:04.899064811 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179739Z [W826 23:05:04.899196328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179851Z [W826 23:05:05.076076063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2179949Z [W826 23:05:05.076165291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180045Z [W826 23:05:05.256047828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180149Z [W826 23:05:05.256141036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180247Z [W826 23:05:05.437097947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180420Z [W826 23:05:05.437232015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180516Z [W826 23:05:05.658103873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180618Z [W826 23:05:05.658366729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180716Z [W826 23:05:06.460070757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180813Z [W826 23:05:06.460179195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2180909Z [W826 23:05:06.627054806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182222Z [W826 23:05:06.627137184 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182327Z [W826 23:05:06.837058853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182429Z [W826 23:05:06.837154161 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182528Z [W826 23:05:06.997121589 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182656Z [W826 23:05:06.997306066 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182754Z [W826 23:05:07.169048470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182851Z [W826 23:05:07.169108769 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2182946Z [W826 23:05:07.342063584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183066Z [W826 23:05:07.342122243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183162Z [W826 23:05:07.568040693 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183259Z [W826 23:05:07.568118742 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183356Z [W826 23:05:07.743037786 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183473Z [W826 23:05:07.743129965 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183570Z [W826 23:05:07.915035916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183669Z [W826 23:05:07.915120395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183766Z [W826 23:05:08.078065846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183863Z [W826 23:05:08.078192704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2183959Z [W826 23:05:08.249097671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2184056Z [W826 23:05:08.249275748 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2184152Z [W826 23:05:08.417036564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185475Z [W826 23:05:08.417120383 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185602Z [W826 23:05:08.591036663 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185703Z [W826 23:05:08.591124131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185801Z [W826 23:05:08.756035912 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185901Z [W826 23:05:08.756136691 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2185998Z [W826 23:05:08.936034457 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186095Z [W826 23:05:08.936123605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186190Z [W826 23:05:09.115176856 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186292Z [W826 23:05:09.115246695 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186389Z [W826 23:05:09.316040085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186486Z [W826 23:05:09.316181863 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2186522Z PASSED [10.3174s] [ 96%] 2025-08-26T23:15:41.2186627Z test_fx.py::TestVisionTracing::test_torchvision_models_resnet101 PASSED [17.9851s] [ 96%] 2025-08-26T23:15:41.2186731Z test_fx.py::TestVisionTracing::test_torchvision_models_resnet152 PASSED [28.0155s] [ 96%] 2025-08-26T23:15:41.2186833Z test_fx.py::TestVisionTracing::test_torchvision_models_resnet18 PASSED [3.3522s] [ 96%] 2025-08-26T23:15:41.2186930Z test_fx.py::TestVisionTracing::test_torchvision_models_resnet34 PASSED [5.9716s] [ 96%] 2025-08-26T23:15:41.2187026Z test_fx.py::TestVisionTracing::test_torchvision_models_resnet50 PASSED [8.5802s] [ 96%] 2025-08-26T23:15:41.2187151Z test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_32x8d PASSED [18.1743s] [ 96%] 2025-08-26T23:15:41.2187260Z test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_64x4d PASSED [27.5019s] [ 96%] 2025-08-26T23:15:41.2187370Z test_fx.py::TestVisionTracing::test_torchvision_models_resnext50_32x4d PASSED [12.6469s] [ 96%] 2025-08-26T23:15:41.2187617Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_mobilenet_v3_large [W826 23:07:11.756608402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2188937Z [W826 23:07:11.906162106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189051Z [W826 23:07:11.960098629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189152Z [W826 23:07:12.126561329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189278Z [W826 23:07:12.184169447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189380Z [W826 23:07:12.332222444 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189478Z [W826 23:07:12.397352867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189574Z [W826 23:07:12.570422637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189674Z [W826 23:07:12.570542775 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189776Z [W826 23:07:12.570628434 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189877Z [W826 23:07:12.632267599 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2189976Z [W826 23:07:12.791541548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190077Z [W826 23:07:12.791733454 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190194Z [W826 23:07:12.791844092 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190293Z [W826 23:07:12.856238897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190460Z [W826 23:07:12.025266947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190563Z [W826 23:07:12.025371745 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190665Z [W826 23:07:12.025443334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190762Z [W826 23:07:13.085323738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190858Z [W826 23:07:13.249244035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2190958Z [W826 23:07:13.317592480 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192285Z [W826 23:07:13.425121221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192394Z [W826 23:07:13.486089458 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192492Z [W826 23:07:13.601064737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192593Z [W826 23:07:13.662789452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192690Z [W826 23:07:13.790179122 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192787Z [W826 23:07:13.853188368 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192884Z [W826 23:07:13.022904447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2192984Z [W826 23:07:13.023116475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193119Z [W826 23:07:13.023244573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193217Z [W826 23:07:14.079061517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193314Z [W826 23:07:14.253158710 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193502Z [W826 23:07:14.253261889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193600Z [W826 23:07:14.253371417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193701Z [W826 23:07:14.309075943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193802Z [W826 23:07:14.433447910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2193921Z [W826 23:07:14.433649477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2194021Z [W826 23:07:14.433782575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2194119Z [W826 23:07:14.492303409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2194216Z [W826 23:07:14.596372142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2194316Z [W826 23:07:14.596567979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2195646Z [W826 23:07:14.596725237 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2195752Z [W826 23:07:14.626172591 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2195851Z [W826 23:07:14.685160547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2195951Z [W826 23:07:14.685292405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196074Z [W826 23:07:14.685440233 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196171Z [W826 23:07:14.766071543 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196269Z [W826 23:07:14.830524736 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196370Z [W826 23:07:15.081370217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196469Z [W826 23:07:15.081751801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196565Z [W826 23:07:15.142215926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196662Z [W826 23:07:15.226047986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196761Z [W826 23:07:15.247036427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196863Z [W826 23:07:15.412213526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2196963Z [W826 23:07:15.481353129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197060Z [W826 23:07:15.660108091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197158Z [W826 23:07:15.725420842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197255Z [W826 23:07:15.861092547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197351Z [W826 23:07:15.931634739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197448Z [W826 23:07:16.089190264 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2197545Z [W826 23:07:16.089331501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199025Z [W826 23:07:16.089399560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199128Z [W826 23:07:16.144041892 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199228Z [W826 23:07:16.306416063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199347Z [W826 23:07:16.306548671 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199448Z [W826 23:07:16.306622810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199545Z [W826 23:07:16.376844296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199642Z [W826 23:07:16.539182288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199751Z [W826 23:07:16.539253967 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199853Z [W826 23:07:16.539306176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2199950Z [W826 23:07:16.602046016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200049Z [W826 23:07:16.766352716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200147Z [W826 23:07:16.819677610 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200245Z [W826 23:07:16.919057164 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200411Z [W826 23:07:16.982058130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200508Z [W826 23:07:17.115083085 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200607Z [W826 23:07:17.182050421 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200734Z [W826 23:07:17.309050658 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200831Z [W826 23:07:17.373336864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2200930Z [W826 23:07:17.548283894 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2201030Z [W826 23:07:17.548443091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2201132Z [W826 23:07:17.548542710 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2202860Z [W826 23:07:17.621624414 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2202976Z [W826 23:07:17.803946592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203080Z [W826 23:07:17.804124000 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203185Z [W826 23:07:17.804246208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203282Z [W826 23:07:17.864070192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203379Z [W826 23:07:17.994130752 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203481Z [W826 23:07:17.994214560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203580Z [W826 23:07:17.994308919 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203677Z [W826 23:07:18.059119877 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203774Z [W826 23:07:18.181184979 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2203874Z [W826 23:07:18.181349406 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2204022Z [W826 23:07:18.181487574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2204122Z [W826 23:07:18.252065286 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2204220Z [W826 23:07:18.392963452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2204333Z [W826 23:07:18.393155669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2204433Z [W826 23:07:18.393312236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206429Z [W826 23:07:18.449124130 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206545Z [W826 23:07:18.510174446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206676Z [W826 23:07:18.759416331 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206777Z [W826 23:07:18.759764806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206874Z [W826 23:07:18.823182236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2206971Z [W826 23:07:18.910113889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207077Z [W826 23:07:19.397740264 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207176Z [W826 23:07:19.543095452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207273Z [W826 23:07:19.613070272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207372Z [W826 23:07:19.773202777 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207470Z [W826 23:07:19.838060035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207593Z [W826 23:07:19.976605836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207690Z [W826 23:07:19.042068565 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207789Z [W826 23:07:20.212214319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207888Z [W826 23:07:20.212303617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2207986Z [W826 23:07:20.212362636 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208082Z [W826 23:07:20.265031328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208187Z [W826 23:07:20.443162970 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208287Z [W826 23:07:20.443264559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208387Z [W826 23:07:20.443319767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208484Z [W826 23:07:20.506298404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208583Z [W826 23:07:20.684425347 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208681Z [W826 23:07:20.684548325 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208781Z [W826 23:07:20.684607504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208878Z [W826 23:07:20.745497041 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2208975Z [W826 23:07:20.927201639 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209075Z [W826 23:07:20.981885971 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209193Z [W826 23:07:21.108279767 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209290Z [W826 23:07:21.178226687 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209390Z [W826 23:07:21.295179686 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209499Z [W826 23:07:21.363894825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209599Z [W826 23:07:21.482203593 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209696Z [W826 23:07:21.548339572 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209795Z [W826 23:07:21.706206801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2209908Z [W826 23:07:21.706342639 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210009Z [W826 23:07:21.706421598 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210107Z [W826 23:07:21.769121668 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210205Z [W826 23:07:21.941296791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210304Z [W826 23:07:21.941431989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210471Z [W826 23:07:21.941512057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210569Z [W826 23:07:21.005363440 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210668Z [W826 23:07:22.133096486 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210767Z [W826 23:07:22.133177485 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2210905Z [W826 23:07:22.133261573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211002Z [W826 23:07:22.192593065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211101Z [W826 23:07:22.309164079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211198Z [W826 23:07:22.309326787 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211298Z [W826 23:07:22.309432105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211396Z [W826 23:07:22.372082506 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211494Z [W826 23:07:22.510352712 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211594Z [W826 23:07:22.510554789 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211695Z [W826 23:07:22.510701047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211792Z [W826 23:07:22.574049947 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211891Z [W826 23:07:22.632871646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2211988Z [W826 23:07:22.873149247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212087Z [W826 23:07:22.873369334 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212185Z [W826 23:07:22.926287193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212284Z [W826 23:07:22.003089279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212325Z PASSED [11.3786s] [ 96%] 2025-08-26T23:15:41.2212585Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet101 [W826 23:07:23.376099650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212685Z [W826 23:07:23.421640700 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212786Z [W826 23:07:23.507137735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2212900Z [W826 23:07:23.575279433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213002Z [W826 23:07:23.644368326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213099Z [W826 23:07:23.708154731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213199Z [W826 23:07:23.795397869 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213314Z [W826 23:07:23.864350545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213416Z [W826 23:07:23.934308655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213513Z [W826 23:07:23.023317567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213613Z [W826 23:07:24.085589064 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213711Z [W826 23:07:24.154085717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213810Z [W826 23:07:24.239112890 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2213907Z [W826 23:07:24.307163148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214005Z [W826 23:07:24.385320315 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214104Z [W826 23:07:24.442121634 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214215Z [W826 23:07:24.528309239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214313Z [W826 23:07:24.603304713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214411Z [W826 23:07:24.700147916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214509Z [W826 23:07:24.833139633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214608Z [W826 23:07:24.920110635 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214706Z [W826 23:07:24.021586079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214805Z [W826 23:07:25.163058345 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2214903Z [W826 23:07:25.229340961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2215009Z [W826 23:07:25.285778717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2215107Z [W826 23:07:25.375661806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2215207Z [W826 23:07:25.445049535 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2215304Z [W826 23:07:25.520089078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2215404Z [W826 23:07:25.637734716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2216687Z [W826 23:07:25.696113992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2216794Z [W826 23:07:25.836043903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2216892Z [W826 23:07:25.911075396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217012Z [W826 23:07:25.022369831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217110Z [W826 23:07:26.077145181 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217207Z [W826 23:07:26.195085845 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217320Z [W826 23:07:26.252119601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217418Z [W826 23:07:26.383542801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217515Z [W826 23:07:26.458692943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217613Z [W826 23:07:26.600056792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217727Z [W826 23:07:26.663170476 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217829Z [W826 23:07:26.792053604 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2217926Z [W826 23:07:26.863079438 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218024Z [W826 23:07:26.002048293 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218123Z [W826 23:07:27.067433013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218221Z [W826 23:07:27.187940068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218319Z [W826 23:07:27.251416226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218419Z [W826 23:07:27.398058755 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218518Z [W826 23:07:27.455884860 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218640Z [W826 23:07:27.580038530 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218738Z [W826 23:07:27.637068426 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218836Z [W826 23:07:27.762038583 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2218936Z [W826 23:07:27.820053175 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219036Z [W826 23:07:27.931438757 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219133Z [W826 23:07:27.995069104 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219231Z [W826 23:07:28.109041377 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219330Z [W826 23:07:28.174059493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219431Z [W826 23:07:28.297039670 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219527Z [W826 23:07:28.364043135 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219625Z [W826 23:07:28.489302838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219722Z [W826 23:07:28.553293379 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219822Z [W826 23:07:28.680186517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2219920Z [W826 23:07:28.736023172 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221051Z [W826 23:07:28.864071492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221152Z [W826 23:07:28.927081488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221286Z [W826 23:07:29.049337337 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221382Z [W826 23:07:29.101319278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221480Z [W826 23:07:29.217978962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221594Z [W826 23:07:29.288304897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221693Z [W826 23:07:29.408048633 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221790Z [W826 23:07:29.467075329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2221888Z [W826 23:07:29.583120861 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222003Z [W826 23:07:29.645201781 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222104Z [W826 23:07:29.771137805 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222202Z [W826 23:07:29.844158079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222300Z [W826 23:07:30.083095540 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222398Z [W826 23:07:30.327071325 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222495Z [W826 23:07:30.779176617 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222593Z [W826 23:07:30.779932056 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222691Z [W826 23:07:30.833295437 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222791Z [W826 23:07:30.913345835 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2222907Z [W826 23:07:30.024110038 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2223004Z [W826 23:07:31.090420853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2223101Z [W826 23:07:31.173311918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224136Z [W826 23:07:31.247114890 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224236Z [W826 23:07:31.309146891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224334Z [W826 23:07:31.378048497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224431Z [W826 23:07:31.450930693 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224532Z [W826 23:07:31.514744447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224633Z [W826 23:07:31.579045653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224731Z [W826 23:07:31.662044695 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224828Z [W826 23:07:31.722061386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2224928Z [W826 23:07:31.797044221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225025Z [W826 23:07:31.879042359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225123Z [W826 23:07:31.940165123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225220Z [W826 23:07:31.026050773 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225320Z [W826 23:07:32.088050535 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225436Z [W826 23:07:32.168033283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225534Z [W826 23:07:32.233052087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225632Z [W826 23:07:32.282302082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225744Z [W826 23:07:32.368192931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225843Z [W826 23:07:32.427196977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2225941Z [W826 23:07:32.487078390 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2226038Z [W826 23:07:32.567057840 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2226153Z [W826 23:07:32.638220601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227160Z [W826 23:07:32.700361540 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227259Z [W826 23:07:32.786093432 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227356Z [W826 23:07:32.874145418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227456Z [W826 23:07:32.928181030 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227553Z [W826 23:07:33.049475373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227651Z [W826 23:07:33.111392955 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227748Z [W826 23:07:33.227083532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227848Z [W826 23:07:33.287286361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2227963Z [W826 23:07:33.406207010 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228061Z [W826 23:07:33.476181300 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228158Z [W826 23:07:33.604050174 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228257Z [W826 23:07:33.658466199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228356Z [W826 23:07:33.779058872 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228453Z [W826 23:07:33.848323203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228550Z [W826 23:07:33.963182964 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228651Z [W826 23:07:33.023142015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228751Z [W826 23:07:34.144318410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228848Z [W826 23:07:34.199411326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2228945Z [W826 23:07:34.329199530 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2229043Z [W826 23:07:34.390197247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2229140Z [W826 23:07:34.526751439 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230142Z [W826 23:07:34.589316641 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230241Z [W826 23:07:34.706162362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230412Z [W826 23:07:34.769181487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230535Z [W826 23:07:34.882094067 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230632Z [W826 23:07:34.952091497 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230728Z [W826 23:07:35.074047620 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230843Z [W826 23:07:35.130063281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2230941Z [W826 23:07:35.253065718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231040Z [W826 23:07:35.308511129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231137Z [W826 23:07:35.434047517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231252Z [W826 23:07:35.502359883 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231352Z [W826 23:07:35.617042755 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231450Z [W826 23:07:35.680069641 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231546Z [W826 23:07:35.809591820 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231644Z [W826 23:07:35.882275559 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231740Z [W826 23:07:35.997039951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231838Z [W826 23:07:36.061145660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2231935Z [W826 23:07:36.188044858 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2232036Z [W826 23:07:36.248064558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2232150Z [W826 23:07:36.383047214 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2232247Z [W826 23:07:36.446065050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2232343Z [W826 23:07:36.570043842 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233373Z [W826 23:07:36.638051072 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233544Z [W826 23:07:36.768307449 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233643Z [W826 23:07:36.839082138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233739Z [W826 23:07:36.977039038 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233841Z [W826 23:07:36.036108783 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2233943Z [W826 23:07:37.191177306 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234044Z [W826 23:07:37.253234165 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234142Z [W826 23:07:37.484080079 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234242Z [W826 23:07:37.713065050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234339Z [W826 23:07:38.137624720 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234437Z [W826 23:07:38.138109093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234534Z [W826 23:07:38.198098424 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234632Z [W826 23:07:38.278534987 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234749Z [W826 23:07:38.015128090 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234847Z [W826 23:07:39.058086390 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2234945Z [W826 23:07:39.137715204 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2235057Z [W826 23:07:39.201142893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2235156Z [W826 23:07:39.265119625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2235254Z [W826 23:07:39.315050018 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2235351Z [W826 23:07:39.408204687 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2235471Z [W826 23:07:39.462829360 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236490Z [W826 23:07:39.520143722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236590Z [W826 23:07:39.608589862 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236688Z [W826 23:07:39.665394662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236790Z [W826 23:07:39.720630316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236887Z [W826 23:07:39.786096793 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2236984Z [W826 23:07:39.849305247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237081Z [W826 23:07:39.925132818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237181Z [W826 23:07:39.982381821 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237296Z [W826 23:07:40.053041621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237395Z [W826 23:07:40.109683243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237491Z [W826 23:07:40.169039513 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237589Z [W826 23:07:40.247037452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237685Z [W826 23:07:40.308075679 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237783Z [W826 23:07:40.373086803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237879Z [W826 23:07:40.451747352 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2237978Z [W826 23:07:40.512166417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2238076Z [W826 23:07:40.588528931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2238173Z [W826 23:07:40.664282593 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2238270Z [W826 23:07:40.732050327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2238368Z [W826 23:07:40.816130853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2238466Z [W826 23:07:40.963164276 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239474Z [W826 23:07:40.017293517 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239573Z [W826 23:07:41.134306465 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239671Z [W826 23:07:41.197056574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239789Z [W826 23:07:41.284239134 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239886Z [W826 23:07:41.351142101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2239984Z [W826 23:07:41.478195046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240097Z [W826 23:07:41.539079075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240196Z [W826 23:07:41.658101001 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240293Z [W826 23:07:41.701077541 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240453Z [W826 23:07:41.844291462 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240570Z [W826 23:07:41.905166759 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240672Z [W826 23:07:41.036655998 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240768Z [W826 23:07:42.100784267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240866Z [W826 23:07:42.212077302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2240965Z [W826 23:07:42.274074852 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241064Z [W826 23:07:42.391037611 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241160Z [W826 23:07:42.452285493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241257Z [W826 23:07:42.579439068 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241358Z [W826 23:07:42.639966891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241482Z [W826 23:07:42.758178750 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2241579Z [W826 23:07:42.814202732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2242601Z [W826 23:07:42.938251384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2242703Z [W826 23:07:42.010125034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2242802Z [W826 23:07:43.134208825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2242898Z [W826 23:07:43.198365333 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2242997Z [W826 23:07:43.319240833 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243096Z [W826 23:07:43.386219008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243198Z [W826 23:07:43.499101529 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243294Z [W826 23:07:43.564279922 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243391Z [W826 23:07:43.678050019 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243490Z [W826 23:07:43.744068219 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243588Z [W826 23:07:43.868253988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243685Z [W826 23:07:43.921114507 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243782Z [W826 23:07:43.039113050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2243880Z [W826 23:07:44.100280653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244001Z [W826 23:07:44.229067923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244098Z [W826 23:07:44.294118098 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244197Z [W826 23:07:44.428147408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244312Z [W826 23:07:44.491080725 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244411Z [W826 23:07:44.627518488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244508Z [W826 23:07:44.693160174 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244605Z [W826 23:07:44.814070203 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2244716Z [W826 23:07:44.868569207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2245726Z [W826 23:07:44.991179791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2245824Z [W826 23:07:44.045037715 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2245921Z [W826 23:07:45.276364502 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246020Z [W826 23:07:45.502113522 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246117Z [W826 23:07:45.916104523 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246213Z [W826 23:07:45.916431998 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246310Z [W826 23:07:45.977044269 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246409Z [W826 23:07:46.066035721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246466Z PASSED [23.0643s] [ 96%] 2025-08-26T23:15:41.2246688Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet50 [W826 23:07:46.442115866 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246786Z [W826 23:07:46.508070077 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246885Z [W826 23:07:46.592273962 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2246986Z [W826 23:07:46.654046836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247083Z [W826 23:07:46.727662551 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247180Z [W826 23:07:46.785043292 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247279Z [W826 23:07:46.884181140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247378Z [W826 23:07:46.948064193 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247475Z [W826 23:07:46.013562381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247571Z [W826 23:07:47.102175009 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247668Z [W826 23:07:47.161073907 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2247765Z [W826 23:07:47.228776131 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2248765Z [W826 23:07:47.308029761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2248864Z [W826 23:07:47.375071875 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2248962Z [W826 23:07:47.455226942 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249078Z [W826 23:07:47.517066105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249174Z [W826 23:07:47.607061182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249271Z [W826 23:07:47.660184478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249387Z [W826 23:07:47.723153344 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249485Z [W826 23:07:47.800254656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249583Z [W826 23:07:47.856447665 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249681Z [W826 23:07:47.919262993 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249790Z [W826 23:07:47.000054560 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249891Z [W826 23:07:48.066116260 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2249988Z [W826 23:07:48.126051762 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250085Z [W826 23:07:48.219532006 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250182Z [W826 23:07:48.281113093 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250279Z [W826 23:07:48.347230162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250440Z [W826 23:07:48.487061054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250538Z [W826 23:07:48.568228205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250638Z [W826 23:07:48.694711160 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250764Z [W826 23:07:48.755519898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2250861Z [W826 23:07:48.883055376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2251885Z [W826 23:07:48.943078638 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2251988Z [W826 23:07:49.059133340 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252086Z [W826 23:07:49.098289587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252184Z [W826 23:07:49.224166101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252281Z [W826 23:07:49.286556216 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252381Z [W826 23:07:49.398200414 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252479Z [W826 23:07:49.464121296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252577Z [W826 23:07:49.692235812 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252673Z [W826 23:07:49.904095813 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252773Z [W826 23:07:50.346150438 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252869Z [W826 23:07:50.346566761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2252966Z [W826 23:07:50.420101717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253062Z [W826 23:07:50.485070294 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253160Z [W826 23:07:50.591184916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253283Z [W826 23:07:50.650068915 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253380Z [W826 23:07:50.707049681 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253477Z [W826 23:07:50.777280217 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253601Z [W826 23:07:50.833094512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253699Z [W826 23:07:50.900052468 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253796Z [W826 23:07:50.967049864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2253892Z [W826 23:07:50.035080734 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2254924Z [W826 23:07:51.100291195 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255026Z [W826 23:07:51.169125373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255123Z [W826 23:07:51.226070180 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255221Z [W826 23:07:51.304276446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255324Z [W826 23:07:51.366073171 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255421Z [W826 23:07:51.425043297 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255518Z [W826 23:07:51.499115035 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255614Z [W826 23:07:51.551053179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255714Z [W826 23:07:51.636236329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255830Z [W826 23:07:51.696093232 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2255928Z [W826 23:07:51.744056825 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256024Z [W826 23:07:51.783042515 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256122Z [W826 23:07:51.810073735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256218Z [W826 23:07:51.836029853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256315Z [W826 23:07:51.877037662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256412Z [W826 23:07:51.902048853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256510Z [W826 23:07:51.930034248 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256608Z [W826 23:07:51.970029202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256705Z [W826 23:07:51.996029940 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256801Z [W826 23:07:51.024528568 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256899Z [W826 23:07:52.071031493 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2256997Z [W826 23:07:52.095044609 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258014Z [W826 23:07:52.151032721 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258112Z [W826 23:07:52.175047258 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258212Z [W826 23:07:52.221026982 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258331Z [W826 23:07:52.249094386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258431Z [W826 23:07:52.296039045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258528Z [W826 23:07:52.318054672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258639Z [W826 23:07:52.373621121 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258736Z [W826 23:07:52.422516720 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258833Z [W826 23:07:52.494070226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2258930Z [W826 23:07:52.524040123 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259044Z [W826 23:07:52.643056329 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259143Z [W826 23:07:52.750045179 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259239Z [W826 23:07:52.941522670 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259335Z [W826 23:07:52.941818225 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259433Z [W826 23:07:52.968062637 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259528Z [W826 23:07:52.998993270 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259626Z [W826 23:07:53.392056226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259722Z [W826 23:07:53.447597954 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259823Z [W826 23:07:53.517448226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2259935Z [W826 23:07:53.567036015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2260032Z [W826 23:07:53.626923359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261097Z [W826 23:07:53.682061393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261200Z [W826 23:07:53.772807080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261298Z [W826 23:07:53.829835376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261396Z [W826 23:07:53.893207836 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261492Z [W826 23:07:53.980089490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261592Z [W826 23:07:53.040097911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261691Z [W826 23:07:54.108576953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261788Z [W826 23:07:54.191125774 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261884Z [W826 23:07:54.249329742 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2261983Z [W826 23:07:54.337296690 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262080Z [W826 23:07:54.397387640 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262177Z [W826 23:07:54.481640383 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262273Z [W826 23:07:54.542138138 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262371Z [W826 23:07:54.603055574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262511Z [W826 23:07:54.682055078 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262610Z [W826 23:07:54.745204083 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262708Z [W826 23:07:54.810201218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262836Z [W826 23:07:54.895187351 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2262935Z [W826 23:07:54.964369823 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2263032Z [W826 23:07:54.019120414 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2263129Z [W826 23:07:55.100044278 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264171Z [W826 23:07:55.165852921 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264272Z [W826 23:07:55.225119154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264370Z [W826 23:07:55.343040988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264466Z [W826 23:07:55.403063199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264566Z [W826 23:07:55.544036433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264662Z [W826 23:07:55.604046135 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264760Z [W826 23:07:55.725275358 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264856Z [W826 23:07:55.780439243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2264956Z [W826 23:07:55.894073602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265074Z [W826 23:07:55.952233801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265172Z [W826 23:07:56.057090173 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265268Z [W826 23:07:56.121266401 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265368Z [W826 23:07:56.241056727 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265466Z [W826 23:07:56.285195678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265564Z [W826 23:07:56.526170669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265661Z [W826 23:07:56.772059205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265761Z [W826 23:07:57.204582603 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265859Z [W826 23:07:57.204884239 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2265956Z [W826 23:07:57.267255354 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2266053Z [W826 23:07:57.341962873 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2266092Z PASSED [11.2650s] [ 96%] 2025-08-26T23:15:41.2267230Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet101 [W826 23:07:57.684111441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267330Z [W826 23:07:57.737047210 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267427Z [W826 23:07:57.811132697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267544Z [W826 23:07:57.857160120 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267643Z [W826 23:07:57.921789732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267740Z [W826 23:07:57.994080977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267837Z [W826 23:07:58.097985343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2267948Z [W826 23:07:58.158172221 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268046Z [W826 23:07:58.219201867 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268142Z [W826 23:07:58.312138419 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268240Z [W826 23:07:58.377205574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268354Z [W826 23:07:58.433264685 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268452Z [W826 23:07:58.532165957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268549Z [W826 23:07:58.597230182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268647Z [W826 23:07:58.688655057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268744Z [W826 23:07:58.746167935 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268842Z [W826 23:07:58.814447891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2268938Z [W826 23:07:58.883087482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2269035Z [W826 23:07:58.949113792 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2269136Z [W826 23:07:58.032454800 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2269253Z [W826 23:07:59.101073491 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2269350Z [W826 23:07:59.173058450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2270508Z [W826 23:07:59.244064655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2270613Z [W826 23:07:59.310090625 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2270712Z [W826 23:07:59.374094526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2270809Z [W826 23:07:59.462124943 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2270906Z [W826 23:07:59.535220065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271006Z [W826 23:07:59.595289026 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271106Z [W826 23:07:59.718147655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271204Z [W826 23:07:59.772257605 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271302Z [W826 23:07:59.889090516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271398Z [W826 23:07:59.959419150 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271495Z [W826 23:08:00.086068273 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271591Z [W826 23:08:00.147103408 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271688Z [W826 23:08:00.277749699 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271834Z [W826 23:08:00.345608492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2271932Z [W826 23:08:00.483279647 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272029Z [W826 23:08:00.533126542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272126Z [W826 23:08:00.673091911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272258Z [W826 23:08:00.732105418 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272357Z [W826 23:08:00.861992621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272454Z [W826 23:08:00.914233719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2272552Z [W826 23:08:01.055504920 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2273742Z [W826 23:08:01.115126567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2273843Z [W826 23:08:01.247057489 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2273939Z [W826 23:08:01.315582091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274039Z [W826 23:08:01.458085893 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274140Z [W826 23:08:01.526201791 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274237Z [W826 23:08:01.653506803 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274334Z [W826 23:08:01.726253281 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274430Z [W826 23:08:01.848636818 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274532Z [W826 23:08:01.920154404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274665Z [W826 23:08:02.054879624 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274762Z [W826 23:08:02.127105500 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274859Z [W826 23:08:02.253053553 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2274955Z [W826 23:08:02.321200061 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275054Z [W826 23:08:02.441144754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275149Z [W826 23:08:02.502115110 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275246Z [W826 23:08:02.638279338 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275345Z [W826 23:08:02.687910707 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275443Z [W826 23:08:02.810094916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275545Z [W826 23:08:02.876146546 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275642Z [W826 23:08:02.012149986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2275739Z [W826 23:08:03.072787427 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2276752Z [W826 23:08:03.195315991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2276852Z [W826 23:08:03.256301918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2276951Z [W826 23:08:03.386269519 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277070Z [W826 23:08:03.451767707 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277169Z [W826 23:08:03.587167257 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277266Z [W826 23:08:03.653677739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277363Z [W826 23:08:03.780082655 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277475Z [W826 23:08:03.838211015 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277573Z [W826 23:08:03.954184298 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277670Z [W826 23:08:03.006104182 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277767Z [W826 23:08:04.232135659 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277881Z [W826 23:08:04.470084804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2277979Z [W826 23:08:04.640402245 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278075Z [W826 23:08:04.767099646 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278172Z [W826 23:08:04.825428623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278269Z [W826 23:08:04.912134149 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278368Z [W826 23:08:04.967056318 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278464Z [W826 23:08:04.021119510 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278561Z [W826 23:08:05.077191969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278663Z [W826 23:08:05.162257931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278776Z [W826 23:08:05.227504243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2278874Z [W826 23:08:05.293083810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2279889Z [W826 23:08:05.373071478 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2279988Z [W826 23:08:05.425863389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280086Z [W826 23:08:05.474205357 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280183Z [W826 23:08:05.567144119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280280Z [W826 23:08:05.631064951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280443Z [W826 23:08:05.702675537 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280542Z [W826 23:08:05.770360702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280638Z [W826 23:08:05.860043724 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280735Z [W826 23:08:05.925779037 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280832Z [W826 23:08:05.982127975 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2280931Z [W826 23:08:06.071646479 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281027Z [W826 23:08:06.133598870 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281124Z [W826 23:08:06.202200251 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281252Z [W826 23:08:06.284104910 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281350Z [W826 23:08:06.344119981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281449Z [W826 23:08:06.407097878 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281547Z [W826 23:08:06.478801362 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281664Z [W826 23:08:06.546301459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281762Z [W826 23:08:06.621147356 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281858Z [W826 23:08:06.745061729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2281955Z [W826 23:08:06.804075146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2282996Z [W826 23:08:06.932884845 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283095Z [W826 23:08:06.969166005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283192Z [W826 23:08:06.035122307 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283288Z [W826 23:08:07.076593308 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283388Z [W826 23:08:07.205591704 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283485Z [W826 23:08:07.255100574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283582Z [W826 23:08:07.362391050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283679Z [W826 23:08:07.410690488 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283782Z [W826 23:08:07.548924284 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283897Z [W826 23:08:07.610209996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2283995Z [W826 23:08:07.683074863 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284091Z [W826 23:08:07.718338539 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284192Z [W826 23:08:07.812498822 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284288Z [W826 23:08:07.877700545 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284386Z [W826 23:08:07.989096888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284481Z [W826 23:08:07.044264832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284580Z [W826 23:08:08.150363265 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284676Z [W826 23:08:08.213312711 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284773Z [W826 23:08:08.338610405 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284869Z [W826 23:08:08.368101178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2284968Z [W826 23:08:08.427040495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2285973Z [W826 23:08:08.455080450 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286072Z [W826 23:08:08.586154536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286168Z [W826 23:08:08.646064388 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286284Z [W826 23:08:08.762858629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286381Z [W826 23:08:08.822200040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286478Z [W826 23:08:08.940040656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286574Z [W826 23:08:08.009834988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286686Z [W826 23:08:09.127165771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286783Z [W826 23:08:09.173926322 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286881Z [W826 23:08:09.269167520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2286978Z [W826 23:08:09.323090034 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287096Z [W826 23:08:09.424169053 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287192Z [W826 23:08:09.483451986 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287291Z [W826 23:08:09.583079046 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287387Z [W826 23:08:09.653407761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287487Z [W826 23:08:09.781042558 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287586Z [W826 23:08:09.848564335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287683Z [W826 23:08:09.915033279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287779Z [W826 23:08:09.946081199 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287881Z [W826 23:08:10.083469088 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2287997Z [W826 23:08:10.144216538 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2288998Z [W826 23:08:10.270085882 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289096Z [W826 23:08:10.304065347 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289197Z [W826 23:08:10.542646643 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289293Z [W826 23:08:10.657056361 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289390Z [W826 23:08:10.857485435 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289486Z [W826 23:08:11.505084717 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289588Z [W826 23:08:11.573044287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289686Z [W826 23:08:11.631452023 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289785Z [W826 23:08:11.662034099 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289881Z [W826 23:08:11.692069495 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2289978Z [W826 23:08:11.726606152 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290076Z [W826 23:08:11.809179851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290173Z [W826 23:08:11.837067828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290269Z [W826 23:08:11.892041526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290442Z [W826 23:08:11.981056308 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290540Z [W826 23:08:11.022074486 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290637Z [W826 23:08:12.083779452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290733Z [W826 23:08:12.168347642 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290850Z [W826 23:08:12.235192729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2290947Z [W826 23:08:12.326364728 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2291044Z [W826 23:08:12.357364509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2291139Z [W826 23:08:12.397151956 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292174Z [W826 23:08:12.422076159 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292272Z [W826 23:08:12.466791571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292369Z [W826 23:08:12.569234250 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292466Z [W826 23:08:12.630044918 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292566Z [W826 23:08:12.699133852 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292663Z [W826 23:08:12.783039672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292760Z [W826 23:08:12.840060718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292856Z [W826 23:08:12.897270211 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2292958Z [W826 23:08:12.978033308 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293075Z [W826 23:08:12.036051409 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293173Z [W826 23:08:13.094816890 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293270Z [W826 23:08:13.186567020 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293366Z [W826 23:08:13.217060428 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293463Z [W826 23:08:13.326041057 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293560Z [W826 23:08:13.386751178 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293656Z [W826 23:08:13.511188044 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293756Z [W826 23:08:13.566052432 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293853Z [W826 23:08:13.684793754 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2293950Z [W826 23:08:13.745131310 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2294046Z [W826 23:08:13.858076030 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2294145Z [W826 23:08:13.884059177 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295154Z [W826 23:08:13.945106952 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295254Z [W826 23:08:13.977216676 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295352Z [W826 23:08:14.112509376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295472Z [W826 23:08:14.182478847 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295572Z [W826 23:08:14.286753518 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295668Z [W826 23:08:14.357612914 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295765Z [W826 23:08:14.493064373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295876Z [W826 23:08:14.536843509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2295973Z [W826 23:08:14.606221978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296069Z [W826 23:08:14.678376576 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296166Z [W826 23:08:14.782088905 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296280Z [W826 23:08:14.842569459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296378Z [W826 23:08:14.974052868 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296474Z [W826 23:08:15.050074897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296571Z [W826 23:08:15.196034586 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296668Z [W826 23:08:15.258054287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296767Z [W826 23:08:15.390038148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296863Z [W826 23:08:15.456060528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2296960Z [W826 23:08:15.589044543 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2297062Z [W826 23:08:15.640329846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2297171Z [W826 23:08:15.761266355 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298170Z [W826 23:08:15.823102259 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298269Z [W826 23:08:15.946106215 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298368Z [W826 23:08:15.005295969 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298466Z [W826 23:08:16.121989802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298562Z [W826 23:08:16.173069208 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298659Z [W826 23:08:16.289833140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298760Z [W826 23:08:16.344073119 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298858Z [W826 23:08:16.468888328 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2298954Z [W826 23:08:16.533219184 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299052Z [W826 23:08:16.665267794 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299150Z [W826 23:08:16.729107047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299248Z [W826 23:08:16.870114381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299344Z [W826 23:08:16.926071874 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299441Z [W826 23:08:17.049041571 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299557Z [W826 23:08:17.109028513 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299655Z [W826 23:08:17.352043302 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299753Z [W826 23:08:17.592040377 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299851Z [W826 23:08:17.747057500 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2299888Z PASSED [20.4010s] [ 97%] 2025-08-26T23:15:41.2300113Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet50 [W826 23:08:17.044117351 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2300211Z [W826 23:08:18.104757932 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301287Z [W826 23:08:18.169046099 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301417Z [W826 23:08:18.229493853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301515Z [W826 23:08:18.294721555 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301611Z [W826 23:08:18.362181573 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301709Z [W826 23:08:18.442049664 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301807Z [W826 23:08:18.500325481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2301905Z [W826 23:08:18.557352187 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302001Z [W826 23:08:18.637376226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302099Z [W826 23:08:18.705262897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302219Z [W826 23:08:18.757172411 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302317Z [W826 23:08:18.838126005 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302413Z [W826 23:08:18.900049977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302510Z [W826 23:08:18.976089075 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302608Z [W826 23:08:18.039139290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302706Z [W826 23:08:19.113084241 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302802Z [W826 23:08:19.175130690 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2302899Z [W826 23:08:19.249673742 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2303000Z [W826 23:08:19.325486584 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2303098Z [W826 23:08:19.385332087 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2303194Z [W826 23:08:19.448142526 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2303291Z [W826 23:08:19.539259546 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2303387Z [W826 23:08:19.596172534 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304395Z [W826 23:08:19.653070822 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304493Z [W826 23:08:19.756140991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304590Z [W826 23:08:19.808052435 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304718Z [W826 23:08:19.857183091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304816Z [W826 23:08:19.956180381 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2304913Z [W826 23:08:19.989424698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305011Z [W826 23:08:19.047042065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305132Z [W826 23:08:20.074056806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305229Z [W826 23:08:20.145526144 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305327Z [W826 23:08:20.209199770 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305424Z [W826 23:08:20.340157417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305546Z [W826 23:08:20.412102566 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305644Z [W826 23:08:20.519082806 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305740Z [W826 23:08:20.583119966 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305837Z [W826 23:08:20.718048773 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2305934Z [W826 23:08:20.785659429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2306031Z [W826 23:08:20.956059378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2306128Z [W826 23:08:21.056044743 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2306225Z [W826 23:08:21.128088482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2306337Z [W826 23:08:21.173074291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2306435Z [W826 23:08:21.200328348 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307437Z [W826 23:08:21.232039768 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307536Z [W826 23:08:21.260028154 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307636Z [W826 23:08:21.288055900 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307734Z [W826 23:08:21.316033236 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307830Z [W826 23:08:21.361882452 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2307926Z [W826 23:08:21.392046155 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308028Z [W826 23:08:21.420138369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308126Z [W826 23:08:21.458166643 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308222Z [W826 23:08:21.486085050 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308320Z [W826 23:08:21.516314263 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308418Z [W826 23:08:21.550048122 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308517Z [W826 23:08:21.576033838 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308613Z [W826 23:08:21.614051992 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308710Z [W826 23:08:21.640039749 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308832Z [W826 23:08:21.672031414 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2308929Z [W826 23:08:21.703044384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2309026Z [W826 23:08:21.731036901 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2309123Z [W826 23:08:21.766036501 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2309236Z [W826 23:08:21.790049677 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2309334Z [W826 23:08:21.811032279 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2309430Z [W826 23:08:21.840036040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2310501Z [W826 23:08:21.865140049 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2310644Z [W826 23:08:21.890047672 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2310741Z [W826 23:08:21.928184045 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2310839Z [W826 23:08:21.963028737 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2310935Z [W826 23:08:21.984064288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311035Z [W826 23:08:21.039089265 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311133Z [W826 23:08:22.064109926 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311230Z [W826 23:08:22.109059465 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311326Z [W826 23:08:22.143184519 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311442Z [W826 23:08:22.200099206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311539Z [W826 23:08:22.227116797 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311636Z [W826 23:08:22.273046492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311732Z [W826 23:08:22.298091903 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311829Z [W826 23:08:22.359058729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2311924Z [W826 23:08:22.385601587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312021Z [W826 23:08:22.443065816 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312117Z [W826 23:08:22.465083933 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312220Z [W826 23:08:22.552113895 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312316Z [W826 23:08:22.653057156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312413Z [W826 23:08:22.721106626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2312509Z [W826 23:08:22.030041376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2313596Z [W826 23:08:23.054043082 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2313699Z [W826 23:08:23.089046433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2313798Z [W826 23:08:23.117056949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2313896Z [W826 23:08:23.139063435 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314022Z [W826 23:08:23.164034697 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314119Z [W826 23:08:23.196148621 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314216Z [W826 23:08:23.213531898 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314311Z [W826 23:08:23.224025209 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314425Z [W826 23:08:23.257032149 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314522Z [W826 23:08:23.283048925 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314620Z [W826 23:08:23.315434284 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314717Z [W826 23:08:23.348046291 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314834Z [W826 23:08:23.370027567 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2314931Z [W826 23:08:23.401595319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315028Z [W826 23:08:23.424021040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315124Z [W826 23:08:23.451056460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315224Z [W826 23:08:23.461195587 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315322Z [W826 23:08:23.485030425 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315419Z [W826 23:08:23.517032531 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315515Z [W826 23:08:23.540142731 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315632Z [W826 23:08:23.571381977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2315729Z [W826 23:08:23.609032388 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2316739Z [W826 23:08:23.632040389 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2316837Z [W826 23:08:23.660030355 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2316937Z [W826 23:08:23.699033884 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317033Z [W826 23:08:23.722029156 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317130Z [W826 23:08:23.747749007 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317227Z [W826 23:08:23.797048490 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317332Z [W826 23:08:23.822063631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317428Z [W826 23:08:23.876492857 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317525Z [W826 23:08:23.900043590 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317621Z [W826 23:08:23.951028729 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317719Z [W826 23:08:23.978038608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317815Z [W826 23:08:23.029018607 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2317911Z [W826 23:08:24.052041678 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318007Z [W826 23:08:24.112030469 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318126Z [W826 23:08:24.138042575 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318222Z [W826 23:08:24.184033769 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318321Z [W826 23:08:24.198705206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318418Z [W826 23:08:24.263033983 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318530Z [W826 23:08:24.360030063 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318628Z [W826 23:08:24.428358889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2318666Z PASSED [6.6649s] [ 97%] 2025-08-26T23:15:41.2319793Z test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_lraspp_mobilenet_v3_large [W826 23:08:24.484786004 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2319912Z [W826 23:08:24.552168304 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320009Z [W826 23:08:24.577078446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320106Z [W826 23:08:24.641461771 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320202Z [W826 23:08:24.664034990 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320302Z [W826 23:08:24.721034146 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320465Z [W826 23:08:24.749043682 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320562Z [W826 23:08:24.809690564 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320662Z [W826 23:08:24.809747283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320784Z [W826 23:08:24.809814231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320881Z [W826 23:08:24.820038716 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2320979Z [W826 23:08:24.868060319 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321076Z [W826 23:08:24.868094388 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321174Z [W826 23:08:24.868128008 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321273Z [W826 23:08:24.889925808 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321371Z [W826 23:08:24.936062899 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321470Z [W826 23:08:24.936097429 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321569Z [W826 23:08:24.936130118 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321666Z [W826 23:08:24.960695846 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321763Z [W826 23:08:24.028040145 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2321860Z [W826 23:08:24.048877931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2322874Z [W826 23:08:25.103218547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2322974Z [W826 23:08:25.124200320 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323071Z [W826 23:08:25.182201951 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323171Z [W826 23:08:25.205082105 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323292Z [W826 23:08:25.252060413 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323390Z [W826 23:08:25.276057550 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323486Z [W826 23:08:25.353870802 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323583Z [W826 23:08:25.353956981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323703Z [W826 23:08:25.354064988 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323801Z [W826 23:08:25.378038606 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2323898Z [W826 23:08:25.445091650 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324014Z [W826 23:08:25.445164989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324116Z [W826 23:08:25.445252467 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324218Z [W826 23:08:25.469078336 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324314Z [W826 23:08:25.523092048 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324412Z [W826 23:08:25.523170327 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324508Z [W826 23:08:25.523257446 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324606Z [W826 23:08:25.547039596 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324702Z [W826 23:08:25.598082422 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324802Z [W826 23:08:25.598187722 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2324915Z [W826 23:08:25.598314680 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2325921Z [W826 23:08:25.623052975 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326019Z [W826 23:08:25.674127840 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326116Z [W826 23:08:25.674234810 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326216Z [W826 23:08:25.674349817 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326313Z [W826 23:08:25.697058763 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326409Z [W826 23:08:25.722083205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326510Z [W826 23:08:25.750121889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326609Z [W826 23:08:25.750289547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326708Z [W826 23:08:25.758028780 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326804Z [W826 23:08:25.770110267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326901Z [W826 23:08:25.845063152 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2326998Z [W826 23:08:25.874160631 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327096Z [W826 23:08:25.956365106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327193Z [W826 23:08:25.977038713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327290Z [W826 23:08:25.043037713 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327407Z [W826 23:08:26.070056794 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327505Z [W826 23:08:26.134153644 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327602Z [W826 23:08:26.134222853 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327699Z [W826 23:08:26.134282692 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327810Z [W826 23:08:26.155027387 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2327907Z [W826 23:08:26.217059468 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2328004Z [W826 23:08:26.217101477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329024Z [W826 23:08:26.217149977 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329126Z [W826 23:08:26.240039080 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329224Z [W826 23:08:26.304107549 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329320Z [W826 23:08:26.304143299 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329418Z [W826 23:08:26.304175648 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329517Z [W826 23:08:26.327033832 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329615Z [W826 23:08:26.388541871 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329711Z [W826 23:08:26.413411214 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329811Z [W826 23:08:26.458917335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2329925Z [W826 23:08:26.464035588 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330023Z [W826 23:08:26.507032176 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330119Z [W826 23:08:26.528040528 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330215Z [W826 23:08:26.578913657 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330312Z [W826 23:08:26.601042192 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330470Z [W826 23:08:26.661099052 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330567Z [W826 23:08:26.661164091 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330665Z [W826 23:08:26.661241270 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330763Z [W826 23:08:26.685035290 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330860Z [W826 23:08:26.744068547 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2330956Z [W826 23:08:26.744137226 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2331053Z [W826 23:08:26.744231073 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332062Z [W826 23:08:26.774044202 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332164Z [W826 23:08:26.832059553 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332261Z [W826 23:08:26.832119332 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332360Z [W826 23:08:26.832217551 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332504Z [W826 23:08:26.853036396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332602Z [W826 23:08:26.898071404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332698Z [W826 23:08:26.898169542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332796Z [W826 23:08:26.898304240 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2332911Z [W826 23:08:26.922041851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333008Z [W826 23:08:26.970071283 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333105Z [W826 23:08:26.970171252 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333221Z [W826 23:08:26.970300380 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333320Z [W826 23:08:26.995032366 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333417Z [W826 23:08:26.022046246 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333513Z [W826 23:08:27.049070367 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333611Z [W826 23:08:27.049228364 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333708Z [W826 23:08:27.056026911 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333806Z [W826 23:08:27.418415003 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2333902Z [W826 23:08:27.494066827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2334004Z [W826 23:08:27.522053623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2334121Z [W826 23:08:27.601026487 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335128Z [W826 23:08:27.623247831 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335226Z [W826 23:08:27.681029316 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335324Z [W826 23:08:27.706058536 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335423Z [W826 23:08:27.786264651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335520Z [W826 23:08:27.795546601 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335616Z [W826 23:08:27.795599070 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335717Z [W826 23:08:27.818293247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335817Z [W826 23:08:27.883387961 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2335914Z [W826 23:08:27.883521579 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336010Z [W826 23:08:27.883581398 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336107Z [W826 23:08:27.906454912 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336204Z [W826 23:08:27.974219735 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336303Z [W826 23:08:27.974330953 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336400Z [W826 23:08:27.974390512 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336498Z [W826 23:08:27.999063989 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336616Z [W826 23:08:28.098097359 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336713Z [W826 23:08:28.135046929 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336811Z [W826 23:08:28.203090378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2336908Z [W826 23:08:28.232127459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2337020Z [W826 23:08:28.287056107 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2337118Z [W826 23:08:28.311050303 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338121Z [W826 23:08:28.366109400 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338239Z [W826 23:08:28.391036923 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338339Z [W826 23:08:28.454131667 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338436Z [W826 23:08:28.454210335 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338533Z [W826 23:08:28.454287354 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338629Z [W826 23:08:28.482030804 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338730Z [W826 23:08:28.551074778 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338828Z [W826 23:08:28.551144827 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2338925Z [W826 23:08:28.551211916 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339022Z [W826 23:08:28.574048600 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339137Z [W826 23:08:28.630029173 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339234Z [W826 23:08:28.630086482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339331Z [W826 23:08:28.630165761 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339428Z [W826 23:08:28.649027544 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339525Z [W826 23:08:28.705083395 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339622Z [W826 23:08:28.705193453 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339720Z [W826 23:08:28.705297043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339820Z [W826 23:08:28.733462106 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2339920Z [W826 23:08:28.781065864 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2340016Z [W826 23:08:28.781182404 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2340113Z [W826 23:08:28.781324391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2340209Z [W826 23:08:28.808032247 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341277Z [W826 23:08:28.829031848 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341376Z [W826 23:08:28.857733044 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341473Z [W826 23:08:28.857855402 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341573Z [W826 23:08:28.865023263 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341644Z PASSED [4.4395s] [ 97%] 2025-08-26T23:15:41.2341841Z test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x0_5 [W826 23:08:29.321030577 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2341939Z [W826 23:08:29.427854460 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342035Z [W826 23:08:29.460078821 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342151Z [W826 23:08:29.515031369 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342248Z [W826 23:08:29.532051971 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342347Z [W826 23:08:29.562363272 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342470Z [W826 23:08:29.571737100 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342573Z [W826 23:08:29.621648054 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342669Z [W826 23:08:29.662016662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342766Z [W826 23:08:29.702607218 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342863Z [W826 23:08:29.705944798 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2342961Z [W826 23:08:29.751447739 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2343057Z [W826 23:08:29.777111719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2343154Z [W826 23:08:29.833024532 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2343251Z [W826 23:08:29.856088373 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2343371Z [W826 23:08:29.919029970 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344405Z [W826 23:08:29.941093906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344505Z [W826 23:08:29.002024224 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344601Z [W826 23:08:29.026083709 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344701Z [W826 23:08:29.046565908 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344799Z [W826 23:08:30.050458669 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344896Z [W826 23:08:30.088057040 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2344994Z [W826 23:08:30.092831108 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345096Z [W826 23:08:30.112360602 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345194Z [W826 23:08:30.171029724 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345291Z [W826 23:08:30.196164013 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345387Z [W826 23:08:30.257028931 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345485Z [W826 23:08:30.281296623 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345580Z [W826 23:08:30.304452553 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345678Z [W826 23:08:30.308397433 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345774Z [W826 23:08:30.352064062 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345892Z [W826 23:08:30.366493143 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2345988Z [W826 23:08:30.419399162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2346085Z [W826 23:08:30.448115227 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2346181Z [W826 23:08:30.551028698 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2346294Z [W826 23:08:30.653034393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2346391Z [W826 23:08:30.675038220 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347385Z [W826 23:08:30.732025067 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347501Z [W826 23:08:30.765045417 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347604Z [W826 23:08:30.827028189 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347700Z [W826 23:08:30.860039509 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347797Z [W826 23:08:30.925025204 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347896Z [W826 23:08:30.995025384 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2347996Z [W826 23:08:31.099022949 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348092Z [W826 23:08:31.126089889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348189Z [W826 23:08:31.191022516 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348288Z [W826 23:08:31.218060276 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348407Z [W826 23:08:31.277026653 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348505Z [W826 23:08:31.295612141 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348601Z [W826 23:08:31.296934681 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348698Z [W826 23:08:31.297232897 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348795Z [W826 23:08:31.298121243 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348892Z [W826 23:08:31.298379629 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2348989Z [W826 23:08:31.307447542 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2349090Z [W826 23:08:31.333100524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2349188Z [W826 23:08:31.430092374 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2349285Z [W826 23:08:31.466942296 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2349382Z [W826 23:08:31.546030978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2349479Z [W826 23:08:31.604240267 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2350549Z [W826 23:08:31.629045662 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2350647Z [W826 23:08:31.691027162 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2350747Z [W826 23:08:31.715033548 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2350846Z [W826 23:08:31.775033641 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2350988Z [W826 23:08:31.798083430 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351085Z [W826 23:08:31.865028207 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351182Z [W826 23:08:31.892088957 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351280Z [W826 23:08:31.954033809 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351396Z [W826 23:08:31.977077470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351494Z [W826 23:08:32.426038481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351591Z [W826 23:08:32.529020551 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351715Z [W826 23:08:32.561068386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351816Z [W826 23:08:32.619107747 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2351913Z [W826 23:08:32.654045747 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352010Z [W826 23:08:32.716025659 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352106Z [W826 23:08:32.748047494 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352206Z [W826 23:08:32.799035481 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352302Z [W826 23:08:32.873023681 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352400Z [W826 23:08:32.967026157 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352499Z [W826 23:08:32.987269201 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2352622Z [W826 23:08:32.010024656 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2353695Z [W826 23:08:32.024738913 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2353793Z [W826 23:08:32.036017223 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2353891Z [W826 23:08:33.060086978 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2353990Z [W826 23:08:33.117022615 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354088Z [W826 23:08:33.139074702 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354184Z [W826 23:08:33.207021503 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354284Z [W826 23:08:33.232221881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354385Z [W826 23:08:33.287024851 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354482Z [W826 23:08:33.312077341 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354578Z [W826 23:08:33.372023504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354675Z [W826 23:08:33.399079574 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354772Z [W826 23:08:33.464018140 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354868Z [W826 23:08:33.530023190 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2354965Z [W826 23:08:33.553027732 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355064Z [W826 23:08:33.612021608 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355190Z [W826 23:08:33.633097459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355287Z [W826 23:08:33.701026240 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355384Z [W826 23:08:33.728122170 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355484Z [W826 23:08:33.786021393 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355596Z [W826 23:08:33.808684520 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2355695Z [W826 23:08:33.878034410 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2356702Z [W826 23:08:33.904583168 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2356757Z PASSED [5.0630s] [ 97%] 2025-08-26T23:15:41.2356951Z test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_0 [W826 23:08:33.047034350 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357051Z [W826 23:08:35.584046891 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357148Z [W826 23:08:35.714081872 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357245Z [W826 23:08:35.741878881 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357345Z [W826 23:08:35.804043879 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357442Z [W826 23:08:35.831210459 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357539Z [W826 23:08:35.895304378 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357638Z [W826 23:08:35.921133386 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357764Z [W826 23:08:35.989045277 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357862Z [W826 23:08:36.149038205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2357959Z [W826 23:08:37.890063036 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358056Z [W826 23:08:37.002039420 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358154Z [W826 23:08:37.025272719 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358253Z [W826 23:08:38.088031858 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358350Z [W826 23:08:38.114167142 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358450Z [W826 23:08:38.180047905 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358549Z [W826 23:08:38.206172639 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358646Z [W826 23:08:38.270066101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2358743Z [W826 23:08:38.772226996 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2359748Z [W826 23:08:40.586965031 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2359848Z [W826 23:08:40.701023524 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2359946Z [W826 23:08:40.728135343 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360042Z [W826 23:08:40.790022626 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360143Z [W826 23:08:40.820104360 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360261Z [W826 23:08:40.892023391 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360429Z [W826 23:08:40.917091441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360525Z [W826 23:08:40.966023390 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360563Z PASSED [7.0658s] [ 97%] 2025-08-26T23:15:41.2360780Z test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_5 [W826 23:08:41.110274205 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360879Z [W826 23:08:43.108042738 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2360976Z [W826 23:08:43.273041709 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361094Z [W826 23:08:43.315273230 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361193Z [W826 23:08:43.382033968 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361293Z [W826 23:08:43.412059663 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361389Z [W826 23:08:43.481029829 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361487Z [W826 23:08:43.516058849 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361583Z [W826 23:08:43.581030594 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361680Z [W826 23:08:43.747032811 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361776Z [W826 23:08:45.913045065 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361876Z [W826 23:08:45.032033683 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2361992Z [W826 23:08:46.070048828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363013Z [W826 23:08:46.136038129 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363110Z [W826 23:08:46.173044477 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363207Z [W826 23:08:46.243030888 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363306Z [W826 23:08:46.281051661 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363404Z [W826 23:08:46.349031492 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363500Z [W826 23:08:46.843026981 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363601Z [W826 23:08:48.869073785 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363701Z [W826 23:08:48.997099016 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363799Z [W826 23:08:48.031050482 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363896Z [W826 23:08:49.102622358 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2363993Z [W826 23:08:49.139068396 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364091Z [W826 23:08:49.200152801 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364188Z [W826 23:08:49.236029287 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364285Z [W826 23:08:49.304025837 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364322Z PASSED [8.3777s] [ 97%] 2025-08-26T23:15:41.2364512Z test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x2_0 [W826 23:08:49.513086651 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364643Z [W826 23:08:52.498038113 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364739Z [W826 23:08:55.869029828 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2364776Z PASSED [9.5970s] [ 97%] 2025-08-26T23:15:41.2364980Z test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_0 [W826 23:09:00.161063153 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2365079Z [W826 23:09:00.183024441 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366090Z [W826 23:09:01.456089889 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366209Z [W826 23:09:01.484028326 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366311Z [W826 23:09:02.831046125 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366408Z [W826 23:09:02.861028101 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366444Z PASSED [3.9553s] [ 97%] 2025-08-26T23:15:41.2366635Z test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_1 [W826 23:09:03.664273756 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366736Z [W826 23:09:03.676608779 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366833Z [W826 23:09:03.741251800 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2366929Z [W826 23:09:03.749098991 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367025Z [W826 23:09:03.814310743 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367142Z [W826 23:09:03.842056504 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367239Z [W826 23:09:03.927108475 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367336Z [W826 23:09:03.951075313 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367432Z [W826 23:09:04.672057313 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367530Z [W826 23:09:04.684148670 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367627Z [W826 23:09:04.739033148 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367725Z [W826 23:09:04.749056376 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367821Z [W826 23:09:04.804277620 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2367923Z [W826 23:09:04.829226592 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2368020Z [W826 23:09:04.914037447 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2368116Z [W826 23:09:04.941033688 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369126Z [W826 23:09:05.781093206 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369226Z [W826 23:09:05.788063250 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369323Z [W826 23:09:05.841042288 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369421Z [W826 23:09:05.850067231 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369517Z [W826 23:09:05.905096047 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369636Z [W826 23:09:05.932022470 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369733Z [W826 23:09:05.020039906 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369830Z [W826 23:09:06.050027312 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:15:41.2369865Z PASSED [3.1837s] [ 97%] 2025-08-26T23:15:41.2369965Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_b PASSED [23.6096s] [ 97%] 2025-08-26T23:15:41.2370075Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_s PASSED [22.4213s] [ 97%] 2025-08-26T23:15:41.2370169Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_t PASSED [11.5563s] [ 97%] 2025-08-26T23:15:41.2370268Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_b PASSED [32.6450s] [ 97%] 2025-08-26T23:15:41.2370496Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s Command took >30min, returning 124 2025-08-26T23:15:41.2370534Z Got exit code 124 2025-08-26T23:15:41.2370573Z Retrying single test... 2025-08-26T23:15:41.2371016Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:15:41.2371056Z import pkg_resources 2025-08-26T23:15:41.2371172Z Test results will be stored in test-reports/python-pytest/test_fx/test_fx-2b8b9779170b88d1.xml 2025-08-26T23:15:41.2371234Z ============================= test session starts ============================== 2025-08-26T23:15:41.2371347Z platform linux -- Python 3.12.11, pytest-7.3.2, pluggy-1.6.0 -- /opt/conda/envs/py_3.12/bin/python 2025-08-26T23:15:41.2372314Z cachedir: .pytest_cache 2025-08-26T23:15:41.2372478Z hypothesis profile 'pytorch_ci' -> database=None, max_examples=50, derandomize=True, suppress_health_check=[HealthCheck.too_slow] 2025-08-26T23:15:41.2372563Z rootdir: /var/lib/jenkins/pytorch 2025-08-26T23:15:41.2372603Z configfile: pytest.ini 2025-08-26T23:15:41.2372771Z plugins: hypothesis-5.35.1, subtests-0.13.1, cpp-2.3.0, flakefinder-1.1.0, rerunfailures-14.0, xdist-3.3.1, xdoctest-1.1.0, typeguard-4.3.0 2025-08-26T23:15:41.2372850Z collecting ... collected 1269 items / 1268 deselected / 1 selected 2025-08-26T23:15:41.2373010Z stepcurrent: skipping 1243 already run items. Running only test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s 2025-08-26T23:15:41.2373053Z Running 1 items in this shard 2025-08-26T23:15:41.2373057Z 2025-08-26T23:15:41.2373162Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s PASSED [31.6656s] [100%] 2025-08-26T23:15:41.2373165Z 2025-08-26T23:15:41.2373325Z - generated xml file: /var/lib/jenkins/pytorch/test/test-reports/python-pytest/test_fx/test_fx-2b8b9779170b88d1.xml - 2025-08-26T23:15:41.2373394Z ===================== 1 passed, 1268 deselected in 31.70s ====================== 2025-08-26T23:15:41.2373432Z Got exit code 0 2025-08-26T23:15:41.2373515Z Test succeeeded in new process, continuing with the rest of the tests 2025-08-26T23:15:41.2373933Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:15:41.2373972Z import pkg_resources 2025-08-26T23:15:41.2374083Z Test results will be stored in test-reports/python-pytest/test_fx/test_fx-635e47ca0b53dabc.xml 2025-08-26T23:15:41.2374141Z ============================= test session starts ============================== 2025-08-26T23:15:41.2374251Z platform linux -- Python 3.12.11, pytest-7.3.2, pluggy-1.6.0 -- /opt/conda/envs/py_3.12/bin/python 2025-08-26T23:15:41.2374290Z cachedir: .pytest_cache 2025-08-26T23:15:41.2374485Z hypothesis profile 'pytorch_ci' -> database=None, max_examples=50, derandomize=True, suppress_health_check=[HealthCheck.too_slow] 2025-08-26T23:15:41.2374530Z rootdir: /var/lib/jenkins/pytorch 2025-08-26T23:15:41.2374567Z configfile: pytest.ini 2025-08-26T23:15:41.2375638Z plugins: hypothesis-5.35.1, subtests-0.13.1, cpp-2.3.0, flakefinder-1.1.0, rerunfailures-14.0, xdist-3.3.1, xdoctest-1.1.0, typeguard-4.3.0 2025-08-26T23:15:41.2375716Z collecting ... collected 1269 items / 1244 deselected / 25 selected 2025-08-26T23:15:41.2375809Z stepcurrent: skipping 1244 already run items. 2025-08-26T23:15:41.2375853Z Running 25 items in this shard 2025-08-26T23:15:41.2375855Z 2025-08-26T23:15:41.2375961Z test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_t PASSED [17.5120s] [ 4%] 2025-08-26T23:15:41.2376055Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg11 PASSED [2.0048s] [ 8%] 2025-08-26T23:15:41.2376179Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg11_bn PASSED [2.3607s] [ 12%] 2025-08-26T23:15:41.2376277Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg13 PASSED [2.5240s] [ 16%] 2025-08-26T23:15:41.2376373Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg13_bn PASSED [2.3854s] [ 20%] 2025-08-26T23:15:41.2376463Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg16 PASSED [2.9793s] [ 24%] 2025-08-26T23:15:41.2376556Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg16_bn PASSED [3.2669s] [ 28%] 2025-08-26T23:15:41.2376648Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg19 PASSED [3.3733s] [ 32%] 2025-08-26T23:15:41.2376741Z test_fx.py::TestVisionTracing::test_torchvision_models_vgg19_bn PASSED [3.4614s] [ 36%] 2025-08-26T23:15:41.2376843Z test_fx.py::TestVisionTracing::test_torchvision_models_video_mc3_18 PASSED [3.0388s] [ 40%] 2025-08-26T23:15:41.2376951Z test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v1_b PASSED [19.8344s] [ 44%] 2025-08-26T23:15:41.2377061Z test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v2_s PASSED [29.6324s] [ 48%] 2025-08-26T23:15:41.2377187Z test_fx.py::TestVisionTracing::test_torchvision_models_video_r2plus1d_18 PASSED [5.0824s] [ 52%] 2025-08-26T23:15:41.2377288Z test_fx.py::TestVisionTracing::test_torchvision_models_video_r3d_18 PASSED [2.7094s] [ 56%] 2025-08-26T23:15:41.2377386Z test_fx.py::TestVisionTracing::test_torchvision_models_video_s3d PASSED [10.1639s] [ 60%] 2025-08-26T23:15:41.2377494Z test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_b PASSED [21.1547s] [ 64%] 2025-08-26T23:15:41.2377602Z test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_s PASSED [20.7022s] [ 68%] 2025-08-26T23:15:41.2378618Z test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_t PASSED [10.8054s] [ 72%] 2025-08-26T23:15:41.2378716Z test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_16 PASSED [5.3181s] [ 76%] 2025-08-26T23:15:41.2378814Z test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_32 PASSED [5.0944s] [ 80%] 2025-08-26T23:15:41.2378912Z test_fx.py::TestVisionTracing::test_torchvision_models_vit_h_14 PASSED [14.9915s] [ 84%] 2025-08-26T23:15:41.2379006Z test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_16 PASSED [10.7152s] [ 88%] 2025-08-26T23:15:41.2379100Z test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_32 PASSED [10.9662s] [ 92%] 2025-08-26T23:15:41.2379206Z test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet101_2 PASSED [16.9793s] [ 96%] 2025-08-26T23:15:41.2379314Z test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet50_2 PASSED [8.7261s] [100%] 2025-08-26T23:15:41.2379316Z 2025-08-26T23:15:41.2379474Z - generated xml file: /var/lib/jenkins/pytorch/test/test-reports/python-pytest/test_fx/test_fx-635e47ca0b53dabc.xml - 2025-08-26T23:15:41.2379546Z =============== 25 passed, 1244 deselected in 235.87s (0:03:55) ================ 2025-08-26T23:15:41.2379719Z The following tests failed and then succeeded when run in a new process['test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s'] 2025-08-26T23:15:41.2379742Z 2025-08-26T23:15:41.2379854Z FINISHED PRINTING LOG FILE of test_fx 1/1 (test/test-reports/test_fx_1.1_de6e6b79f446acef_.log) 2025-08-26T23:15:41.2379856Z 2025-08-26T23:15:41.2379947Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T23:15:41.2379994Z Uploading artifacts took 0.00 seconds 2025-08-26T23:15:41.2380054Z Running test_hub 1/1 ... [2025-08-26 23:15:41.070840] 2025-08-26T23:15:41.2380118Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:15:41.2380453Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_hub.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:15:41.071013] 2025-08-26T23:15:58.5212563Z 2025-08-26T23:15:58.5213706Z test_hub 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_hub_1.1_46853a3035c68cd2_.log 2025-08-26T23:15:58.5216034Z Running 20 items in this shard: test/test_hub.py::TestHub::test_download_url_to_file, test/test_hub.py::TestHub::test_get_set_dir, test/test_hub.py::TestHub::test_hub_parse_repo_info, test/test_hub.py::TestHub::test_list_entrypoints, test/test_hub.py::TestHub::test_load_commit_from_forked_repo, test/test_hub.py::TestHub::test_load_from_branch, test/test_hub.py::TestHub::test_load_from_github, test/test_hub.py::TestHub::test_load_from_local_dir, test/test_hub.py::TestHub::test_load_legacy_zip_checkpoint, test/test_hub.py::TestHub::test_load_state_dict_from_url, test/test_hub.py::TestHub::test_load_zip_1_6_checkpoint, test/test_hub.py::TestHub::test_trust_repo_builtin_trusted_owners, test/test_hub.py::TestHub::test_trust_repo_check_no, test/test_hub.py::TestHub::test_trust_repo_check_yes, test/test_hub.py::TestHub::test_trust_repo_false_emptystring, test/test_hub.py::TestHub::test_trust_repo_false_no, test/test_hub.py::TestHub::test_trust_repo_legacy, test/test_hub.py::TestHub::test_trust_repo_none, test/test_hub.py::TestHub::test_trust_repo_true, test/test_hub.py::TestHub::test_trusted_repo_false_yes 2025-08-26T23:15:58.5218093Z 2025-08-26T23:15:58.5218326Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-08-26 23:15:58.521095] 2025-08-26T23:15:58.5218674Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:15:58.5219332Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:15:58.521318] 2025-08-26T23:16:03.4455259Z 2025-08-26T23:16:03.4457599Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_16bf1d533841219b_.log 2025-08-26T23:16:03.4469379Z Running 23 items in this shard: test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_default_constructor_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_device_guard_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_device_guard_set_index_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_divide_neg_exp_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_exp_neg_is_leaf_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_fill_infinity_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_get_current_device_index_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_identity_does_not_hog_memory_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_is_contiguous_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_abs_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_amax_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_amax_vec_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_empty_like_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_is_cpu_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_narrow_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_new_empty_dtype_variant_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_ones_like_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_pad_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_transpose_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_my_zero__cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_neg_exp_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_slow_sgd_cuda, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCUDA::test_stream_cuda 2025-08-26T23:16:03.4477139Z 2025-08-26T23:16:03.4477307Z Running test_extension_utils 1/1 ... [2025-08-26 23:16:03.445410] 2025-08-26T23:16:03.4477535Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:16:03.4478072Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_extension_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:16:03.445658] 2025-08-26T23:16:06.1653607Z 2025-08-26T23:16:06.1655165Z test_extension_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_extension_utils_1.1_942410aab4b7f7fe_.log 2025-08-26T23:16:06.1661940Z Running 2 items in this shard: test/test_extension_utils.py::TestExtensionUtils::test_external_module_register, test/test_extension_utils.py::TestExtensionUtils::test_external_module_register_with_renamed_backend 2025-08-26T23:16:06.1662286Z 2025-08-26T23:16:06.1662393Z Running test_native_mha 1/1 ... [2025-08-26 23:16:06.165606] 2025-08-26T23:16:06.1662719Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:16:06.1663097Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_native_mha.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:16:06.165860] 2025-08-26T23:16:11.9411333Z 2025-08-26T23:16:11.9412420Z test_native_mha 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_mha_1.1_ec0a74271f023035_.log 2025-08-26T23:16:11.9433396Z Running 54 items in this shard: test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_attention_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_attention_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_encoder_decoder_attention_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_encoder_decoder_attention_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cuda_float16, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_transform_bias_rescale_qkv_cuda_float32, test/test_native_mha.py::TestMHADeviceTypeCUDA::test_transform_bias_rescale_qkv_nested_cuda_float32 2025-08-26T23:16:11.9446521Z 2025-08-26T23:16:11.9446595Z Running test_optim 1/1 ... [2025-08-26 23:16:11.941300] 2025-08-26T23:16:11.9446746Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:16:11.9447130Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_optim.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:16:11.941582] 2025-08-26T23:20:28.8729822Z 2025-08-26T23:20:28.8730947Z test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_1.1_ce8aa814becd571a_.log 2025-08-26T23:20:28.8868224Z Running 1008 items in this shard: test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_T_cur_reset, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_1, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_4, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr3, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr_state_dict, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_list, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_scalar, test/test_optim.py::TestLRScheduler::test_add_param_group_errors_reduce_lr_on_plateau, test/test_optim.py::TestLRScheduler::test_chained_lr1, test/test_optim.py::TestLRScheduler::test_chained_lr2, test/test_optim.py::TestLRScheduler::test_chained_lr2_get_last_lr_before_step, test/test_optim.py::TestLRScheduler::test_chained_lr3, test/test_optim.py::TestLRScheduler::test_chained_lr4, test/test_optim.py::TestLRScheduler::test_chained_lr5, test/test_optim.py::TestLRScheduler::test_closed_form_constantlr, test/test_optim.py::TestLRScheduler::test_closed_form_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_closed_form_exp_lr, test/test_optim.py::TestLRScheduler::test_closed_form_linearlr, test/test_optim.py::TestLRScheduler::test_closed_form_multi_step_lr, test/test_optim.py::TestLRScheduler::test_closed_form_poly_lr, 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test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_load_state_dict_pre_post_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_foreach_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_mixed_device_dtype_impl_fused_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_non_empty_state_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optim_infos_do_not_specify_global_cliquey_kwargs_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_optimizer_can_be_printed_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_group_with_lrscheduler_goes_right_direction_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_lr_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_param_groups_weight_decay_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_peak_memory_foreach_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_False_Adagrad_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_False_SGD_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_False_SparseAdam_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_True_Adagrad_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_True_SGD_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_rosenbrock_sparse_with_lrsched_True_SparseAdam_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_False_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_save_load_equality_with_weights_only_is_named_optim_True_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_second_order_optims_return_consistent_types_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_ASGD_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Adadelta_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Adafactor_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Adagrad_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_AdamW_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Adam_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Adamax_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_NAdam_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_RAdam_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_RMSprop_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_Rprop_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_set_default_dtype_works_with_foreach_SGD_cuda_float64, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_post_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_pre_post_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_state_dict_with_cuda_params_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_all_hooks_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_for_zero_grads_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_is_noop_when_params_have_no_grad_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_post_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_step_pre_hook_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_0_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_1_SparseAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_ASGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Adadelta_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Adafactor_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Adagrad_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_AdamW_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Adam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Adamax_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_LBFGS_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Muon_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_NAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_RAdam_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_RMSprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_Rprop_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_SGD_cuda_float32, test/test_optim.py::TestOptimRenewedCUDA::test_tensor_lr_num_dim_2_SparseAdam_cuda_float32 2025-08-26T23:20:28.8994917Z 2025-08-26T23:20:28.8999942Z Running test_tensorboard 1/1 ... [2025-08-26 23:20:28.873872] 2025-08-26T23:20:28.9000126Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:20:28.9000593Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_tensorboard.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:20:28.874108] 2025-08-26T23:20:32.4979712Z 2025-08-26T23:20:32.4980885Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_9412a84a15aaccb5_.log 2025-08-26T23:20:32.4989987Z Running 50 items in this shard: test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_autograd_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram_raw, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_write, test/test_tensorboard.py::TestTensorBoardUtils::test_convert_to_HWC_dtype_remains_same, test/test_tensorboard.py::TestTensorBoardUtils::test_numpy_vid_uint8, test/test_tensorboard.py::TestTensorBoardUtils::test_prepare_video, test/test_tensorboard.py::TestTensorBoardUtils::test_to_HWC, test/test_tensorboard.py::TestTensorBoardWriter::test_writer, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_pathlib, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_close, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_ctx, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding_64, test/test_tensorboard.py::TestTensorBoardSummary::test_audio, test/test_tensorboard.py::TestTensorBoardSummary::test_custom_scalars, test/test_tensorboard.py::TestTensorBoardSummary::test_empty_input, test/test_tensorboard.py::TestTensorBoardSummary::test_float32_image, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_auto, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_doane, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_fd, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_3_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_boxes, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_without_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_list_input, test/test_tensorboard.py::TestTensorBoardSummary::test_mesh, test/test_tensorboard.py::TestTensorBoardSummary::test_scalar_new_style, test/test_tensorboard.py::TestTensorBoardSummary::test_text, test/test_tensorboard.py::TestTensorBoardSummary::test_uint8_image, test/test_tensorboard.py::TestTensorBoardSummary::test_video, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_mlp_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_nested_nn_squential, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph_dict_input, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_torchvision_smoke, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_wrong_input_size, test/test_tensorboard.py::TestTensorBoardFigure::test_figure, test/test_tensorboard.py::TestTensorBoardFigure::test_figure_list, test/test_tensorboard.py::TestTensorBoardNumpy::test_pytorch_np_expect_fail, test/test_tensorboard.py::TestTensorBoardNumpy::test_scalar, test/test_tensorboard.py::TestTensorProtoSummary::test_complex_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_empty_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_float_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_bfloat16_proto_type_14, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_float16_proto_type_19, test/test_tensorboard.py::TestTensorProtoSummary::test_int_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_scalar_tensor_proto 2025-08-26T23:20:32.4998554Z 2025-08-26T23:20:32.4998637Z Running test_spectral_ops 1/1 ... [2025-08-26 23:20:32.498161] 2025-08-26T23:20:32.5004242Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:20:32.5004810Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:20:32.498380] 2025-08-26T23:21:54.8914975Z 2025-08-26T23:21:54.8919279Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_b4d3e7034a3ad07a_.log 2025-08-26T23:21:54.8959396Z Running 347 items in this shard: test/test_spectral_ops.py::TestFFTCUDA::test_batch_istft_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_complex_istft_real_equiv_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_complex_stft_definition_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_complex_stft_onesided_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_complex_stft_real_equiv_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_complex_stft_roundtrip_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_complex_stft_roundtrip_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_cufft_context_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_cufft_context_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_cufft_plan_cache_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft2_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft2_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft2_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fftn_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_fftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft2_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft2_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft2_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfftn_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_hfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft2_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft2_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft2_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifftn_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ifftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfft2_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_ihfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_empty_fft__refs_fft_irfft2_cuda_complex32, 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test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifft2_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifft_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifftn_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ifftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ihfft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ihfft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_ihfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfft2_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfft_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfftn_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_irfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_rfft2_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_rfft_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_half_and_chalf_not_power_of_two_error_fft_rfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_ifft_rfft_irfft_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fft_input_modification_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_fft_invalid_dtypes_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_fft_plan_repeatable_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_round_trip_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fft_type_promotion_cuda_int8, test/test_spectral_ops.py::TestFFTCUDA::test_fftfreq_numpy_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftfreq_numpy_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fftfreq_out_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftfreq_out_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_fftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_fftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_hfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_hfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_ifftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_ifftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_ihfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_irfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_irfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid__refs_fft_rfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_fftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_fftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_hfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_hfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_ifftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_ifftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_ihfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_irfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_irfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_invalid_fft_rfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_noop_transform_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_noop_transform_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_noop_transform_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_noop_transform_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_noop_transform_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_complex32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftn_round_trip_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_frequencies_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_frequencies_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_numpy_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_numpy_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_numpy_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_fftshift_numpy_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_hfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_hfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_hfftn_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_ihfftn_cuda_float16, test/test_spectral_ops.py::TestFFTCUDA::test_ihfftn_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_ihfftn_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_against_librosa_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_linearity_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_of_sine_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_requires_window_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_istft_round_trip_simple_cases_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_round_trip_various_params_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_round_trip_with_padding_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_istft_throws_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_fft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_fft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_hfft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_hfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_ifft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_ifft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_ihfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_irfft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_irfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d__refs_fft_rfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_fft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_fft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_hfft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_hfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_ifft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_ifft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_ihfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_irfft_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_irfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_1d_fft_rfft_cuda_float32, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_fftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_fftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_hfftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_hfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_ifftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_ifftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_irfftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd__refs_fft_irfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_fftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_fftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_hfftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_hfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_ifftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_ifftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_irfftn_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_reference_nd_fft_irfftn_cuda_complex64, test/test_spectral_ops.py::TestFFTCUDA::test_stft_align_to_window_only_requires_non_center_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_stft_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_stft_requires_complex_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_stft_requires_window_cuda, test/test_spectral_ops.py::TestFFTCUDA::test_stft_roundtrip_complex_window_cuda_complex128, test/test_spectral_ops.py::TestFFTCUDA::test_stft_roundtrip_complex_window_cuda_float64, test/test_spectral_ops.py::TestFFTCUDA::test_stft_window_device_cuda 2025-08-26T23:21:54.9001990Z 2025-08-26T23:21:54.9002060Z Running doctests 1/1 ... [2025-08-26 23:21:54.891801] 2025-08-26T23:21:54.9160224Z Start doctest_module('/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch') 2025-08-26T23:21:54.9161252Z Listing tests 2025-08-26T23:21:54.9645582Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=565. 2025-08-26T23:21:54.9645926Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:54.9646068Z 2025-08-26T23:21:54.9646177Z Load a model from a github repo or a local directory. 2025-08-26T23:21:54.9646281Z 2025-08-26T23:21:54.9646381Z Note: Loading a model is the typical use case, but this can also be used to 2025-08-26T23:21:54.9646599Z for loading other objects such as tokenizers, loss functions, etc. 2025-08-26T23:21:54.9646719Z 2025-08-26T23:21:54.9646800Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-08-26T23:21:54.9646979Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-08-26T23:21:54.9647519Z ref (a tag or a branch). 2025-08-26T23:21:54.9647597Z 2025-08-26T23:21:54.9647669Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-08-26T23:21:54.9647816Z path to a local directory. 2025-08-26T23:21:54.9647890Z 2025-08-26T23:21:54.9647947Z Args: 2025-08-26T23:21:54.9648049Z repo_or_dir (str): If ``source`` is 'github', 2025-08-26T23:21:54.9648277Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-08-26T23:21:54.9648628Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-08-26T23:21:54.9648872Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-08-26T23:21:54.9649081Z If ``source`` is 'local' then it should be a path to a local directory. 2025-08-26T23:21:54.9649345Z model (str): the name of a callable (entrypoint) defined in the 2025-08-26T23:21:54.9649512Z repo/dir's ``hubconf.py``. 2025-08-26T23:21:54.9649673Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T23:21:54.9649857Z source (str, optional): 'github' or 'local'. Specifies how 2025-08-26T23:21:54.9650029Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-08-26T23:21:54.9650216Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-08-26T23:21:54.9650517Z This parameter was introduced in v1.12 and helps ensuring that users 2025-08-26T23:21:54.9650705Z only run code from repos that they trust. 2025-08-26T23:21:54.9650792Z 2025-08-26T23:21:54.9650876Z - If ``False``, a prompt will ask the user whether the repo should 2025-08-26T23:21:54.9651034Z be trusted. 2025-08-26T23:21:54.9651168Z - If ``True``, the repo will be added to the trusted list and loaded 2025-08-26T23:21:54.9651334Z without requiring explicit confirmation. 2025-08-26T23:21:54.9651512Z - If ``"check"``, the repo will be checked against the list of 2025-08-26T23:21:54.9651768Z trusted repos in the cache. If it is not present in that list, the 2025-08-26T23:21:54.9651962Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-08-26T23:21:54.9652147Z - If ``None``: this will raise a warning, inviting the user to set 2025-08-26T23:21:54.9652325Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-08-26T23:21:54.9652513Z is only present for backward compatibility and will be removed in 2025-08-26T23:21:54.9652678Z v2.0. 2025-08-26T23:21:54.9652733Z 2025-08-26T23:21:54.9652818Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-08-26T23:21:54.9658109Z force_reload (bool, optional): whether to force a fresh download of 2025-08-26T23:21:54.9658374Z the github repo unconditionally. Does not have any effect if 2025-08-26T23:21:54.9658538Z ``source = 'local'``. Default is ``False``. 2025-08-26T23:21:54.9658711Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-08-26T23:21:54.9658911Z local caches. Note that the message about first download cannot be 2025-08-26T23:21:54.9659089Z muted. Does not have any effect if ``source = 'local'``. 2025-08-26T23:21:54.9659232Z Default is ``True``. 2025-08-26T23:21:54.9659417Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-08-26T23:21:54.9659675Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-08-26T23:21:54.9659926Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-08-26T23:21:54.9660136Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-08-26T23:21:54.9660323Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T23:21:54.9660539Z 2025-08-26T23:21:54.9660705Z Returns: 2025-08-26T23:21:54.9660833Z The output of the ``model`` callable when called with the given 2025-08-26T23:21:54.9660981Z ``*args`` and ``**kwargs``. 2025-08-26T23:21:54.9661050Z 2025-08-26T23:21:54.9661088Z Example: 2025-08-26T23:21:54.9661185Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:21:54.9661314Z >>> # from a github repo 2025-08-26T23:21:54.9661422Z >>> repo = "pytorch/vision" 2025-08-26T23:21:54.9661530Z >>> model = torch.hub.load( 2025-08-26T23:21:54.9661724Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-08-26T23:21:54.9661862Z ... ) 2025-08-26T23:21:54.9661950Z >>> # from a local directory 2025-08-26T23:21:54.9662079Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T23:21:54.9662203Z >>> # xdoctest: +SKIP 2025-08-26T23:21:54.9662359Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-08-26T23:21:54.9662510Z 2025-08-26T23:21:54.9662615Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:54.9662745Z 2025-08-26T23:21:54.9662913Z msg = Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=657. 2025-08-26T23:21:54.9663197Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:54.9663325Z 2025-08-26T23:21:54.9663396Z Load a model from a local directory with a ``hubconf.py``. 2025-08-26T23:21:54.9663498Z 2025-08-26T23:21:54.9663532Z Args: 2025-08-26T23:21:54.9663650Z hubconf_dir (str): path to a local directory that contains a 2025-08-26T23:21:54.9663792Z ``hubconf.py``. 2025-08-26T23:21:54.9663922Z model (str): name of an entrypoint defined in the directory's 2025-08-26T23:21:54.9664060Z ``hubconf.py``. 2025-08-26T23:21:54.9664194Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T23:21:54.9664388Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T23:21:54.9664504Z 2025-08-26T23:21:54.9664537Z Returns: 2025-08-26T23:21:54.9664666Z a single model with corresponding pretrained weights. 2025-08-26T23:21:54.9664766Z 2025-08-26T23:21:54.9664802Z Example: 2025-08-26T23:21:54.9664898Z >>> # xdoctest: +SKIP("stub local path") 2025-08-26T23:21:54.9665028Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T23:21:54.9665152Z >>> model = _load_local( 2025-08-26T23:21:54.9665255Z ... path, 2025-08-26T23:21:54.9665344Z ... "resnet50", 2025-08-26T23:21:54.9665457Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-08-26T23:21:54.9665586Z ... ) 2025-08-26T23:21:54.9665634Z 2025-08-26T23:21:54.9665723Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:54.9665850Z 2025-08-26T23:21:54.9666014Z msg = Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=696. 2025-08-26T23:21:54.9666308Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:54.9666496Z Download object at the given URL to a local path. 2025-08-26T23:21:54.9666589Z 2025-08-26T23:21:54.9666635Z Args: 2025-08-26T23:21:54.9666735Z url (str): URL of the object to download 2025-08-26T23:21:54.9666910Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-08-26T23:21:54.9667168Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-08-26T23:21:54.9667363Z Default: None 2025-08-26T23:21:54.9667525Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-08-26T23:21:54.9667699Z Default: True 2025-08-26T23:21:54.9667760Z 2025-08-26T23:21:54.9667802Z Example: 2025-08-26T23:21:54.9667911Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:21:54.9668047Z >>> # xdoctest: +REQUIRES(POSIX) 2025-08-26T23:21:54.9668193Z >>> torch.hub.download_url_to_file( 2025-08-26T23:21:54.9668391Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-08-26T23:21:54.9668556Z ... "/tmp/temporary_file", 2025-08-26T23:21:54.9668679Z ... ) 2025-08-26T23:21:54.9668733Z 2025-08-26T23:21:54.9668767Z 2025-08-26T23:21:54.9668906Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:54.9669035Z 2025-08-26T23:21:54.9669239Z msg = Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=821. 2025-08-26T23:21:54.9669534Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:54.9669720Z Loads the Torch serialized object at the given URL. 2025-08-26T23:21:54.9669814Z 2025-08-26T23:21:54.9669888Z If downloaded file is a zip file, it will be automatically 2025-08-26T23:21:54.9670048Z decompressed. 2025-08-26T23:21:54.9670108Z 2025-08-26T23:21:54.9670191Z If the object is already present in `model_dir`, it's deserialized and 2025-08-26T23:21:54.9670418Z returned. 2025-08-26T23:21:54.9670554Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-08-26T23:21:54.9670747Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-08-26T23:21:54.9672708Z 2025-08-26T23:21:54.9672742Z Args: 2025-08-26T23:21:54.9672838Z url (str): URL of the object to download 2025-08-26T23:21:54.9672997Z model_dir (str, optional): directory in which to save the object 2025-08-26T23:21:54.9673229Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-08-26T23:21:54.9673481Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-08-26T23:21:54.9673646Z Default: True 2025-08-26T23:21:54.9673826Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-08-26T23:21:54.9674105Z ``filename-.ext`` where ```` is the first eight or more 2025-08-26T23:21:54.9674305Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-08-26T23:21:54.9674575Z ensure unique names and to verify the contents of the file. 2025-08-26T23:21:54.9676683Z Default: False 2025-08-26T23:21:54.9676886Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-08-26T23:21:54.9677161Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-08-26T23:21:54.9677402Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-08-26T23:21:54.9677535Z 2025-08-26T23:21:54.9677573Z Example: 2025-08-26T23:21:54.9677682Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:21:54.9677826Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-08-26T23:21:54.9678002Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-08-26T23:21:54.9678147Z ... ) 2025-08-26T23:21:54.9678198Z 2025-08-26T23:21:54.9678228Z 2025-08-26T23:21:54.9678361Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:54.9679626Z 2025-08-26T23:21:55.0134617Z msg = Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py line=1493. 2025-08-26T23:21:55.0134946Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0135407Z 2025-08-26T23:21:55.0135985Z dim_order(ambiguity_check=False) -> tuple 2025-08-26T23:21:55.0136212Z 2025-08-26T23:21:55.0136345Z Returns the uniquely determined tuple of int describing the dim order or 2025-08-26T23:21:55.0136638Z physical layout of :attr:`self`. 2025-08-26T23:21:55.0136758Z 2025-08-26T23:21:55.0137182Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-08-26T23:21:55.0137486Z starting from the outermost to the innermost dimension. 2025-08-26T23:21:55.0137631Z 2025-08-26T23:21:55.0137739Z Note that the dim order may not always be uniquely determined. 2025-08-26T23:21:55.0138075Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-08-26T23:21:55.0144083Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-08-26T23:21:55.0144446Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-08-26T23:21:55.0144754Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-08-26T23:21:55.0145006Z Otherwise, it will raise TypeError. 2025-08-26T23:21:55.0145185Z 2025-08-26T23:21:55.0145228Z Args: 2025-08-26T23:21:55.0145429Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-08-26T23:21:55.0145623Z 2025-08-26T23:21:55.0145696Z Examples:: 2025-08-26T23:21:55.0145763Z 2025-08-26T23:21:55.0145826Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-08-26T23:21:55.0145975Z (0, 1, 2, 3) 2025-08-26T23:21:55.0146108Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-08-26T23:21:55.0146275Z (0, 2, 1, 3) 2025-08-26T23:21:55.0147975Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-08-26T23:21:55.0148152Z (0, 2, 3, 1) 2025-08-26T23:21:55.0148272Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-08-26T23:21:55.0148403Z (0, 1, 2, 3) 2025-08-26T23:21:55.0148503Z >>> try: 2025-08-26T23:21:55.0148645Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-08-26T23:21:55.0148817Z ... except RuntimeError as e: 2025-08-26T23:21:55.0148957Z ... print(e) 2025-08-26T23:21:55.0149162Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-08-26T23:21:55.0149469Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-08-26T23:21:55.0149663Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-08-26T23:21:55.0150950Z ... ) # It can be mapped to contiguous format 2025-08-26T23:21:55.0151068Z (0, 1, 2, 3) 2025-08-26T23:21:55.0151151Z >>> try: 2025-08-26T23:21:55.0151263Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-08-26T23:21:55.0151412Z ... except TypeError as e: 2025-08-26T23:21:55.0151516Z ... print(e) 2025-08-26T23:21:55.0151657Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-08-26T23:21:55.0151776Z 2025-08-26T23:21:55.0151812Z .. warning:: 2025-08-26T23:21:55.0151931Z The dim_order tensor API is experimental and subject to change. 2025-08-26T23:21:55.0152042Z 2025-08-26T23:21:55.0152133Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0152261Z 2025-08-26T23:21:55.0324376Z msg = Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py line=397. 2025-08-26T23:21:55.0324899Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0325254Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-08-26T23:21:55.0325445Z 2025-08-26T23:21:55.0325555Z This is helpful when you want to visualize data over some 2025-08-26T23:21:55.0325798Z range of inputs. See below for a plotting example. 2025-08-26T23:21:55.0325950Z 2025-08-26T23:21:55.0326048Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-08-26T23:21:55.0326304Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-08-26T23:21:55.0326574Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-08-26T23:21:55.0326829Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-08-26T23:21:55.0329313Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-08-26T23:21:55.0329588Z to the result shape. 2025-08-26T23:21:55.0329694Z 2025-08-26T23:21:55.0329758Z .. note:: 2025-08-26T23:21:55.0329948Z 0D inputs are treated equivalently to 1D inputs of a 2025-08-26T23:21:55.0330163Z single element. 2025-08-26T23:21:55.0330261Z 2025-08-26T23:21:55.0330321Z .. warning:: 2025-08-26T23:21:55.0330709Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-08-26T23:21:55.0330966Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-08-26T23:21:55.0331113Z 2025-08-26T23:21:55.0331205Z In the future `torch.meshgrid` will transition to 2025-08-26T23:21:55.0331411Z `indexing='xy'` as the default. 2025-08-26T23:21:55.0333605Z 2025-08-26T23:21:55.0333738Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-08-26T23:21:55.0334012Z this issue with the goal of migrating to NumPy's behavior. 2025-08-26T23:21:55.0334179Z 2025-08-26T23:21:55.0334239Z .. seealso:: 2025-08-26T23:21:55.0334328Z 2025-08-26T23:21:55.0334439Z :func:`torch.cartesian_prod` has the same effect but it 2025-08-26T23:21:55.0334668Z collects the data in a tensor of vectors. 2025-08-26T23:21:55.0334805Z 2025-08-26T23:21:55.0334859Z Args: 2025-08-26T23:21:55.0335094Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-08-26T23:21:55.0335386Z treated as tensors of size :math:`(1,)` automatically 2025-08-26T23:21:55.0335551Z 2025-08-26T23:21:55.0335645Z indexing: (str, optional): the indexing mode, either "xy" 2025-08-26T23:21:55.0335903Z or "ij", defaults to "ij". See warning for future changes. 2025-08-26T23:21:55.0336045Z 2025-08-26T23:21:55.0336149Z If "xy" is selected, the first dimension corresponds 2025-08-26T23:21:55.0336420Z to the cardinality of the second input and the second 2025-08-26T23:21:55.0336677Z dimension corresponds to the cardinality of the first 2025-08-26T23:21:55.0336901Z input. 2025-08-26T23:21:55.0336996Z 2025-08-26T23:21:55.0337087Z If "ij" is selected, the dimensions are in the same 2025-08-26T23:21:55.0337358Z order as the cardinality of the inputs. 2025-08-26T23:21:55.0337490Z 2025-08-26T23:21:55.0337551Z Returns: 2025-08-26T23:21:55.0337745Z seq (sequence of Tensors): If the input has :math:`N` 2025-08-26T23:21:55.0338004Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-08-26T23:21:55.0338256Z output will also have :math:`N` tensors, where each tensor 2025-08-26T23:21:55.0338512Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-08-26T23:21:55.0338648Z 2025-08-26T23:21:55.0338704Z Example:: 2025-08-26T23:21:55.0338804Z 2025-08-26T23:21:55.0338870Z >>> x = torch.tensor([1, 2, 3]) 2025-08-26T23:21:55.0339077Z >>> y = torch.tensor([4, 5, 6]) 2025-08-26T23:21:55.0339198Z 2025-08-26T23:21:55.0340959Z Observe the element-wise pairings across the grid, (1, 4), 2025-08-26T23:21:55.0341204Z (1, 5), ..., (3, 6). This is the same thing as the 2025-08-26T23:21:55.0341419Z cartesian product. 2025-08-26T23:21:55.0341608Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-08-26T23:21:55.0341813Z >>> grid_x 2025-08-26T23:21:55.0341960Z tensor([[1, 1, 1], 2025-08-26T23:21:55.0342116Z [2, 2, 2], 2025-08-26T23:21:55.0342262Z [3, 3, 3]]) 2025-08-26T23:21:55.0342414Z >>> grid_y 2025-08-26T23:21:55.0342556Z tensor([[4, 5, 6], 2025-08-26T23:21:55.0342721Z [4, 5, 6], 2025-08-26T23:21:55.0344325Z [4, 5, 6]]) 2025-08-26T23:21:55.0344531Z 2025-08-26T23:21:55.0344624Z This correspondence can be seen when these grids are 2025-08-26T23:21:55.0344841Z stacked properly. 2025-08-26T23:21:55.0345067Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-08-26T23:21:55.0345302Z ... torch.cartesian_prod(x, y)) 2025-08-26T23:21:55.0345484Z True 2025-08-26T23:21:55.0345555Z 2025-08-26T23:21:55.0345664Z `torch.meshgrid` is commonly used to produce a grid for 2025-08-26T23:21:55.0345948Z plotting. 2025-08-26T23:21:55.0346109Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-08-26T23:21:55.0346320Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-08-26T23:21:55.0346525Z >>> import matplotlib.pyplot as plt 2025-08-26T23:21:55.0348072Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-08-26T23:21:55.0348352Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-08-26T23:21:55.0348554Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-08-26T23:21:55.0348771Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-08-26T23:21:55.0348968Z >>> ax = plt.axes(projection='3d') 2025-08-26T23:21:55.0349192Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-08-26T23:21:55.0349387Z >>> plt.show() 2025-08-26T23:21:55.0349479Z 2025-08-26T23:21:55.0349562Z .. image:: ../_static/img/meshgrid.png 2025-08-26T23:21:55.0349738Z :width: 512 2025-08-26T23:21:55.0349837Z 2025-08-26T23:21:55.0349885Z 2025-08-26T23:21:55.0350082Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0351783Z 2025-08-26T23:21:55.0352056Z msg = Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py line=793. 2025-08-26T23:21:55.0352515Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0353011Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-08-26T23:21:55.0353280Z 2025-08-26T23:21:55.0353362Z Returns the unique elements of the input tensor. 2025-08-26T23:21:55.0353520Z 2025-08-26T23:21:55.0353676Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-08-26T23:21:55.0354001Z this function also eliminates non-consecutive duplicate values. 2025-08-26T23:21:55.0354191Z 2025-08-26T23:21:55.0354317Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-08-26T23:21:55.0354804Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-08-26T23:21:55.0355162Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-08-26T23:21:55.0355476Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-08-26T23:21:55.0355622Z 2025-08-26T23:21:55.0355677Z Args: 2025-08-26T23:21:55.0357221Z input (Tensor): the input tensor 2025-08-26T23:21:55.0357468Z sorted (bool): Whether to sort the unique elements in ascending order 2025-08-26T23:21:55.0357707Z before returning as output. 2025-08-26T23:21:55.0357951Z return_inverse (bool): Whether to also return the indices for where 2025-08-26T23:21:55.0358251Z elements in the original input ended up in the returned unique list. 2025-08-26T23:21:55.0358556Z return_counts (bool): Whether to also return the counts for each unique 2025-08-26T23:21:55.0358780Z element. 2025-08-26T23:21:55.0358983Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-08-26T23:21:55.0359271Z unique of the flattened input is returned. Otherwise, each of the 2025-08-26T23:21:55.0359551Z tensors indexed by the given dimension is treated as one of the 2025-08-26T23:21:55.0359848Z elements to apply the unique operation upon. See examples for more 2025-08-26T23:21:55.0362385Z details. Default: ``None`` 2025-08-26T23:21:55.0362522Z 2025-08-26T23:21:55.0362570Z Returns: 2025-08-26T23:21:55.0362800Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-08-26T23:21:55.0363010Z 2025-08-26T23:21:55.0363127Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-08-26T23:21:55.0363358Z - **inverse_indices** (*Tensor*): (optional) if 2025-08-26T23:21:55.0363653Z :attr:`return_inverse` is True, there will be an additional 2025-08-26T23:21:55.0363935Z returned tensor (same shape as input) representing the indices 2025-08-26T23:21:55.0364219Z for where elements in the original input map to in the output; 2025-08-26T23:21:55.0364499Z otherwise, this function will only return a single tensor. 2025-08-26T23:21:55.0364754Z - **counts** (*Tensor*): (optional) if 2025-08-26T23:21:55.0364976Z :attr:`return_counts` is True, there will be an additional 2025-08-26T23:21:55.0366634Z returned tensor (same shape as output or output.size(dim), 2025-08-26T23:21:55.0366905Z if dim was specified) representing the number of occurrences 2025-08-26T23:21:55.0367140Z for each unique value or tensor. 2025-08-26T23:21:55.0367261Z 2025-08-26T23:21:55.0367329Z Example:: 2025-08-26T23:21:55.0367400Z 2025-08-26T23:21:55.0367514Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-08-26T23:21:55.0367744Z >>> output 2025-08-26T23:21:55.0367875Z tensor([1, 2, 3]) 2025-08-26T23:21:55.0367980Z 2025-08-26T23:21:55.0368053Z >>> output, inverse_indices = torch.unique( 2025-08-26T23:21:55.0368315Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T23:21:55.0368558Z >>> output 2025-08-26T23:21:55.0370076Z tensor([1, 2, 3]) 2025-08-26T23:21:55.0370227Z >>> inverse_indices 2025-08-26T23:21:55.0370518Z tensor([0, 2, 1, 2]) 2025-08-26T23:21:55.0370620Z 2025-08-26T23:21:55.0370693Z >>> output, inverse_indices = torch.unique( 2025-08-26T23:21:55.0370955Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T23:21:55.0371198Z >>> output 2025-08-26T23:21:55.0371331Z tensor([1, 2, 3]) 2025-08-26T23:21:55.0371471Z >>> inverse_indices 2025-08-26T23:21:55.0371640Z tensor([[0, 2], 2025-08-26T23:21:55.0371776Z [1, 2]]) 2025-08-26T23:21:55.0371876Z 2025-08-26T23:21:55.0371931Z >>> a = torch.tensor([ 2025-08-26T23:21:55.0373474Z ... [ 2025-08-26T23:21:55.0373609Z ... [1, 1, 0, 0], 2025-08-26T23:21:55.0373771Z ... [1, 1, 0, 0], 2025-08-26T23:21:55.0373928Z ... [0, 0, 1, 1], 2025-08-26T23:21:55.0374080Z ... ], 2025-08-26T23:21:55.0374199Z ... [ 2025-08-26T23:21:55.0374343Z ... [0, 0, 1, 1], 2025-08-26T23:21:55.0374493Z ... [0, 0, 1, 1], 2025-08-26T23:21:55.0374642Z ... [1, 1, 1, 1], 2025-08-26T23:21:55.0374784Z ... ], 2025-08-26T23:21:55.0374907Z ... [ 2025-08-26T23:21:55.0376395Z ... [1, 1, 0, 0], 2025-08-26T23:21:55.0376555Z ... [1, 1, 0, 0], 2025-08-26T23:21:55.0376707Z ... [0, 0, 1, 1], 2025-08-26T23:21:55.0376860Z ... ], 2025-08-26T23:21:55.0376984Z ... ]) 2025-08-26T23:21:55.0377059Z 2025-08-26T23:21:55.0377176Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-08-26T23:21:55.0377466Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-08-26T23:21:55.0377717Z >>> # each other, so one of them will be removed. 2025-08-26T23:21:55.0377905Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-08-26T23:21:55.0378136Z tensor(True) 2025-08-26T23:21:55.0378295Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-08-26T23:21:55.0379873Z >>> a_unique_dim0 2025-08-26T23:21:55.0380021Z tensor([[[0, 0, 1, 1], 2025-08-26T23:21:55.0380174Z [0, 0, 1, 1], 2025-08-26T23:21:55.0380323Z [1, 1, 1, 1]], 2025-08-26T23:21:55.0380564Z [[1, 1, 0, 0], 2025-08-26T23:21:55.0380705Z [1, 1, 0, 0], 2025-08-26T23:21:55.0380946Z [0, 0, 1, 1]]]) 2025-08-26T23:21:55.0381048Z 2025-08-26T23:21:55.0381174Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-08-26T23:21:55.0381410Z >>> # `a_unique_dim0`: 2025-08-26T23:21:55.0381581Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-08-26T23:21:55.0381772Z tensor(True) 2025-08-26T23:21:55.0383393Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-08-26T23:21:55.0383575Z tensor(True) 2025-08-26T23:21:55.0383687Z 2025-08-26T23:21:55.0383836Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-08-26T23:21:55.0384131Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-08-26T23:21:55.0384359Z >>> # them will be removed. 2025-08-26T23:21:55.0384519Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-08-26T23:21:55.0384694Z tensor(True) 2025-08-26T23:21:55.0384871Z >>> torch.unique(a, dim=1) 2025-08-26T23:21:55.0385031Z tensor([[[0, 0, 1, 1], 2025-08-26T23:21:55.0385224Z [1, 1, 0, 0]], 2025-08-26T23:21:55.0385381Z [[1, 1, 1, 1], 2025-08-26T23:21:55.0387017Z [0, 0, 1, 1]], 2025-08-26T23:21:55.0387160Z [[0, 0, 1, 1], 2025-08-26T23:21:55.0387333Z [1, 1, 0, 0]]]) 2025-08-26T23:21:55.0387453Z 2025-08-26T23:21:55.0387567Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-08-26T23:21:55.0387840Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-08-26T23:21:55.0388153Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-08-26T23:21:55.0388387Z >>> # sub-tensors will be removed. 2025-08-26T23:21:55.0388605Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-08-26T23:21:55.0388755Z tensor(True) 2025-08-26T23:21:55.0388894Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-08-26T23:21:55.0389098Z tensor(True) 2025-08-26T23:21:55.0390847Z >>> torch.unique(a, dim=2) 2025-08-26T23:21:55.0391012Z tensor([[[0, 1], 2025-08-26T23:21:55.0391178Z [0, 1], 2025-08-26T23:21:55.0391344Z [1, 0]], 2025-08-26T23:21:55.0391473Z [[1, 0], 2025-08-26T23:21:55.0391633Z [1, 0], 2025-08-26T23:21:55.0391804Z [1, 1]], 2025-08-26T23:21:55.0391933Z [[0, 1], 2025-08-26T23:21:55.0392060Z [0, 1], 2025-08-26T23:21:55.0392199Z [1, 0]]]) 2025-08-26T23:21:55.0392381Z 2025-08-26T23:21:55.0394078Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0394307Z 2025-08-26T23:21:55.0448164Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py line=1285. 2025-08-26T23:21:55.0448737Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0449132Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-08-26T23:21:55.0449433Z 2025-08-26T23:21:55.0449528Z Loads an object saved with :func:`torch.save` from a file. 2025-08-26T23:21:55.0449673Z 2025-08-26T23:21:55.0449824Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-08-26T23:21:55.0450180Z which underlie tensors, specially. They are first deserialized on the 2025-08-26T23:21:55.0450692Z CPU and are then moved to the device they were saved from. If this fails 2025-08-26T23:21:55.0451015Z (e.g. because the run time system doesn't have certain devices), an exception 2025-08-26T23:21:55.0451359Z is raised. However, storages can be dynamically remapped to an alternative 2025-08-26T23:21:55.0454039Z set of devices using the :attr:`map_location` argument. 2025-08-26T23:21:55.0454207Z 2025-08-26T23:21:55.0454440Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-08-26T23:21:55.0454912Z storage with two arguments: storage and location. The storage argument 2025-08-26T23:21:55.0455224Z will be the initial deserialization of the storage, residing on the CPU. 2025-08-26T23:21:55.0455572Z Each serialized storage has a location tag associated with it which 2025-08-26T23:21:55.0455839Z identifies the device it was saved from, and this tag is the second 2025-08-26T23:21:55.0456214Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-08-26T23:21:55.0456592Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-08-26T23:21:55.0456917Z :attr:`map_location` should return either ``None`` or a storage. If 2025-08-26T23:21:55.0457229Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-08-26T23:21:55.0457595Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-08-26T23:21:55.0457920Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-08-26T23:21:55.0458155Z 2025-08-26T23:21:55.0458274Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-08-26T23:21:55.0458667Z a device tag, it indicates the location where all tensors should be loaded. 2025-08-26T23:21:55.0458852Z 2025-08-26T23:21:55.0459037Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-08-26T23:21:55.0459381Z appearing in the file (keys), to ones that specify where to put the 2025-08-26T23:21:55.0459661Z storages (values). 2025-08-26T23:21:55.0459794Z 2025-08-26T23:21:55.0459910Z User extensions can register their own location tags and tagging and 2025-08-26T23:21:55.0460329Z deserialization methods using :func:`torch.serialization.register_package`. 2025-08-26T23:21:55.0460615Z 2025-08-26T23:21:55.0460847Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-08-26T23:21:55.0461026Z 2025-08-26T23:21:55.0461163Z Args: 2025-08-26T23:21:55.0461424Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-08-26T23:21:55.0461776Z or a string or os.PathLike object containing a file name 2025-08-26T23:21:55.0463658Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-08-26T23:21:55.0463989Z locations 2025-08-26T23:21:55.0464213Z pickle_module: module used for unpickling metadata and objects (has to 2025-08-26T23:21:55.0464612Z match the :attr:`pickle_module` used to serialize file) 2025-08-26T23:21:55.0464871Z weights_only: Indicates whether unpickler should be restricted to 2025-08-26T23:21:55.0465181Z loading only tensors, primitive types, dictionaries 2025-08-26T23:21:55.0465469Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-08-26T23:21:55.0465741Z See :ref:`weights-only` for more details. 2025-08-26T23:21:55.0466062Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-08-26T23:21:55.0466516Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-08-26T23:21:55.0467003Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-08-26T23:21:55.0468977Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-08-26T23:21:55.0469518Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-08-26T23:21:55.0469889Z will be lazily loaded when their data is accessed. 2025-08-26T23:21:55.0470166Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-08-26T23:21:55.0470644Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-08-26T23:21:55.0470939Z :attr:`errors=...`. 2025-08-26T23:21:55.0471038Z 2025-08-26T23:21:55.0471092Z .. warning:: 2025-08-26T23:21:55.0471283Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-08-26T23:21:55.0471617Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-08-26T23:21:55.0472012Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-08-26T23:21:55.0472394Z during unpickling. Never load data that could have come from an untrusted 2025-08-26T23:21:55.0474163Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-08-26T23:21:55.0474490Z 2025-08-26T23:21:55.0474548Z .. note:: 2025-08-26T23:21:55.0474809Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-08-26T23:21:55.0475168Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-08-26T23:21:55.0475551Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-08-26T23:21:55.0475779Z 2025-08-26T23:21:55.0475854Z .. note:: 2025-08-26T23:21:55.0476063Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-08-26T23:21:55.0476468Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-08-26T23:21:55.0476772Z when loading files saved by Python 2 in Python 3. If this default 2025-08-26T23:21:55.0477158Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-08-26T23:21:55.0477542Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-08-26T23:21:55.0479319Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-08-26T23:21:55.0479670Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-08-26T23:21:55.0479852Z 2025-08-26T23:21:55.0479922Z Example: 2025-08-26T23:21:55.0480099Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-08-26T23:21:55.0480315Z >>> torch.load("tensors.pt", weights_only=True) 2025-08-26T23:21:55.0480616Z # Load all tensors onto the CPU 2025-08-26T23:21:55.0480827Z >>> torch.load( 2025-08-26T23:21:55.0480975Z ... "tensors.pt", 2025-08-26T23:21:55.0481167Z ... map_location=torch.device("cpu"), 2025-08-26T23:21:55.0481396Z ... weights_only=True, 2025-08-26T23:21:55.0484134Z ... ) 2025-08-26T23:21:55.0484300Z # Load all tensors onto the CPU, using a function 2025-08-26T23:21:55.0484539Z >>> torch.load( 2025-08-26T23:21:55.0484676Z ... "tensors.pt", 2025-08-26T23:21:55.0484888Z ... map_location=lambda storage, loc: storage, 2025-08-26T23:21:55.0485090Z ... weights_only=True, 2025-08-26T23:21:55.0485239Z ... ) 2025-08-26T23:21:55.0485379Z # Load all tensors onto GPU 1 2025-08-26T23:21:55.0485589Z >>> torch.load( 2025-08-26T23:21:55.0485739Z ... "tensors.pt", 2025-08-26T23:21:55.0485969Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-08-26T23:21:55.0488117Z ... weights_only=True, 2025-08-26T23:21:55.0488326Z ... ) # type: ignore[attr-defined] 2025-08-26T23:21:55.0488530Z # Map tensors from GPU 1 to GPU 0 2025-08-26T23:21:55.0488817Z >>> torch.load( 2025-08-26T23:21:55.0488952Z ... "tensors.pt", 2025-08-26T23:21:55.0489156Z ... map_location={"cuda:1": "cuda:0"}, 2025-08-26T23:21:55.0489366Z ... weights_only=True, 2025-08-26T23:21:55.0489510Z ... ) 2025-08-26T23:21:55.0489655Z # Load tensor from io.BytesIO object 2025-08-26T23:21:55.0489976Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-08-26T23:21:55.0490247Z >>> with open("tensor.pt", "rb") as f: 2025-08-26T23:21:55.0492118Z ... buffer = io.BytesIO(f.read()) 2025-08-26T23:21:55.0492332Z >>> torch.load(buffer, weights_only=False) 2025-08-26T23:21:55.0492576Z # Load a module with 'ascii' encoding for unpickling 2025-08-26T23:21:55.0492835Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-08-26T23:21:55.0493196Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-08-26T23:21:55.0493428Z 2025-08-26T23:21:55.0493694Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0493896Z 2025-08-26T23:21:55.0494174Z msg = Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=375. 2025-08-26T23:21:55.0494665Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.0494998Z Registers the function implementation as the fallback for the given key. 2025-08-26T23:21:55.0495226Z 2025-08-26T23:21:55.0495367Z This function only works for a library with global namespace ("_"). 2025-08-26T23:21:55.0496941Z 2025-08-26T23:21:55.0496992Z Args: 2025-08-26T23:21:55.0497242Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-08-26T23:21:55.0497551Z to register a fallthrough. 2025-08-26T23:21:55.0497897Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-08-26T23:21:55.0498245Z the dispatch key that the library was created with. 2025-08-26T23:21:55.0498642Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-08-26T23:21:55.0499134Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-08-26T23:21:55.0499378Z 2025-08-26T23:21:55.0499450Z Example:: 2025-08-26T23:21:55.0499548Z 2025-08-26T23:21:55.0499622Z >>> my_lib = Library("_", "IMPL") 2025-08-26T23:21:55.0499809Z >>> def fallback_kernel(op, *args, **kwargs): 2025-08-26T23:21:55.0500003Z >>> # Handle all autocast ops generically 2025-08-26T23:21:55.0501696Z >>> # ... 2025-08-26T23:21:55.0501862Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T23:21:55.0502089Z 2025-08-26T23:21:55.0502477Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-08-26T23:21:55.0502916Z 2025-08-26T23:21:55.0502987Z my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T23:21:55.0503205Z ^ 2025-08-26T23:21:55.0522752Z msg = Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=948. 2025-08-26T23:21:55.0523275Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.0523637Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-08-26T23:21:55.0523837Z 2025-08-26T23:21:55.0525948Z Also sometimes known as a "meta kernel", "abstract impl". 2025-08-26T23:21:55.0526116Z 2025-08-26T23:21:55.0526260Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-08-26T23:21:55.0526609Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-08-26T23:21:55.0527059Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-08-26T23:21:55.0527352Z what the properties of the output Tensors are. 2025-08-26T23:21:55.0527520Z 2025-08-26T23:21:55.0527641Z The FakeTensor implementation has the same signature as the operator. 2025-08-26T23:21:55.0527985Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-08-26T23:21:55.0528318Z implementation, assume that all Tensor inputs to the operator are 2025-08-26T23:21:55.0528640Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-08-26T23:21:55.0528901Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-08-26T23:21:55.0532173Z The FakeTensor implementation must consist of only PyTorch operations 2025-08-26T23:21:55.0532573Z (and may not directly access the storage or data of any input or 2025-08-26T23:21:55.0532920Z intermediate Tensors). 2025-08-26T23:21:55.0533019Z 2025-08-26T23:21:55.0533182Z This API may be used as a decorator (see examples). 2025-08-26T23:21:55.0533331Z 2025-08-26T23:21:55.0533431Z For a detailed guide on custom ops, please see 2025-08-26T23:21:55.0533706Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-08-26T23:21:55.0533936Z 2025-08-26T23:21:55.0533983Z Args: 2025-08-26T23:21:55.0534162Z op_name: Operator name (along with the overload) or OpOverload object. 2025-08-26T23:21:55.0534445Z func: Fake tensor implementation. 2025-08-26T23:21:55.0534692Z lib (Optional[Library]): Library to register the fake tensor to. 2025-08-26T23:21:55.0535028Z allow_override: Flag controlling if we want to override an 2025-08-26T23:21:55.0536976Z existing registered fake impl. This is by default off, 2025-08-26T23:21:55.0537251Z and will error you're trying to register a fake impl to 2025-08-26T23:21:55.0537518Z an operator that already has a fake impl. This also only 2025-08-26T23:21:55.0537855Z applies if the custom operator was not created via 2025-08-26T23:21:55.0538109Z torch.library.custom_op, as overriding and existing fake 2025-08-26T23:21:55.0538374Z impl is already allowed. 2025-08-26T23:21:55.0538489Z 2025-08-26T23:21:55.0538558Z Examples: 2025-08-26T23:21:55.0538710Z >>> import torch 2025-08-26T23:21:55.0538889Z >>> import numpy as np 2025-08-26T23:21:55.0539067Z >>> from torch import Tensor 2025-08-26T23:21:55.0539228Z >>> 2025-08-26T23:21:55.0541003Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T23:21:55.0541286Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-08-26T23:21:55.0541629Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T23:21:55.0541938Z >>> raise NotImplementedError("Implementation goes here") 2025-08-26T23:21:55.0542174Z >>> 2025-08-26T23:21:55.0542359Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-08-26T23:21:55.0542596Z >>> def _(x, weight, bias): 2025-08-26T23:21:55.0542753Z >>> assert x.dim() == 2 2025-08-26T23:21:55.0542965Z >>> assert weight.dim() == 2 2025-08-26T23:21:55.0543163Z >>> assert bias.dim() == 1 2025-08-26T23:21:55.0543358Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T23:21:55.0545072Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T23:21:55.0545299Z >>> assert x.device == weight.device 2025-08-26T23:21:55.0545463Z >>> 2025-08-26T23:21:55.0545610Z >>> return (x @ weight.t()) + bias 2025-08-26T23:21:55.0545824Z >>> 2025-08-26T23:21:55.0545977Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-08-26T23:21:55.0546242Z >>> x = torch.randn(2, 3) 2025-08-26T23:21:55.0546452Z >>> w = torch.randn(3, 3) 2025-08-26T23:21:55.0546618Z >>> b = torch.randn(3) 2025-08-26T23:21:55.0546841Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-08-26T23:21:55.0547026Z >>> 2025-08-26T23:21:55.0548675Z >>> assert y.shape == (2, 3) 2025-08-26T23:21:55.0548847Z >>> 2025-08-26T23:21:55.0549049Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T23:21:55.0549365Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-08-26T23:21:55.0549648Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-08-26T23:21:55.0549856Z >>> x_np = x.numpy(force=True) 2025-08-26T23:21:55.0550118Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T23:21:55.0550338Z >>> return torch.tensor(res, device=x.device) 2025-08-26T23:21:55.0550642Z >>> 2025-08-26T23:21:55.0552896Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-08-26T23:21:55.0553142Z >>> def _(x): 2025-08-26T23:21:55.0553339Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T23:21:55.0553564Z >>> # Since we cannot peek at the data in an fake impl, 2025-08-26T23:21:55.0553848Z >>> # we use the ctx object to construct a new symint that 2025-08-26T23:21:55.0554054Z >>> # represents the data-dependent size. 2025-08-26T23:21:55.0554283Z >>> ctx = torch.library.get_ctx() 2025-08-26T23:21:55.0554563Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T23:21:55.0554775Z >>> shape = [nnz, x.dim()] 2025-08-26T23:21:55.0555037Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T23:21:55.0555294Z >>> return result 2025-08-26T23:21:55.0555452Z >>> 2025-08-26T23:21:55.0555613Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T23:21:55.0555837Z >>> 2025-08-26T23:21:55.0556031Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-08-26T23:21:55.0556380Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-08-26T23:21:55.0556691Z >>> trace.print_readable() 2025-08-26T23:21:55.0558842Z >>> 2025-08-26T23:21:55.0559084Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-08-26T23:21:55.0559288Z 2025-08-26T23:21:55.0559333Z 2025-08-26T23:21:55.0559712Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-08-26T23:21:55.0560084Z 2025-08-26T23:21:55.0560148Z _._ = None 2025-08-26T23:21:55.0560273Z ^ 2025-08-26T23:21:55.0560715Z msg = Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1083. 2025-08-26T23:21:55.0561259Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0561534Z Register a backward formula for this custom op. 2025-08-26T23:21:55.0561680Z 2025-08-26T23:21:55.0561822Z In order for an operator to work with autograd, you need to register 2025-08-26T23:21:55.0562075Z a backward formula: 2025-08-26T23:21:55.0564325Z 1. You must tell us how to compute gradients during the backward pass 2025-08-26T23:21:55.0564620Z by providing us a "backward" function. 2025-08-26T23:21:55.0564844Z 2. If you need any values from the forward to compute gradients, you can 2025-08-26T23:21:55.0565140Z use `setup_context` to save values for backward. 2025-08-26T23:21:55.0565284Z 2025-08-26T23:21:55.0565404Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-08-26T23:21:55.0565714Z - ``grads`` is one or more gradients. The number of gradients matches 2025-08-26T23:21:55.0565936Z the number of outputs of the operator. 2025-08-26T23:21:55.0566214Z The ``ctx`` object is `the same ctx object `_ used by 2025-08-26T23:21:55.0566518Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-08-26T23:21:55.0566862Z same as :meth:`torch.autograd.Function.backward`. 2025-08-26T23:21:55.0566997Z 2025-08-26T23:21:55.0567111Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-08-26T23:21:55.0567457Z Please save quantities needed for backward onto the ``ctx`` object via 2025-08-26T23:21:55.0567830Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-08-26T23:21:55.0568150Z or assigning them as attributes of ``ctx``. If your custom op has 2025-08-26T23:21:55.0568487Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-08-26T23:21:55.0568859Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-08-26T23:21:55.0569019Z 2025-08-26T23:21:55.0570655Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-08-26T23:21:55.0571046Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-08-26T23:21:55.0571332Z not depend on or mutate global state. If you need a non-traceable backward, 2025-08-26T23:21:55.0571670Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-08-26T23:21:55.0571848Z 2025-08-26T23:21:55.0572004Z If you need different autograd behavior on different devices, then we 2025-08-26T23:21:55.0572319Z recommend creating two different custom operators, one for each device 2025-08-26T23:21:55.0572601Z that needs different behavior, and switching between them at runtime. 2025-08-26T23:21:55.0572817Z 2025-08-26T23:21:55.0572868Z Examples: 2025-08-26T23:21:55.0573004Z >>> import torch 2025-08-26T23:21:55.0573203Z >>> import numpy as np 2025-08-26T23:21:55.0573355Z >>> from torch import Tensor 2025-08-26T23:21:55.0574897Z >>> 2025-08-26T23:21:55.0575075Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-08-26T23:21:55.0575374Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-08-26T23:21:55.0575578Z >>> x_np = x.cpu().numpy() 2025-08-26T23:21:55.0575789Z >>> y_np = np.sin(x_np) 2025-08-26T23:21:55.0576022Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T23:21:55.0576211Z >>> 2025-08-26T23:21:55.0576400Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-08-26T23:21:55.0576622Z >>> x, = inputs 2025-08-26T23:21:55.0576775Z >>> ctx.save_for_backward(x) 2025-08-26T23:21:55.0576986Z >>> 2025-08-26T23:21:55.0578574Z >>> def backward(ctx, grad): 2025-08-26T23:21:55.0578770Z >>> x, = ctx.saved_tensors 2025-08-26T23:21:55.0578936Z >>> return grad * x.cos() 2025-08-26T23:21:55.0579121Z >>> 2025-08-26T23:21:55.0579281Z >>> torch.library.register_autograd( 2025-08-26T23:21:55.0579538Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-08-26T23:21:55.0579750Z ... ) 2025-08-26T23:21:55.0579861Z >>> 2025-08-26T23:21:55.0580001Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T23:21:55.0580221Z >>> y = numpy_sin(x) 2025-08-26T23:21:55.0580515Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T23:21:55.0582159Z >>> assert torch.allclose(grad_x, x.cos()) 2025-08-26T23:21:55.0582393Z >>> 2025-08-26T23:21:55.0582534Z >>> # Example with a keyword-only arg 2025-08-26T23:21:55.0582802Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T23:21:55.0583083Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-08-26T23:21:55.0583311Z >>> x_np = x.cpu().numpy() 2025-08-26T23:21:55.0583513Z >>> y_np = x_np * val 2025-08-26T23:21:55.0583693Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T23:21:55.0583946Z >>> 2025-08-26T23:21:55.0584137Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-08-26T23:21:55.0584480Z >>> ctx.val = keyword_only_inputs["val"] 2025-08-26T23:21:55.0586120Z >>> 2025-08-26T23:21:55.0586261Z >>> def backward(ctx, grad): 2025-08-26T23:21:55.0586420Z >>> return grad * ctx.val 2025-08-26T23:21:55.0586573Z >>> 2025-08-26T23:21:55.0586736Z >>> torch.library.register_autograd( 2025-08-26T23:21:55.0586944Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-08-26T23:21:55.0587216Z ... ) 2025-08-26T23:21:55.0587360Z >>> 2025-08-26T23:21:55.0587515Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T23:21:55.0587699Z >>> y = numpy_mul(x, val=3.14) 2025-08-26T23:21:55.0587939Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T23:21:55.0589573Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-08-26T23:21:55.0589798Z 2025-08-26T23:21:55.0589842Z 2025-08-26T23:21:55.0590069Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0590262Z 2025-08-26T23:21:55.0590654Z msg = Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1482. 2025-08-26T23:21:55.0591154Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.0591445Z Returns the computed kernel for a given operator and dispatch key. 2025-08-26T23:21:55.0591648Z 2025-08-26T23:21:55.0591765Z This function retrieves the kernel that would be executed for a given 2025-08-26T23:21:55.0592115Z operator and dispatch key combination. The returned SafeKernelFunction 2025-08-26T23:21:55.0592422Z can be used to call the kernel in a boxed fashion. The intended use 2025-08-26T23:21:55.0592782Z case for this function is to retrieve the original kernel for a given 2025-08-26T23:21:55.0593108Z dispatch key and then register another kernel to the same dispatch key 2025-08-26T23:21:55.0594971Z that calls into the original kernel for certain cases. 2025-08-26T23:21:55.0595116Z 2025-08-26T23:21:55.0595263Z Args: 2025-08-26T23:21:55.0595468Z op: Operator name (along with the overload) or OpOverload object 2025-08-26T23:21:55.0595767Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-08-26T23:21:55.0596109Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-08-26T23:21:55.0596485Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-08-26T23:21:55.0596635Z 2025-08-26T23:21:55.0596698Z Returns: 2025-08-26T23:21:55.0596948Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-08-26T23:21:55.0597208Z call the kernel. 2025-08-26T23:21:55.0597315Z 2025-08-26T23:21:55.0597369Z Raises: 2025-08-26T23:21:55.0597555Z RuntimeError: If the operator does not exist. 2025-08-26T23:21:55.0599122Z 2025-08-26T23:21:55.0599171Z Example: 2025-08-26T23:21:55.0599306Z >>> # Get the CPU kernel for torch.add 2025-08-26T23:21:55.0599568Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-08-26T23:21:55.0599815Z >>> 2025-08-26T23:21:55.0599946Z >>> # You can also use DispatchKey enum 2025-08-26T23:21:55.0600301Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-08-26T23:21:55.0600664Z >>> 2025-08-26T23:21:55.0600826Z >>> # Or use an OpOverload directly 2025-08-26T23:21:55.0601068Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-08-26T23:21:55.0601351Z >>> 2025-08-26T23:21:55.0603010Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-08-26T23:21:55.0603252Z >>> # Get the original kernel for torch.sin 2025-08-26T23:21:55.0603523Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-08-26T23:21:55.0603768Z >>> 2025-08-26T23:21:55.0604047Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-08-26T23:21:55.0604294Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-08-26T23:21:55.0604470Z >>> if (x < 0).any(): 2025-08-26T23:21:55.0604676Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-08-26T23:21:55.0604920Z >>> else: 2025-08-26T23:21:55.0605096Z >>> return torch.zeros_like(x) 2025-08-26T23:21:55.0605250Z >>> 2025-08-26T23:21:55.0606852Z >>> lib = torch.library.Library("aten", "IMPL") 2025-08-26T23:21:55.0607158Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-08-26T23:21:55.0607497Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T23:21:55.0607819Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-08-26T23:21:55.0608055Z >>> 2025-08-26T23:21:55.0608180Z >>> # Test the conditional behavior 2025-08-26T23:21:55.0608404Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-08-26T23:21:55.0608584Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-08-26T23:21:55.0608752Z >>> torch.sin(x_positive) 2025-08-26T23:21:55.0608948Z tensor([0., 0.]) 2025-08-26T23:21:55.0609104Z >>> torch.sin(x_mixed) 2025-08-26T23:21:55.0610776Z tensor([-0.8415, 0.9093]) 2025-08-26T23:21:55.0610935Z 2025-08-26T23:21:55.0611271Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-08-26T23:21:55.0611673Z 2025-08-26T23:21:55.0611772Z which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T23:21:55.0612009Z ^ 2025-08-26T23:21:55.0612346Z msg = Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1571. 2025-08-26T23:21:55.0612848Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0613207Z Given an operator and some sample arguments, tests if the operator is 2025-08-26T23:21:55.0613452Z registered correctly. 2025-08-26T23:21:55.0613548Z 2025-08-26T23:21:55.0613679Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-08-26T23:21:55.0613995Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-08-26T23:21:55.0615738Z and these APIs require that the functions you pass them satisfy certain 2025-08-26T23:21:55.0616078Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-08-26T23:21:55.0616377Z ``opcheck`` tests these metadata and properties. 2025-08-26T23:21:55.0616531Z 2025-08-26T23:21:55.0616594Z Concretely, we test the following: 2025-08-26T23:21:55.0616707Z 2025-08-26T23:21:55.0616805Z - test_schema: If the schema matches the implementation of 2025-08-26T23:21:55.0617109Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-08-26T23:21:55.0617428Z then we check the implementation mutates the Tensor. If the schema 2025-08-26T23:21:55.0617721Z specifies that we return a new Tensor, then we check that the 2025-08-26T23:21:55.0618096Z implementation returns a new Tensor (instead of an existing one or 2025-08-26T23:21:55.0618349Z a view of an existing one). 2025-08-26T23:21:55.0618610Z - test_autograd_registration: If the operator supports training 2025-08-26T23:21:55.0620301Z (autograd): we check that its autograd formula is registered via 2025-08-26T23:21:55.0620680Z torch.library.register_autograd or a manual registration to one 2025-08-26T23:21:55.0620970Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-08-26T23:21:55.0621268Z registrations may lead to undefined behavior. 2025-08-26T23:21:55.0621506Z - test_faketensor: If the operator has a FakeTensor kernel 2025-08-26T23:21:55.0621816Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-08-26T23:21:55.0622157Z but not sufficient) for the operator to work with PyTorch compilation 2025-08-26T23:21:55.0622486Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-08-26T23:21:55.0622830Z (also sometimes known as a meta kernel) was registered for the 2025-08-26T23:21:55.0623087Z operator and that it is correct. This test takes the result of 2025-08-26T23:21:55.0623443Z running the operator on real tensors and the result of running 2025-08-26T23:21:55.0625181Z the operator on FakeTensors and checks that they have the same 2025-08-26T23:21:55.0625458Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-08-26T23:21:55.0625727Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-08-26T23:21:55.0626026Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-08-26T23:21:55.0626320Z This checks that the outputs (and gradients, if applicable) are the 2025-08-26T23:21:55.0626661Z same under eager-mode PyTorch and torch.compile. 2025-08-26T23:21:55.0626910Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-08-26T23:21:55.0627199Z other things it tests are that the operator supports 2025-08-26T23:21:55.0627483Z functionalization and that the backward pass (if it exists) also 2025-08-26T23:21:55.0627753Z supports FakeTensor and functionalization. 2025-08-26T23:21:55.0627875Z 2025-08-26T23:21:55.0628009Z For best results, please call ``opcheck`` multiple times with a 2025-08-26T23:21:55.0629770Z representative set of inputs. If your operator supports 2025-08-26T23:21:55.0630094Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-08-26T23:21:55.0630485Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-08-26T23:21:55.0630786Z use ``opcheck`` with inputs on all supported devices. 2025-08-26T23:21:55.0630968Z 2025-08-26T23:21:55.0631015Z Args: 2025-08-26T23:21:55.0631201Z op: The operator. Must either be a function decorated with 2025-08-26T23:21:55.0631556Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-08-26T23:21:55.0631888Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-08-26T23:21:55.0632120Z args: The args to the operator 2025-08-26T23:21:55.0632296Z kwargs: The kwargs to the operator 2025-08-26T23:21:55.0632582Z test_utils: Tests that we should run. Default: all of them. 2025-08-26T23:21:55.0634284Z Example: ("test_schema", "test_faketensor") 2025-08-26T23:21:55.0634617Z raise_exception: If we should raise an exception on the first 2025-08-26T23:21:55.0634892Z error. If False, we will return a dict with information 2025-08-26T23:21:55.0635097Z on if each test passed or not. 2025-08-26T23:21:55.0635369Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-08-26T23:21:55.0635672Z If specified ``atol`` must also be specified. 2025-08-26T23:21:55.0635909Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T23:21:55.0636180Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T23:21:55.0636483Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-08-26T23:21:55.0636814Z If specified ``rtol`` must also be specified. 2025-08-26T23:21:55.0637050Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T23:21:55.0638778Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T23:21:55.0638963Z 2025-08-26T23:21:55.0639022Z .. warning:: 2025-08-26T23:21:55.0639096Z 2025-08-26T23:21:55.0639214Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-08-26T23:21:55.0639548Z opcheck tests if your usage of torch.library APIs is correct while 2025-08-26T23:21:55.0639917Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-08-26T23:21:55.0640235Z mathematically correct. Use both to test custom ops that support 2025-08-26T23:21:55.0640568Z gradient computation. 2025-08-26T23:21:55.0640705Z 2025-08-26T23:21:55.0640754Z Example: 2025-08-26T23:21:55.0640823Z 2025-08-26T23:21:55.0640902Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:55.0641208Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T23:21:55.0642979Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-08-26T23:21:55.0643223Z >>> x_np = x.numpy(force=True) 2025-08-26T23:21:55.0643427Z >>> z_np = x_np * y 2025-08-26T23:21:55.0643597Z >>> return torch.from_numpy(z_np).to(x.device) 2025-08-26T23:21:55.0643843Z >>> 2025-08-26T23:21:55.0643965Z >>> @numpy_mul.register_fake 2025-08-26T23:21:55.0644168Z >>> def _(x, y): 2025-08-26T23:21:55.0644323Z >>> return torch.empty_like(x) 2025-08-26T23:21:55.0644524Z >>> 2025-08-26T23:21:55.0644660Z >>> def setup_context(ctx, inputs, output): 2025-08-26T23:21:55.0644902Z >>> y, = inputs 2025-08-26T23:21:55.0646536Z >>> ctx.y = y 2025-08-26T23:21:55.0646672Z >>> 2025-08-26T23:21:55.0646810Z >>> def backward(ctx, grad): 2025-08-26T23:21:55.0646998Z >>> return grad * ctx.y, None 2025-08-26T23:21:55.0647194Z >>> 2025-08-26T23:21:55.0647379Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-08-26T23:21:55.0647653Z >>> 2025-08-26T23:21:55.0647769Z >>> sample_inputs = [ 2025-08-26T23:21:55.0647925Z >>> (torch.randn(3), 3.14), 2025-08-26T23:21:55.0648100Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-08-26T23:21:55.0648349Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-08-26T23:21:55.0650035Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-08-26T23:21:55.0650335Z >>> ] 2025-08-26T23:21:55.0650564Z >>> 2025-08-26T23:21:55.0650691Z >>> for args in sample_inputs: 2025-08-26T23:21:55.0650904Z >>> torch.library.opcheck(numpy_mul, args) 2025-08-26T23:21:55.0651033Z 2025-08-26T23:21:55.0651080Z 2025-08-26T23:21:55.0651334Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0651532Z 2025-08-26T23:21:55.0892816Z msg = Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_prims_common/__init__.py line=1877. 2025-08-26T23:21:55.0893433Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0893786Z Computes the minimum storage size to hold the given tensor geometry. 2025-08-26T23:21:55.0894022Z 2025-08-26T23:21:55.0894093Z Example 2025-08-26T23:21:55.0896410Z ======= 2025-08-26T23:21:55.0896484Z 2025-08-26T23:21:55.0896641Z This is the size of a newly allocated tensor's storage, in units of elements 2025-08-26T23:21:55.0896866Z 2025-08-26T23:21:55.0896928Z >>> t = torch.empty((10, 20)) 2025-08-26T23:21:55.0897211Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-08-26T23:21:55.0897452Z 200 2025-08-26T23:21:55.0897516Z 2025-08-26T23:21:55.0897594Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:21:55.0897787Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-08-26T23:21:55.0898037Z >>> size = compute_required_storage_length( 2025-08-26T23:21:55.0898278Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-08-26T23:21:55.0898478Z ... ) 2025-08-26T23:21:55.0898597Z >>> size == t.storage().size() 2025-08-26T23:21:55.0898790Z True 2025-08-26T23:21:55.0898868Z 2025-08-26T23:21:55.0899015Z A valid tensor may have a larger storage size, but never smaller 2025-08-26T23:21:55.0899173Z 2025-08-26T23:21:55.0899234Z >>> slice = torch.empty(100)[20:40] 2025-08-26T23:21:55.0901124Z >>> slice.storage().size() 2025-08-26T23:21:55.0901274Z 100 2025-08-26T23:21:55.0901338Z 2025-08-26T23:21:55.0901425Z >>> compute_required_storage_length( 2025-08-26T23:21:55.0901668Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-08-26T23:21:55.0901852Z ... ) 2025-08-26T23:21:55.0901976Z 40 2025-08-26T23:21:55.0902067Z 2025-08-26T23:21:55.0902115Z 2025-08-26T23:21:55.0902385Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0902642Z 2025-08-26T23:21:55.0910756Z msg = Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py line=202. 2025-08-26T23:21:55.0911275Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0913580Z Return the sum of each row of the given sparse tensor. 2025-08-26T23:21:55.0913835Z 2025-08-26T23:21:55.0913966Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-08-26T23:21:55.0914270Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-08-26T23:21:55.0914717Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-08-26T23:21:55.0915033Z returns a dense tensor instead of a sparse tensor. 2025-08-26T23:21:55.0915162Z 2025-08-26T23:21:55.0915293Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-08-26T23:21:55.0915648Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-08-26T23:21:55.0915802Z 2025-08-26T23:21:55.0915923Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-08-26T23:21:55.0916320Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-08-26T23:21:55.0916566Z 2025-08-26T23:21:55.0916635Z Args: 2025-08-26T23:21:55.0918531Z input (Tensor): the input sparse tensor 2025-08-26T23:21:55.0918874Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-08-26T23:21:55.0919185Z over all dims. 2025-08-26T23:21:55.0919469Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-08-26T23:21:55.0919765Z Default: dtype of :attr:`input`. 2025-08-26T23:21:55.0919905Z 2025-08-26T23:21:55.0919959Z Example:: 2025-08-26T23:21:55.0920030Z 2025-08-26T23:21:55.0920077Z >>> nnz = 3 2025-08-26T23:21:55.0920213Z >>> dims = [5, 5, 2, 3] 2025-08-26T23:21:55.0920523Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-08-26T23:21:55.0920801Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-08-26T23:21:55.0921046Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-08-26T23:21:55.0922740Z >>> size = torch.Size(dims) 2025-08-26T23:21:55.0922972Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:55.0923197Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-08-26T23:21:55.0923368Z >>> S 2025-08-26T23:21:55.0923532Z tensor(indices=tensor([[2, 0, 3], 2025-08-26T23:21:55.0923739Z [2, 4, 1]]), 2025-08-26T23:21:55.0923945Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-08-26T23:21:55.0924181Z [ 0.3411, 0.0918, -0.2312]], 2025-08-26T23:21:55.0924294Z 2025-08-26T23:21:55.0924357Z [[ 0.5348, 0.0634, -2.0494], 2025-08-26T23:21:55.0924539Z [-0.7125, -1.0646, 2.1844]], 2025-08-26T23:21:55.0924697Z 2025-08-26T23:21:55.0924778Z [[ 0.1276, 0.1874, -0.6334], 2025-08-26T23:21:55.0926483Z [-1.9682, -0.5340, 0.7483]]]), 2025-08-26T23:21:55.0926713Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-08-26T23:21:55.0926868Z 2025-08-26T23:21:55.0926988Z # when sum over only part of sparse_dims, return a sparse tensor 2025-08-26T23:21:55.0927283Z >>> torch.sparse.sum(S, [1, 3]) 2025-08-26T23:21:55.0927498Z tensor(indices=tensor([[0, 2, 3]]), 2025-08-26T23:21:55.0927674Z values=tensor([[-1.4512, 0.4073], 2025-08-26T23:21:55.0927914Z [-0.8901, 0.2017], 2025-08-26T23:21:55.0928076Z [-0.3183, -1.7539]]), 2025-08-26T23:21:55.0928299Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-08-26T23:21:55.0928447Z 2025-08-26T23:21:55.0928551Z # when sum over all sparse dim, return a dense tensor 2025-08-26T23:21:55.0928771Z # with summed dims squeezed 2025-08-26T23:21:55.0930539Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-08-26T23:21:55.0930742Z tensor([-2.6596, -1.1450]) 2025-08-26T23:21:55.0930894Z 2025-08-26T23:21:55.0931126Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0931364Z 2025-08-26T23:21:55.0931740Z msg = Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py line=550. 2025-08-26T23:21:55.0932239Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.0932554Z Decorate function, to extend gradcheck for sparse tensors. 2025-08-26T23:21:55.0932755Z 2025-08-26T23:21:55.0932866Z Decorator for torch.autograd.gradcheck or its functools.partial 2025-08-26T23:21:55.0933153Z variants that extends the gradcheck function with support to input 2025-08-26T23:21:55.0933465Z functions that operate on or/and return sparse tensors. 2025-08-26T23:21:55.0933627Z 2025-08-26T23:21:55.0933773Z The specified gradcheck function itself is guaranteed to operate 2025-08-26T23:21:55.0935602Z on strided tensors only. 2025-08-26T23:21:55.0935699Z 2025-08-26T23:21:55.0935754Z For example: 2025-08-26T23:21:55.0935876Z 2025-08-26T23:21:55.0936030Z >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck) 2025-08-26T23:21:55.0936255Z >>> x = ( 2025-08-26T23:21:55.0936477Z ... torch.tensor([[0, 1], [2, 3]], dtype=torch.float64) 2025-08-26T23:21:55.0936706Z ... .to_sparse_coo() 2025-08-26T23:21:55.0936876Z ... .requires_grad_(True) 2025-08-26T23:21:55.0937083Z ... ) 2025-08-26T23:21:55.0937214Z >>> gradcheck(lambda x: x.to_sparse_csr(), x) 2025-08-26T23:21:55.0937415Z True 2025-08-26T23:21:55.0937533Z 2025-08-26T23:21:55.0939263Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.0939442Z 2025-08-26T23:21:55.1031937Z msg = Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/__init__.py line=434. 2025-08-26T23:21:55.1032457Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.1032729Z Retrieves the CUDA runtime API module. 2025-08-26T23:21:55.1032881Z 2025-08-26T23:21:55.1032884Z 2025-08-26T23:21:55.1033051Z This function initializes the CUDA runtime environment if it is not already 2025-08-26T23:21:55.1033401Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-08-26T23:21:55.1033729Z runtime API module provides access to various CUDA runtime functions. 2025-08-26T23:21:55.1033934Z 2025-08-26T23:21:55.1033981Z Args: 2025-08-26T23:21:55.1034130Z ``None`` 2025-08-26T23:21:55.1034217Z 2025-08-26T23:21:55.1034263Z Returns: 2025-08-26T23:21:55.1036481Z module: The CUDA runtime API module (_cudart). 2025-08-26T23:21:55.1036650Z 2025-08-26T23:21:55.1036710Z Raises: 2025-08-26T23:21:55.1036936Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-08-26T23:21:55.1037422Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-08-26T23:21:55.1037664Z 2025-08-26T23:21:55.1037755Z Example of CUDA operations with profiling: 2025-08-26T23:21:55.1038048Z >>> import torch 2025-08-26T23:21:55.1038230Z >>> from torch.cuda import cudart, check_error 2025-08-26T23:21:55.1038476Z >>> import os 2025-08-26T23:21:55.1038604Z >>> 2025-08-26T23:21:55.1038753Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-08-26T23:21:55.1038941Z >>> 2025-08-26T23:21:55.1039108Z >>> def perform_cuda_operations_with_streams(): 2025-08-26T23:21:55.1039331Z >>> stream = torch.cuda.Stream() 2025-08-26T23:21:55.1039568Z >>> with torch.cuda.stream(stream): 2025-08-26T23:21:55.1039826Z >>> x = torch.randn(100, 100, device='cuda') 2025-08-26T23:21:55.1040062Z >>> y = torch.randn(100, 100, device='cuda') 2025-08-26T23:21:55.1040258Z >>> z = torch.mul(x, y) 2025-08-26T23:21:55.1040513Z >>> return z 2025-08-26T23:21:55.1040694Z >>> 2025-08-26T23:21:55.1042363Z >>> torch.cuda.synchronize() 2025-08-26T23:21:55.1042550Z >>> print("====== Start nsys profiling ======") 2025-08-26T23:21:55.1042792Z >>> check_error(cudart().cudaProfilerStart()) 2025-08-26T23:21:55.1043005Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-08-26T23:21:55.1043284Z >>> result = perform_cuda_operations_with_streams() 2025-08-26T23:21:55.1043486Z >>> print("CUDA operations completed.") 2025-08-26T23:21:55.1043738Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-08-26T23:21:55.1043981Z >>> print("====== End nsys profiling ======") 2025-08-26T23:21:55.1044126Z 2025-08-26T23:21:55.1044260Z To run this example and save the profiling information, execute: 2025-08-26T23:21:55.1044638Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T23:21:55.1044913Z 2025-08-26T23:21:55.1045041Z This command profiles the CUDA operations in the provided script and saves 2025-08-26T23:21:55.1046824Z the profiling information to a file named `trace_name.prof`. 2025-08-26T23:21:55.1047211Z The `--profile-from-start off` option ensures that profiling starts only 2025-08-26T23:21:55.1047468Z after the `cudaProfilerStart` call in the script. 2025-08-26T23:21:55.1047762Z The `--csv` and `--print-summary` options format the profiling output as a 2025-08-26T23:21:55.1048074Z CSV file and print a summary, respectively. 2025-08-26T23:21:55.1048318Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-08-26T23:21:55.1048667Z overwrite of the output file if it already exists. 2025-08-26T23:21:55.1048842Z 2025-08-26T23:21:55.1049307Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-08-26T23:21:55.1049773Z 2025-08-26T23:21:55.1049961Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T23:21:55.1051823Z ^ 2025-08-26T23:21:55.1443549Z msg = Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py line=101. 2025-08-26T23:21:55.1444123Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.1444337Z 2025-08-26T23:21:55.1444507Z Append the given callback function to this ``Future``, which will be run 2025-08-26T23:21:55.1444829Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-08-26T23:21:55.1445169Z the same ``Future``, but the order in which they will be executed cannot 2025-08-26T23:21:55.1445462Z be guaranteed (to enforce a certain order consider chaining: 2025-08-26T23:21:55.1445779Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-08-26T23:21:55.1446072Z is the reference to this ``Future``. The callback function can use the 2025-08-26T23:21:55.1446376Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-08-26T23:21:55.1446804Z already completed, the given callback will be run immediately inline. 2025-08-26T23:21:55.1450027Z 2025-08-26T23:21:55.1450169Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-08-26T23:21:55.1450685Z callback might be invoked while the async kernels that are populating 2025-08-26T23:21:55.1450992Z those tensors haven't yet finished executing on the device. However, the 2025-08-26T23:21:55.1451345Z callback will be invoked with some dedicated streams set as current 2025-08-26T23:21:55.1451728Z (fetched from a global pool) which will be synchronized with those 2025-08-26T23:21:55.1452035Z kernels. Hence any operation performed by the callback on these tensors 2025-08-26T23:21:55.1452378Z will be scheduled on the device after the kernels complete. In other 2025-08-26T23:21:55.1452656Z words, as long as the callback doesn't switch streams, it can safely 2025-08-26T23:21:55.1453025Z manipulate the result without any additional synchronization. This is 2025-08-26T23:21:55.1453274Z similar to the non-blocking behavior of :meth:`wait`. 2025-08-26T23:21:55.1453449Z 2025-08-26T23:21:55.1455503Z Similarly, if the callback returns a value that contains tensors that 2025-08-26T23:21:55.1455816Z reside on a GPU, it can do so even if the kernels that are producing 2025-08-26T23:21:55.1456143Z these tensors are still running on the device, as long as the callback 2025-08-26T23:21:55.1456432Z didn't change streams during its execution. If one wants to change 2025-08-26T23:21:55.1456756Z streams, one must be careful to re-synchronize them with the original 2025-08-26T23:21:55.1457067Z streams, that is, those that were current when the callback was invoked. 2025-08-26T23:21:55.1457286Z 2025-08-26T23:21:55.1457335Z Args: 2025-08-26T23:21:55.1457557Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-08-26T23:21:55.1457795Z the only argument. 2025-08-26T23:21:55.1457910Z 2025-08-26T23:21:55.1457962Z Returns: 2025-08-26T23:21:55.1458147Z A new ``Future`` object that holds the return value of the 2025-08-26T23:21:55.1460034Z ``callback`` and will be marked as completed when the given 2025-08-26T23:21:55.1460312Z ``callback`` finishes. 2025-08-26T23:21:55.1460491Z 2025-08-26T23:21:55.1460591Z .. note:: Note that if the callback function throws, either 2025-08-26T23:21:55.1460924Z through the original future being completed with an exception and 2025-08-26T23:21:55.1461206Z calling ``fut.wait()``, or through other code in the callback, the 2025-08-26T23:21:55.1461505Z future returned by ``then`` will be marked appropriately with the 2025-08-26T23:21:55.1461774Z encountered error. However, if this callback later completes 2025-08-26T23:21:55.1462099Z additional futures, those futures are not marked as completed with 2025-08-26T23:21:55.1462406Z an error and the user is responsible for handling completion/waiting 2025-08-26T23:21:55.1462674Z on those futures independently. 2025-08-26T23:21:55.1462804Z 2025-08-26T23:21:55.1462888Z Example:: 2025-08-26T23:21:55.1464375Z 2025-08-26T23:21:55.1464465Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T23:21:55.1464696Z >>> def callback(fut): 2025-08-26T23:21:55.1464862Z ... print(f"RPC return value is {fut.wait()}.") 2025-08-26T23:21:55.1465108Z >>> fut = torch.futures.Future() 2025-08-26T23:21:55.1465319Z >>> # The inserted callback will print the return value when 2025-08-26T23:21:55.1465549Z >>> # receiving the response from "worker1" 2025-08-26T23:21:55.1465780Z >>> cb_fut = fut.then(callback) 2025-08-26T23:21:55.1465940Z >>> chain_cb_fut = cb_fut.then( 2025-08-26T23:21:55.1466176Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-08-26T23:21:55.1466405Z ... ) 2025-08-26T23:21:55.1466558Z >>> fut.set_result(5) 2025-08-26T23:21:55.1468183Z RPC return value is 5. 2025-08-26T23:21:55.1468340Z Chained cb done. None 2025-08-26T23:21:55.1468469Z 2025-08-26T23:21:55.1468657Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.1468662Z 2025-08-26T23:21:55.1469030Z msg = Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py line=211. 2025-08-26T23:21:55.1469165Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.1469169Z 2025-08-26T23:21:55.1469298Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-08-26T23:21:55.1469460Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-08-26T23:21:55.1469546Z cannot be marked completed twice. 2025-08-26T23:21:55.1469549Z 2025-08-26T23:21:55.1469661Z If the result contains tensors that reside on GPUs, this method can be 2025-08-26T23:21:55.1469777Z called even if the asynchronous kernels that are populating those 2025-08-26T23:21:55.1469968Z tensors haven't yet completed running on the device, provided that the 2025-08-26T23:21:55.1470091Z streams on which those kernels were enqueued are set as the current ones 2025-08-26T23:21:55.1470200Z when this method is called. Put simply, it's safe to call this method 2025-08-26T23:21:55.1470321Z immediately after launching those kernels, without any additional 2025-08-26T23:21:55.1470537Z synchronization, as long as one doesn't change streams in between. This 2025-08-26T23:21:55.1470695Z method will record events on all the relevant current streams and will 2025-08-26T23:21:55.1470802Z use them to ensure proper scheduling for all the consumers of this 2025-08-26T23:21:55.1470862Z ``Future``. 2025-08-26T23:21:55.1470865Z 2025-08-26T23:21:55.1472400Z Args: 2025-08-26T23:21:55.1472510Z result (object): the result object of this ``Future``. 2025-08-26T23:21:55.1472514Z 2025-08-26T23:21:55.1472598Z Example:: 2025-08-26T23:21:55.1472601Z 2025-08-26T23:21:55.1472692Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T23:21:55.1472772Z >>> import threading 2025-08-26T23:21:55.1472823Z >>> import time 2025-08-26T23:21:55.1472935Z >>> def slow_set_future(fut, value): 2025-08-26T23:21:55.1473004Z ... time.sleep(0.5) 2025-08-26T23:21:55.1473097Z ... fut.set_result(value) 2025-08-26T23:21:55.1473158Z >>> fut = torch.futures.Future() 2025-08-26T23:21:55.1473237Z >>> t = threading.Thread( 2025-08-26T23:21:55.1473294Z ... target=slow_set_future, 2025-08-26T23:21:55.1473355Z ... args=(fut, torch.ones(2) * 3) 2025-08-26T23:21:55.1473401Z ... ) 2025-08-26T23:21:55.1473449Z >>> t.start() 2025-08-26T23:21:55.1473507Z >>> print(fut.wait()) 2025-08-26T23:21:55.1473560Z tensor([3., 3.]) 2025-08-26T23:21:55.1473625Z >>> t.join() 2025-08-26T23:21:55.1473629Z 2025-08-26T23:21:55.1473792Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.1473796Z 2025-08-26T23:21:55.1504197Z msg = Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py line=66. 2025-08-26T23:21:55.1504343Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.1506434Z Check if the current accelerator is available at runtime: it was build, all the 2025-08-26T23:21:55.1506555Z required drivers are available and at least one device is visible. 2025-08-26T23:21:55.1506633Z See :ref:`accelerator` for details. 2025-08-26T23:21:55.1506636Z 2025-08-26T23:21:55.1506696Z Returns: 2025-08-26T23:21:55.1506889Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-08-26T23:21:55.1506892Z 2025-08-26T23:21:55.1507021Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-08-26T23:21:55.1507174Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-08-26T23:21:55.1507341Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-08-26T23:21:55.1507492Z :ref:`multiprocessing-poison-fork-note`. 2025-08-26T23:21:55.1507495Z 2025-08-26T23:21:55.1507549Z Example:: 2025-08-26T23:21:55.1507552Z 2025-08-26T23:21:55.1507750Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:21:55.1507797Z 2025-08-26T23:21:55.1508119Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-08-26T23:21:55.1508122Z 2025-08-26T23:21:55.1508301Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:21:55.1508364Z ^ 2025-08-26T23:21:55.1510900Z msg = Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py line=212. 2025-08-26T23:21:55.1511088Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.1511200Z Wait for all kernels in all streams on the given device to complete. 2025-08-26T23:21:55.1511203Z 2025-08-26T23:21:55.1511253Z Args: 2025-08-26T23:21:55.1511413Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-08-26T23:21:55.1511532Z the current :ref:`accelerator` device type. If not given, 2025-08-26T23:21:55.1513447Z use :func:`torch.accelerator.current_device_index` by default. 2025-08-26T23:21:55.1513452Z 2025-08-26T23:21:55.1513652Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-08-26T23:21:55.1513662Z 2025-08-26T23:21:55.1513732Z Example:: 2025-08-26T23:21:55.1513735Z 2025-08-26T23:21:55.1513811Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:55.1513949Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:21:55.1514026Z >>> start_event = torch.Event(enable_timing=True) 2025-08-26T23:21:55.1514142Z >>> end_event = torch.Event(enable_timing=True) 2025-08-26T23:21:55.1514225Z >>> start_event.record() 2025-08-26T23:21:55.1514358Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-08-26T23:21:55.1514516Z >>> sum = torch.sum(tensor) 2025-08-26T23:21:55.1514580Z >>> end_event.record() 2025-08-26T23:21:55.1514655Z >>> torch.accelerator.synchronize() 2025-08-26T23:21:55.1514773Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-08-26T23:21:55.1514829Z 2025-08-26T23:21:55.1515166Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-08-26T23:21:55.1515169Z 2025-08-26T23:21:55.1515346Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:21:55.1515411Z ^ 2025-08-26T23:21:55.1522974Z msg = Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/mps/__init__.py line=145. 2025-08-26T23:21:55.1523123Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.1523280Z Compiles compute shader from source and allows one to invoke kernels 2025-08-26T23:21:55.1525117Z defined there from the comfort of Python runtime 2025-08-26T23:21:55.1525177Z Example:: 2025-08-26T23:21:55.1525180Z 2025-08-26T23:21:55.1525263Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-08-26T23:21:55.1525341Z >>> lib = torch.mps.compile_shader( 2025-08-26T23:21:55.1525593Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-08-26T23:21:55.1525640Z ... ) 2025-08-26T23:21:55.1525708Z >>> x = torch.zeros(16, device="mps") 2025-08-26T23:21:55.1525767Z >>> lib.full(x, 3.14) 2025-08-26T23:21:55.1525905Z 2025-08-26T23:21:55.1526056Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.1526059Z 2025-08-26T23:21:55.1730536Z msg = Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/apis.py line=39. 2025-08-26T23:21:55.1730768Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.1730791Z 2025-08-26T23:21:55.1731045Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-08-26T23:21:55.1731180Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-08-26T23:21:55.1731348Z pushes the map into PyTorch operations called by ``func``, effectively 2025-08-26T23:21:55.1731461Z vectorizing those operations. 2025-08-26T23:21:55.1731464Z 2025-08-26T23:21:55.1731572Z vmap is useful for handling batch dimensions: one can write a function 2025-08-26T23:21:55.1731725Z ``func`` that runs on examples and then lift it to a function that can 2025-08-26T23:21:55.1734480Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-08-26T23:21:55.1734603Z compute batched gradients when composed with autograd. 2025-08-26T23:21:55.1734607Z 2025-08-26T23:21:55.1734657Z .. note:: 2025-08-26T23:21:55.1734757Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-08-26T23:21:55.1734827Z convenience. Use whichever one you'd like. 2025-08-26T23:21:55.1734830Z 2025-08-26T23:21:55.1734901Z Args: 2025-08-26T23:21:55.1735034Z func (function): A Python function that takes one or more arguments. 2025-08-26T23:21:55.1735096Z Must return one or more Tensors. 2025-08-26T23:21:55.1735208Z in_dims (int or nested structure): Specifies which dimension of the 2025-08-26T23:21:55.1735344Z inputs should be mapped over. ``in_dims`` should have a 2025-08-26T23:21:55.1735474Z structure like the inputs. If the ``in_dim`` for a particular 2025-08-26T23:21:55.1735588Z input is None, then that indicates there is no map dimension. 2025-08-26T23:21:55.1735695Z Default: 0. 2025-08-26T23:21:55.1735845Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-08-26T23:21:55.1735962Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-08-26T23:21:55.1736060Z it should have one element per output. Default: 0. 2025-08-26T23:21:55.1736162Z randomness (str): Specifies whether the randomness in this 2025-08-26T23:21:55.1736276Z vmap should be the same or different across batches. If 'different', 2025-08-26T23:21:55.1736398Z the randomness for each batch will be different. If 'same', the 2025-08-26T23:21:55.1736538Z randomness will be the same across batches. If 'error', any calls to 2025-08-26T23:21:55.1744127Z random functions will error. Default: 'error'. WARNING: this flag 2025-08-26T23:21:55.1744255Z only applies to random PyTorch operations and does not apply to 2025-08-26T23:21:55.1744331Z Python's random module or numpy randomness. 2025-08-26T23:21:55.1744461Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-08-26T23:21:55.1744593Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-08-26T23:21:55.1744740Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-08-26T23:21:55.1744891Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-08-26T23:21:55.1744897Z 2025-08-26T23:21:55.1744980Z Returns: 2025-08-26T23:21:55.1745142Z Returns a new "batched" function. It takes the same inputs as 2025-08-26T23:21:55.1745253Z ``func``, except each input has an extra dimension at the index 2025-08-26T23:21:55.1745403Z specified by ``in_dims``. It takes returns the same outputs as 2025-08-26T23:21:55.1745514Z ``func``, except each output has an extra dimension at the index 2025-08-26T23:21:55.1745584Z specified by ``out_dims``. 2025-08-26T23:21:55.1745662Z 2025-08-26T23:21:55.1745731Z .. warning: 2025-08-26T23:21:55.1745843Z :func:`vmap` works best with functional-style code. Please do not 2025-08-26T23:21:55.1745966Z perform any side-effects in ``func``, with the exception of 2025-08-26T23:21:55.1746138Z in-place PyTorch operations. Examples of side-effects include mutating 2025-08-26T23:21:55.1746276Z Python data structures and assigning values to variables not captured 2025-08-26T23:21:55.1746329Z in ``func``. 2025-08-26T23:21:55.1746378Z 2025-08-26T23:21:55.1746505Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-08-26T23:21:55.1746654Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-08-26T23:21:55.1746812Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-08-26T23:21:55.1746815Z 2025-08-26T23:21:55.1746908Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:21:55.1747039Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-08-26T23:21:55.1747146Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T23:21:55.1747202Z >>> batched_dot(x, y) 2025-08-26T23:21:55.1747205Z 2025-08-26T23:21:55.1747367Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-08-26T23:21:55.1747427Z model authoring experience. 2025-08-26T23:21:55.1747430Z 2025-08-26T23:21:55.1747498Z >>> batch_size, feature_size = 3, 5 2025-08-26T23:21:55.1747596Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T23:21:55.1747656Z >>> 2025-08-26T23:21:55.1749845Z >>> def model(feature_vec): 2025-08-26T23:21:55.1749926Z >>> # Very simple linear model with activation 2025-08-26T23:21:55.1750043Z >>> return feature_vec.dot(weights).relu() 2025-08-26T23:21:55.1750088Z >>> 2025-08-26T23:21:55.1750170Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T23:21:55.1750243Z >>> result = torch.vmap(model)(examples) 2025-08-26T23:21:55.1750248Z 2025-08-26T23:21:55.1750643Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-08-26T23:21:55.1750785Z or impossible to batch. One example is higher-order gradient computation. 2025-08-26T23:21:55.1750913Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-08-26T23:21:55.1751059Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-08-26T23:21:55.1751200Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-08-26T23:21:55.1751372Z we can vectorize the whole computation, computing the Jacobian in a single 2025-08-26T23:21:55.1751460Z call to ``autograd.grad``. 2025-08-26T23:21:55.1751488Z 2025-08-26T23:21:55.1751554Z >>> # Setup 2025-08-26T23:21:55.1751610Z >>> N = 5 2025-08-26T23:21:55.1751662Z >>> f = lambda x: x**2 2025-08-26T23:21:55.1751734Z >>> x = torch.randn(N, requires_grad=True) 2025-08-26T23:21:55.1751781Z >>> y = f(x) 2025-08-26T23:21:55.1751866Z >>> I_N = torch.eye(N) 2025-08-26T23:21:55.1751915Z >>> 2025-08-26T23:21:55.1751981Z >>> # Sequential approach 2025-08-26T23:21:55.1753814Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-08-26T23:21:55.1753883Z >>> for v in I_N.unbind()] 2025-08-26T23:21:55.1753951Z >>> jacobian = torch.stack(jacobian_rows) 2025-08-26T23:21:55.1754002Z >>> 2025-08-26T23:21:55.1754066Z >>> # vectorized gradient computation 2025-08-26T23:21:55.1754149Z >>> def get_vjp(v): 2025-08-26T23:21:55.1754221Z >>> return torch.autograd.grad(y, x, v) 2025-08-26T23:21:55.1754317Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-08-26T23:21:55.1754321Z 2025-08-26T23:21:55.1754530Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-08-26T23:21:55.1754534Z 2025-08-26T23:21:55.1754627Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:21:55.1754699Z >>> batched_dot = torch.vmap( 2025-08-26T23:21:55.1754820Z ... torch.vmap(torch.dot) 2025-08-26T23:21:55.1754886Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-08-26T23:21:55.1754961Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-08-26T23:21:55.1755033Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-08-26T23:21:55.1755038Z 2025-08-26T23:21:55.1755193Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-08-26T23:21:55.1755275Z the dimension that each inputs are batched along as 2025-08-26T23:21:55.1755278Z 2025-08-26T23:21:55.1755392Z >>> torch.dot # [N], [N] -> [] 2025-08-26T23:21:55.1755505Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-08-26T23:21:55.1755574Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T23:21:55.1755633Z >>> batched_dot( 2025-08-26T23:21:55.1755709Z ... x, y 2025-08-26T23:21:55.1755855Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-08-26T23:21:55.1755858Z 2025-08-26T23:21:55.1755991Z If there are multiple inputs each of which is batched along different dimensions, 2025-08-26T23:21:55.1756094Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-08-26T23:21:55.1756097Z 2025-08-26T23:21:55.1756158Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:21:55.1756296Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-08-26T23:21:55.1757934Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T23:21:55.1758004Z >>> batched_dot( 2025-08-26T23:21:55.1758067Z ... x, y 2025-08-26T23:21:55.1758166Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-08-26T23:21:55.1758169Z 2025-08-26T23:21:55.1758298Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-08-26T23:21:55.1758361Z matching the shape of the input: 2025-08-26T23:21:55.1758365Z 2025-08-26T23:21:55.1758447Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-08-26T23:21:55.1758515Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T23:21:55.1758632Z >>> input = {"x": x, "y": y} 2025-08-26T23:21:55.1758725Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-08-26T23:21:55.1758783Z >>> batched_dot(input) 2025-08-26T23:21:55.1758786Z 2025-08-26T23:21:55.1758982Z By default, the output is batched along the first dimension. However, it can be batched 2025-08-26T23:21:55.1759059Z along any dimension by using ``out_dims`` 2025-08-26T23:21:55.1759063Z 2025-08-26T23:21:55.1759119Z >>> f = lambda x: x**2 2025-08-26T23:21:55.1759176Z >>> x = torch.randn(2, 5) 2025-08-26T23:21:55.1759245Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-08-26T23:21:55.1759301Z >>> batched_pow(x) # [5, 2] 2025-08-26T23:21:55.1759304Z 2025-08-26T23:21:55.1759463Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-08-26T23:21:55.1759543Z accept kwargs 2025-08-26T23:21:55.1759545Z 2025-08-26T23:21:55.1759606Z >>> x = torch.randn([2, 5]) 2025-08-26T23:21:55.1759691Z >>> def fn(x, scale=4.): 2025-08-26T23:21:55.1761404Z >>> return x * scale 2025-08-26T23:21:55.1761456Z >>> 2025-08-26T23:21:55.1761522Z >>> batched_pow = torch.vmap(fn) 2025-08-26T23:21:55.1761605Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-08-26T23:21:55.1761760Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-08-26T23:21:55.1761763Z 2025-08-26T23:21:55.1761843Z .. note:: 2025-08-26T23:21:55.1761962Z vmap does not provide general autobatching or handle variable-length 2025-08-26T23:21:55.1762022Z sequences out of the box. 2025-08-26T23:21:55.1762025Z 2025-08-26T23:21:55.1762160Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.1762164Z 2025-08-26T23:21:55.1762468Z msg = Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/apis.py line=306. 2025-08-26T23:21:55.1762682Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.1762834Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-08-26T23:21:55.1762959Z input(s) specified by ``argnums``. This operator can be nested to 2025-08-26T23:21:55.1763022Z compute higher-order gradients. 2025-08-26T23:21:55.1763025Z 2025-08-26T23:21:55.1763070Z Args: 2025-08-26T23:21:55.1763210Z func (Callable): A Python function that takes one or more arguments. 2025-08-26T23:21:55.1763404Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-08-26T23:21:55.1763558Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-08-26T23:21:55.1763614Z ``(output, aux)``. 2025-08-26T23:21:55.1763796Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-08-26T23:21:55.1763958Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-08-26T23:21:55.1797287Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-08-26T23:21:55.1797484Z auxiliary objects: ``(output, aux)``. Default: False. 2025-08-26T23:21:55.1797489Z 2025-08-26T23:21:55.1797545Z Returns: 2025-08-26T23:21:55.1797720Z Function to compute gradients with respect to its inputs. By default, the output of 2025-08-26T23:21:55.1797885Z the function is the gradient tensor(s) with respect to the first argument. 2025-08-26T23:21:55.1798030Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-08-26T23:21:55.1798222Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-08-26T23:21:55.1798310Z respect to each ``argnums`` value is returned. 2025-08-26T23:21:55.1798316Z 2025-08-26T23:21:55.1798385Z Example of using ``grad``: 2025-08-26T23:21:55.1798388Z 2025-08-26T23:21:55.1798514Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.1798659Z >>> from torch.func import grad 2025-08-26T23:21:55.1798784Z >>> x = torch.randn([]) 2025-08-26T23:21:55.1798854Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-08-26T23:21:55.1798937Z >>> assert torch.allclose(cos_x, x.cos()) 2025-08-26T23:21:55.1799079Z >>> 2025-08-26T23:21:55.1799151Z >>> # Second-order gradients 2025-08-26T23:21:55.1799237Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-08-26T23:21:55.1799368Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-08-26T23:21:55.1799372Z 2025-08-26T23:21:55.1799584Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-08-26T23:21:55.1799587Z 2025-08-26T23:21:55.1799658Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.1799728Z >>> from torch.func import grad, vmap 2025-08-26T23:21:55.1802582Z >>> batch_size, feature_size = 3, 5 2025-08-26T23:21:55.1802641Z >>> 2025-08-26T23:21:55.1802713Z >>> def model(weights, feature_vec): 2025-08-26T23:21:55.1802805Z >>> # Very simple linear model with activation 2025-08-26T23:21:55.1802887Z >>> assert feature_vec.dim() == 1 2025-08-26T23:21:55.1802956Z >>> return feature_vec.dot(weights).relu() 2025-08-26T23:21:55.1803007Z >>> 2025-08-26T23:21:55.1803124Z >>> def compute_loss(weights, example, target): 2025-08-26T23:21:55.1803213Z >>> y = model(weights, example) 2025-08-26T23:21:55.1803300Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-08-26T23:21:55.1803370Z >>> 2025-08-26T23:21:55.1803466Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T23:21:55.1803551Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T23:21:55.1803636Z >>> targets = torch.randn(batch_size) 2025-08-26T23:21:55.1803713Z >>> inputs = (weights, examples, targets) 2025-08-26T23:21:55.1803954Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-08-26T23:21:55.1804006Z ... *inputs 2025-08-26T23:21:55.1804057Z ... ) 2025-08-26T23:21:55.1804061Z 2025-08-26T23:21:55.1804210Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-08-26T23:21:55.1804216Z 2025-08-26T23:21:55.1804271Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.1804334Z >>> from torch.func import grad 2025-08-26T23:21:55.1804437Z >>> def my_loss_func(y, y_pred): 2025-08-26T23:21:55.1806193Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-08-26T23:21:55.1806264Z >>> loss = loss_per_sample.mean() 2025-08-26T23:21:55.1806353Z >>> return loss, (y_pred, loss_per_sample) 2025-08-26T23:21:55.1806434Z >>> 2025-08-26T23:21:55.1806528Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-08-26T23:21:55.1806628Z >>> y_true = torch.rand(4) 2025-08-26T23:21:55.1806702Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-08-26T23:21:55.1806766Z >>> out = fn(y_true, y_preds) 2025-08-26T23:21:55.1806908Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-08-26T23:21:55.1806912Z 2025-08-26T23:21:55.1806994Z .. note:: 2025-08-26T23:21:55.1807104Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-08-26T23:21:55.1807107Z 2025-08-26T23:21:55.1807202Z Case 1: Using ``torch.no_grad`` inside a function: 2025-08-26T23:21:55.1807206Z 2025-08-26T23:21:55.1807262Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.1807316Z >>> def f(x): 2025-08-26T23:21:55.1807379Z >>> with torch.no_grad(): 2025-08-26T23:21:55.1807464Z >>> c = x ** 2 2025-08-26T23:21:55.1807538Z >>> return x - c 2025-08-26T23:21:55.1807541Z 2025-08-26T23:21:55.1807691Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-08-26T23:21:55.1807695Z 2025-08-26T23:21:55.1807810Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-08-26T23:21:55.1807814Z 2025-08-26T23:21:55.1807875Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.1807962Z >>> with torch.no_grad(): 2025-08-26T23:21:55.1809502Z >>> grad(f)(x) 2025-08-26T23:21:55.1809506Z 2025-08-26T23:21:55.1809678Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-08-26T23:21:55.1809824Z outer one. This is because ``grad`` is a "function transform": its result 2025-08-26T23:21:55.1809941Z should not depend on the result of a context manager outside of ``f``. 2025-08-26T23:21:55.1809944Z 2025-08-26T23:21:55.1809989Z 2025-08-26T23:21:55.1810172Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.1810175Z 2025-08-26T23:21:55.2769990Z msg = Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-08-26T23:21:55.2771486Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.2771566Z 2025-08-26T23:21:55.2771899Z Config object that specifies the supported data types passed as arguments to 2025-08-26T23:21:55.2772149Z quantize ops in the reference model spec, for input and output activations, 2025-08-26T23:21:55.2772278Z weights, and biases. 2025-08-26T23:21:55.2772333Z 2025-08-26T23:21:55.2772519Z For example, consider the following reference model: 2025-08-26T23:21:55.2772527Z 2025-08-26T23:21:55.2772718Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-08-26T23:21:55.2772725Z 2025-08-26T23:21:55.2772958Z The pattern in the square brackets refers to the reference pattern of 2025-08-26T23:21:55.2773208Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-08-26T23:21:55.2773459Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-08-26T23:21:55.2774270Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-08-26T23:21:55.2774496Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-08-26T23:21:55.2774633Z the second quantize op (quant2). 2025-08-26T23:21:55.2774638Z 2025-08-26T23:21:55.2774868Z Note that the dtype here does not refer to the interface dtypes of the 2025-08-26T23:21:55.2788231Z op. For example, the "input dtype" here is not the dtype of the input 2025-08-26T23:21:55.2788467Z tensor passed to the quantized linear op. Though it can still be the 2025-08-26T23:21:55.2788585Z same as the interface dtype, this is not always the case, e.g. the 2025-08-26T23:21:55.2788723Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-08-26T23:21:55.2788838Z specified in the DTypeConfig would still be quint8. The semantics of 2025-08-26T23:21:55.2789026Z dtypes here are the same as the semantics of the dtypes specified in 2025-08-26T23:21:55.2789087Z the observers. 2025-08-26T23:21:55.2789091Z 2025-08-26T23:21:55.2789254Z These dtypes are matched against the ones specified in the user's 2025-08-26T23:21:55.2789378Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-08-26T23:21:55.2789504Z specified in the DTypeConfig (if any), then we will quantize the given 2025-08-26T23:21:55.2789628Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-08-26T23:21:55.2789739Z the pattern will not be quantized. 2025-08-26T23:21:55.2789741Z 2025-08-26T23:21:55.2789826Z Example usage:: 2025-08-26T23:21:55.2789830Z 2025-08-26T23:21:55.2789892Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:21:55.2790005Z >>> dtype_config1 = DTypeConfig( 2025-08-26T23:21:55.2790092Z ... input_dtype=torch.quint8, 2025-08-26T23:21:55.2790141Z ... output_dtype=torch.quint8, 2025-08-26T23:21:55.2790182Z ... weight_dtype=torch.qint8, 2025-08-26T23:21:55.2790269Z ... bias_dtype=torch.float) 2025-08-26T23:21:55.2790272Z 2025-08-26T23:21:55.2790319Z >>> dtype_config2 = DTypeConfig( 2025-08-26T23:21:55.2790532Z ... input_dtype=DTypeWithConstraints( 2025-08-26T23:21:55.2792215Z ... dtype=torch.quint8, 2025-08-26T23:21:55.2792269Z ... quant_min_lower_bound=0, 2025-08-26T23:21:55.2792320Z ... quant_max_upper_bound=255, 2025-08-26T23:21:55.2792358Z ... ), 2025-08-26T23:21:55.2792414Z ... output_dtype=DTypeWithConstraints( 2025-08-26T23:21:55.2792461Z ... dtype=torch.quint8, 2025-08-26T23:21:55.2792512Z ... quant_min_lower_bound=0, 2025-08-26T23:21:55.2792559Z ... quant_max_upper_bound=255, 2025-08-26T23:21:55.2792592Z ... ), 2025-08-26T23:21:55.2792649Z ... weight_dtype=DTypeWithConstraints( 2025-08-26T23:21:55.2792692Z ... dtype=torch.qint8, 2025-08-26T23:21:55.2792741Z ... quant_min_lower_bound=-128, 2025-08-26T23:21:55.2792790Z ... quant_max_upper_bound=127, 2025-08-26T23:21:55.2792827Z ... ), 2025-08-26T23:21:55.2792874Z ... bias_dtype=torch.float) 2025-08-26T23:21:55.2792876Z 2025-08-26T23:21:55.2792923Z >>> dtype_config1.input_dtype 2025-08-26T23:21:55.2792963Z torch.quint8 2025-08-26T23:21:55.2792965Z 2025-08-26T23:21:55.2793008Z >>> dtype_config2.input_dtype 2025-08-26T23:21:55.2793043Z torch.quint8 2025-08-26T23:21:55.2793045Z 2025-08-26T23:21:55.2793102Z >>> dtype_config2.input_dtype_with_constraints 2025-08-26T23:21:55.2793321Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-08-26T23:21:55.2793324Z 2025-08-26T23:21:55.2793426Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.2793428Z 2025-08-26T23:21:55.3096556Z msg = Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-08-26T23:21:55.3096751Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3096754Z 2025-08-26T23:21:55.3096854Z Takes in optional filter values and generates two tables with desired information. 2025-08-26T23:21:55.3096856Z 2025-08-26T23:21:55.3096937Z The generated tables are presented in both a list-of-lists format 2025-08-26T23:21:55.3096940Z 2025-08-26T23:21:55.3097059Z The reason for the two tables are that they handle different things: 2025-08-26T23:21:55.3097124Z 1.) the first table handles all tensor level information 2025-08-26T23:21:55.3097206Z 2.) the second table handles and displays all channel based information 2025-08-26T23:21:55.3097208Z 2025-08-26T23:21:55.3097330Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T23:21:55.3097482Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T23:21:55.3097614Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T23:21:55.3097617Z 2025-08-26T23:21:55.3097658Z Tensor table columns: 2025-08-26T23:21:55.3097742Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:21:55.3097814Z ---- --------- --------- --------- --------- --------- 2025-08-26T23:21:55.3097816Z 2025-08-26T23:21:55.3097861Z Per-Channel table columns: 2025-08-26T23:21:55.3097944Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:21:55.3098014Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T23:21:55.3098017Z 2025-08-26T23:21:55.3098049Z Args: 2025-08-26T23:21:55.3098150Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:21:55.3100641Z contain this filter substring 2025-08-26T23:21:55.3100721Z Default = "", results in all the features being printed 2025-08-26T23:21:55.3100861Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:21:55.3100951Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:21:55.3100954Z 2025-08-26T23:21:55.3101013Z Returns a dictionary with two keys: 2025-08-26T23:21:55.3101083Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-08-26T23:21:55.3101173Z "tensor_level_info", "channel_level_info" 2025-08-26T23:21:55.3101217Z Each key maps to a tuple with: 2025-08-26T23:21:55.3101263Z A list of the headers of each table 2025-08-26T23:21:55.3101338Z A list of lists containing the table information row by row 2025-08-26T23:21:55.3101402Z The 0th index row will contain the headers of the columns 2025-08-26T23:21:55.3101453Z The rest of the rows will contain data 2025-08-26T23:21:55.3101456Z 2025-08-26T23:21:55.3101491Z Example Use: 2025-08-26T23:21:55.3101545Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:55.3101602Z >>> mod_report_visualizer.generate_filtered_tables( 2025-08-26T23:21:55.3101676Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:21:55.3101772Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-08-26T23:21:55.3101775Z 2025-08-26T23:21:55.3101866Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3101869Z 2025-08-26T23:21:55.3102173Z msg = Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-08-26T23:21:55.3102266Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3102270Z 2025-08-26T23:21:55.3102365Z Takes in optional filter values and prints out formatted tables of the information. 2025-08-26T23:21:55.3102403Z 2025-08-26T23:21:55.3102529Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-08-26T23:21:55.3102595Z 1.) the first table handles all tensor level information 2025-08-26T23:21:55.3102681Z 2.) the second table handles and displays all channel based information 2025-08-26T23:21:55.3102684Z 2025-08-26T23:21:55.3102820Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T23:21:55.3102938Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T23:21:55.3103078Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T23:21:55.3103081Z 2025-08-26T23:21:55.3103121Z Tensor table columns: 2025-08-26T23:21:55.3103220Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:21:55.3103357Z ---- --------- --------- --------- --------- --------- 2025-08-26T23:21:55.3103361Z 2025-08-26T23:21:55.3103410Z Per-Channel table columns: 2025-08-26T23:21:55.3103412Z 2025-08-26T23:21:55.3103493Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:21:55.3104779Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T23:21:55.3104782Z 2025-08-26T23:21:55.3104816Z Args: 2025-08-26T23:21:55.3104915Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:21:55.3104959Z contain this filter substring 2025-08-26T23:21:55.3105021Z Default = "", results in all the features being printed 2025-08-26T23:21:55.3105113Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:21:55.3105202Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:21:55.3105206Z 2025-08-26T23:21:55.3105240Z Example Use: 2025-08-26T23:21:55.3105310Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:55.3105374Z >>> mod_report_visualizer.generate_table_visualization( 2025-08-26T23:21:55.3105445Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:21:55.3105478Z ... ) 2025-08-26T23:21:55.3105547Z >>> # prints out neatly formatted table with per_channel_min info 2025-08-26T23:21:55.3105596Z >>> # for all modules in block 1 of the model 2025-08-26T23:21:55.3105599Z 2025-08-26T23:21:55.3105688Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3105690Z 2025-08-26T23:21:55.3105990Z msg = Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-08-26T23:21:55.3106081Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3106084Z 2025-08-26T23:21:55.3106168Z Takes in a feature and optional module_filter and plots of the desired data. 2025-08-26T23:21:55.3106170Z 2025-08-26T23:21:55.3106265Z For per channel features, it averages the value across the channels and plots a point 2025-08-26T23:21:55.3106357Z per module. The reason for this is that for models with hundreds of channels, it can 2025-08-26T23:21:55.3106451Z be hard to differentiate one channel line from another, and so the point of generating 2025-08-26T23:21:55.3107537Z a single average point per module is to give a sense of general trends that encourage 2025-08-26T23:21:55.3107576Z further deep dives. 2025-08-26T23:21:55.3107578Z 2025-08-26T23:21:55.3107611Z Note: 2025-08-26T23:21:55.3107705Z Only features in the report that have tensor value data are plottable by this class 2025-08-26T23:21:55.3107770Z When the tensor information is plotted, it will plot: 2025-08-26T23:21:55.3107824Z idx as the x val, feature value as the y_val 2025-08-26T23:21:55.3107910Z When the channel information is plotted, it will plot: 2025-08-26T23:21:55.3108005Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-08-26T23:21:55.3108086Z The reason for this is that we want to be able to compare values across the 2025-08-26T23:21:55.3108169Z channels for same layer, and it will be hard if values are staggered by idx 2025-08-26T23:21:55.3108247Z This means each module is represented by only 1 x value 2025-08-26T23:21:55.3108278Z Args: 2025-08-26T23:21:55.3108359Z feature_filter (str): Filters the features presented to only those that 2025-08-26T23:21:55.3108402Z contain this filter substring 2025-08-26T23:21:55.3108493Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:21:55.3108595Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:21:55.3108598Z 2025-08-26T23:21:55.3108632Z Example Use: 2025-08-26T23:21:55.3108682Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:55.3108743Z >>> mod_report_visualizer.generate_plot_visualization( 2025-08-26T23:21:55.3108815Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:21:55.3108847Z ... ) 2025-08-26T23:21:55.3108914Z >>> # outputs line plot of per_channel_min information for all 2025-08-26T23:21:55.3109922Z >>> # modules in block1 of model each channel gets it's own line, 2025-08-26T23:21:55.3109993Z >>> # and it's plotted across the in-order modules on the x-axis 2025-08-26T23:21:55.3109995Z 2025-08-26T23:21:55.3110085Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3110087Z 2025-08-26T23:21:55.3110500Z msg = Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-08-26T23:21:55.3110634Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3110636Z 2025-08-26T23:21:55.3110733Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-08-26T23:21:55.3110735Z 2025-08-26T23:21:55.3110766Z Note: 2025-08-26T23:21:55.3110858Z Only features in the report that have tensor value data can be viewed as a histogram 2025-08-26T23:21:55.3110951Z If you want to plot a histogram from all the channel values of a specific feature for 2025-08-26T23:21:55.3111039Z a specific model, make sure to specify both the model and the feature properly 2025-08-26T23:21:55.3111126Z in the filters and you should be able to see a distribution of the channel data 2025-08-26T23:21:55.3111128Z 2025-08-26T23:21:55.3111158Z Args: 2025-08-26T23:21:55.3111253Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:21:55.3111296Z contain this filter substring 2025-08-26T23:21:55.3111359Z Default = "", results in all the features being printed 2025-08-26T23:21:55.3111448Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:21:55.3111535Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:21:55.3111614Z num_bins (int, optional): The number of bins to create the histogram with 2025-08-26T23:21:55.3111683Z Default = 10, the values will be split into 10 equal sized bins 2025-08-26T23:21:55.3111685Z 2025-08-26T23:21:55.3111719Z Example Use: 2025-08-26T23:21:55.3111759Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.3112816Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-08-26T23:21:55.3112891Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:21:55.3112923Z ... ) 2025-08-26T23:21:55.3113019Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-08-26T23:21:55.3113144Z information is gathered across all channels for all modules in block 1 for the 2025-08-26T23:21:55.3113222Z per_channel_min and is displayed in a histogram of equally sized bins 2025-08-26T23:21:55.3113224Z 2025-08-26T23:21:55.3113311Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3113313Z 2025-08-26T23:21:55.3164932Z msg = Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-08-26T23:21:55.3165027Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3165037Z 2025-08-26T23:21:55.3166528Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-08-26T23:21:55.3167217Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-08-26T23:21:55.3167418Z though the requirements on the type of model more-so depends on the specific report the user 2025-08-26T23:21:55.3167686Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-08-26T23:21:55.3167879Z a set of Detector classes, each of which generate reports on quantization configuration 2025-08-26T23:21:55.3167961Z issues a use might have. 2025-08-26T23:21:55.3167966Z 2025-08-26T23:21:55.3168067Z Currently supports generating reports on: 2025-08-26T23:21:55.3168221Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-08-26T23:21:55.3168433Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-08-26T23:21:55.3168610Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-08-26T23:21:55.3175184Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-08-26T23:21:55.3175192Z 2025-08-26T23:21:55.3175543Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-08-26T23:21:55.3175749Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-08-26T23:21:55.3175951Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-08-26T23:21:55.3176066Z has the capability to remove all the observers it inserted as well. 2025-08-26T23:21:55.3176069Z 2025-08-26T23:21:55.3176246Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-08-26T23:21:55.3176252Z 2025-08-26T23:21:55.3176475Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-08-26T23:21:55.3176720Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-08-26T23:21:55.3176724Z 2025-08-26T23:21:55.3176880Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-08-26T23:21:55.3177080Z This set is generated by calling the get_detector_name() of each detector 2025-08-26T23:21:55.3177083Z 2025-08-26T23:21:55.3177286Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-08-26T23:21:55.3177451Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-08-26T23:21:55.3177528Z can be removed at the end if desired 2025-08-26T23:21:55.3177536Z 2025-08-26T23:21:55.3177697Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-08-26T23:21:55.3177817Z This is to ensure we only insert observers once with the ModelReport instance 2025-08-26T23:21:55.3177824Z 2025-08-26T23:21:55.3177959Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-08-26T23:21:55.3178114Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-08-26T23:21:55.3178367Z instance. This also allows the functionality where we can generate the report multiple times 2025-08-26T23:21:55.3178459Z as long as we haven't removed the observers yet. 2025-08-26T23:21:55.3178463Z 2025-08-26T23:21:55.3178512Z Note: 2025-08-26T23:21:55.3178686Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-08-26T23:21:55.3180813Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-08-26T23:21:55.3180940Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-08-26T23:21:55.3180994Z the QuantizationTracer class. 2025-08-26T23:21:55.3180997Z 2025-08-26T23:21:55.3181048Z General Flow for Fx workflow: 2025-08-26T23:21:55.3181204Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-08-26T23:21:55.3181296Z 2.) Prepare your model with prepare_fx 2025-08-26T23:21:55.3181400Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-08-26T23:21:55.3181451Z 4.) Calibrate your model with data 2025-08-26T23:21:55.3181595Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-08-26T23:21:55.3181636Z Optional 2025-08-26T23:21:55.3181747Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-08-26T23:21:55.3181853Z 7.) To help in parsing report information and debugging, view report info as a: 2025-08-26T23:21:55.3181900Z - Table 2025-08-26T23:21:55.3181943Z - Histogram 2025-08-26T23:21:55.3181981Z - Line plot 2025-08-26T23:21:55.3182108Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-08-26T23:21:55.3182112Z 2025-08-26T23:21:55.3182165Z Example (with QuantizationTracer): 2025-08-26T23:21:55.3182213Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.3182263Z >>> # get the necessary qconfig 2025-08-26T23:21:55.3182365Z >>> config = PrepareCustomConfig() 2025-08-26T23:21:55.3182435Z >>> skipped_module_names, skipped_module_classes = ( 2025-08-26T23:21:55.3182512Z ... get_skipped_module_name_and_classes(config, False) 2025-08-26T23:21:55.3183820Z ... ) 2025-08-26T23:21:55.3183826Z 2025-08-26T23:21:55.3183891Z >>> # initialize our model and get GraphModule 2025-08-26T23:21:55.3183941Z >>> model = SomeModel() 2025-08-26T23:21:55.3184045Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-08-26T23:21:55.3184115Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-08-26T23:21:55.3184117Z 2025-08-26T23:21:55.3184188Z >>> # get our set of detectors and ModelReport instance 2025-08-26T23:21:55.3184230Z >>> detector_set = set( 2025-08-26T23:21:55.3184270Z ... [ 2025-08-26T23:21:55.3184335Z ... DynamicStaticDetector(tolerance=0.5), 2025-08-26T23:21:55.3184422Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-08-26T23:21:55.3184462Z ... ] 2025-08-26T23:21:55.3184499Z ... ) 2025-08-26T23:21:55.3184584Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-08-26T23:21:55.3184586Z 2025-08-26T23:21:55.3184659Z >>> # now we insert the observers and calibrate the model 2025-08-26T23:21:55.3184765Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-08-26T23:21:55.3184822Z >>> for i in range(num_callibration_batches): 2025-08-26T23:21:55.3184882Z >>> example_input = get_callibration_input() 2025-08-26T23:21:55.3184942Z >>> tracer_model_with_observers(example_input) 2025-08-26T23:21:55.3184944Z 2025-08-26T23:21:55.3185055Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-08-26T23:21:55.3185126Z >>> reports = tracer_reporter.generate_model_report( 2025-08-26T23:21:55.3185248Z ... remove_inserted_observers=True 2025-08-26T23:21:55.3186457Z ... ) 2025-08-26T23:21:55.3186460Z 2025-08-26T23:21:55.3186562Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-08-26T23:21:55.3186629Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-08-26T23:21:55.3186632Z 2025-08-26T23:21:55.3186741Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-08-26T23:21:55.3186854Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-08-26T23:21:55.3186858Z 2025-08-26T23:21:55.3186970Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-08-26T23:21:55.3187059Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-08-26T23:21:55.3187063Z 2025-08-26T23:21:55.3187064Z 2025-08-26T23:21:55.3187186Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3187190Z 2025-08-26T23:21:55.3470578Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-08-26T23:21:55.3470743Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3470750Z 2025-08-26T23:21:55.3470864Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-08-26T23:21:55.3470962Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-08-26T23:21:55.3471060Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-08-26T23:21:55.3471101Z input by the user. 2025-08-26T23:21:55.3471193Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-08-26T23:21:55.3471274Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-08-26T23:21:55.3471280Z 2025-08-26T23:21:55.3471346Z Note:: 2025-08-26T23:21:55.3471479Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-08-26T23:21:55.3471579Z 2025-08-26T23:21:55.3471612Z Args: 2025-08-26T23:21:55.3471658Z model (nn.Module): 2025-08-26T23:21:55.3474111Z The model whose layers will be sparsified. The layers that needs to be 2025-08-26T23:21:55.3474292Z sparsified should be added separately using the register_layer() function 2025-08-26T23:21:55.3474353Z aggregate_fn (Optional, Callable): 2025-08-26T23:21:55.3474552Z default aggregate_fn that is used if not specified while registering the layer. 2025-08-26T23:21:55.3474623Z specifies how inputs should be aggregated over time. 2025-08-26T23:21:55.3474740Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-08-26T23:21:55.3474780Z Example 2025-08-26T23:21:55.3474864Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-08-26T23:21:55.3474918Z reduce_fn (Optional, Callable): 2025-08-26T23:21:55.3475025Z default reduce_fn that is used if not specified while registering the layer. 2025-08-26T23:21:55.3475126Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-08-26T23:21:55.3475188Z calling agg_fn() on all inputs. 2025-08-26T23:21:55.3475230Z Example 2025-08-26T23:21:55.3475313Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-08-26T23:21:55.3475361Z mask_fn (Optional, Callable): 2025-08-26T23:21:55.3475482Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-08-26T23:21:55.3475583Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-08-26T23:21:55.3475630Z register_layer(). 2025-08-26T23:21:55.3475776Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-08-26T23:21:55.3475864Z arguments. 2025-08-26T23:21:55.3475914Z features (Optional, list): 2025-08-26T23:21:55.3477304Z default selected features to sparsify. 2025-08-26T23:21:55.3477417Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-08-26T23:21:55.3477462Z For example, 2025-08-26T23:21:55.3477594Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-08-26T23:21:55.3477646Z feature_dim (Optional, int): 2025-08-26T23:21:55.3477753Z default dimension of input features. Again, features along this dim will be chosen 2025-08-26T23:21:55.3477800Z for sparsification. 2025-08-26T23:21:55.3477846Z sparse_config (Dict): 2025-08-26T23:21:55.3477957Z Default configuration for the mask_fn. This config will be passed 2025-08-26T23:21:55.3478001Z with the mask_fn() 2025-08-26T23:21:55.3478007Z 2025-08-26T23:21:55.3478048Z Example: 2025-08-26T23:21:55.3478093Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.3478138Z >>> model = SomeModel() 2025-08-26T23:21:55.3478234Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-08-26T23:21:55.3478277Z >>> # Initialize aggregate_fn 2025-08-26T23:21:55.3478317Z >>> def agg_fn(x, y): 2025-08-26T23:21:55.3478358Z >>> return x + y 2025-08-26T23:21:55.3478395Z >>> 2025-08-26T23:21:55.3478443Z >>> # Initialize reduce_fn 2025-08-26T23:21:55.3478479Z >>> def reduce_fn(x): 2025-08-26T23:21:55.3478526Z >>> return torch.mean(x, dim=0) 2025-08-26T23:21:55.3478562Z >>> 2025-08-26T23:21:55.3479740Z >>> # Initialize mask_fn 2025-08-26T23:21:55.3479786Z >>> def mask_fn(data): 2025-08-26T23:21:55.3479849Z >>> return torch.eye(data.shape).to(data.device) 2025-08-26T23:21:55.3479889Z >>> 2025-08-26T23:21:55.3479925Z >>> 2025-08-26T23:21:55.3479972Z >>> act_sparsifier.register_layer( 2025-08-26T23:21:55.3480030Z ... model.some_layer, 2025-08-26T23:21:55.3480070Z ... aggregate_fn=agg_fn, 2025-08-26T23:21:55.3480109Z ... reduce_fn=reduce_fn, 2025-08-26T23:21:55.3480163Z ... mask_fn=mask_fn, 2025-08-26T23:21:55.3480195Z ... ) 2025-08-26T23:21:55.3480225Z >>> 2025-08-26T23:21:55.3480264Z >>> # start training process 2025-08-26T23:21:55.3480300Z >>> for _ in [...]: 2025-08-26T23:21:55.3480436Z >>> # epoch starts 2025-08-26T23:21:55.3480505Z >>> # model.forward(), compute_loss() and model.backwards() 2025-08-26T23:21:55.3480540Z >>> # epoch ends 2025-08-26T23:21:55.3480581Z >>> act_sparsifier.step() 2025-08-26T23:21:55.3480620Z >>> # end training process 2025-08-26T23:21:55.3480659Z >>> sparsifier.squash_mask() 2025-08-26T23:21:55.3480663Z 2025-08-26T23:21:55.3480754Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3480757Z 2025-08-26T23:21:55.3482460Z msg = Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-08-26T23:21:55.3482567Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3482570Z 2025-08-26T23:21:55.3482649Z Abstract method that needs to be implemented by the child class. 2025-08-26T23:21:55.3482739Z The expected return type should is a dictionary of name to schedule_param value 2025-08-26T23:21:55.3482834Z The returned values will be updated in sparsifier when the scheduler step() function 2025-08-26T23:21:55.3482867Z is called. 2025-08-26T23:21:55.3482869Z 2025-08-26T23:21:55.3482903Z Example: 2025-08-26T23:21:55.3482946Z >>> def get_schedule_param(self): 2025-08-26T23:21:55.3482990Z ... new_param = {} 2025-08-26T23:21:55.3483132Z ... for name in self.sparsifier.data_groups.keys(): 2025-08-26T23:21:55.3483212Z ... new_param[name] = ( 2025-08-26T23:21:55.3483289Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-08-26T23:21:55.3483321Z ... ) 2025-08-26T23:21:55.3483360Z ... return new_param 2025-08-26T23:21:55.3483363Z 2025-08-26T23:21:55.3483479Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-08-26T23:21:55.3483514Z would be halved 2025-08-26T23:21:55.3483516Z 2025-08-26T23:21:55.3483623Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3483627Z 2025-08-26T23:21:55.3572080Z msg = Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-08-26T23:21:55.3572214Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.3572343Z Squashes the sparse masks into the appropriate tensors. 2025-08-26T23:21:55.3572349Z 2025-08-26T23:21:55.3574417Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-08-26T23:21:55.3574498Z the module will have a `sparse_params` dict attached to it. 2025-08-26T23:21:55.3574501Z 2025-08-26T23:21:55.3574541Z Args: 2025-08-26T23:21:55.3574613Z params_to_keep: List of keys to save in the module or a dict 2025-08-26T23:21:55.3574678Z representing the modules and keys that will have 2025-08-26T23:21:55.3574729Z sparsity parameters saved 2025-08-26T23:21:55.3574808Z params_to_keep_per_layer: Dict to specify the params that should be 2025-08-26T23:21:55.3574866Z saved for specific layers. The keys in the dict 2025-08-26T23:21:55.3574925Z should be the module fqn, while the values should 2025-08-26T23:21:55.3574986Z be a list of strings with the names of the variables 2025-08-26T23:21:55.3575069Z to save in the `sparse_params` 2025-08-26T23:21:55.3575072Z 2025-08-26T23:21:55.3575107Z Examples: 2025-08-26T23:21:55.3575161Z >>> # xdoctest: +SKIP("locals are undefined") 2025-08-26T23:21:55.3575208Z >>> # Don't save any sparse params 2025-08-26T23:21:55.3575254Z >>> sparsifier.squash_mask() 2025-08-26T23:21:55.3575308Z >>> hasattr(model.submodule1, "sparse_params") 2025-08-26T23:21:55.3575350Z False 2025-08-26T23:21:55.3575352Z 2025-08-26T23:21:55.3575401Z >>> # Keep sparse params per layer 2025-08-26T23:21:55.3575533Z >>> sparsifier.squash_mask( 2025-08-26T23:21:55.3575576Z ... params_to_keep_per_layer={ 2025-08-26T23:21:55.3575630Z ... "submodule1.linear1": ("foo", "bar"), 2025-08-26T23:21:55.3576844Z ... "submodule2.linear42": ("baz",), 2025-08-26T23:21:55.3576884Z ... } 2025-08-26T23:21:55.3576917Z ... ) 2025-08-26T23:21:55.3576981Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:21:55.3577020Z {'foo': 42, 'bar': 24} 2025-08-26T23:21:55.3577082Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:21:55.3577119Z {'baz': 0.1} 2025-08-26T23:21:55.3577122Z 2025-08-26T23:21:55.3577170Z >>> # Keep sparse params for all layers 2025-08-26T23:21:55.3577237Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-08-26T23:21:55.3577295Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:21:55.3577334Z {'foo': 42, 'bar': 24} 2025-08-26T23:21:55.3577393Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:21:55.3577430Z {'foo': 42, 'bar': 24} 2025-08-26T23:21:55.3577434Z 2025-08-26T23:21:55.3577510Z >>> # Keep some sparse params for all layers, and specific ones for 2025-08-26T23:21:55.3577599Z >>> # some other layers 2025-08-26T23:21:55.3577643Z >>> sparsifier.squash_mask( 2025-08-26T23:21:55.3577689Z ... params_to_keep=("foo", "bar"), 2025-08-26T23:21:55.3577758Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-08-26T23:21:55.3577790Z ... ) 2025-08-26T23:21:55.3577848Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:21:55.3577885Z {'foo': 42, 'bar': 24} 2025-08-26T23:21:55.3577961Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:21:55.3579029Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-08-26T23:21:55.3579062Z 2025-08-26T23:21:55.3579154Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.3579157Z 2025-08-26T23:21:55.4111683Z msg = Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-08-26T23:21:55.4112213Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4112475Z A quantized long short-term memory (LSTM). 2025-08-26T23:21:55.4112609Z 2025-08-26T23:21:55.4112767Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-08-26T23:21:55.4112973Z 2025-08-26T23:21:55.4113031Z Attributes: 2025-08-26T23:21:55.4113186Z layers : instances of the `_LSTMLayer` 2025-08-26T23:21:55.4113318Z 2025-08-26T23:21:55.4113394Z .. note:: 2025-08-26T23:21:55.4118106Z To access the weights and biases, you need to access them per layer. 2025-08-26T23:21:55.4118374Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-08-26T23:21:55.4118523Z 2025-08-26T23:21:55.4118579Z Examples:: 2025-08-26T23:21:55.4118724Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4118889Z >>> custom_module_config = { 2025-08-26T23:21:55.4119078Z ... 'float_to_observed_custom_module_class': { 2025-08-26T23:21:55.4119492Z ... nn.LSTM: nn.quantizable.LSTM, 2025-08-26T23:21:55.4119655Z ... }, 2025-08-26T23:21:55.4119808Z ... 'observed_to_quantized_custom_module_class': { 2025-08-26T23:21:55.4120032Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-08-26T23:21:55.4120176Z ... } 2025-08-26T23:21:55.4120285Z ... } 2025-08-26T23:21:55.4120605Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-08-26T23:21:55.4120837Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-08-26T23:21:55.4121021Z 2025-08-26T23:21:55.4121199Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4121355Z 2025-08-26T23:21:55.4161005Z msg = Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-08-26T23:21:55.4161371Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4161628Z Applies a 1D convolution over a quantized input signal composed of 2025-08-26T23:21:55.4161826Z several quantized input planes. 2025-08-26T23:21:55.4161911Z 2025-08-26T23:21:55.4162004Z For details on input arguments, parameters, and implementation see 2025-08-26T23:21:55.4162195Z :class:`~torch.nn.Conv1d`. 2025-08-26T23:21:55.4162273Z 2025-08-26T23:21:55.4162323Z .. note:: 2025-08-26T23:21:55.4164476Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-08-26T23:21:55.4164618Z 2025-08-26T23:21:55.4164659Z .. note:: 2025-08-26T23:21:55.4164783Z Only `torch.quint8` is supported for the input data type. 2025-08-26T23:21:55.4164900Z 2025-08-26T23:21:55.4164901Z 2025-08-26T23:21:55.4164937Z Attributes: 2025-08-26T23:21:55.4165077Z weight (Tensor): packed tensor derived from the learnable weight 2025-08-26T23:21:55.4165332Z parameter. 2025-08-26T23:21:55.4165478Z scale (Tensor): scalar for the output scale 2025-08-26T23:21:55.4165641Z zero_point (Tensor): scalar for the output zero point 2025-08-26T23:21:55.4165745Z 2025-08-26T23:21:55.4165809Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-08-26T23:21:55.4165910Z 2025-08-26T23:21:55.4165949Z Examples:: 2025-08-26T23:21:55.4166006Z 2025-08-26T23:21:55.4166069Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-08-26T23:21:55.4167602Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-08-26T23:21:55.4167746Z >>> input = torch.randn(20, 16, 100) 2025-08-26T23:21:55.4167878Z >>> # quantize input to quint8 2025-08-26T23:21:55.4168001Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4168158Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-08-26T23:21:55.4168384Z ... dtype=torch.quint8) 2025-08-26T23:21:55.4168521Z >>> output = m(q_input) 2025-08-26T23:21:55.4168598Z 2025-08-26T23:21:55.4168633Z 2025-08-26T23:21:55.4168774Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4168912Z 2025-08-26T23:21:55.4359075Z msg = Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py line=120. 2025-08-26T23:21:55.4361178Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4362597Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-08-26T23:21:55.4362928Z 2025-08-26T23:21:55.4363082Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-08-26T23:21:55.4363440Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-08-26T23:21:55.4363758Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-08-26T23:21:55.4364010Z (UAI 2018). 2025-08-26T23:21:55.4364121Z 2025-08-26T23:21:55.4364652Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-08-26T23:21:55.4364980Z but using exponential weights instead of equal weights across iterations. 2025-08-26T23:21:55.4365176Z 2025-08-26T23:21:55.4365318Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-08-26T23:21:55.4365639Z on the device :attr:`device` and allows to compute running averages of the 2025-08-26T23:21:55.4371767Z parameters of the :attr:`model`. 2025-08-26T23:21:55.4371887Z 2025-08-26T23:21:55.4371938Z Args: 2025-08-26T23:21:55.4372208Z model (torch.nn.Module): model to use with SWA/EMA 2025-08-26T23:21:55.4372450Z device (torch.device, optional): if provided, the averaged model will be 2025-08-26T23:21:55.4372656Z stored on the :attr:`device` 2025-08-26T23:21:55.4372848Z avg_fn (function, optional): the averaging function used to update 2025-08-26T23:21:55.4373081Z parameters; the function must take in the current value of the 2025-08-26T23:21:55.4373327Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-08-26T23:21:55.4373554Z parameter, and the number of models already averaged; if None, 2025-08-26T23:21:55.4373768Z an equally weighted average is used (default: None) 2025-08-26T23:21:55.4373995Z multi_avg_fn (function, optional): the averaging function used to update 2025-08-26T23:21:55.4374268Z parameters inplace; the function must take in the current values of the 2025-08-26T23:21:55.4374705Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-08-26T23:21:55.4374986Z parameters as a list, and the number of models already averaged; if None, 2025-08-26T23:21:55.4375223Z an equally weighted average is used (default: None) 2025-08-26T23:21:55.4375454Z use_buffers (bool): if ``True``, it will compute running averages for 2025-08-26T23:21:55.4375826Z both the parameters and the buffers of the model. (default: ``False``) 2025-08-26T23:21:55.4375979Z 2025-08-26T23:21:55.4376035Z Example: 2025-08-26T23:21:55.4376169Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:55.4376362Z >>> loader, optimizer, model, loss_fn = ... 2025-08-26T23:21:55.4376562Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-08-26T23:21:55.4378575Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-08-26T23:21:55.4378806Z >>> T_max=300) 2025-08-26T23:21:55.4378959Z >>> swa_start = 160 2025-08-26T23:21:55.4379113Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-08-26T23:21:55.4379277Z >>> for i in range(300): 2025-08-26T23:21:55.4379484Z >>> for input, target in loader: 2025-08-26T23:21:55.4379639Z >>> optimizer.zero_grad() 2025-08-26T23:21:55.4379803Z >>> loss_fn(model(input), target).backward() 2025-08-26T23:21:55.4379974Z >>> optimizer.step() 2025-08-26T23:21:55.4380164Z >>> if i > swa_start: 2025-08-26T23:21:55.4380289Z >>> swa_model.update_parameters(model) 2025-08-26T23:21:55.4381688Z >>> swa_scheduler.step() 2025-08-26T23:21:55.4381809Z >>> else: 2025-08-26T23:21:55.4381908Z >>> scheduler.step() 2025-08-26T23:21:55.4382014Z >>> 2025-08-26T23:21:55.4382124Z >>> # Update bn statistics for the swa_model at the end 2025-08-26T23:21:55.4382285Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-08-26T23:21:55.4382387Z 2025-08-26T23:21:55.4382496Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-08-26T23:21:55.4382720Z If no averaging function is provided, the default is to compute 2025-08-26T23:21:55.4382884Z equally-weighted average of the weights (SWA). 2025-08-26T23:21:55.4382980Z 2025-08-26T23:21:55.4383051Z Example: 2025-08-26T23:21:55.4383152Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:55.4384352Z >>> # Compute exponential moving averages of the weights and buffers 2025-08-26T23:21:55.4384536Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-08-26T23:21:55.4384718Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-08-26T23:21:55.4384836Z 2025-08-26T23:21:55.4384899Z .. note:: 2025-08-26T23:21:55.4385029Z When using SWA/EMA with models containing Batch Normalization you may 2025-08-26T23:21:55.4385219Z need to update the activation statistics for Batch Normalization. 2025-08-26T23:21:55.4385415Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-08-26T23:21:55.4385622Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-08-26T23:21:55.4385832Z statistics in a post-training step by passing data through the model. The 2025-08-26T23:21:55.4386040Z second does it during the parameter update phase by averaging all buffers. 2025-08-26T23:21:55.4386262Z Empirical evidence has shown that updating the statistics in normalization 2025-08-26T23:21:55.4387495Z layers increases accuracy, but you may wish to empirically test which 2025-08-26T23:21:55.4387679Z approach yields the best results in your problem. 2025-08-26T23:21:55.4387775Z 2025-08-26T23:21:55.4387811Z .. note:: 2025-08-26T23:21:55.4387954Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-08-26T23:21:55.4388086Z 2025-08-26T23:21:55.4388120Z .. note:: 2025-08-26T23:21:55.4388242Z When :meth:`update_parameters` is called for the first time (i.e. 2025-08-26T23:21:55.4388422Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-08-26T23:21:55.4388644Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-08-26T23:21:55.4388822Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-08-26T23:21:55.4388973Z to update the parameters. 2025-08-26T23:21:55.4389051Z 2025-08-26T23:21:55.4389133Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T23:21:55.4390329Z https://arxiv.org/abs/1803.05407 2025-08-26T23:21:55.4390710Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-08-26T23:21:55.4390865Z Average: 2025-08-26T23:21:55.4390960Z https://arxiv.org/abs/1806.05594 2025-08-26T23:21:55.4391111Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-08-26T23:21:55.4391260Z https://arxiv.org/abs/1904.11943 2025-08-26T23:21:55.4391417Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-08-26T23:21:55.4391589Z Generalizes Well: 2025-08-26T23:21:55.4391696Z https://arxiv.org/abs/2001.02312 2025-08-26T23:21:55.4391809Z .. _Polyak averaging: 2025-08-26T23:21:55.4391941Z https://paperswithcode.com/method/polyak-averaging 2025-08-26T23:21:55.4393062Z 2025-08-26T23:21:55.4393194Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4393319Z 2025-08-26T23:21:55.4393485Z msg = Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py line=375. 2025-08-26T23:21:55.4393775Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4393980Z Anneals the learning rate in each parameter group to a fixed value. 2025-08-26T23:21:55.4394093Z 2025-08-26T23:21:55.4394177Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-08-26T23:21:55.4394491Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-08-26T23:21:55.4394609Z 2025-08-26T23:21:55.4394644Z Args: 2025-08-26T23:21:55.4394757Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-08-26T23:21:55.4394965Z swa_lrs (float or list): the learning rate value for all param groups 2025-08-26T23:21:55.4395125Z together or separately for each group. 2025-08-26T23:21:55.4396292Z annealing_epochs (int): number of epochs in the annealing phase 2025-08-26T23:21:55.4396435Z (default: 10) 2025-08-26T23:21:55.4396574Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-08-26T23:21:55.4396761Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-08-26T23:21:55.4396909Z (default: "cos") 2025-08-26T23:21:55.4397045Z last_epoch (int): the index of the last epoch (default: -1) 2025-08-26T23:21:55.4397147Z 2025-08-26T23:21:55.4397214Z The :class:`SWALR` scheduler can be used together with other 2025-08-26T23:21:55.4397393Z schedulers to switch to a constant learning rate late in the training 2025-08-26T23:21:55.4397545Z as in the example below. 2025-08-26T23:21:55.4397613Z 2025-08-26T23:21:55.4397647Z Example: 2025-08-26T23:21:55.4397746Z >>> # xdoctest: +SKIP("Undefined variables") 2025-08-26T23:21:55.4398843Z >>> loader, optimizer, model = ... 2025-08-26T23:21:55.4398964Z >>> lr_lambda = lambda epoch: 0.9 2025-08-26T23:21:55.4399119Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-08-26T23:21:55.4399274Z >>> lr_lambda=lr_lambda) 2025-08-26T23:21:55.4399414Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-08-26T23:21:55.4399577Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-08-26T23:21:55.4399713Z >>> swa_start = 160 2025-08-26T23:21:55.4399815Z >>> for i in range(300): 2025-08-26T23:21:55.4399927Z >>> for input, target in loader: 2025-08-26T23:21:55.4400047Z >>> optimizer.zero_grad() 2025-08-26T23:21:55.4400204Z >>> loss_fn(model(input), target).backward() 2025-08-26T23:21:55.4401438Z >>> optimizer.step() 2025-08-26T23:21:55.4401550Z >>> if i > swa_start: 2025-08-26T23:21:55.4401659Z >>> swa_scheduler.step() 2025-08-26T23:21:55.4401767Z >>> else: 2025-08-26T23:21:55.4401863Z >>> scheduler.step() 2025-08-26T23:21:55.4401936Z 2025-08-26T23:21:55.4402015Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T23:21:55.4402211Z https://arxiv.org/abs/1803.05407 2025-08-26T23:21:55.4402318Z 2025-08-26T23:21:55.4402449Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4402571Z 2025-08-26T23:21:55.4463631Z msg = Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/optimizer.py line=867. 2025-08-26T23:21:55.4465648Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4465822Z Load the optimizer state. 2025-08-26T23:21:55.4465892Z 2025-08-26T23:21:55.4465925Z Args: 2025-08-26T23:21:55.4466048Z state_dict (dict): optimizer state. Should be an object returned 2025-08-26T23:21:55.4466202Z from a call to :meth:`state_dict`. 2025-08-26T23:21:55.4466286Z 2025-08-26T23:21:55.4466324Z .. warning:: 2025-08-26T23:21:55.4466502Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-08-26T23:21:55.4466733Z as calling it beforehand will overwrite the loaded learning rates. 2025-08-26T23:21:55.4466847Z 2025-08-26T23:21:55.4466881Z .. note:: 2025-08-26T23:21:55.4467042Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-08-26T23:21:55.4467255Z in :meth:`state_dict`) will not affect the loading process. 2025-08-26T23:21:55.4468648Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-08-26T23:21:55.4468858Z differ from those initialized in the optimizer), 2025-08-26T23:21:55.4469058Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-08-26T23:21:55.4469237Z accordingly. 2025-08-26T23:21:55.4469402Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-08-26T23:21:55.4469651Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-08-26T23:21:55.4469857Z the optimizer ``param_names`` will remain unchanged. 2025-08-26T23:21:55.4469954Z 2025-08-26T23:21:55.4469988Z Example: 2025-08-26T23:21:55.4470080Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4470200Z >>> model = torch.nn.Linear(10, 10) 2025-08-26T23:21:55.4471518Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-08-26T23:21:55.4471684Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-08-26T23:21:55.4471817Z ... optim, 2025-08-26T23:21:55.4471918Z ... start_factor=0.1, 2025-08-26T23:21:55.4472028Z ... end_factor=1, 2025-08-26T23:21:55.4472138Z ... total_iters=20, 2025-08-26T23:21:55.4472242Z ... ) 2025-08-26T23:21:55.4472363Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-08-26T23:21:55.4472504Z ... optim, 2025-08-26T23:21:55.4472602Z ... T_max=80, 2025-08-26T23:21:55.4472704Z ... eta_min=3e-5, 2025-08-26T23:21:55.4473808Z ... ) 2025-08-26T23:21:55.4473922Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-08-26T23:21:55.4474048Z ... optim, 2025-08-26T23:21:55.4474162Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T23:21:55.4474324Z ... milestones=[20], 2025-08-26T23:21:55.4474524Z ... ) 2025-08-26T23:21:55.4474635Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-08-26T23:21:55.4474801Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-08-26T23:21:55.4474974Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-08-26T23:21:55.4475074Z 2025-08-26T23:21:55.4475106Z 2025-08-26T23:21:55.4475258Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4475383Z 2025-08-26T23:21:55.4568926Z msg = Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=808. 2025-08-26T23:21:55.4569294Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4569543Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-08-26T23:21:55.4569770Z 2025-08-26T23:21:55.4569899Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-08-26T23:21:55.4570140Z intervals by which each scheduler should be called at a given epoch. 2025-08-26T23:21:55.4570257Z 2025-08-26T23:21:55.4570291Z Args: 2025-08-26T23:21:55.4570492Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:21:55.4570637Z schedulers (list): List of chained schedulers. 2025-08-26T23:21:55.4570807Z milestones (list): List of integers that reflects milestone points. 2025-08-26T23:21:55.4570986Z last_epoch (int): The index of last epoch. Default: -1. 2025-08-26T23:21:55.4571090Z 2025-08-26T23:21:55.4571141Z Example: 2025-08-26T23:21:55.4571239Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4572732Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-08-26T23:21:55.4572873Z >>> # lr = 0.005 if epoch == 0 2025-08-26T23:21:55.4572989Z >>> # lr = 0.005 if epoch == 1 2025-08-26T23:21:55.4573101Z >>> # lr = 0.005 if epoch == 2 2025-08-26T23:21:55.4573246Z >>> # ... 2025-08-26T23:21:55.4573340Z >>> # lr = 0.05 if epoch == 20 2025-08-26T23:21:55.4573454Z >>> # lr = 0.045 if epoch == 21 2025-08-26T23:21:55.4573565Z >>> # lr = 0.0405 if epoch == 22 2025-08-26T23:21:55.4573709Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-08-26T23:21:55.4573879Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-08-26T23:21:55.4574016Z >>> scheduler = SequentialLR( 2025-08-26T23:21:55.4575201Z ... optimizer, 2025-08-26T23:21:55.4575319Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T23:21:55.4575444Z ... milestones=[20], 2025-08-26T23:21:55.4575544Z ... ) 2025-08-26T23:21:55.4575633Z >>> for epoch in range(100): 2025-08-26T23:21:55.4575744Z >>> train(...) 2025-08-26T23:21:55.4575843Z >>> validate(...) 2025-08-26T23:21:55.4575951Z >>> scheduler.step() 2025-08-26T23:21:55.4576023Z 2025-08-26T23:21:55.4576094Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-08-26T23:21:55.4576223Z 2025-08-26T23:21:55.4576356Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4577473Z 2025-08-26T23:21:55.4580193Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-08-26T23:21:55.4580618Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.4580816Z Reduce learning rate when a metric has stopped improving. 2025-08-26T23:21:55.4580942Z 2025-08-26T23:21:55.4581020Z Models often benefit from reducing the learning rate by a factor 2025-08-26T23:21:55.4581200Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-08-26T23:21:55.4581378Z quantity and if no improvement is seen for a 'patience' number 2025-08-26T23:21:55.4581585Z of epochs, the learning rate is reduced. 2025-08-26T23:21:55.4581669Z 2025-08-26T23:21:55.4581702Z Args: 2025-08-26T23:21:55.4581798Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:21:55.4581948Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-08-26T23:21:55.4583513Z be reduced when the quantity monitored has stopped 2025-08-26T23:21:55.4583675Z decreasing; in `max` mode it will be reduced when the 2025-08-26T23:21:55.4583891Z quantity monitored has stopped increasing. Default: 'min'. 2025-08-26T23:21:55.4584062Z factor (float): Factor by which the learning rate will be 2025-08-26T23:21:55.4584225Z reduced. new_lr = lr * factor. Default: 0.1. 2025-08-26T23:21:55.4584399Z patience (int): The number of allowed epochs with no improvement after 2025-08-26T23:21:55.4584584Z which the learning rate will be reduced. 2025-08-26T23:21:55.4584754Z For example, consider the case of having no patience (`patience = 0`). 2025-08-26T23:21:55.4585000Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-08-26T23:21:55.4585234Z In the second epoch, if the performance is worse than the baseline, 2025-08-26T23:21:55.4585408Z we have what is considered an intolerable epoch. 2025-08-26T23:21:55.4587115Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-08-26T23:21:55.4587312Z the learning rate is reduced at the end of this epoch. 2025-08-26T23:21:55.4587529Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-08-26T23:21:55.4587788Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-08-26T23:21:55.4588002Z the learning rate is not adjusted. 2025-08-26T23:21:55.4588128Z Default: 10. 2025-08-26T23:21:55.4588330Z threshold (float): Threshold for measuring the new optimum, 2025-08-26T23:21:55.4588496Z to only focus on significant changes. Default: 1e-4. 2025-08-26T23:21:55.4588656Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-08-26T23:21:55.4588815Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-08-26T23:21:55.4588968Z mode or best * ( 1 - threshold ) in `min` mode. 2025-08-26T23:21:55.4589118Z In `abs` mode, dynamic_threshold = best + threshold in 2025-08-26T23:21:55.4589282Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-08-26T23:21:55.4589451Z cooldown (int): Number of epochs to wait before resuming 2025-08-26T23:21:55.4589621Z normal operation after lr has been reduced. Default: 0. 2025-08-26T23:21:55.4589786Z min_lr (float or list): A scalar or a list of scalars. A 2025-08-26T23:21:55.4589948Z lower bound on the learning rate of all param groups 2025-08-26T23:21:55.4590101Z or each group respectively. Default: 0. 2025-08-26T23:21:55.4590257Z eps (float): Minimal decay applied to lr. If the difference 2025-08-26T23:21:55.4590519Z between new and old lr is smaller than eps, the update is 2025-08-26T23:21:55.4590666Z ignored. Default: 1e-8. 2025-08-26T23:21:55.4590744Z 2025-08-26T23:21:55.4590782Z Example: 2025-08-26T23:21:55.4590887Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4591069Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T23:21:55.4592549Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-08-26T23:21:55.4592683Z >>> for epoch in range(10): 2025-08-26T23:21:55.4592801Z >>> train(...) 2025-08-26T23:21:55.4592905Z >>> val_loss = validate(...) 2025-08-26T23:21:55.4593040Z >>> # Note that step should be called after validate() 2025-08-26T23:21:55.4593213Z >>> scheduler.step(val_loss) 2025-08-26T23:21:55.4593295Z 2025-08-26T23:21:55.4593371Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-08-26T23:21:55.4593505Z 2025-08-26T23:21:55.4593694Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-08-26T23:21:55.4593870Z 2025-08-26T23:21:55.4593913Z scheduler.step(val_loss) 2025-08-26T23:21:55.4596111Z ^ 2025-08-26T23:21:55.4596379Z msg = Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-08-26T23:21:55.4596693Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4596938Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-08-26T23:21:55.4597108Z 2025-08-26T23:21:55.4597208Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-08-26T23:21:55.4597448Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-08-26T23:21:55.4597658Z The distance between the two boundaries can be scaled on a per-iteration 2025-08-26T23:21:55.4597820Z or per-cycle basis. 2025-08-26T23:21:55.4597884Z 2025-08-26T23:21:55.4597972Z Cyclical learning rate policy changes the learning rate after every batch. 2025-08-26T23:21:55.4598170Z `step` should be called after a batch has been used for training. 2025-08-26T23:21:55.4598276Z 2025-08-26T23:21:55.4599788Z This class has three built-in policies, as put forth in the paper: 2025-08-26T23:21:55.4599903Z 2025-08-26T23:21:55.4599997Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-08-26T23:21:55.4600214Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-08-26T23:21:55.4600537Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-08-26T23:21:55.4600775Z at each cycle iteration. 2025-08-26T23:21:55.4600846Z 2025-08-26T23:21:55.4600933Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-08-26T23:21:55.4601053Z 2025-08-26T23:21:55.4601087Z Args: 2025-08-26T23:21:55.4601193Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:21:55.4601345Z base_lr (float or list): Initial learning rate which is the 2025-08-26T23:21:55.4601515Z lower boundary in the cycle for each parameter group. 2025-08-26T23:21:55.4601686Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T23:21:55.4602941Z for each parameter group. Functionally, 2025-08-26T23:21:55.4603092Z it defines the cycle amplitude (max_lr - base_lr). 2025-08-26T23:21:55.4603238Z The lr at any cycle is the sum of base_lr 2025-08-26T23:21:55.4603379Z and some scaling of the amplitude; therefore 2025-08-26T23:21:55.4603523Z max_lr may not actually be reached depending on 2025-08-26T23:21:55.4603655Z scaling function. 2025-08-26T23:21:55.4603786Z step_size_up (int): Number of training iterations in the 2025-08-26T23:21:55.4603935Z increasing half of a cycle. Default: 2000 2025-08-26T23:21:55.4604087Z step_size_down (int): Number of training iterations in the 2025-08-26T23:21:55.4604250Z decreasing half of a cycle. If step_size_down is None, 2025-08-26T23:21:55.4604400Z it is set to step_size_up. Default: None 2025-08-26T23:21:55.4605542Z mode (str): One of {triangular, triangular2, exp_range}. 2025-08-26T23:21:55.4605697Z Values correspond to policies detailed above. 2025-08-26T23:21:55.4605842Z If scale_fn is not None, this argument is ignored. 2025-08-26T23:21:55.4605973Z Default: 'triangular' 2025-08-26T23:21:55.4606109Z gamma (float): Constant in 'exp_range' scaling function: 2025-08-26T23:21:55.4606284Z gamma**(cycle iterations) 2025-08-26T23:21:55.4606395Z Default: 1.0 2025-08-26T23:21:55.4606526Z scale_fn (function): Custom scaling policy defined by a single 2025-08-26T23:21:55.4606676Z argument lambda function, where 2025-08-26T23:21:55.4606801Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-08-26T23:21:55.4606924Z If specified, then 'mode' is ignored. 2025-08-26T23:21:55.4608054Z Default: None 2025-08-26T23:21:55.4608194Z scale_mode (str): {'cycle', 'iterations'}. 2025-08-26T23:21:55.4608327Z Defines whether scale_fn is evaluated on 2025-08-26T23:21:55.4608461Z cycle number or cycle iterations (training 2025-08-26T23:21:55.4608591Z iterations since start of cycle). 2025-08-26T23:21:55.4608709Z Default: 'cycle' 2025-08-26T23:21:55.4608867Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T23:21:55.4609043Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T23:21:55.4609183Z Default: True 2025-08-26T23:21:55.4609322Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T23:21:55.4609510Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T23:21:55.4610735Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T23:21:55.4610892Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T23:21:55.4611019Z Default: 0.8 2025-08-26T23:21:55.4611156Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T23:21:55.4611318Z for each parameter group. Functionally, 2025-08-26T23:21:55.4611474Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T23:21:55.4611649Z The momentum at any cycle is the difference of max_momentum 2025-08-26T23:21:55.4611805Z and some scaling of the amplitude; therefore 2025-08-26T23:21:55.4611990Z base_momentum may not actually be reached depending on 2025-08-26T23:21:55.4612154Z scaling function. Note that momentum is cycled inversely 2025-08-26T23:21:55.4612330Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T23:21:55.4613443Z and learning rate is 'base_lr' 2025-08-26T23:21:55.4613559Z Default: 0.9 2025-08-26T23:21:55.4613700Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T23:21:55.4613896Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T23:21:55.4614086Z batch instead of after each epoch, this number represents the total 2025-08-26T23:21:55.4614277Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T23:21:55.4614464Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T23:21:55.4614608Z Default: -1 2025-08-26T23:21:55.4614671Z 2025-08-26T23:21:55.4614706Z Example: 2025-08-26T23:21:55.4614795Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4614948Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T23:21:55.4616070Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-08-26T23:21:55.4616204Z ... optimizer, 2025-08-26T23:21:55.4616303Z ... base_lr=0.01, 2025-08-26T23:21:55.4616404Z ... max_lr=0.1, 2025-08-26T23:21:55.4616507Z ... step_size_up=10, 2025-08-26T23:21:55.4616608Z ... ) 2025-08-26T23:21:55.4616714Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T23:21:55.4616847Z >>> for epoch in range(10): 2025-08-26T23:21:55.4616961Z >>> for batch in data_loader: 2025-08-26T23:21:55.4617076Z >>> train_batch(...) 2025-08-26T23:21:55.4617191Z >>> scheduler.step() 2025-08-26T23:21:55.4617292Z 2025-08-26T23:21:55.4618297Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-08-26T23:21:55.4618395Z 2025-08-26T23:21:55.4618507Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-08-26T23:21:55.4618713Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-08-26T23:21:55.4618837Z 2025-08-26T23:21:55.4618971Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4619098Z 2025-08-26T23:21:55.4619339Z msg = Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1722. 2025-08-26T23:21:55.4619674Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4619891Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-08-26T23:21:55.4620036Z 2025-08-26T23:21:55.4620106Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-08-26T23:21:55.4620293Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-08-26T23:21:55.4620555Z of epochs between two warm restarts in SGDR: 2025-08-26T23:21:55.4620640Z 2025-08-26T23:21:55.4621679Z .. math:: 2025-08-26T23:21:55.4621798Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-08-26T23:21:55.4621956Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-08-26T23:21:55.4622046Z 2025-08-26T23:21:55.4622114Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-08-26T23:21:55.4622282Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-08-26T23:21:55.4622386Z 2025-08-26T23:21:55.4622428Z It has been proposed in 2025-08-26T23:21:55.4622559Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-08-26T23:21:55.4622656Z 2025-08-26T23:21:55.4622692Z Args: 2025-08-26T23:21:55.4622789Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:21:55.4622938Z T_0 (int): Number of iterations until the first restart. 2025-08-26T23:21:55.4623166Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-08-26T23:21:55.4624342Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-08-26T23:21:55.4624527Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-08-26T23:21:55.4624643Z 2025-08-26T23:21:55.4624710Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-08-26T23:21:55.4624855Z https://arxiv.org/abs/1608.03983 2025-08-26T23:21:55.4624936Z 2025-08-26T23:21:55.4624969Z Example: 2025-08-26T23:21:55.4625058Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4625194Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-08-26T23:21:55.4625383Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-08-26T23:21:55.4625545Z ... optimizer, T_0=20 2025-08-26T23:21:55.4625648Z ... ) 2025-08-26T23:21:55.4625737Z >>> for epoch in range(100): 2025-08-26T23:21:55.4626803Z >>> train(...) 2025-08-26T23:21:55.4626908Z >>> validate(...) 2025-08-26T23:21:55.4627013Z >>> scheduler.step() 2025-08-26T23:21:55.4627084Z 2025-08-26T23:21:55.4627172Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-08-26T23:21:55.4627321Z 2025-08-26T23:21:55.4627451Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4627576Z 2025-08-26T23:21:55.4627770Z msg = Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1872. 2025-08-26T23:21:55.4628072Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.4628304Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-08-26T23:21:55.4628476Z 2025-08-26T23:21:55.4628582Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-08-26T23:21:55.4628824Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-08-26T23:21:55.4630029Z lower than the initial learning rate. 2025-08-26T23:21:55.4630188Z This policy was initially described in the paper `Super-Convergence: 2025-08-26T23:21:55.4630455Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-08-26T23:21:55.4630591Z 2025-08-26T23:21:55.4630679Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-08-26T23:21:55.4630873Z `step` should be called after a batch has been used for training. 2025-08-26T23:21:55.4630979Z 2025-08-26T23:21:55.4631022Z This scheduler is not chainable. 2025-08-26T23:21:55.4631098Z 2025-08-26T23:21:55.4631222Z Note also that the total number of steps in the cycle can be determined in one 2025-08-26T23:21:55.4631396Z of two ways (listed in order of precedence): 2025-08-26T23:21:55.4631482Z 2025-08-26T23:21:55.4631541Z #. A value for total_steps is explicitly provided. 2025-08-26T23:21:55.4631701Z #. A number of epochs (epochs) and a number of steps per epoch 2025-08-26T23:21:55.4632841Z (steps_per_epoch) are provided. 2025-08-26T23:21:55.4632984Z In this case, the number of total steps is inferred by 2025-08-26T23:21:55.4633127Z total_steps = epochs * steps_per_epoch 2025-08-26T23:21:55.4633208Z 2025-08-26T23:21:55.4633296Z You must either provide a value for total_steps or provide a value for both 2025-08-26T23:21:55.4633457Z epochs and steps_per_epoch. 2025-08-26T23:21:55.4633529Z 2025-08-26T23:21:55.4633637Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-08-26T23:21:55.4633879Z claims that "unpublished work has shown even better results by using only two phases". To 2025-08-26T23:21:55.4634104Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-08-26T23:21:55.4634230Z 2025-08-26T23:21:55.4634297Z Args: 2025-08-26T23:21:55.4634472Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:21:55.4634630Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T23:21:55.4635762Z for each parameter group. 2025-08-26T23:21:55.4635919Z total_steps (int): The total number of steps in the cycle. Note that 2025-08-26T23:21:55.4636107Z if a value is not provided here, then it must be inferred by providing 2025-08-26T23:21:55.4636267Z a value for epochs and steps_per_epoch. 2025-08-26T23:21:55.4636388Z Default: None 2025-08-26T23:21:55.4636523Z epochs (int): The number of epochs to train for. This is used along 2025-08-26T23:21:55.4636718Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-08-26T23:21:55.4636895Z if a value for total_steps is not provided. 2025-08-26T23:21:55.4637019Z Default: None 2025-08-26T23:21:55.4637161Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-08-26T23:21:55.4637358Z used along with epochs in order to infer the total number of steps in the 2025-08-26T23:21:55.4638493Z cycle if a value for total_steps is not provided. 2025-08-26T23:21:55.4638624Z Default: None 2025-08-26T23:21:55.4638768Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-08-26T23:21:55.4638929Z increasing the learning rate. 2025-08-26T23:21:55.4639044Z Default: 0.3 2025-08-26T23:21:55.4639151Z anneal_strategy (str): {'cos', 'linear'} 2025-08-26T23:21:55.4639319Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-08-26T23:21:55.4639481Z linear annealing. 2025-08-26T23:21:55.4639586Z Default: 'cos' 2025-08-26T23:21:55.4639721Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T23:21:55.4639927Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T23:21:55.4641146Z Default: True 2025-08-26T23:21:55.4641285Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T23:21:55.4641472Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T23:21:55.4641643Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T23:21:55.4641833Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T23:21:55.4641958Z Default: 0.85 2025-08-26T23:21:55.4642093Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T23:21:55.4642255Z for each parameter group. Functionally, 2025-08-26T23:21:55.4642411Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T23:21:55.4642581Z Note that momentum is cycled inversely 2025-08-26T23:21:55.4642742Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T23:21:55.4643884Z and learning rate is 'base_lr' 2025-08-26T23:21:55.4643998Z Default: 0.95 2025-08-26T23:21:55.4644126Z div_factor (float): Determines the initial learning rate via 2025-08-26T23:21:55.4644271Z initial_lr = max_lr/div_factor 2025-08-26T23:21:55.4644382Z Default: 25 2025-08-26T23:21:55.4644458Z final_div_factor (float): Determines the minimum learning rate via 2025-08-26T23:21:55.4644506Z min_lr = initial_lr/final_div_factor 2025-08-26T23:21:55.4644542Z Default: 1e4 2025-08-26T23:21:55.4644632Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-08-26T23:21:55.4644723Z learning rate according to 'final_div_factor' instead of modifying the second 2025-08-26T23:21:55.4644812Z phase (the first two phases will be symmetrical about the step indicated by 2025-08-26T23:21:55.4644875Z 'pct_start'). 2025-08-26T23:21:55.4644957Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T23:21:55.4645035Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T23:21:55.4645113Z batch instead of after each epoch, this number represents the total 2025-08-26T23:21:55.4645196Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T23:21:55.4645267Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T23:21:55.4646270Z Default: -1 2025-08-26T23:21:55.4646273Z 2025-08-26T23:21:55.4646309Z Example: 2025-08-26T23:21:55.4646349Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.4646408Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T23:21:55.4646494Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-08-26T23:21:55.4646560Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-08-26T23:21:55.4646637Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-08-26T23:21:55.4646670Z ... ) 2025-08-26T23:21:55.4646711Z >>> for epoch in range(10): 2025-08-26T23:21:55.4646755Z >>> for batch in data_loader: 2025-08-26T23:21:55.4646794Z >>> train_batch(...) 2025-08-26T23:21:55.4646834Z >>> optimizer.step() 2025-08-26T23:21:55.4646873Z >>> scheduler.step() 2025-08-26T23:21:55.4646876Z 2025-08-26T23:21:55.4646941Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-08-26T23:21:55.4646943Z 2025-08-26T23:21:55.4647047Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-08-26T23:21:55.4647093Z https://arxiv.org/abs/1708.07120 2025-08-26T23:21:55.4647125Z 2025-08-26T23:21:55.4647214Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.4647249Z 2025-08-26T23:21:55.7272162Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_profile.py line=94. 2025-08-26T23:21:55.7272343Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.7272347Z 2025-08-26T23:21:55.7277343Z Registers a fake kernel based on the given operator profiles. This fake 2025-08-26T23:21:55.7277631Z kernel registration will override any existing fake kernel registrations. 2025-08-26T23:21:55.7277634Z 2025-08-26T23:21:55.7277722Z The input is a dictionary mapping operator names to a set of operator 2025-08-26T23:21:55.7277819Z profiles, which we will use to generate fake kernels. The operator profiles 2025-08-26T23:21:55.7277896Z are a record of the input and output tensor metadata. Based on this 2025-08-26T23:21:55.7278059Z information we will match a given input to the recorded profile, and return 2025-08-26T23:21:55.7278157Z an output with the same metadata as in the recorded profile. If a profile 2025-08-26T23:21:55.7278224Z doesn't exist then an exception will be thrown. 2025-08-26T23:21:55.7278226Z 2025-08-26T23:21:55.7278311Z The fake kernel generation is considered unsafe because it relies on the 2025-08-26T23:21:55.7278404Z rigid, pre-defined operator profiles that do not account for potential 2025-08-26T23:21:55.7278495Z variations in output behavior. Specifically, the generated kernels assume a 2025-08-26T23:21:55.7278591Z fixed relationship between input and output ranks. However, in reality, it's 2025-08-26T23:21:55.7278679Z possible that data-dependent operations may produce outputs of different 2025-08-26T23:21:55.7278764Z ranks even when given inputs of the same rank. The generated fake kernels 2025-08-26T23:21:55.7278845Z are inflexible and unable to accommodate these nuances, making them 2025-08-26T23:21:55.7278891Z potentially unsafe. 2025-08-26T23:21:55.7278896Z 2025-08-26T23:21:55.7278932Z Args: 2025-08-26T23:21:55.7279071Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-08-26T23:21:55.7279146Z name to a set of operator profiles from which we will generate fake 2025-08-26T23:21:55.7279182Z kernels. 2025-08-26T23:21:55.7279185Z 2025-08-26T23:21:55.7279218Z Examples: 2025-08-26T23:21:55.7279221Z 2025-08-26T23:21:55.7280930Z >>> # Example: Registering an op-profile from draft-export 2025-08-26T23:21:55.7280973Z >>> import torch 2025-08-26T23:21:55.7281043Z >>> from torch.export._draft_export import draft_export 2025-08-26T23:21:55.7281075Z >>> 2025-08-26T23:21:55.7281172Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-08-26T23:21:55.7281226Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T23:21:55.7281265Z >>> return x + y 2025-08-26T23:21:55.7281298Z >>> 2025-08-26T23:21:55.7281344Z >>> class M(torch.nn.Module): 2025-08-26T23:21:55.7281386Z >>> def forward(self, a, b): 2025-08-26T23:21:55.7281448Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-08-26T23:21:55.7281486Z >>> return res 2025-08-26T23:21:55.7281517Z >>> 2025-08-26T23:21:55.7281584Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-08-26T23:21:55.7281614Z >>> 2025-08-26T23:21:55.7281723Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-08-26T23:21:55.7281773Z >>> decomp = ep.run_decompositions() 2025-08-26T23:21:55.7281776Z 2025-08-26T23:21:55.7281778Z 2025-08-26T23:21:55.7281869Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.7281871Z 2025-08-26T23:21:55.7319996Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py line=397. 2025-08-26T23:21:55.7321182Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:55.7326519Z Register a FakeTensor implementation for this custom op. 2025-08-26T23:21:55.7326532Z 2025-08-26T23:21:55.7326644Z This is necessary to get the operator to work efficiently with torch.compile. 2025-08-26T23:21:55.7326648Z 2025-08-26T23:21:55.7326746Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-08-26T23:21:55.7326833Z specifies the behavior of this operator on Tensors that carry no data. 2025-08-26T23:21:55.7326991Z Given some input Tensors with certain properties 2025-08-26T23:21:55.7327090Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-08-26T23:21:55.7327148Z the output Tensors are. 2025-08-26T23:21:55.7327151Z 2025-08-26T23:21:55.7327233Z Please see :func:`torch.library.register_fake` for more details. 2025-08-26T23:21:55.7327316Z 2025-08-26T23:21:55.7327360Z Args: 2025-08-26T23:21:55.7327433Z fn (Callable): The function to register as the FakeTensor 2025-08-26T23:21:55.7327487Z implementation. 2025-08-26T23:21:55.7327492Z 2025-08-26T23:21:55.7327532Z Examples: 2025-08-26T23:21:55.7327582Z >>> import torch 2025-08-26T23:21:55.7327629Z >>> import numpy as np 2025-08-26T23:21:55.7327684Z >>> from torch import Tensor 2025-08-26T23:21:55.7327722Z >>> 2025-08-26T23:21:55.7327801Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T23:21:55.7327917Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-08-26T23:21:55.7328000Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T23:21:55.7328057Z >>> return (x @ weight.t()) + bias 2025-08-26T23:21:55.7328094Z >>> 2025-08-26T23:21:55.7328145Z >>> @linear.register_fake 2025-08-26T23:21:55.7328190Z >>> def _(x, weight, bias): 2025-08-26T23:21:55.7328237Z >>> assert x.dim() == 2 2025-08-26T23:21:55.7328349Z >>> assert weight.dim() == 2 2025-08-26T23:21:55.7328400Z >>> assert bias.dim() == 1 2025-08-26T23:21:55.7328455Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T23:21:55.7328515Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T23:21:55.7328569Z >>> assert x.device == weight.device 2025-08-26T23:21:55.7328635Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-08-26T23:21:55.7329989Z >>> 2025-08-26T23:21:55.7330036Z >>> x = torch.randn(2, 2) 2025-08-26T23:21:55.7330080Z >>> weight = torch.randn(2, 2) 2025-08-26T23:21:55.7330121Z >>> bias = torch.randn(2) 2025-08-26T23:21:55.7330176Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:21:55.7330248Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-08-26T23:21:55.7330301Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:21:55.7330487Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-08-26T23:21:55.7330519Z >>> 2025-08-26T23:21:55.7330596Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T23:21:55.7330669Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-08-26T23:21:55.7330717Z >>> def nonzero(x: Tensor) -> Tensor: 2025-08-26T23:21:55.7330761Z >>> x_np = x.cpu().numpy() 2025-08-26T23:21:55.7330813Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T23:21:55.7330866Z >>> return torch.tensor(res, device=x.device) 2025-08-26T23:21:55.7330898Z >>> 2025-08-26T23:21:55.7330940Z >>> @nonzero.register_fake 2025-08-26T23:21:55.7330979Z >>> def _(x): 2025-08-26T23:21:55.7331039Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T23:21:55.7331143Z >>> # Since we cannot peek at the data in an abstract impl, 2025-08-26T23:21:55.7331203Z >>> # we use the ctx object to construct a new symint that 2025-08-26T23:21:55.7332357Z >>> # represents the data-dependent size. 2025-08-26T23:21:55.7332407Z >>> ctx = torch.library.get_ctx() 2025-08-26T23:21:55.7332455Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T23:21:55.7332496Z >>> shape = [nnz, x.dim()] 2025-08-26T23:21:55.7332621Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T23:21:55.7332662Z >>> return result 2025-08-26T23:21:55.7332694Z >>> 2025-08-26T23:21:55.7332740Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-08-26T23:21:55.7332792Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:21:55.7332849Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-08-26T23:21:55.7332921Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:21:55.7332975Z >>> assert torch.allclose(out, x.nonzero()) 2025-08-26T23:21:55.7332978Z 2025-08-26T23:21:55.7333010Z 2025-08-26T23:21:55.7333197Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-08-26T23:21:55.7333200Z 2025-08-26T23:21:55.7333232Z _._ = None 2025-08-26T23:21:55.7333262Z ^ 2025-08-26T23:21:55.7354855Z msg = Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/triton.py line=96. 2025-08-26T23:21:55.7354963Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.7355198Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-08-26T23:21:55.7355222Z 2025-08-26T23:21:55.7355300Z This is a more structured way of using triton kernels with PyTorch. 2025-08-26T23:21:55.7357717Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-08-26T23:21:55.7357916Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-08-26T23:21:55.7357959Z that is simpler; 2025-08-26T23:21:55.7358050Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-08-26T23:21:55.7358138Z want to create an operator that behaves like PyTorch built-in operators. 2025-08-26T23:21:55.7358222Z For example, you may use a ``torch.library`` wrapper API to define the 2025-08-26T23:21:55.7358303Z behavior of the triton kernel when passed a tensor subclass or under 2025-08-26T23:21:55.7358344Z a TorchDispatchMode. 2025-08-26T23:21:55.7358347Z 2025-08-26T23:21:55.7358437Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-08-26T23:21:55.7358478Z when the implementation 2025-08-26T23:21:55.7358561Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-08-26T23:21:55.7358629Z custom operators as opaque (:func:`torch.compile` and 2025-08-26T23:21:55.7358715Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-08-26T23:21:55.7358798Z makes the implementation visible to these subsystems, allowing them 2025-08-26T23:21:55.7358851Z to optimize the triton kernel(s). 2025-08-26T23:21:55.7358853Z 2025-08-26T23:21:55.7358925Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-08-26T23:21:55.7359010Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-08-26T23:21:55.7359087Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-08-26T23:21:55.7359089Z 2025-08-26T23:21:55.7359125Z Args: 2025-08-26T23:21:55.7359209Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-08-26T23:21:55.7360838Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-08-26T23:21:55.7360919Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-08-26T23:21:55.7361057Z To avoid name collisions, please use your project name as the namespace; 2025-08-26T23:21:55.7361132Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-08-26T23:21:55.7361232Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-08-26T23:21:55.7361317Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-08-26T23:21:55.7361435Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-08-26T23:21:55.7361507Z schema (None | str): A schema string for the operator. If None 2025-08-26T23:21:55.7361582Z (recommended) we'll infer a schema for the operator from its type 2025-08-26T23:21:55.7361668Z annotations. We recommend letting us infer a schema unless you 2025-08-26T23:21:55.7361735Z have a specific reason not to. 2025-08-26T23:21:55.7361797Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-08-26T23:21:55.7361803Z 2025-08-26T23:21:55.7361839Z Example:: 2025-08-26T23:21:55.7361841Z 2025-08-26T23:21:55.7361895Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:55.7361934Z >>> import torch 2025-08-26T23:21:55.7361994Z >>> from torch.library import triton_op, wrap_triton 2025-08-26T23:21:55.7362027Z >>> 2025-08-26T23:21:55.7362064Z >>> import triton 2025-08-26T23:21:55.7362114Z >>> from triton import language as tl 2025-08-26T23:21:55.7362145Z >>> 2025-08-26T23:21:55.7362181Z >>> @triton.jit 2025-08-26T23:21:55.7362218Z >>> def add_kernel( 2025-08-26T23:21:55.7362256Z >>> in_ptr0, 2025-08-26T23:21:55.7362290Z >>> in_ptr1, 2025-08-26T23:21:55.7362326Z >>> out_ptr, 2025-08-26T23:21:55.7362362Z >>> n_elements, 2025-08-26T23:21:55.7362408Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T23:21:55.7362442Z >>> ): 2025-08-26T23:21:55.7362507Z >>> pid = tl.program_id(axis=0) 2025-08-26T23:21:55.7363695Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T23:21:55.7363760Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T23:21:55.7363802Z >>> mask = offsets < n_elements 2025-08-26T23:21:55.7363853Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T23:21:55.7363900Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T23:21:55.7363943Z >>> output = x + y 2025-08-26T23:21:55.7363999Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T23:21:55.7364032Z >>> 2025-08-26T23:21:55.7364083Z >>> @triton_op("mylib::add", mutates_args={}) 2025-08-26T23:21:55.7364158Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-08-26T23:21:55.7364206Z >>> output = torch.empty_like(x) 2025-08-26T23:21:55.7364250Z >>> n_elements = output.numel() 2025-08-26T23:21:55.7364282Z >>> 2025-08-26T23:21:55.7364321Z >>> def grid(meta): 2025-08-26T23:21:55.7364385Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T23:21:55.7364418Z >>> 2025-08-26T23:21:55.7364485Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-08-26T23:21:55.7364554Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-08-26T23:21:55.7364594Z >>> return output 2025-08-26T23:21:55.7364626Z >>> 2025-08-26T23:21:55.7364664Z >>> @torch.compile 2025-08-26T23:21:55.7364700Z >>> def f(x, y): 2025-08-26T23:21:55.7365755Z >>> return add(x, y) 2025-08-26T23:21:55.7365789Z >>> 2025-08-26T23:21:55.7365836Z >>> x = torch.randn(3, device="cuda") 2025-08-26T23:21:55.7365882Z >>> y = torch.randn(3, device="cuda") 2025-08-26T23:21:55.7365912Z >>> 2025-08-26T23:21:55.7365972Z >>> z = f(x, y) 2025-08-26T23:21:55.7366017Z >>> assert torch.allclose(z, x + y) 2025-08-26T23:21:55.7366020Z 2025-08-26T23:21:55.7366050Z 2025-08-26T23:21:55.7366141Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.7366144Z 2025-08-26T23:21:55.7366319Z msg = Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/triton.py line=296. 2025-08-26T23:21:55.7366427Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.7366496Z Allows capture of a triton kernel into a graph via make_fx or 2025-08-26T23:21:55.7366540Z non-strict ``torch.export``. 2025-08-26T23:21:55.7366542Z 2025-08-26T23:21:55.7366610Z These technologies perform Dispatcher-based tracing (via 2025-08-26T23:21:55.7366683Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-08-26T23:21:55.7366773Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-08-26T23:21:55.7366819Z can actually be traced into a graph. 2025-08-26T23:21:55.7366822Z 2025-08-26T23:21:55.7366897Z Please use this API together with :func:`torch.library.triton_op`. 2025-08-26T23:21:55.7366900Z 2025-08-26T23:21:55.7366934Z Examples: 2025-08-26T23:21:55.7366937Z 2025-08-26T23:21:55.7366976Z >>> # xdoctest: +SKIP 2025-08-26T23:21:55.7367013Z >>> import torch 2025-08-26T23:21:55.7367049Z >>> import triton 2025-08-26T23:21:55.7368068Z >>> from triton import language as tl 2025-08-26T23:21:55.7368138Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T23:21:55.7368188Z >>> from torch.library import wrap_triton 2025-08-26T23:21:55.7368218Z >>> 2025-08-26T23:21:55.7368253Z >>> @triton.jit 2025-08-26T23:21:55.7368290Z >>> def add_kernel( 2025-08-26T23:21:55.7368327Z >>> in_ptr0, 2025-08-26T23:21:55.7368360Z >>> in_ptr1, 2025-08-26T23:21:55.7368396Z >>> out_ptr, 2025-08-26T23:21:55.7368431Z >>> n_elements, 2025-08-26T23:21:55.7368493Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T23:21:55.7368525Z >>> ): 2025-08-26T23:21:55.7368568Z >>> pid = tl.program_id(axis=0) 2025-08-26T23:21:55.7368612Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T23:21:55.7368669Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T23:21:55.7368710Z >>> mask = offsets < n_elements 2025-08-26T23:21:55.7368761Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T23:21:55.7368810Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T23:21:55.7368848Z >>> output = x + y 2025-08-26T23:21:55.7368905Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T23:21:55.7368935Z >>> 2025-08-26T23:21:55.7369926Z >>> def add(x, y): 2025-08-26T23:21:55.7369975Z >>> output = torch.empty_like(x) 2025-08-26T23:21:55.7370019Z >>> n_elements = output.numel() 2025-08-26T23:21:55.7370051Z >>> 2025-08-26T23:21:55.7370092Z >>> def grid_fn(meta): 2025-08-26T23:21:55.7370156Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T23:21:55.7370188Z >>> 2025-08-26T23:21:55.7370257Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-08-26T23:21:55.7370296Z >>> return output 2025-08-26T23:21:55.7370326Z >>> 2025-08-26T23:21:55.7370453Z >>> x = torch.randn(3, device="cuda") 2025-08-26T23:21:55.7370497Z >>> y = torch.randn(3, device="cuda") 2025-08-26T23:21:55.7370539Z >>> gm = make_fx(add)(x, y) 2025-08-26T23:21:55.7370576Z >>> print(gm.code) 2025-08-26T23:21:55.7370619Z >>> # def forward(self, x_1, y_1): 2025-08-26T23:21:55.7370707Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-08-26T23:21:55.7370794Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-08-26T23:21:55.7370884Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-08-26T23:21:55.7370931Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-08-26T23:21:55.7370991Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-08-26T23:21:55.7371040Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-08-26T23:21:55.7371076Z >>> # }) 2025-08-26T23:21:55.7372105Z >>> # return empty_like 2025-08-26T23:21:55.7372108Z 2025-08-26T23:21:55.7372141Z 2025-08-26T23:21:55.7372232Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.7372234Z 2025-08-26T23:21:55.8663400Z msg = Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-08-26T23:21:55.8663956Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.8664210Z Return a new dict with new, potentially nested, key value pair 2025-08-26T23:21:55.8664338Z 2025-08-26T23:21:55.8664386Z >>> purchase = { 2025-08-26T23:21:55.8664509Z ... "name": "Alice", 2025-08-26T23:21:55.8664670Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:21:55.8667835Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:21:55.8667986Z ... } 2025-08-26T23:21:55.8668132Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-08-26T23:21:55.8668317Z {'credit card': '5555-1234-1234-1234', 2025-08-26T23:21:55.8668462Z 'name': 'Alice', 2025-08-26T23:21:55.8668615Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-08-26T23:21:55.8668766Z 2025-08-26T23:21:55.8668919Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.8669070Z 2025-08-26T23:21:55.8669396Z msg = Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-08-26T23:21:55.8669799Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.8670033Z Update value in a (potentially) nested dictionary 2025-08-26T23:21:55.8670207Z 2025-08-26T23:21:55.8670245Z inputs: 2025-08-26T23:21:55.8670578Z d - dictionary on which to operate 2025-08-26T23:21:55.8670750Z keys - list or tuple giving the location of the value to be changed in d 2025-08-26T23:21:55.8670929Z func - function to operate on that value 2025-08-26T23:21:55.8671021Z 2025-08-26T23:21:55.8671098Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-08-26T23:21:55.8671307Z original dictionary with v replaced by func(v), but does not mutate the 2025-08-26T23:21:55.8671491Z original dictionary. 2025-08-26T23:21:55.8671562Z 2025-08-26T23:21:55.8671653Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-08-26T23:21:55.8671865Z specified by the keys, with the innermost value set to func(default). 2025-08-26T23:21:55.8671992Z 2025-08-26T23:21:55.8672044Z >>> inc = lambda x: x + 1 2025-08-26T23:21:55.8672171Z >>> update_in({"a": 0}, ["a"], inc) 2025-08-26T23:21:55.8672297Z {'a': 1} 2025-08-26T23:21:55.8672352Z 2025-08-26T23:21:55.8672398Z >>> transaction = { 2025-08-26T23:21:55.8672507Z ... "name": "Alice", 2025-08-26T23:21:55.8672661Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:21:55.8672832Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:21:55.8672958Z ... } 2025-08-26T23:21:55.8673094Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-08-26T23:21:55.8673258Z {'credit card': '5555-1234-1234-1234', 2025-08-26T23:21:55.8673382Z 'name': 'Alice', 2025-08-26T23:21:55.8673561Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-08-26T23:21:55.8673667Z 2025-08-26T23:21:55.8675350Z >>> # updating a value when k0 is not in d 2025-08-26T23:21:55.8675504Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-08-26T23:21:55.8675636Z {1: {2: {3: 'bar'}}} 2025-08-26T23:21:55.8675747Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-08-26T23:21:55.8675871Z {1: 'foo', 2: {3: {4: 1}}} 2025-08-26T23:21:55.8675973Z 2025-08-26T23:21:55.8676151Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.8676283Z 2025-08-26T23:21:55.8676514Z msg = Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-08-26T23:21:55.8676874Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.8677095Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-08-26T23:21:55.8677201Z 2025-08-26T23:21:55.8677279Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-08-26T23:21:55.8678602Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-08-26T23:21:55.8678721Z 2025-08-26T23:21:55.8678804Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-08-26T23:21:55.8678973Z structures such as dictionaries and lists. 2025-08-26T23:21:55.8679063Z 2025-08-26T23:21:55.8679101Z >>> transaction = { 2025-08-26T23:21:55.8679210Z ... "name": "Alice", 2025-08-26T23:21:55.8679349Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:21:55.8679511Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:21:55.8679631Z ... } 2025-08-26T23:21:55.8679735Z >>> get_in(["purchase", "items", 0], transaction) 2025-08-26T23:21:55.8679861Z 'Apple' 2025-08-26T23:21:55.8679957Z >>> get_in(["name"], transaction) 2025-08-26T23:21:55.8681193Z 'Alice' 2025-08-26T23:21:55.8681293Z >>> get_in(["purchase", "total"], transaction) 2025-08-26T23:21:55.8681467Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-08-26T23:21:55.8681609Z >>> get_in(["purchase", "items", 10], transaction) 2025-08-26T23:21:55.8681743Z >>> get_in(["purchase", "total"], transaction, 0) 2025-08-26T23:21:55.8681858Z 0 2025-08-26T23:21:55.8681942Z >>> get_in(["y"], {}, no_default=True) 2025-08-26T23:21:55.8682058Z Traceback (most recent call last): 2025-08-26T23:21:55.8682165Z ... 2025-08-26T23:21:55.8682243Z KeyError: 'y' 2025-08-26T23:21:55.8682295Z 2025-08-26T23:21:55.8682329Z See Also: 2025-08-26T23:21:55.8683382Z itertoolz.get 2025-08-26T23:21:55.8683479Z operator.getitem 2025-08-26T23:21:55.8683569Z 2025-08-26T23:21:55.8683697Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.8683823Z 2025-08-26T23:21:55.8684039Z msg = Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-08-26T23:21:55.8684377Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.8684545Z Group a collection by a key function 2025-08-26T23:21:55.8684621Z 2025-08-26T23:21:55.8684684Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-08-26T23:21:55.8684827Z >>> groupby(len, names) # doctest: +SKIP 2025-08-26T23:21:55.8684968Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-08-26T23:21:55.8685062Z 2025-08-26T23:21:55.8685104Z >>> iseven = lambda x: x % 2 == 0 2025-08-26T23:21:55.8686184Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-08-26T23:21:55.8686325Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-08-26T23:21:55.8686401Z 2025-08-26T23:21:55.8686457Z Non-callable keys imply grouping on a member. 2025-08-26T23:21:55.8686544Z 2025-08-26T23:21:55.8686614Z >>> groupby( 2025-08-26T23:21:55.8686698Z ... "gender", 2025-08-26T23:21:55.8686785Z ... [ 2025-08-26T23:21:55.8686874Z ... {"name": "Alice", "gender": "F"}, 2025-08-26T23:21:55.8686996Z ... {"name": "Bob", "gender": "M"}, 2025-08-26T23:21:55.8687117Z ... {"name": "Charlie", "gender": "M"}, 2025-08-26T23:21:55.8687228Z ... ], 2025-08-26T23:21:55.8687312Z ... ) # doctest:+SKIP 2025-08-26T23:21:55.8688376Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-08-26T23:21:55.8688516Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-08-26T23:21:55.8688633Z {'gender': 'M', 'name': 'Charlie'}]} 2025-08-26T23:21:55.8688710Z 2025-08-26T23:21:55.8688763Z Not to be confused with ``itertools.groupby`` 2025-08-26T23:21:55.8688847Z 2025-08-26T23:21:55.8688880Z See Also: 2025-08-26T23:21:55.8688958Z countby 2025-08-26T23:21:55.8689052Z 2025-08-26T23:21:55.8689181Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.8689306Z 2025-08-26T23:21:55.9181314Z msg = Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py line=734. 2025-08-26T23:21:55.9181939Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:55.9186337Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-08-26T23:21:55.9186809Z Label will only appear if CPU activity tracing is enabled. 2025-08-26T23:21:55.9187004Z 2025-08-26T23:21:55.9187105Z It is useful when tracing the code profile. 2025-08-26T23:21:55.9187261Z 2025-08-26T23:21:55.9187325Z Args: 2025-08-26T23:21:55.9187514Z name (str): Label assigned to the block of code. 2025-08-26T23:21:55.9187805Z node_id (int): ID of node, for distributed profiling. Unset in 2025-08-26T23:21:55.9188074Z non-distributed cases. 2025-08-26T23:21:55.9188205Z 2025-08-26T23:21:55.9188272Z Example: 2025-08-26T23:21:55.9188664Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-08-26T23:21:55.9188946Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-08-26T23:21:55.9189216Z >>> with torch.autograd.profiler.profile() as prof: 2025-08-26T23:21:55.9191812Z ... y = x**2 2025-08-26T23:21:55.9192000Z ... with torch.autograd.profiler.record_function( 2025-08-26T23:21:55.9192197Z ... "label-z" 2025-08-26T23:21:55.9192356Z ... ): # label the block 2025-08-26T23:21:55.9192520Z ... z = y**3 2025-08-26T23:21:55.9192670Z ... y.backward() 2025-08-26T23:21:55.9192819Z >>> # xdoctest: +IGNORE_WANT 2025-08-26T23:21:55.9193001Z >>> # NOTE: some columns were removed for brevity 2025-08-26T23:21:55.9193244Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-08-26T23:21:55.9193518Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:21:55.9193798Z Name Self CPU total % CPU time avg Number of Calls 2025-08-26T23:21:55.9195827Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:21:55.9196067Z pow 60.77% 47.470us 3 2025-08-26T23:21:55.9196268Z mul 21.73% 25.465us 2 2025-08-26T23:21:55.9196482Z PowBackward0 12.03% 121.891us 1 2025-08-26T23:21:55.9196746Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-08-26T23:21:55.9196992Z label-z 2.13% 12.421us 1 2025-08-26T23:21:55.9197233Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-08-26T23:21:55.9197495Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:21:55.9197783Z Self CPU time total: 234.344us 2025-08-26T23:21:55.9197956Z CUDA time total: 0.000us 2025-08-26T23:21:55.9198061Z 2025-08-26T23:21:55.9198109Z 2025-08-26T23:21:55.9199876Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:55.9200057Z 2025-08-26T23:21:56.1334225Z msg = Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-08-26T23:21:56.1334890Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1335266Z Register a container-like type as pytree node. 2025-08-26T23:21:56.1335447Z 2025-08-26T23:21:56.1335520Z Args: 2025-08-26T23:21:56.1335758Z cls (type): A Python type to treat as an internal pytree node. 2025-08-26T23:21:56.1336230Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-08-26T23:21:56.1336687Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-08-26T23:21:56.1337133Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-08-26T23:21:56.1337496Z passed to the ``unflatten_fn``. 2025-08-26T23:21:56.1342977Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-08-26T23:21:56.1343413Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-08-26T23:21:56.1343746Z The function should return an instance of ``cls``. 2025-08-26T23:21:56.1344061Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-08-26T23:21:56.1344382Z qualified name used when serializing the tree spec. 2025-08-26T23:21:56.1344724Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-08-26T23:21:56.1345230Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-08-26T23:21:56.1345615Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-08-26T23:21:56.1346010Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-08-26T23:21:56.1346395Z how to convert the custom json dumpable representation of the context back to the 2025-08-26T23:21:56.1346779Z original context. This is used for json deserialization, which is being used in 2025-08-26T23:21:56.1347072Z :mod:`torch.export` right now. 2025-08-26T23:21:56.1347209Z 2025-08-26T23:21:56.1347295Z Example:: 2025-08-26T23:21:56.1347382Z 2025-08-26T23:21:56.1347462Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1347677Z >>> # Registry a Python type with lambda functions 2025-08-26T23:21:56.1347904Z >>> register_pytree_node( 2025-08-26T23:21:56.1350569Z ... set, 2025-08-26T23:21:56.1350704Z ... lambda s: (sorted(s), None, None), 2025-08-26T23:21:56.1350871Z ... lambda children, _: set(children), 2025-08-26T23:21:56.1351012Z ... ) 2025-08-26T23:21:56.1351113Z 2025-08-26T23:21:56.1351285Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1351446Z 2025-08-26T23:21:56.1404618Z msg = Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1218. 2025-08-26T23:21:56.1404993Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1405136Z 2025-08-26T23:21:56.1405222Z Context passed to policy function during selective checkpointing. 2025-08-26T23:21:56.1405343Z 2025-08-26T23:21:56.1405431Z This class is used to pass relevant metadata to the policy function during 2025-08-26T23:21:56.1407308Z selective checkpointing. The metadata includes whether the current invocation 2025-08-26T23:21:56.1407620Z of the policy function is during recomputation or not. 2025-08-26T23:21:56.1407724Z 2025-08-26T23:21:56.1407764Z Example: 2025-08-26T23:21:56.1407857Z >>> # xdoctest: +SKIP(stub) 2025-08-26T23:21:56.1407965Z >>> 2025-08-26T23:21:56.1408069Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T23:21:56.1408213Z >>> print(ctx.is_recompute) 2025-08-26T23:21:56.1408327Z >>> 2025-08-26T23:21:56.1408500Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T23:21:56.1408674Z >>> 2025-08-26T23:21:56.1408777Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T23:21:56.1411007Z >>> fn, x, y, 2025-08-26T23:21:56.1411109Z >>> use_reentrant=False, 2025-08-26T23:21:56.1411227Z >>> context_fn=context_fn, 2025-08-26T23:21:56.1411414Z >>> ) 2025-08-26T23:21:56.1411459Z 2025-08-26T23:21:56.1411561Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1411691Z 2025-08-26T23:21:56.1411906Z msg = Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1358. 2025-08-26T23:21:56.1412245Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1412377Z 2025-08-26T23:21:56.1412462Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-08-26T23:21:56.1412584Z 2025-08-26T23:21:56.1412666Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-08-26T23:21:56.1412843Z operations are recomputed during the backward pass. 2025-08-26T23:21:56.1412939Z 2025-08-26T23:21:56.1414053Z Args: 2025-08-26T23:21:56.1414149Z policy_fn_or_list (Callable or List): 2025-08-26T23:21:56.1414297Z - If a policy function is provided, it should accept a 2025-08-26T23:21:56.1414486Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-08-26T23:21:56.1414716Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-08-26T23:21:56.1414912Z indicating whether the execution of the op should be recomputed or not. 2025-08-26T23:21:56.1415106Z - If a list of operations is provided, it is equivalent to a policy 2025-08-26T23:21:56.1415283Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-08-26T23:21:56.1415465Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-08-26T23:21:56.1415613Z operations. 2025-08-26T23:21:56.1415743Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-08-26T23:21:56.1416914Z raised if any tensors cached by selective activation checkpoint are 2025-08-26T23:21:56.1417107Z mutated in order to ensure correctness. If set to `True`, this check 2025-08-26T23:21:56.1417254Z is disabled. 2025-08-26T23:21:56.1417345Z Returns: 2025-08-26T23:21:56.1417434Z A tuple of two context managers. 2025-08-26T23:21:56.1417514Z 2025-08-26T23:21:56.1417549Z Example: 2025-08-26T23:21:56.1417633Z >>> # xdoctest: +REQUIRES(LINUX) 2025-08-26T23:21:56.1417746Z >>> import functools 2025-08-26T23:21:56.1417840Z >>> 2025-08-26T23:21:56.1417931Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-08-26T23:21:56.1418062Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-08-26T23:21:56.1419117Z >>> 2025-08-26T23:21:56.1419199Z >>> ops_to_save = [ 2025-08-26T23:21:56.1419306Z >>> torch.ops.aten.mm.default, 2025-08-26T23:21:56.1419416Z >>> ] 2025-08-26T23:21:56.1419490Z >>> 2025-08-26T23:21:56.1419580Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T23:21:56.1419703Z >>> if op in ops_to_save: 2025-08-26T23:21:56.1419822Z >>> return CheckpointPolicy.MUST_SAVE 2025-08-26T23:21:56.1419937Z >>> else: 2025-08-26T23:21:56.1420044Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-08-26T23:21:56.1420200Z >>> 2025-08-26T23:21:56.1421354Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T23:21:56.1421519Z >>> 2025-08-26T23:21:56.1421596Z >>> # or equivalently 2025-08-26T23:21:56.1421753Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-08-26T23:21:56.1421913Z >>> 2025-08-26T23:21:56.1421986Z >>> def fn(x, y): 2025-08-26T23:21:56.1422116Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-08-26T23:21:56.1422286Z >>> 2025-08-26T23:21:56.1422380Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T23:21:56.1422500Z >>> fn, x, y, 2025-08-26T23:21:56.1422594Z >>> use_reentrant=False, 2025-08-26T23:21:56.1423636Z >>> context_fn=context_fn, 2025-08-26T23:21:56.1423743Z >>> ) 2025-08-26T23:21:56.1423786Z 2025-08-26T23:21:56.1423902Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1424027Z 2025-08-26T23:21:56.1608936Z msg = Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-08-26T23:21:56.1609873Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1610227Z 2025-08-26T23:21:56.1610660Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-08-26T23:21:56.1611033Z 2025-08-26T23:21:56.1611326Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-08-26T23:21:56.1611942Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-08-26T23:21:56.1612499Z server like load. It can emulate multiple calling threads to a single module 2025-08-26T23:21:56.1613046Z provided. In the future we plan to enhance this component to support inter and 2025-08-26T23:21:56.1617024Z intra-op parallelism as well as multiple models running in a single process. 2025-08-26T23:21:56.1617386Z 2025-08-26T23:21:56.1617741Z Please note that even though nn.Module is supported, it might incur an overhead 2025-08-26T23:21:56.1618304Z from the need to hold GIL every time we execute Python code or pass around 2025-08-26T23:21:56.1618855Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-08-26T23:21:56.1619407Z model for inference deployment it is better to switch to using it in this 2025-08-26T23:21:56.1619825Z benchmark. 2025-08-26T23:21:56.1619956Z 2025-08-26T23:21:56.1620053Z Example:: 2025-08-26T23:21:56.1620184Z 2025-08-26T23:21:56.1620308Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:56.1620546Z >>> from torch.utils import ThroughputBenchmark 2025-08-26T23:21:56.1620681Z >>> bench = ThroughputBenchmark(my_module) 2025-08-26T23:21:56.1620823Z >>> # Pre-populate benchmark's data set with the inputs 2025-08-26T23:21:56.1622020Z >>> for input in inputs: 2025-08-26T23:21:56.1622171Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-08-26T23:21:56.1622338Z ... bench.add_input(input[0], x2=input[1]) 2025-08-26T23:21:56.1622491Z >>> # Inputs supplied above are randomly used during the execution 2025-08-26T23:21:56.1622637Z >>> stats = bench.benchmark( 2025-08-26T23:21:56.1622746Z ... num_calling_threads=4, 2025-08-26T23:21:56.1622857Z ... num_warmup_iters = 100, 2025-08-26T23:21:56.1622968Z ... num_iters = 1000, 2025-08-26T23:21:56.1623065Z ... ) 2025-08-26T23:21:56.1623177Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-08-26T23:21:56.1623341Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-08-26T23:21:56.1623441Z 2025-08-26T23:21:56.1624509Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1624637Z 2025-08-26T23:21:56.1692990Z msg = Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1159. 2025-08-26T23:21:56.1693389Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1693528Z 2025-08-26T23:21:56.1693591Z Create a :class:`setuptools.Extension` for C++. 2025-08-26T23:21:56.1693683Z 2025-08-26T23:21:56.1693769Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:21:56.1693969Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-08-26T23:21:56.1694084Z 2025-08-26T23:21:56.1694182Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:21:56.1694347Z constructor. Full list arguments can be found at 2025-08-26T23:21:56.1694562Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T23:21:56.1694713Z 2025-08-26T23:21:56.1694750Z .. warning:: 2025-08-26T23:21:56.1696858Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:21:56.1697136Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:21:56.1697337Z the user's responsibility in their library to not use APIs from 2025-08-26T23:21:56.1697527Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:21:56.1697723Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:21:56.1697914Z example, to give access to custom ops from python, the library should 2025-08-26T23:21:56.1698074Z register the ops through the dispatcher. 2025-08-26T23:21:56.1698161Z 2025-08-26T23:21:56.1698243Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:21:56.1698427Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:21:56.1698609Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:21:56.1698799Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:21:56.1698987Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:21:56.1700828Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:21:56.1700995Z CPython version of choice. 2025-08-26T23:21:56.1701070Z 2025-08-26T23:21:56.1701113Z Example: 2025-08-26T23:21:56.1701205Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1701361Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:21:56.1701495Z >>> from setuptools import setup 2025-08-26T23:21:56.1701652Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-08-26T23:21:56.1701796Z >>> setup( 2025-08-26T23:21:56.1701890Z ... name='extension', 2025-08-26T23:21:56.1701991Z ... ext_modules=[ 2025-08-26T23:21:56.1702089Z ... CppExtension( 2025-08-26T23:21:56.1702194Z ... name='extension', 2025-08-26T23:21:56.1702316Z ... sources=['extension.cpp'], 2025-08-26T23:21:56.1702442Z ... extra_compile_args=['-g'], 2025-08-26T23:21:56.1702584Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-08-26T23:21:56.1702718Z ... ], 2025-08-26T23:21:56.1702811Z ... cmdclass={ 2025-08-26T23:21:56.1704345Z ... 'build_ext': BuildExtension 2025-08-26T23:21:56.1704471Z ... }) 2025-08-26T23:21:56.1704521Z 2025-08-26T23:21:56.1704610Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1704740Z 2025-08-26T23:21:56.1704934Z msg = Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1229. 2025-08-26T23:21:56.1705244Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1705376Z 2025-08-26T23:21:56.1705437Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-08-26T23:21:56.1705530Z 2025-08-26T23:21:56.1705617Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:21:56.1705855Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-08-26T23:21:56.1706051Z extension. This includes the CUDA include path, library path and runtime 2025-08-26T23:21:56.1706197Z library. 2025-08-26T23:21:56.1706241Z 2025-08-26T23:21:56.1707611Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:21:56.1707778Z constructor. Full list arguments can be found at 2025-08-26T23:21:56.1707980Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T23:21:56.1708167Z 2025-08-26T23:21:56.1708203Z .. warning:: 2025-08-26T23:21:56.1708331Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:21:56.1708522Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:21:56.1708704Z the user's responsibility in their library to not use APIs from 2025-08-26T23:21:56.1708918Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:21:56.1709125Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:21:56.1709313Z example, to give access to custom ops from python, the library should 2025-08-26T23:21:56.1709469Z register the ops through the dispatcher. 2025-08-26T23:21:56.1709552Z 2025-08-26T23:21:56.1709631Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:21:56.1709813Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:21:56.1709994Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:21:56.1710178Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:21:56.1710462Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:21:56.1710647Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:21:56.1710801Z CPython version of choice. 2025-08-26T23:21:56.1710870Z 2025-08-26T23:21:56.1710907Z Example: 2025-08-26T23:21:56.1710994Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1711148Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:21:56.1711289Z >>> from setuptools import setup 2025-08-26T23:21:56.1711451Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-08-26T23:21:56.1711606Z >>> setup( 2025-08-26T23:21:56.1712750Z ... name='cuda_extension', 2025-08-26T23:21:56.1712862Z ... ext_modules=[ 2025-08-26T23:21:56.1712963Z ... CUDAExtension( 2025-08-26T23:21:56.1713072Z ... name='cuda_extension', 2025-08-26T23:21:56.1713209Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:21:56.1713356Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T23:21:56.1713488Z ... 'nvcc': ['-O2']}, 2025-08-26T23:21:56.1713627Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-08-26T23:21:56.1713750Z ... ], 2025-08-26T23:21:56.1713831Z ... cmdclass={ 2025-08-26T23:21:56.1713931Z ... 'build_ext': BuildExtension 2025-08-26T23:21:56.1715072Z ... }) 2025-08-26T23:21:56.1715125Z 2025-08-26T23:21:56.1715164Z Compute capabilities: 2025-08-26T23:21:56.1715224Z 2025-08-26T23:21:56.1715328Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T23:21:56.1715574Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-08-26T23:21:56.1715813Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-08-26T23:21:56.1716054Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-08-26T23:21:56.1716292Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-08-26T23:21:56.1716472Z support (see below for details on PTX). 2025-08-26T23:21:56.1716550Z 2025-08-26T23:21:56.1716694Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-08-26T23:21:56.1716879Z CCs you want the extension to support: 2025-08-26T23:21:56.1716958Z 2025-08-26T23:21:56.1717027Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-08-26T23:21:56.1718166Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-08-26T23:21:56.1718286Z 2025-08-26T23:21:56.1718420Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-08-26T23:21:56.1718673Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-08-26T23:21:56.1718919Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-08-26T23:21:56.1719158Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-08-26T23:21:56.1719425Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-08-26T23:21:56.1719671Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-08-26T23:21:56.1719912Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-08-26T23:21:56.1720164Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-08-26T23:21:56.1720438Z "8.0 8.6" would be better. 2025-08-26T23:21:56.1720502Z 2025-08-26T23:21:56.1720610Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T23:21:56.1721814Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T23:21:56.1721950Z 2025-08-26T23:21:56.1722065Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-08-26T23:21:56.1722294Z To workaround the issue, move python binding logic to pure C++ file. 2025-08-26T23:21:56.1722409Z 2025-08-26T23:21:56.1722444Z Example use: 2025-08-26T23:21:56.1722564Z #include 2025-08-26T23:21:56.1722687Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-08-26T23:21:56.1722777Z 2025-08-26T23:21:56.1722811Z Instead of: 2025-08-26T23:21:56.1722897Z #include 2025-08-26T23:21:56.1723026Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-08-26T23:21:56.1723120Z 2025-08-26T23:21:56.1723217Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-08-26T23:21:56.1723520Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-08-26T23:21:56.1724687Z 2025-08-26T23:21:56.1724729Z Relocatable device code linking: 2025-08-26T23:21:56.1724802Z 2025-08-26T23:21:56.1724899Z If you want to reference device symbols across compilation units (across object files), 2025-08-26T23:21:56.1725124Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-08-26T23:21:56.1725375Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-08-26T23:21:56.1725642Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-08-26T23:21:56.1725900Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-08-26T23:21:56.1726113Z helps reduce the protentional perf degradation of `-rdc`. 2025-08-26T23:21:56.1726275Z Note that it needs to be used at both steps to be useful. 2025-08-26T23:21:56.1726371Z 2025-08-26T23:21:56.1726498Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-08-26T23:21:56.1726723Z There is also a case where `-dlink` is used without `-rdc`: 2025-08-26T23:21:56.1727855Z when an extension is linked against a static lib containing rdc-compiled objects 2025-08-26T23:21:56.1728089Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-08-26T23:21:56.1728201Z 2025-08-26T23:21:56.1728277Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-08-26T23:21:56.1728384Z 2025-08-26T23:21:56.1728418Z Example: 2025-08-26T23:21:56.1728501Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1728620Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:21:56.1728744Z >>> CUDAExtension( 2025-08-26T23:21:56.1728843Z ... name='cuda_extension', 2025-08-26T23:21:56.1728999Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:21:56.1729130Z ... dlink=True, 2025-08-26T23:21:56.1729237Z ... dlink_libraries=["dlink_lib"], 2025-08-26T23:21:56.1730309Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T23:21:56.1730536Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-08-26T23:21:56.1730653Z 2025-08-26T23:21:56.1730742Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1730869Z 2025-08-26T23:21:56.1731057Z msg = Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1420. 2025-08-26T23:21:56.1731363Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1731492Z 2025-08-26T23:21:56.1731553Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-08-26T23:21:56.1731650Z 2025-08-26T23:21:56.1731737Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:21:56.1731928Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-08-26T23:21:56.1732068Z extension. 2025-08-26T23:21:56.1732115Z 2025-08-26T23:21:56.1732190Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:21:56.1732330Z constructor. 2025-08-26T23:21:56.1732380Z 2025-08-26T23:21:56.1733375Z .. warning:: 2025-08-26T23:21:56.1733506Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:21:56.1733724Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:21:56.1733910Z the user's responsibility in their library to not use APIs from 2025-08-26T23:21:56.1734095Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:21:56.1734285Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:21:56.1734474Z example, to give access to custom ops from python, the library should 2025-08-26T23:21:56.1734632Z register the ops through the dispatcher. 2025-08-26T23:21:56.1734715Z 2025-08-26T23:21:56.1734793Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:21:56.1734977Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:21:56.1735157Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:21:56.1736684Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:21:56.1736877Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:21:56.1737064Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:21:56.1737217Z CPython version of choice. 2025-08-26T23:21:56.1737286Z 2025-08-26T23:21:56.1737320Z Example: 2025-08-26T23:21:56.1737405Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1737526Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:21:56.1737698Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-08-26T23:21:56.1737845Z >>> setup( 2025-08-26T23:21:56.1737936Z ... name='xpu_extension', 2025-08-26T23:21:56.1738043Z ... ext_modules=[ 2025-08-26T23:21:56.1739107Z ... SyclExtension( 2025-08-26T23:21:56.1739220Z ... name='xpu_extension', 2025-08-26T23:21:56.1739361Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-08-26T23:21:56.1739552Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-08-26T23:21:56.1739686Z ... ], 2025-08-26T23:21:56.1739768Z ... cmdclass={ 2025-08-26T23:21:56.1739869Z ... 'build_ext': BuildExtension 2025-08-26T23:21:56.1739975Z ... }) 2025-08-26T23:21:56.1740023Z 2025-08-26T23:21:56.1740130Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T23:21:56.1740486Z building process of the extension. If down the road a new card is installed the 2025-08-26T23:21:56.1740700Z extension may need to be recompiled. You can override the default behavior using 2025-08-26T23:21:56.1741880Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-08-26T23:21:56.1742055Z to support: 2025-08-26T23:21:56.1742102Z 2025-08-26T23:21:56.1742212Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-08-26T23:21:56.1742319Z 2025-08-26T23:21:56.1742429Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T23:21:56.1742667Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T23:21:56.1742804Z 2025-08-26T23:21:56.1742858Z Note: Ninja is required to build SyclExtension. 2025-08-26T23:21:56.1742945Z 2025-08-26T23:21:56.1743034Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1743157Z 2025-08-26T23:21:56.1743328Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1597. 2025-08-26T23:21:56.1743620Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1743748Z 2025-08-26T23:21:56.1743803Z Load a PyTorch C++ extension just-in-time (JIT). 2025-08-26T23:21:56.1743892Z 2025-08-26T23:21:56.1743969Z To load an extension, a Ninja build file is emitted, which is used to 2025-08-26T23:21:56.1745102Z compile the given sources into a dynamic library. This library is 2025-08-26T23:21:56.1745324Z subsequently loaded into the current Python process as a module and 2025-08-26T23:21:56.1745486Z returned from this function, ready for use. 2025-08-26T23:21:56.1745569Z 2025-08-26T23:21:56.1745645Z By default, the directory to which the build file is emitted and the 2025-08-26T23:21:56.1745836Z resulting library compiled to is ``/torch_extensions/``, where 2025-08-26T23:21:56.1746029Z ```` is the temporary folder on the current platform and ```` 2025-08-26T23:21:56.1746210Z the name of the extension. This location can be overridden in two ways. 2025-08-26T23:21:56.1746393Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-08-26T23:21:56.1746577Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-08-26T23:21:56.1746768Z into subfolders of this directory. Second, if the ``build_directory`` 2025-08-26T23:21:56.1747874Z argument to this function is supplied, it overrides the entire path, i.e. 2025-08-26T23:21:56.1748058Z the library will be compiled into that folder directly. 2025-08-26T23:21:56.1748153Z 2025-08-26T23:21:56.1748229Z To compile the sources, the default system compiler (``c++``) is used, 2025-08-26T23:21:56.1748422Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-08-26T23:21:56.1748619Z additional arguments to the compilation process, ``extra_cflags`` or 2025-08-26T23:21:56.1748809Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-08-26T23:21:56.1748997Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-08-26T23:21:56.1749166Z ``extra_cflags`` to pass further include directories. 2025-08-26T23:21:56.1749259Z 2025-08-26T23:21:56.1749341Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-08-26T23:21:56.1749525Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-08-26T23:21:56.1749739Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-08-26T23:21:56.1750945Z passing the CUDA lib64 directory as a library directory, and linking 2025-08-26T23:21:56.1751115Z ``cudart``. You can pass additional flags to nvcc via 2025-08-26T23:21:56.1751282Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-08-26T23:21:56.1751468Z heuristics for finding the CUDA install directory are used, which usually 2025-08-26T23:21:56.1751692Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-08-26T23:21:56.1751836Z safest option. 2025-08-26T23:21:56.1751889Z 2025-08-26T23:21:56.1751970Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-08-26T23:21:56.1752157Z files (``.sycl``) along with other sources. Such files will be detected 2025-08-26T23:21:56.1752339Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-08-26T23:21:56.1752544Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-08-26T23:21:56.1752726Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-08-26T23:21:56.1753818Z SYCL compiler is expected to be found via system PATH environment 2025-08-26T23:21:56.1753964Z variable. 2025-08-26T23:21:56.1754010Z 2025-08-26T23:21:56.1754042Z Args: 2025-08-26T23:21:56.1754162Z name: The name of the extension to build. This MUST be the same as the 2025-08-26T23:21:56.1754312Z name of the pybind11 module! 2025-08-26T23:21:56.1754541Z sources: A list of relative or absolute paths to C++ source files. 2025-08-26T23:21:56.1754727Z extra_cflags: optional list of compiler flags to forward to the build. 2025-08-26T23:21:56.1754919Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-08-26T23:21:56.1754978Z when building CUDA sources. 2025-08-26T23:21:56.1755055Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-08-26T23:21:56.1755106Z compiler when building SYCL sources. 2025-08-26T23:21:56.1755214Z extra_ldflags: optional list of linker flags to forward to the build. 2025-08-26T23:21:56.1755291Z extra_include_paths: optional list of include directories to forward 2025-08-26T23:21:56.1755327Z to the build. 2025-08-26T23:21:56.1756340Z build_directory: optional path to use as build workspace. 2025-08-26T23:21:56.1756411Z verbose: If ``True``, turns on verbose logging of load steps. 2025-08-26T23:21:56.1756489Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T23:21:56.1756551Z the build. If set to ``None`` (default), this value is 2025-08-26T23:21:56.1756624Z automatically determined based on the existence of ``.cu`` or 2025-08-26T23:21:56.1756687Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-08-26T23:21:56.1756729Z and libraries to be included. 2025-08-26T23:21:56.1756807Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T23:21:56.1756868Z the build. If set to ``None`` (default), this value is 2025-08-26T23:21:56.1756945Z automatically determined based on the existence of ``.sycl`` in 2025-08-26T23:21:56.1757008Z ``sources``. Set it to `True`` to force SYCL headers and 2025-08-26T23:21:56.1757050Z libraries to be included. 2025-08-26T23:21:56.1757124Z is_python_module: If ``True`` (default), imports the produced shared 2025-08-26T23:21:56.1757196Z library as a Python module. If ``False``, behavior depends on 2025-08-26T23:21:56.1757234Z ``is_standalone``. 2025-08-26T23:21:56.1757306Z is_standalone: If ``False`` (default) loads the constructed extension 2025-08-26T23:21:56.1757376Z into the process as a plain dynamic library. If ``True``, build a 2025-08-26T23:21:56.1757417Z standalone executable. 2025-08-26T23:21:56.1757420Z 2025-08-26T23:21:56.1757454Z Returns: 2025-08-26T23:21:56.1757498Z If ``is_python_module`` is ``True``: 2025-08-26T23:21:56.1757590Z Returns the loaded PyTorch extension as a Python module. 2025-08-26T23:21:56.1757593Z 2025-08-26T23:21:56.1757667Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-08-26T23:21:56.1758660Z Returns nothing. (The shared library is loaded into the process as 2025-08-26T23:21:56.1758697Z a side effect.) 2025-08-26T23:21:56.1758701Z 2025-08-26T23:21:56.1758742Z If ``is_standalone`` is ``True``. 2025-08-26T23:21:56.1758832Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-08-26T23:21:56.1758899Z added to the PATH environment variable as a side effect.) 2025-08-26T23:21:56.1758902Z 2025-08-26T23:21:56.1758934Z Example: 2025-08-26T23:21:56.1758974Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.1759025Z >>> from torch.utils.cpp_extension import load 2025-08-26T23:21:56.1759061Z >>> module = load( 2025-08-26T23:21:56.1759114Z ... name='extension', 2025-08-26T23:21:56.1759176Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:21:56.1759220Z ... extra_cflags=['-O2'], 2025-08-26T23:21:56.1759257Z ... verbose=True) 2025-08-26T23:21:56.1759259Z 2025-08-26T23:21:56.1759348Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1759350Z 2025-08-26T23:21:56.1759530Z msg = Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1882. 2025-08-26T23:21:56.1759622Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.1759624Z 2025-08-26T23:21:56.1759701Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-08-26T23:21:56.1759704Z 2025-08-26T23:21:56.1759784Z This function behaves exactly like :func:`load`, but takes its sources as 2025-08-26T23:21:56.1759866Z strings rather than filenames. These strings are stored to files in the 2025-08-26T23:21:56.1759944Z build directory, after which the behavior of :func:`load_inline` is 2025-08-26T23:21:56.1760005Z identical to :func:`load`. 2025-08-26T23:21:56.1760008Z 2025-08-26T23:21:56.1761021Z See `the 2025-08-26T23:21:56.1761142Z tests `_ 2025-08-26T23:21:56.1761189Z for good examples of using this function. 2025-08-26T23:21:56.1761191Z 2025-08-26T23:21:56.1761274Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-08-26T23:21:56.1761361Z the necessary header includes, as well as the (pybind11) binding code. More 2025-08-26T23:21:56.1761447Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-08-26T23:21:56.1761518Z single ``.cpp`` file. This file is then prepended with ``#include 2025-08-26T23:21:56.1761556Z `` 2025-08-26T23:21:56.1761559Z 2025-08-26T23:21:56.1761640Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-08-26T23:21:56.1761725Z automatically generated for each function specified. ``functions`` can 2025-08-26T23:21:56.1761804Z either be a list of function names, or a dictionary mapping from function 2025-08-26T23:21:56.1761883Z names to docstrings. If a list is given, the name of each function is used 2025-08-26T23:21:56.1761918Z as its docstring. 2025-08-26T23:21:56.1761921Z 2025-08-26T23:21:56.1761997Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-08-26T23:21:56.1762063Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-08-26T23:21:56.1762139Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-08-26T23:21:56.1762218Z separately, but ultimately linked into a single library. Note that no 2025-08-26T23:21:56.1762298Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-08-26T23:21:56.1762374Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-08-26T23:21:56.1762453Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-08-26T23:21:56.1762533Z include its name in ``functions``). 2025-08-26T23:21:56.1762537Z 2025-08-26T23:21:56.1763509Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-08-26T23:21:56.1763588Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-08-26T23:21:56.1763660Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-08-26T23:21:56.1763736Z linked into a single library. Note that no bindings are generated for 2025-08-26T23:21:56.1763836Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-08-26T23:21:56.1763911Z create a C++ function that calls it, and either declare or define this 2025-08-26T23:21:56.1763984Z C++ function in one of the ``cpp_sources`` (and include its name 2025-08-26T23:21:56.1764019Z in ``functions``). 2025-08-26T23:21:56.1764021Z 2025-08-26T23:21:56.1764041Z 2025-08-26T23:21:56.1764043Z 2025-08-26T23:21:56.1764113Z See :func:`load` for a description of arguments omitted below. 2025-08-26T23:21:56.1764117Z 2025-08-26T23:21:56.1764148Z Args: 2025-08-26T23:21:56.1764229Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-08-26T23:21:56.1764307Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-08-26T23:21:56.1764384Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-08-26T23:21:56.1764457Z functions: A list of function names for which to generate function 2025-08-26T23:21:56.1764534Z bindings. If a dictionary is given, it should map function names to 2025-08-26T23:21:56.1764602Z docstrings (which are otherwise just the function names). 2025-08-26T23:21:56.1764680Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T23:21:56.1764738Z the build. If set to ``None`` (default), this value is 2025-08-26T23:21:56.1764814Z automatically determined based on whether ``cuda_sources`` is 2025-08-26T23:21:56.1764872Z provided. Set it to ``True`` to force CUDA headers 2025-08-26T23:21:56.1764932Z and libraries to be included. 2025-08-26T23:21:56.1765009Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T23:21:56.1765954Z the build. If set to ``None`` (default), this value is 2025-08-26T23:21:56.1766028Z automatically determined based on whether ``sycl_sources`` is 2025-08-26T23:21:56.1766086Z provided. Set it to ``True`` to force SYCL headers 2025-08-26T23:21:56.1766129Z and libraries to be included. 2025-08-26T23:21:56.1766204Z with_pytorch_error_handling: Determines whether pytorch error and 2025-08-26T23:21:56.1766276Z warning macros are handled by pytorch instead of pybind. To do 2025-08-26T23:21:56.1766356Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-08-26T23:21:56.1766429Z function. This redirection might cause issues in obscure cases 2025-08-26T23:21:56.1766496Z of cpp. This flag should be set to ``False`` when this redirect 2025-08-26T23:21:56.1766534Z causes issues. 2025-08-26T23:21:56.1766625Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-08-26T23:21:56.1766706Z ``#include `` and ``#include `` lines. 2025-08-26T23:21:56.1766767Z Use this option to improve cold start times when you 2025-08-26T23:21:56.1766858Z already include the necessary headers in your source code. Default: ``False``. 2025-08-26T23:21:56.1766861Z 2025-08-26T23:21:56.1766895Z Example: 2025-08-26T23:21:56.1766951Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:21:56.1767010Z >>> from torch.utils.cpp_extension import load_inline 2025-08-26T23:21:56.1767046Z >>> source = """ 2025-08-26T23:21:56.1767105Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-08-26T23:21:56.1767148Z return x.sin() + y.sin(); 2025-08-26T23:21:56.1767179Z } 2025-08-26T23:21:56.1768119Z """ 2025-08-26T23:21:56.1768177Z >>> module = load_inline(name='inline_extension', 2025-08-26T23:21:56.1768225Z ... cpp_sources=[source], 2025-08-26T23:21:56.1768271Z ... functions=['sin_add']) 2025-08-26T23:21:56.1768273Z 2025-08-26T23:21:56.1768307Z .. note:: 2025-08-26T23:21:56.1768394Z Since load_inline will just-in-time compile the source code, please ensure 2025-08-26T23:21:56.1768506Z that you have the right toolchains installed in the runtime. For example, 2025-08-26T23:21:56.1768584Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-08-26T23:21:56.1768669Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-08-26T23:21:56.1768756Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-08-26T23:21:56.1768853Z are not included when you install torch and must be additionally installed. 2025-08-26T23:21:56.1768855Z 2025-08-26T23:21:56.1768948Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-08-26T23:21:56.1769025Z the extension. This may use up too many resources on some systems. One 2025-08-26T23:21:56.1769103Z can control the number of workers by setting the `MAX_JOBS` environment 2025-08-26T23:21:56.1769148Z variable to a non-negative number. 2025-08-26T23:21:56.1769150Z 2025-08-26T23:21:56.1769237Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.1769241Z 2025-08-26T23:21:56.2096730Z msg = Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py line=227. 2025-08-26T23:21:56.2097058Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2097330Z Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights). 2025-08-26T23:21:56.2097348Z 2025-08-26T23:21:56.2097446Z Args: 2025-08-26T23:21:56.2100967Z weights (sequence) : a sequence of weights, not necessary summing up to one 2025-08-26T23:21:56.2101042Z num_samples (int): number of samples to draw 2025-08-26T23:21:56.2101130Z replacement (bool): if ``True``, samples are drawn with replacement. 2025-08-26T23:21:56.2101208Z If not, they are drawn without replacement, which means that when a 2025-08-26T23:21:56.2101287Z sample index is drawn for a row, it cannot be drawn again for that row. 2025-08-26T23:21:56.2101353Z generator (Generator): Generator used in sampling. 2025-08-26T23:21:56.2101356Z 2025-08-26T23:21:56.2101392Z Example: 2025-08-26T23:21:56.2101452Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:56.2101485Z >>> list( 2025-08-26T23:21:56.2101533Z ... WeightedRandomSampler( 2025-08-26T23:21:56.2101594Z ... [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True 2025-08-26T23:21:56.2101626Z ... ) 2025-08-26T23:21:56.2101662Z ... ) 2025-08-26T23:21:56.2101697Z [4, 4, 1, 4, 5] 2025-08-26T23:21:56.2101730Z >>> list( 2025-08-26T23:21:56.2101777Z ... WeightedRandomSampler( 2025-08-26T23:21:56.2101837Z ... [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False 2025-08-26T23:21:56.2101872Z ... ) 2025-08-26T23:21:56.2101907Z ... ) 2025-08-26T23:21:56.2101940Z [0, 1, 4, 3, 2] 2025-08-26T23:21:56.2101972Z 2025-08-26T23:21:56.2102065Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2102067Z 2025-08-26T23:21:56.2103391Z msg = Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py line=300. 2025-08-26T23:21:56.2103490Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2103560Z Wraps another sampler to yield a mini-batch of indices. 2025-08-26T23:21:56.2103597Z 2025-08-26T23:21:56.2103630Z Args: 2025-08-26T23:21:56.2103714Z sampler (Sampler or Iterable): Base sampler. Can be any iterable object 2025-08-26T23:21:56.2103764Z batch_size (int): Size of mini-batch. 2025-08-26T23:21:56.2103838Z drop_last (bool): If ``True``, the sampler will drop the last batch if 2025-08-26T23:21:56.2103889Z its size would be less than ``batch_size`` 2025-08-26T23:21:56.2103892Z 2025-08-26T23:21:56.2103926Z Example: 2025-08-26T23:21:56.2103979Z >>> list( 2025-08-26T23:21:56.2104023Z ... BatchSampler( 2025-08-26T23:21:56.2104097Z ... SequentialSampler(range(10)), batch_size=3, drop_last=False 2025-08-26T23:21:56.2104130Z ... ) 2025-08-26T23:21:56.2104161Z ... ) 2025-08-26T23:21:56.2104203Z [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] 2025-08-26T23:21:56.2104254Z >>> list( 2025-08-26T23:21:56.2104345Z ... BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True) 2025-08-26T23:21:56.2104378Z ... ) 2025-08-26T23:21:56.2104417Z [[0, 1, 2], [3, 4, 5], [6, 7, 8]] 2025-08-26T23:21:56.2104449Z 2025-08-26T23:21:56.2104539Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2104541Z 2025-08-26T23:21:56.2140499Z msg = Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/distributed.py line=18. 2025-08-26T23:21:56.2140615Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2141532Z Sampler that restricts data loading to a subset of the dataset. 2025-08-26T23:21:56.2141556Z 2025-08-26T23:21:56.2141631Z It is especially useful in conjunction with 2025-08-26T23:21:56.2141737Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-08-26T23:21:56.2141889Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-08-26T23:21:56.2141986Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-08-26T23:21:56.2142274Z original dataset that is exclusive to it. 2025-08-26T23:21:56.2142277Z 2025-08-26T23:21:56.2142341Z .. note:: 2025-08-26T23:21:56.2142441Z Dataset is assumed to be of constant size and that any instance of it always 2025-08-26T23:21:56.2142504Z returns the same elements in the same order. 2025-08-26T23:21:56.2142508Z 2025-08-26T23:21:56.2142553Z Args: 2025-08-26T23:21:56.2142615Z dataset: Dataset used for sampling. 2025-08-26T23:21:56.2142705Z num_replicas (int, optional): Number of processes participating in 2025-08-26T23:21:56.2142808Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-08-26T23:21:56.2142859Z current distributed group. 2025-08-26T23:21:56.2142957Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-08-26T23:21:56.2143036Z By default, :attr:`rank` is retrieved from the current distributed 2025-08-26T23:21:56.2143084Z group. 2025-08-26T23:21:56.2147421Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-08-26T23:21:56.2147467Z indices. 2025-08-26T23:21:56.2147546Z seed (int, optional): random seed used to shuffle the sampler if 2025-08-26T23:21:56.2147627Z :attr:`shuffle=True`. This number should be identical across all 2025-08-26T23:21:56.2147697Z processes in the distributed group. Default: ``0``. 2025-08-26T23:21:56.2147778Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-08-26T23:21:56.2147849Z tail of the data to make it evenly divisible across the number of 2025-08-26T23:21:56.2147920Z replicas. If ``False``, the sampler will add extra indices to make 2025-08-26T23:21:56.2147995Z the data evenly divisible across the replicas. Default: ``False``. 2025-08-26T23:21:56.2148075Z 2025-08-26T23:21:56.2148113Z .. warning:: 2025-08-26T23:21:56.2148188Z In distributed mode, calling the :meth:`set_epoch` method at 2025-08-26T23:21:56.2148281Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-08-26T23:21:56.2148372Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-08-26T23:21:56.2148422Z the same ordering will be always used. 2025-08-26T23:21:56.2148424Z 2025-08-26T23:21:56.2148458Z Example:: 2025-08-26T23:21:56.2148512Z 2025-08-26T23:21:56.2148558Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.2148636Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-08-26T23:21:56.2148708Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-08-26T23:21:56.2148754Z ... sampler=sampler) 2025-08-26T23:21:56.2148862Z >>> for epoch in range(start_epoch, n_epochs): 2025-08-26T23:21:56.2148905Z ... if is_distributed: 2025-08-26T23:21:56.2150212Z ... sampler.set_epoch(epoch) 2025-08-26T23:21:56.2150255Z ... train(loader) 2025-08-26T23:21:56.2150287Z 2025-08-26T23:21:56.2150494Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2150497Z 2025-08-26T23:21:56.2234186Z msg = Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py line=56. 2025-08-26T23:21:56.2238873Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2238904Z 2025-08-26T23:21:56.2239001Z Iterable-style DataPipe. 2025-08-26T23:21:56.2239006Z 2025-08-26T23:21:56.2239170Z All DataPipes that represent an iterable of data samples should subclass this. 2025-08-26T23:21:56.2239336Z This style of DataPipes is particularly useful when data come from a stream, or 2025-08-26T23:21:56.2239569Z when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its 2025-08-26T23:21:56.2240063Z elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``. 2025-08-26T23:21:56.2240070Z 2025-08-26T23:21:56.2240238Z All subclasses should overwrite :meth:`__iter__`, which would return an 2025-08-26T23:21:56.2240572Z iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its 2025-08-26T23:21:56.2240792Z method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should 2025-08-26T23:21:56.2240960Z override ``reset()`` if necessary. The common usages include resetting buffers, pointers, 2025-08-26T23:21:56.2241097Z and various state variables within the custom ``IterDataPipe``. 2025-08-26T23:21:56.2241102Z 2025-08-26T23:21:56.2241161Z Note: 2025-08-26T23:21:56.2241301Z Only `one` iterator can be valid for each ``IterDataPipe`` at a time, 2025-08-26T23:21:56.2241515Z and the creation a second iterator will invalidate the first one. This constraint is necessary because 2025-08-26T23:21:56.2241723Z some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators. 2025-08-26T23:21:56.2247646Z The code example below presents details on how this constraint looks in practice. 2025-08-26T23:21:56.2247866Z If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_. 2025-08-26T23:21:56.2247869Z 2025-08-26T23:21:56.2248050Z These DataPipes can be invoked in two ways, using the class constructor or applying their 2025-08-26T23:21:56.2248259Z functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes). 2025-08-26T23:21:56.2248443Z You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple 2025-08-26T23:21:56.2248529Z operations in succession. 2025-08-26T23:21:56.2248533Z 2025-08-26T23:21:56.2248733Z .. _GitHub IterDataPipe Single Iterator Issue: 2025-08-26T23:21:56.2248843Z https://github.com/pytorch/data/issues/45 2025-08-26T23:21:56.2248845Z 2025-08-26T23:21:56.2248898Z Note: 2025-08-26T23:21:56.2249045Z When a subclass is used with :class:`~torch.utils.data.DataLoader`, each 2025-08-26T23:21:56.2249204Z item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader` 2025-08-26T23:21:56.2249335Z iterator. When :attr:`num_workers > 0`, each worker process will have a 2025-08-26T23:21:56.2249562Z different copy of the DataPipe object, so it is often desired to configure 2025-08-26T23:21:56.2249701Z each copy independently to avoid having duplicate data returned from the 2025-08-26T23:21:56.2249840Z workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker 2025-08-26T23:21:56.2249979Z process, returns information about the worker. It can be used in either the 2025-08-26T23:21:56.2250167Z dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's 2025-08-26T23:21:56.2250254Z :attr:`worker_init_fn` option to modify each copy's behavior. 2025-08-26T23:21:56.2250259Z 2025-08-26T23:21:56.2250305Z Examples: 2025-08-26T23:21:56.2250451Z General Usage: 2025-08-26T23:21:56.2250516Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.2252234Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T23:21:56.2252301Z >>> dp = IterableWrapper(range(10)) 2025-08-26T23:21:56.2252391Z >>> map_dp_1 = Mapper(dp, lambda x: x + 1) # Using class constructor 2025-08-26T23:21:56.2252443Z >>> map_dp_2 = dp.map( 2025-08-26T23:21:56.2252492Z ... lambda x: x + 1 2025-08-26T23:21:56.2252559Z ... ) # Using functional form (recommended) 2025-08-26T23:21:56.2252605Z >>> list(map_dp_1) 2025-08-26T23:21:56.2252655Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T23:21:56.2252702Z >>> list(map_dp_2) 2025-08-26T23:21:56.2252749Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T23:21:56.2252876Z >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0) 2025-08-26T23:21:56.2252929Z >>> list(filter_dp) 2025-08-26T23:21:56.2252968Z [2, 4, 6, 8, 10] 2025-08-26T23:21:56.2253024Z Single Iterator Constraint Example: 2025-08-26T23:21:56.2253116Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T23:21:56.2253182Z >>> source_dp = IterableWrapper(range(10)) 2025-08-26T23:21:56.2253236Z >>> it1 = iter(source_dp) 2025-08-26T23:21:56.2253275Z >>> list(it1) 2025-08-26T23:21:56.2253322Z [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 2025-08-26T23:21:56.2253369Z >>> it1 = iter(source_dp) 2025-08-26T23:21:56.2253415Z >>> it2 = iter( 2025-08-26T23:21:56.2253460Z ... source_dp 2025-08-26T23:21:56.2254856Z ... ) # The creation of a new iterator invalidates `it1` 2025-08-26T23:21:56.2254904Z >>> next(it2) 2025-08-26T23:21:56.2254947Z 0 2025-08-26T23:21:56.2255038Z >>> next(it1) # Further usage of `it1` will raise a `RunTimeError` 2025-08-26T23:21:56.2255042Z 2025-08-26T23:21:56.2255151Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2255154Z 2025-08-26T23:21:56.2364708Z msg = Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155. 2025-08-26T23:21:56.2364857Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2364861Z 2025-08-26T23:21:56.2365028Z Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``. 2025-08-26T23:21:56.2365030Z 2025-08-26T23:21:56.2365078Z (functional name: ``groupby``). 2025-08-26T23:21:56.2365080Z 2025-08-26T23:21:56.2365227Z The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group 2025-08-26T23:21:56.2365408Z will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full, 2025-08-26T23:21:56.2365528Z the DataPipe will yield the largest batch with the same key, provided that its size is larger 2025-08-26T23:21:56.2365647Z than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``. 2025-08-26T23:21:56.2365649Z 2025-08-26T23:21:56.2365797Z After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity 2025-08-26T23:21:56.2365942Z will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``. 2025-08-26T23:21:56.2365944Z 2025-08-26T23:21:56.2365981Z Args: 2025-08-26T23:21:56.2366039Z datapipe: Iterable datapipe to be grouped 2025-08-26T23:21:56.2366145Z group_key_fn: Function used to generate group key from the data of the source datapipe 2025-08-26T23:21:56.2366256Z keep_key: Option to yield the matching key along with the items in a tuple, 2025-08-26T23:21:56.2368513Z resulting in `(key, [items])` otherwise returning [items] 2025-08-26T23:21:56.2368592Z buffer_size: The size of buffer for ungrouped data 2025-08-26T23:21:56.2368706Z group_size: The max size of each group, a batch is yielded as soon as it reaches this size 2025-08-26T23:21:56.2368838Z guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full 2025-08-26T23:21:56.2368976Z drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer 2025-08-26T23:21:56.2369026Z when the buffer is full 2025-08-26T23:21:56.2369029Z 2025-08-26T23:21:56.2369075Z Example: 2025-08-26T23:21:56.2369115Z >>> import os 2025-08-26T23:21:56.2369163Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.2369237Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:21:56.2369283Z >>> def group_fn(file): 2025-08-26T23:21:56.2369344Z ... return os.path.basename(file).split(".")[0] 2025-08-26T23:21:56.2369397Z >>> source_dp = IterableWrapper( 2025-08-26T23:21:56.2369505Z ... ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"] 2025-08-26T23:21:56.2369542Z ... ) 2025-08-26T23:21:56.2369603Z >>> dp0 = source_dp.groupby(group_key_fn=group_fn) 2025-08-26T23:21:56.2369641Z >>> list(dp0) 2025-08-26T23:21:56.2369710Z [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']] 2025-08-26T23:21:56.2369790Z >>> # A group is yielded as soon as its size equals to `group_size` 2025-08-26T23:21:56.2369862Z >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2) 2025-08-26T23:21:56.2369904Z >>> list(dp1) 2025-08-26T23:21:56.2369972Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T23:21:56.2371806Z >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size` 2025-08-26T23:21:56.2371860Z >>> dp2 = source_dp.groupby( 2025-08-26T23:21:56.2371906Z ... group_key_fn=group_fn, 2025-08-26T23:21:56.2371955Z ... buffer_size=3, 2025-08-26T23:21:56.2371995Z ... group_size=3, 2025-08-26T23:21:56.2372039Z ... guaranteed_group_size=2, 2025-08-26T23:21:56.2372072Z ... ) 2025-08-26T23:21:56.2372106Z >>> list(dp2) 2025-08-26T23:21:56.2372169Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T23:21:56.2372171Z 2025-08-26T23:21:56.2372266Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2372269Z 2025-08-26T23:21:56.2372522Z msg = Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18. 2025-08-26T23:21:56.2372639Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2372643Z 2025-08-26T23:21:56.2372783Z Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``). 2025-08-26T23:21:56.2372834Z 2025-08-26T23:21:56.2372866Z Args: 2025-08-26T23:21:56.2372934Z datapipe: Iterable datapipe that provides pathnames 2025-08-26T23:21:56.2373004Z mode: An optional string that specifies the mode in which 2025-08-26T23:21:56.2373084Z the file is opened by ``open()``. It defaults to ``r``, other options are 2025-08-26T23:21:56.2373149Z ``b`` for reading in binary mode and ``t`` for text mode. 2025-08-26T23:21:56.2373257Z encoding: An optional string that specifies the encoding of the 2025-08-26T23:21:56.2373356Z underlying file. It defaults to ``None`` to match the default encoding of ``open``. 2025-08-26T23:21:56.2374757Z length: Nominal length of the datapipe 2025-08-26T23:21:56.2374760Z 2025-08-26T23:21:56.2374794Z Note: 2025-08-26T23:21:56.2374908Z The opened file handles will be closed by Python's GC periodically. Users can choose 2025-08-26T23:21:56.2374977Z to close them explicitly. 2025-08-26T23:21:56.2374983Z 2025-08-26T23:21:56.2375018Z Example: 2025-08-26T23:21:56.2375058Z >>> # xdoctest: +SKIP 2025-08-26T23:21:56.2375112Z >>> from torchdata.datapipes.iter import ( 2025-08-26T23:21:56.2375151Z ... FileLister, 2025-08-26T23:21:56.2375186Z ... FileOpener, 2025-08-26T23:21:56.2375225Z ... StreamReader, 2025-08-26T23:21:56.2375257Z ... ) 2025-08-26T23:21:56.2375346Z >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt")) 2025-08-26T23:21:56.2375388Z >>> dp = FileOpener(dp) 2025-08-26T23:21:56.2375430Z >>> dp = StreamReader(dp) 2025-08-26T23:21:56.2375464Z >>> list(dp) 2025-08-26T23:21:56.2375504Z [('./abc.txt', 'abc')] 2025-08-26T23:21:56.2375506Z 2025-08-26T23:21:56.2375597Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2375599Z 2025-08-26T23:21:56.2401146Z msg = Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=375. 2025-08-26T23:21:56.2401305Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2401316Z 2025-08-26T23:21:56.2401480Z Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``). 2025-08-26T23:21:56.2401482Z 2025-08-26T23:21:56.2401557Z A list of the child DataPipes is returned from this operation. 2025-08-26T23:21:56.2401560Z 2025-08-26T23:21:56.2403596Z Args: 2025-08-26T23:21:56.2403671Z datapipe: Iterable DataPipe being filtered 2025-08-26T23:21:56.2403759Z num_instances: number of instances of the DataPipe to create 2025-08-26T23:21:56.2403906Z classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None`` 2025-08-26T23:21:56.2404023Z drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None`` 2025-08-26T23:21:56.2404142Z buffer_size: this defines the maximum number of inputs that the buffer can hold across all child 2025-08-26T23:21:56.2404212Z DataPipes while waiting for their values to be yielded. 2025-08-26T23:21:56.2404281Z Defaults to ``1000``. Use ``-1`` for the unlimited buffer. 2025-08-26T23:21:56.2404284Z 2025-08-26T23:21:56.2404319Z Examples: 2025-08-26T23:21:56.2404372Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:21:56.2404441Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:21:56.2404484Z >>> def odd_or_even(n): 2025-08-26T23:21:56.2404521Z ... return n % 2 2025-08-26T23:21:56.2404572Z >>> source_dp = IterableWrapper(range(5)) 2025-08-26T23:21:56.2404655Z >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even) 2025-08-26T23:21:56.2404693Z >>> list(dp1) 2025-08-26T23:21:56.2404729Z [0, 2, 4] 2025-08-26T23:21:56.2404767Z >>> list(dp2) 2025-08-26T23:21:56.2404800Z [1, 3] 2025-08-26T23:21:56.2404927Z >>> # It can also filter out any element that gets `None` from the `classifier_fn` 2025-08-26T23:21:56.2406310Z >>> def odd_or_even_no_zero(n): 2025-08-26T23:21:56.2406361Z ... return n % 2 if n != 0 else None 2025-08-26T23:21:56.2406413Z >>> dp1, dp2 = source_dp.demux( 2025-08-26T23:21:56.2406496Z ... num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True 2025-08-26T23:21:56.2406531Z ... ) 2025-08-26T23:21:56.2406565Z >>> list(dp1) 2025-08-26T23:21:56.2406597Z [2, 4] 2025-08-26T23:21:56.2406656Z >>> list(dp2) 2025-08-26T23:21:56.2406689Z [1, 3] 2025-08-26T23:21:56.2406691Z 2025-08-26T23:21:56.2406781Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2406784Z 2025-08-26T23:21:56.2407023Z msg = Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=594. 2025-08-26T23:21:56.2407137Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2407141Z 2025-08-26T23:21:56.2407253Z Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``). 2025-08-26T23:21:56.2407256Z 2025-08-26T23:21:56.2407377Z As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration, 2025-08-26T23:21:56.2407451Z and so on. It ends when the shortest input DataPipe is exhausted. 2025-08-26T23:21:56.2407453Z 2025-08-26T23:21:56.2407486Z Args: 2025-08-26T23:21:56.2407626Z datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted 2025-08-26T23:21:56.2407629Z 2025-08-26T23:21:56.2407661Z Example: 2025-08-26T23:21:56.2407712Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:21:56.2407780Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:21:56.2407821Z >>> dp1, dp2, dp3 = ( 2025-08-26T23:21:56.2407867Z ... IterableWrapper(range(3)), 2025-08-26T23:21:56.2409016Z ... IterableWrapper(range(10, 15)), 2025-08-26T23:21:56.2409062Z ... IterableWrapper(range(20, 25)), 2025-08-26T23:21:56.2409094Z ... ) 2025-08-26T23:21:56.2409135Z >>> list(dp1.mux(dp2, dp3)) 2025-08-26T23:21:56.2409176Z [0, 10, 20, 1, 11, 21, 2, 12, 22] 2025-08-26T23:21:56.2409178Z 2025-08-26T23:21:56.2409268Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2409271Z 2025-08-26T23:21:56.2409496Z msg = Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=665. 2025-08-26T23:21:56.2409587Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.2409589Z 2025-08-26T23:21:56.2409699Z Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``). 2025-08-26T23:21:56.2409703Z 2025-08-26T23:21:56.2409786Z The output is stopped as soon as the shortest input DataPipe is exhausted. 2025-08-26T23:21:56.2409791Z 2025-08-26T23:21:56.2409822Z Args: 2025-08-26T23:21:56.2409878Z *datapipes: Iterable DataPipes being aggregated 2025-08-26T23:21:56.2409882Z 2025-08-26T23:21:56.2409914Z Example: 2025-08-26T23:21:56.2409962Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:21:56.2410030Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:21:56.2410068Z >>> dp1, dp2, dp3 = ( 2025-08-26T23:21:56.2410113Z ... IterableWrapper(range(5)), 2025-08-26T23:21:56.2410157Z ... IterableWrapper(range(10, 15)), 2025-08-26T23:21:56.2410201Z ... IterableWrapper(range(20, 25)), 2025-08-26T23:21:56.2410232Z ... ) 2025-08-26T23:21:56.2410273Z >>> list(dp1.zip(dp2, dp3)) 2025-08-26T23:21:56.2411433Z [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)] 2025-08-26T23:21:56.2411438Z 2025-08-26T23:21:56.2411535Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.2411579Z 2025-08-26T23:21:56.6818520Z msg = Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_comparison.py line=1331. 2025-08-26T23:21:56.6819610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:56.6820105Z Asserts that ``actual`` and ``expected`` are close. 2025-08-26T23:21:56.6820232Z 2025-08-26T23:21:56.6820860Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-08-26T23:21:56.6821096Z 2025-08-26T23:21:56.6821175Z .. math:: 2025-08-26T23:21:56.6821247Z 2025-08-26T23:21:56.6827427Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-08-26T23:21:56.6827701Z 2025-08-26T23:21:56.6827991Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-08-26T23:21:56.6828323Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-08-26T23:21:56.6828486Z 2025-08-26T23:21:56.6828601Z In addition, they are only considered close if they have the same 2025-08-26T23:21:56.6828761Z 2025-08-26T23:21:56.6828870Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-08-26T23:21:56.6829100Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-08-26T23:21:56.6829314Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-08-26T23:21:56.6829510Z - stride (if ``check_stride`` is ``True``). 2025-08-26T23:21:56.6829633Z 2025-08-26T23:21:56.6829788Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-08-26T23:21:56.6830009Z 2025-08-26T23:21:56.6830208Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-08-26T23:21:56.6830702Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-08-26T23:21:56.6831044Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-08-26T23:21:56.6831329Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-08-26T23:21:56.6831516Z 2025-08-26T23:21:56.6831638Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-08-26T23:21:56.6831929Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-08-26T23:21:56.6832152Z definition above. 2025-08-26T23:21:56.6832227Z 2025-08-26T23:21:56.6832354Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-08-26T23:21:56.6832666Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-08-26T23:21:56.6833004Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-08-26T23:21:56.6833334Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-08-26T23:21:56.6833614Z their elements are considered close according to the above definition. 2025-08-26T23:21:56.6833754Z 2025-08-26T23:21:56.6833798Z .. note:: 2025-08-26T23:21:56.6833862Z 2025-08-26T23:21:56.6833996Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-08-26T23:21:56.6834294Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-08-26T23:21:56.6834633Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-08-26T23:21:56.6834791Z 2025-08-26T23:21:56.6834832Z Args: 2025-08-26T23:21:56.6834939Z actual (Any): Actual input. 2025-08-26T23:21:56.6835134Z expected (Any): Expected input. 2025-08-26T23:21:56.6835374Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-08-26T23:21:56.6835622Z are allowed. Otherwise type equality is required. 2025-08-26T23:21:56.6835869Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-08-26T23:21:56.6836171Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T23:21:56.6836454Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-08-26T23:21:56.6836731Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T23:21:56.6836978Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-08-26T23:21:56.6837249Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-08-26T23:21:56.6837505Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-08-26T23:21:56.6837740Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-08-26T23:21:56.6838004Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-08-26T23:21:56.6838311Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-08-26T23:21:56.6838554Z :func:`torch.promote_types`) before being compared. 2025-08-26T23:21:56.6838800Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-08-26T23:21:56.6839096Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-08-26T23:21:56.6839303Z compared. 2025-08-26T23:21:56.6839529Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-08-26T23:21:56.6839843Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-08-26T23:21:56.6840133Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-08-26T23:21:56.6840405Z should return the new message. 2025-08-26T23:21:56.6840489Z 2025-08-26T23:21:56.6840526Z Raises: 2025-08-26T23:21:56.6840660Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-08-26T23:21:56.6842458Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-08-26T23:21:56.6842679Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-08-26T23:21:56.6842951Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-08-26T23:21:56.6843153Z different types. 2025-08-26T23:21:56.6843347Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-08-26T23:21:56.6843631Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-08-26T23:21:56.6843903Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-08-26T23:21:56.6844153Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-08-26T23:21:56.6844336Z :attr:`~torch.Tensor.layout`. 2025-08-26T23:21:56.6844494Z AssertionError: If only one of corresponding tensors is quantized. 2025-08-26T23:21:56.6844735Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-08-26T23:21:56.6846095Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-08-26T23:21:56.6846333Z :attr:`~torch.Tensor.device`. 2025-08-26T23:21:56.6846522Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-08-26T23:21:56.6846789Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-08-26T23:21:56.6847088Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-08-26T23:21:56.6847248Z 2025-08-26T23:21:56.6847374Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-08-26T23:21:56.6847589Z ``dtype``'s, the maximum of both tolerances is used. 2025-08-26T23:21:56.6847682Z 2025-08-26T23:21:56.6847760Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6847901Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-08-26T23:21:56.6848030Z +===========================+============+==========+ 2025-08-26T23:21:56.6848167Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-08-26T23:21:56.6849329Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6849470Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-08-26T23:21:56.6849601Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6849733Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6849862Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6849992Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-08-26T23:21:56.6850120Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6850250Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-08-26T23:21:56.6850466Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6850598Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6850753Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6851906Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-08-26T23:21:56.6852038Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6852168Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6852297Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6852429Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6852558Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6852687Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6852814Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6852943Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6853074Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6853205Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:21:56.6854307Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6854435Z | other | ``0.0`` | ``0.0`` | 2025-08-26T23:21:56.6854559Z +---------------------------+------------+----------+ 2025-08-26T23:21:56.6854641Z 2025-08-26T23:21:56.6854677Z .. note:: 2025-08-26T23:21:56.6854729Z 2025-08-26T23:21:56.6854863Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-08-26T23:21:56.6855151Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-08-26T23:21:56.6855398Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-08-26T23:21:56.6855528Z 2025-08-26T23:21:56.6855570Z >>> import functools 2025-08-26T23:21:56.6855729Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-08-26T23:21:56.6855939Z >>> assert_equal(1e-9, 1e-10) 2025-08-26T23:21:56.6856059Z Traceback (most recent call last): 2025-08-26T23:21:56.6857135Z ... 2025-08-26T23:21:56.6857229Z AssertionError: Scalars are not equal! 2025-08-26T23:21:56.6857345Z 2025-08-26T23:21:56.6857441Z Expected 1e-10 but got 1e-09. 2025-08-26T23:21:56.6857563Z Absolute difference: 9.000000000000001e-10 2025-08-26T23:21:56.6857714Z Relative difference: 9.0 2025-08-26T23:21:56.6857787Z 2025-08-26T23:21:56.6857821Z Examples: 2025-08-26T23:21:56.6857914Z >>> # tensor to tensor comparison 2025-08-26T23:21:56.6858042Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-08-26T23:21:56.6858178Z >>> actual = torch.acos(torch.cos(expected)) 2025-08-26T23:21:56.6858318Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6859393Z 2025-08-26T23:21:56.6859441Z >>> # scalar to scalar comparison 2025-08-26T23:21:56.6859556Z >>> import math 2025-08-26T23:21:56.6859656Z >>> expected = math.sqrt(2.0) 2025-08-26T23:21:56.6859771Z >>> actual = 2.0 / math.sqrt(2.0) 2025-08-26T23:21:56.6859900Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6859988Z 2025-08-26T23:21:56.6860039Z >>> # numpy array to numpy array comparison 2025-08-26T23:21:56.6860161Z >>> import numpy as np 2025-08-26T23:21:56.6860277Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-08-26T23:21:56.6860533Z >>> actual = np.arccos(np.cos(expected)) 2025-08-26T23:21:56.6860667Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6860755Z 2025-08-26T23:21:56.6860801Z >>> # sequence to sequence comparison 2025-08-26T23:21:56.6861929Z >>> import numpy as np 2025-08-26T23:21:56.6862088Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-08-26T23:21:56.6862263Z >>> # length and their elements have to match. 2025-08-26T23:21:56.6862441Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-08-26T23:21:56.6862578Z >>> actual = tuple(expected) 2025-08-26T23:21:56.6862704Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6862792Z 2025-08-26T23:21:56.6862839Z >>> # mapping to mapping comparison 2025-08-26T23:21:56.6862964Z >>> from collections import OrderedDict 2025-08-26T23:21:56.6863085Z >>> import numpy as np 2025-08-26T23:21:56.6863192Z >>> foo = torch.tensor(1.0) 2025-08-26T23:21:56.6864255Z >>> bar = 2.0 2025-08-26T23:21:56.6864354Z >>> baz = np.array(3.0) 2025-08-26T23:21:56.6864513Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-08-26T23:21:56.6864713Z >>> # have to have the same set of keys and their elements have to match. 2025-08-26T23:21:56.6864896Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-08-26T23:21:56.6865061Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-08-26T23:21:56.6865200Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6865289Z 2025-08-26T23:21:56.6865339Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T23:21:56.6865463Z >>> actual = expected.clone() 2025-08-26T23:21:56.6865601Z >>> # By default, directly related instances can be compared 2025-08-26T23:21:56.6865777Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-08-26T23:21:56.6866921Z >>> # This check can be made more strict with allow_subclasses=False 2025-08-26T23:21:56.6867075Z >>> torch.testing.assert_close( 2025-08-26T23:21:56.6867225Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-08-26T23:21:56.6867364Z ... ) 2025-08-26T23:21:56.6867457Z Traceback (most recent call last): 2025-08-26T23:21:56.6867601Z ... 2025-08-26T23:21:56.6867722Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T23:21:56.6867909Z and . 2025-08-26T23:21:56.6868103Z >>> # If the inputs are not directly related, they are never considered close 2025-08-26T23:21:56.6868283Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-08-26T23:21:56.6868425Z Traceback (most recent call last): 2025-08-26T23:21:56.6869515Z ... 2025-08-26T23:21:56.6869668Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T23:21:56.6869846Z and . 2025-08-26T23:21:56.6870013Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-08-26T23:21:56.6870186Z >>> # their type if check_dtype=False. 2025-08-26T23:21:56.6870435Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-08-26T23:21:56.6870537Z 2025-08-26T23:21:56.6870580Z >>> # NaN != NaN by default. 2025-08-26T23:21:56.6870700Z >>> expected = torch.tensor(float("Nan")) 2025-08-26T23:21:56.6870822Z >>> actual = expected.clone() 2025-08-26T23:21:56.6870950Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:21:56.6871082Z Traceback (most recent call last): 2025-08-26T23:21:56.6872172Z ... 2025-08-26T23:21:56.6872265Z AssertionError: Scalars are not close! 2025-08-26T23:21:56.6872382Z 2025-08-26T23:21:56.6872476Z Expected nan but got nan. 2025-08-26T23:21:56.6872603Z Absolute difference: nan (up to 1e-05 allowed) 2025-08-26T23:21:56.6872746Z Relative difference: nan (up to 1.3e-06 allowed) 2025-08-26T23:21:56.6872906Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-08-26T23:21:56.6873015Z 2025-08-26T23:21:56.6873066Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T23:21:56.6873194Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-08-26T23:21:56.6873359Z >>> # The default error message can be overwritten. 2025-08-26T23:21:56.6873492Z >>> torch.testing.assert_close( 2025-08-26T23:21:56.6874705Z ... actual, expected, msg="Argh, the tensors are not close!" 2025-08-26T23:21:56.6874844Z ... ) 2025-08-26T23:21:56.6874936Z Traceback (most recent call last): 2025-08-26T23:21:56.6875044Z ... 2025-08-26T23:21:56.6875147Z AssertionError: Argh, the tensors are not close! 2025-08-26T23:21:56.6875313Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-08-26T23:21:56.6875466Z >>> # extra information 2025-08-26T23:21:56.6875574Z >>> torch.testing.assert_close( 2025-08-26T23:21:56.6875721Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-08-26T23:21:56.6875862Z ... ) 2025-08-26T23:21:56.6875952Z Traceback (most recent call last): 2025-08-26T23:21:56.6877039Z ... 2025-08-26T23:21:56.6877127Z AssertionError: Header 2025-08-26T23:21:56.6877228Z 2025-08-26T23:21:56.6877321Z Tensor-likes are not close! 2025-08-26T23:21:56.6877428Z 2025-08-26T23:21:56.6877523Z Mismatched elements: 2 / 3 (66.7%) 2025-08-26T23:21:56.6877679Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-08-26T23:21:56.6877876Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-08-26T23:21:56.6878024Z 2025-08-26T23:21:56.6878108Z Footer 2025-08-26T23:21:56.6878186Z 2025-08-26T23:21:56.6879271Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:56.6879398Z 2025-08-26T23:21:57.2311383Z msg = Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-08-26T23:21:57.2312088Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.2312238Z 2025-08-26T23:21:57.2312323Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-08-26T23:21:57.2312522Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-08-26T23:21:57.2312724Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-08-26T23:21:57.2312923Z its samples are on simplex, and are reparametrizable. 2025-08-26T23:21:57.2313093Z 2025-08-26T23:21:57.2313165Z Example:: 2025-08-26T23:21:57.2318475Z 2025-08-26T23:21:57.2318568Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:57.2318736Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-08-26T23:21:57.2318891Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-08-26T23:21:57.2319124Z >>> m.sample() 2025-08-26T23:21:57.2319225Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-08-26T23:21:57.2319314Z 2025-08-26T23:21:57.2319366Z Args: 2025-08-26T23:21:57.2319465Z temperature (Tensor): relaxation temperature 2025-08-26T23:21:57.2319599Z probs (Tensor): event probabilities 2025-08-26T23:21:57.2319752Z logits (Tensor): unnormalized log probability for each event 2025-08-26T23:21:57.2319860Z 2025-08-26T23:21:57.2319950Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.2320083Z 2025-08-26T23:21:57.2320434Z msg = Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-08-26T23:21:57.2320779Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.2320917Z 2025-08-26T23:21:57.2321001Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-08-26T23:21:57.2321216Z distribution where all component are from different parameterizations of 2025-08-26T23:21:57.2321428Z the same distribution type. It is parameterized by a `Categorical` 2025-08-26T23:21:57.2321689Z "selecting distribution" (over `k` component) and a component 2025-08-26T23:21:57.2321882Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-08-26T23:21:57.2322068Z (equal to `[k]`) which indexes each (batch of) component. 2025-08-26T23:21:57.2322166Z 2025-08-26T23:21:57.2322211Z Examples:: 2025-08-26T23:21:57.2322264Z 2025-08-26T23:21:57.2322320Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.2322487Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-08-26T23:21:57.2322648Z >>> # weighted normal distributions 2025-08-26T23:21:57.2322782Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T23:21:57.2322924Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-08-26T23:21:57.2323071Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:21:57.2323160Z 2025-08-26T23:21:57.2323237Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-08-26T23:21:57.2323401Z >>> # weighted bivariate normal distributions 2025-08-26T23:21:57.2323536Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T23:21:57.2323660Z >>> comp = D.Independent(D.Normal( 2025-08-26T23:21:57.2323789Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-08-26T23:21:57.2323922Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:21:57.2324001Z 2025-08-26T23:21:57.2324072Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-08-26T23:21:57.2326021Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-08-26T23:21:57.2326194Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-08-26T23:21:57.2326321Z >>> comp = D.Independent(D.Normal( 2025-08-26T23:21:57.2326449Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-08-26T23:21:57.2326582Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:21:57.2326665Z 2025-08-26T23:21:57.2326697Z Args: 2025-08-26T23:21:57.2326855Z mixture_distribution: `torch.distributions.Categorical`-like 2025-08-26T23:21:57.2327037Z instance. Manages the probability of selecting component. 2025-08-26T23:21:57.2327203Z The number of categories must match the rightmost batch 2025-08-26T23:21:57.2327369Z dimension of the `component_distribution`. Must have either 2025-08-26T23:21:57.2327528Z scalar `batch_shape` or `batch_shape` matching 2025-08-26T23:21:57.2328848Z `component_distribution.batch_shape[:-1]` 2025-08-26T23:21:57.2329055Z component_distribution: `torch.distributions.Distribution`-like 2025-08-26T23:21:57.2329239Z instance. Right-most batch dimension indexes component. 2025-08-26T23:21:57.2329341Z 2025-08-26T23:21:57.2329430Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.2329555Z 2025-08-26T23:21:57.2469376Z msg = Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-08-26T23:21:57.2469723Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.2469879Z 2025-08-26T23:21:57.2469946Z Creates a RelaxedBernoulli distribution, parametrized by 2025-08-26T23:21:57.2470118Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-08-26T23:21:57.2470299Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-08-26T23:21:57.2470592Z so the values are in (0, 1), and has reparametrizable samples. 2025-08-26T23:21:57.2470696Z 2025-08-26T23:21:57.2470732Z Example:: 2025-08-26T23:21:57.2472336Z 2025-08-26T23:21:57.2472406Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:57.2472549Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-08-26T23:21:57.2472683Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-08-26T23:21:57.2472811Z >>> m.sample() 2025-08-26T23:21:57.2472918Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-08-26T23:21:57.2472999Z 2025-08-26T23:21:57.2473031Z Args: 2025-08-26T23:21:57.2473177Z temperature (Tensor): relaxation temperature 2025-08-26T23:21:57.2473328Z probs (Number, Tensor): the probability of sampling `1` 2025-08-26T23:21:57.2473486Z logits (Number, Tensor): the log-odds of sampling `1` 2025-08-26T23:21:57.2473581Z 2025-08-26T23:21:57.2473671Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.2473795Z 2025-08-26T23:21:57.2585490Z msg = Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-08-26T23:21:57.2587121Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.2587430Z 2025-08-26T23:21:57.2587655Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-08-26T23:21:57.2588096Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-08-26T23:21:57.2588287Z 2025-08-26T23:21:57.2588414Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-08-26T23:21:57.2588586Z 2025-08-26T23:21:57.2588650Z Example: 2025-08-26T23:21:57.2588829Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T23:21:57.2589079Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:57.2589314Z >>> m = LowRankMultivariateNormal( 2025-08-26T23:21:57.2589571Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-08-26T23:21:57.2596068Z ... ) 2025-08-26T23:21:57.2596353Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-08-26T23:21:57.2596655Z tensor([-0.2102, -0.5429]) 2025-08-26T23:21:57.2596769Z 2025-08-26T23:21:57.2596819Z Args: 2025-08-26T23:21:57.2597024Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-08-26T23:21:57.2597367Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-08-26T23:21:57.2597998Z `batch_shape + event_shape + (rank,)` 2025-08-26T23:21:57.2598258Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-08-26T23:21:57.2598529Z `batch_shape + event_shape` 2025-08-26T23:21:57.2598654Z 2025-08-26T23:21:57.2598702Z Note: 2025-08-26T23:21:57.2598911Z The computation for determinant and inverse of covariance matrix is avoided when 2025-08-26T23:21:57.2599323Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-08-26T23:21:57.2599661Z `_ and 2025-08-26T23:21:57.2600035Z `matrix determinant lemma `_. 2025-08-26T23:21:57.2600509Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-08-26T23:21:57.2602400Z the small size "capacitance" matrix:: 2025-08-26T23:21:57.2602501Z 2025-08-26T23:21:57.2602587Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-08-26T23:21:57.2602709Z 2025-08-26T23:21:57.2602815Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.2602963Z 2025-08-26T23:21:57.3194619Z msg = Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=286. 2025-08-26T23:21:57.3195604Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3195975Z 2025-08-26T23:21:57.3196203Z Test if two objects are equal, and print an error message if test fails. 2025-08-26T23:21:57.3196527Z 2025-08-26T23:21:57.3196702Z The test is performed with ``actual == desired``. 2025-08-26T23:21:57.3196957Z 2025-08-26T23:21:57.3197061Z Parameters 2025-08-26T23:21:57.3202685Z ---------- 2025-08-26T23:21:57.3202831Z test_string : str 2025-08-26T23:21:57.3202975Z The message supplied to AssertionError. 2025-08-26T23:21:57.3203142Z actual : object 2025-08-26T23:21:57.3203517Z The object to test for equality against `desired`. 2025-08-26T23:21:57.3203686Z desired : object 2025-08-26T23:21:57.3203803Z The expected result. 2025-08-26T23:21:57.3203890Z 2025-08-26T23:21:57.3203940Z Examples 2025-08-26T23:21:57.3204041Z -------- 2025-08-26T23:21:57.3204158Z >>> np.testing.print_assert_equal( 2025-08-26T23:21:57.3204326Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-08-26T23:21:57.3204483Z ... ) # doctest: +SKIP 2025-08-26T23:21:57.3204616Z >>> np.testing.print_assert_equal( 2025-08-26T23:21:57.3204779Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-08-26T23:21:57.3204932Z ... ) # doctest: +SKIP 2025-08-26T23:21:57.3205075Z Traceback (most recent call last): 2025-08-26T23:21:57.3205217Z ... 2025-08-26T23:21:57.3205338Z AssertionError: Test XYZ of func xyz failed 2025-08-26T23:21:57.3205497Z ACTUAL: 2025-08-26T23:21:57.3205605Z [0, 1] 2025-08-26T23:21:57.3205711Z DESIRED: 2025-08-26T23:21:57.3207839Z [0, 2] 2025-08-26T23:21:57.3207895Z 2025-08-26T23:21:57.3207897Z 2025-08-26T23:21:57.3208023Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3208187Z 2025-08-26T23:21:57.3208438Z msg = Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=331. 2025-08-26T23:21:57.3208833Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3209006Z 2025-08-26T23:21:57.3209107Z Raises an AssertionError if two items are not equal up to desired 2025-08-26T23:21:57.3209284Z precision. 2025-08-26T23:21:57.3209351Z 2025-08-26T23:21:57.3209437Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:21:57.3209648Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:21:57.3209870Z instead of this function for more consistent floating point 2025-08-26T23:21:57.3210051Z comparisons. 2025-08-26T23:21:57.3210165Z 2025-08-26T23:21:57.3210245Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-08-26T23:21:57.3212446Z 2025-08-26T23:21:57.3212518Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-08-26T23:21:57.3212621Z 2025-08-26T23:21:57.3212707Z That is a looser test than originally documented, but agrees with what the 2025-08-26T23:21:57.3212942Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-08-26T23:21:57.3213209Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-08-26T23:21:57.3213377Z delegates to assert_array_almost_equal 2025-08-26T23:21:57.3213459Z 2025-08-26T23:21:57.3213493Z Parameters 2025-08-26T23:21:57.3213573Z ---------- 2025-08-26T23:21:57.3213655Z actual : array_like 2025-08-26T23:21:57.3213749Z The object to check. 2025-08-26T23:21:57.3213911Z desired : array_like 2025-08-26T23:21:57.3215122Z The expected object. 2025-08-26T23:21:57.3215228Z decimal : int, optional 2025-08-26T23:21:57.3215337Z Desired precision, default is 7. 2025-08-26T23:21:57.3215454Z err_msg : str, optional 2025-08-26T23:21:57.3215570Z The error message to be printed in case of failure. 2025-08-26T23:21:57.3215700Z verbose : bool, optional 2025-08-26T23:21:57.3215838Z If True, the conflicting values are appended to the error message. 2025-08-26T23:21:57.3215951Z 2025-08-26T23:21:57.3215983Z Raises 2025-08-26T23:21:57.3216056Z ------ 2025-08-26T23:21:57.3216134Z AssertionError 2025-08-26T23:21:57.3216260Z If actual and desired are not equal up to specified precision. 2025-08-26T23:21:57.3216370Z 2025-08-26T23:21:57.3217406Z See Also 2025-08-26T23:21:57.3217486Z -------- 2025-08-26T23:21:57.3217619Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:21:57.3217791Z relative and/or absolute precision. 2025-08-26T23:21:57.3217958Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:21:57.3218074Z 2025-08-26T23:21:57.3218107Z Examples 2025-08-26T23:21:57.3218181Z -------- 2025-08-26T23:21:57.3218312Z >>> from torch._numpy.testing import assert_almost_equal 2025-08-26T23:21:57.3218462Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-08-26T23:21:57.3218612Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-08-26T23:21:57.3218757Z Traceback (most recent call last): 2025-08-26T23:21:57.3219843Z ... 2025-08-26T23:21:57.3219925Z AssertionError: 2025-08-26T23:21:57.3220026Z Arrays are not almost equal to 10 decimals 2025-08-26T23:21:57.3220140Z ACTUAL: 2.3333333333333 2025-08-26T23:21:57.3220233Z DESIRED: 2.33333334 2025-08-26T23:21:57.3220289Z 2025-08-26T23:21:57.3220417Z >>> assert_almost_equal( 2025-08-26T23:21:57.3220551Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-08-26T23:21:57.3220690Z ... ) 2025-08-26T23:21:57.3220776Z Traceback (most recent call last): 2025-08-26T23:21:57.3220878Z ... 2025-08-26T23:21:57.3220955Z AssertionError: 2025-08-26T23:21:57.3222218Z Arrays are not almost equal to 9 decimals 2025-08-26T23:21:57.3222358Z 2025-08-26T23:21:57.3222447Z Mismatched elements: 1 / 2 (50%) 2025-08-26T23:21:57.3222571Z Max absolute difference: 6.666699636781459e-09 2025-08-26T23:21:57.3222700Z Max relative difference: 2.8571569790287484e-09 2025-08-26T23:21:57.3222831Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T23:21:57.3222967Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T23:21:57.3223052Z 2025-08-26T23:21:57.3223056Z 2025-08-26T23:21:57.3223147Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3223272Z 2025-08-26T23:21:57.3223467Z msg = Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=457. 2025-08-26T23:21:57.3223783Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3223955Z 2025-08-26T23:21:57.3225262Z Raises an AssertionError if two items are not equal up to significant 2025-08-26T23:21:57.3225427Z digits. 2025-08-26T23:21:57.3225472Z 2025-08-26T23:21:57.3225539Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:21:57.3225710Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:21:57.3225879Z instead of this function for more consistent floating point 2025-08-26T23:21:57.3226015Z comparisons. 2025-08-26T23:21:57.3226075Z 2025-08-26T23:21:57.3226171Z Given two numbers, check that they are approximately equal. 2025-08-26T23:21:57.3226352Z Approximately equal is defined as the number of significant digits 2025-08-26T23:21:57.3226495Z that agree. 2025-08-26T23:21:57.3226544Z 2025-08-26T23:21:57.3226577Z Parameters 2025-08-26T23:21:57.3226653Z ---------- 2025-08-26T23:21:57.3227744Z actual : scalar 2025-08-26T23:21:57.3227860Z The object to check. 2025-08-26T23:21:57.3227955Z desired : scalar 2025-08-26T23:21:57.3228046Z The expected object. 2025-08-26T23:21:57.3228146Z significant : int, optional 2025-08-26T23:21:57.3228256Z Desired precision, default is 7. 2025-08-26T23:21:57.3228368Z err_msg : str, optional 2025-08-26T23:21:57.3228483Z The error message to be printed in case of failure. 2025-08-26T23:21:57.3228611Z verbose : bool, optional 2025-08-26T23:21:57.3228744Z If True, the conflicting values are appended to the error message. 2025-08-26T23:21:57.3228853Z 2025-08-26T23:21:57.3228882Z Raises 2025-08-26T23:21:57.3229921Z ------ 2025-08-26T23:21:57.3229998Z AssertionError 2025-08-26T23:21:57.3230119Z If actual and desired are not equal up to specified precision. 2025-08-26T23:21:57.3230225Z 2025-08-26T23:21:57.3230257Z See Also 2025-08-26T23:21:57.3230406Z -------- 2025-08-26T23:21:57.3230534Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:21:57.3230706Z relative and/or absolute precision. 2025-08-26T23:21:57.3230863Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:21:57.3230976Z 2025-08-26T23:21:57.3231039Z Examples 2025-08-26T23:21:57.3231112Z -------- 2025-08-26T23:21:57.3231199Z >>> np.testing.assert_approx_equal( 2025-08-26T23:21:57.3232303Z ... 0.12345677777777e-20, 0.1234567e-20 2025-08-26T23:21:57.3232415Z ... ) # doctest: +SKIP 2025-08-26T23:21:57.3232515Z >>> np.testing.assert_approx_equal( 2025-08-26T23:21:57.3232624Z ... 0.12345670e-20, 2025-08-26T23:21:57.3232725Z ... 0.12345671e-20, # doctest: +SKIP 2025-08-26T23:21:57.3232835Z ... significant=8, 2025-08-26T23:21:57.3232921Z ... ) 2025-08-26T23:21:57.3233005Z >>> np.testing.assert_approx_equal( 2025-08-26T23:21:57.3233110Z ... 0.12345670e-20, 2025-08-26T23:21:57.3233205Z ... 0.12345672e-20, # doctest: +SKIP 2025-08-26T23:21:57.3233313Z ... significant=8, 2025-08-26T23:21:57.3234357Z ... ) 2025-08-26T23:21:57.3234532Z Traceback (most recent call last): 2025-08-26T23:21:57.3234636Z ... 2025-08-26T23:21:57.3234712Z AssertionError: 2025-08-26T23:21:57.3234815Z Items are not equal to 8 significant digits: 2025-08-26T23:21:57.3234930Z ACTUAL: 1.234567e-21 2025-08-26T23:21:57.3235021Z DESIRED: 1.2345672e-21 2025-08-26T23:21:57.3235078Z 2025-08-26T23:21:57.3235139Z the evaluated condition that raises the exception is 2025-08-26T23:21:57.3235233Z 2025-08-26T23:21:57.3235309Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-08-26T23:21:57.3235443Z True 2025-08-26T23:21:57.3235486Z 2025-08-26T23:21:57.3235488Z 2025-08-26T23:21:57.3235579Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3236697Z 2025-08-26T23:21:57.3236892Z msg = Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=744. 2025-08-26T23:21:57.3237211Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3237341Z 2025-08-26T23:21:57.3237448Z Raises an AssertionError if two array_like objects are not equal. 2025-08-26T23:21:57.3237557Z 2025-08-26T23:21:57.3237633Z Given two array_like objects, check that the shape is equal and all 2025-08-26T23:21:57.3237818Z elements of these objects are equal (but see the Notes for the special 2025-08-26T23:21:57.3238003Z handling of a scalar). An exception is raised at shape mismatch or 2025-08-26T23:21:57.3238189Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-08-26T23:21:57.3238397Z are compared like numbers, no assertion is raised if both objects have 2025-08-26T23:21:57.3238548Z NaNs in the same positions. 2025-08-26T23:21:57.3238616Z 2025-08-26T23:21:57.3238696Z The usual caution for verifying equality with floating point numbers is 2025-08-26T23:21:57.3238843Z advised. 2025-08-26T23:21:57.3238890Z 2025-08-26T23:21:57.3239896Z Parameters 2025-08-26T23:21:57.3240000Z ---------- 2025-08-26T23:21:57.3240076Z x : array_like 2025-08-26T23:21:57.3240164Z The actual object to check. 2025-08-26T23:21:57.3240267Z y : array_like 2025-08-26T23:21:57.3240430Z The desired, expected object. 2025-08-26T23:21:57.3240538Z err_msg : str, optional 2025-08-26T23:21:57.3240652Z The error message to be printed in case of failure. 2025-08-26T23:21:57.3240780Z verbose : bool, optional 2025-08-26T23:21:57.3240914Z If True, the conflicting values are appended to the error message. 2025-08-26T23:21:57.3241056Z strict : bool, optional 2025-08-26T23:21:57.3242136Z If True, raise an AssertionError when either the shape or the data 2025-08-26T23:21:57.3242314Z type of the array_like objects does not match. The special 2025-08-26T23:21:57.3242486Z handling for scalars mentioned in the Notes section is disabled. 2025-08-26T23:21:57.3242593Z 2025-08-26T23:21:57.3242625Z Raises 2025-08-26T23:21:57.3242696Z ------ 2025-08-26T23:21:57.3242771Z AssertionError 2025-08-26T23:21:57.3242870Z If actual and desired objects are not equal. 2025-08-26T23:21:57.3242955Z 2025-08-26T23:21:57.3242988Z See Also 2025-08-26T23:21:57.3243061Z -------- 2025-08-26T23:21:57.3243231Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:21:57.3243398Z relative and/or absolute precision. 2025-08-26T23:21:57.3244486Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:21:57.3244601Z 2025-08-26T23:21:57.3244632Z Notes 2025-08-26T23:21:57.3244704Z ----- 2025-08-26T23:21:57.3244814Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-08-26T23:21:57.3244999Z function checks that each element of the array_like object is equal to 2025-08-26T23:21:57.3245193Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-08-26T23:21:57.3245307Z 2025-08-26T23:21:57.3245339Z Examples 2025-08-26T23:21:57.3245412Z -------- 2025-08-26T23:21:57.3245504Z The first assert does not raise an exception: 2025-08-26T23:21:57.3245591Z 2025-08-26T23:21:57.3245635Z >>> np.testing.assert_array_equal( 2025-08-26T23:21:57.3245765Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-08-26T23:21:57.3246807Z ... ) 2025-08-26T23:21:57.3246852Z 2025-08-26T23:21:57.3246937Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-08-26T23:21:57.3247093Z functions for these cases instead: 2025-08-26T23:21:57.3247166Z 2025-08-26T23:21:57.3247207Z >>> np.testing.assert_allclose( 2025-08-26T23:21:57.3247349Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-08-26T23:21:57.3247487Z ... ) 2025-08-26T23:21:57.3247529Z 2025-08-26T23:21:57.3247605Z As mentioned in the Notes section, `assert_array_equal` has special 2025-08-26T23:21:57.3247790Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-08-26T23:21:57.3247903Z 2025-08-26T23:21:57.3247944Z >>> x = np.full((2, 5), fill_value=3) 2025-08-26T23:21:57.3248063Z >>> np.testing.assert_array_equal(x, 3) 2025-08-26T23:21:57.3248139Z 2025-08-26T23:21:57.3248217Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-08-26T23:21:57.3249312Z array: 2025-08-26T23:21:57.3249359Z 2025-08-26T23:21:57.3249416Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-08-26T23:21:57.3249547Z Traceback (most recent call last): 2025-08-26T23:21:57.3249649Z ... 2025-08-26T23:21:57.3249724Z AssertionError: 2025-08-26T23:21:57.3249810Z Arrays are not equal 2025-08-26T23:21:57.3249899Z 2025-08-26T23:21:57.3249984Z (shapes (2, 5), () mismatch) 2025-08-26T23:21:57.3250113Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-08-26T23:21:57.3250219Z [3, 3, 3, 3, 3]]) 2025-08-26T23:21:57.3250313Z y: torch.ndarray(3) 2025-08-26T23:21:57.3250446Z 2025-08-26T23:21:57.3251466Z The `strict` parameter also ensures that the array data types match: 2025-08-26T23:21:57.3251581Z 2025-08-26T23:21:57.3251619Z >>> x = np.array([2, 2, 2]) 2025-08-26T23:21:57.3251765Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-08-26T23:21:57.3251908Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-08-26T23:21:57.3252043Z Traceback (most recent call last): 2025-08-26T23:21:57.3252148Z ... 2025-08-26T23:21:57.3252223Z AssertionError: 2025-08-26T23:21:57.3252308Z Arrays are not equal 2025-08-26T23:21:57.3252393Z 2025-08-26T23:21:57.3252493Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-08-26T23:21:57.3252620Z x: torch.ndarray([2, 2, 2]) 2025-08-26T23:21:57.3253666Z y: torch.ndarray([2., 2., 2.]) 2025-08-26T23:21:57.3253737Z 2025-08-26T23:21:57.3253831Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3253956Z 2025-08-26T23:21:57.3254157Z msg = Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=851. 2025-08-26T23:21:57.3254478Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3254608Z 2025-08-26T23:21:57.3254684Z Raises an AssertionError if two objects are not equal up to desired 2025-08-26T23:21:57.3254829Z precision. 2025-08-26T23:21:57.3254876Z 2025-08-26T23:21:57.3254964Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:21:57.3255126Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:21:57.3255293Z instead of this function for more consistent floating point 2025-08-26T23:21:57.3255430Z comparisons. 2025-08-26T23:21:57.3255489Z 2025-08-26T23:21:57.3255576Z The test verifies identical shapes and that the elements of ``actual`` and 2025-08-26T23:21:57.3256682Z ``desired`` satisfy. 2025-08-26T23:21:57.3256740Z 2025-08-26T23:21:57.3256790Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-08-26T23:21:57.3256876Z 2025-08-26T23:21:57.3256956Z That is a looser test than originally documented, but agrees with what the 2025-08-26T23:21:57.3257155Z actual implementation did up to rounding vagaries. An exception is raised 2025-08-26T23:21:57.3257359Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-08-26T23:21:57.3257553Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-08-26T23:21:57.3257711Z objects have NaNs in the same positions. 2025-08-26T23:21:57.3257790Z 2025-08-26T23:21:57.3257824Z Parameters 2025-08-26T23:21:57.3257901Z ---------- 2025-08-26T23:21:57.3257978Z x : array_like 2025-08-26T23:21:57.3258066Z The actual object to check. 2025-08-26T23:21:57.3259108Z y : array_like 2025-08-26T23:21:57.3259199Z The desired, expected object. 2025-08-26T23:21:57.3259308Z decimal : int, optional 2025-08-26T23:21:57.3259411Z Desired precision, default is 6. 2025-08-26T23:21:57.3259522Z err_msg : str, optional 2025-08-26T23:21:57.3259636Z The error message to be printed in case of failure. 2025-08-26T23:21:57.3259765Z verbose : bool, optional 2025-08-26T23:21:57.3259899Z If True, the conflicting values are appended to the error message. 2025-08-26T23:21:57.3260008Z 2025-08-26T23:21:57.3260039Z Raises 2025-08-26T23:21:57.3260140Z ------ 2025-08-26T23:21:57.3260215Z AssertionError 2025-08-26T23:21:57.3261389Z If actual and desired are not equal up to specified precision. 2025-08-26T23:21:57.3261494Z 2025-08-26T23:21:57.3261527Z See Also 2025-08-26T23:21:57.3261600Z -------- 2025-08-26T23:21:57.3261724Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:21:57.3261892Z relative and/or absolute precision. 2025-08-26T23:21:57.3262084Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:21:57.3262196Z 2025-08-26T23:21:57.3262228Z Examples 2025-08-26T23:21:57.3262301Z -------- 2025-08-26T23:21:57.3262391Z the first assert does not raise an exception 2025-08-26T23:21:57.3262475Z 2025-08-26T23:21:57.3262564Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-08-26T23:21:57.3262692Z 2025-08-26T23:21:57.3262757Z >>> np.testing.assert_array_almost_equal( 2025-08-26T23:21:57.3263845Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-08-26T23:21:57.3263969Z ... ) 2025-08-26T23:21:57.3264054Z Traceback (most recent call last): 2025-08-26T23:21:57.3264158Z ... 2025-08-26T23:21:57.3264233Z AssertionError: 2025-08-26T23:21:57.3264328Z Arrays are not almost equal to 5 decimals 2025-08-26T23:21:57.3264437Z 2025-08-26T23:21:57.3264521Z Mismatched elements: 1 / 3 (33.3%) 2025-08-26T23:21:57.3264640Z Max absolute difference: 5.999999999994898e-05 2025-08-26T23:21:57.3264771Z Max relative difference: 2.5713661239633743e-05 2025-08-26T23:21:57.3264914Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T23:21:57.3266016Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-08-26T23:21:57.3266110Z 2025-08-26T23:21:57.3266156Z >>> np.testing.assert_array_almost_equal( 2025-08-26T23:21:57.3266287Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-08-26T23:21:57.3266405Z ... ) 2025-08-26T23:21:57.3266486Z Traceback (most recent call last): 2025-08-26T23:21:57.3266590Z ... 2025-08-26T23:21:57.3266665Z AssertionError: 2025-08-26T23:21:57.3266784Z Arrays are not almost equal to 5 decimals 2025-08-26T23:21:57.3266897Z 2025-08-26T23:21:57.3266981Z x and y nan location mismatch: 2025-08-26T23:21:57.3267109Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T23:21:57.3268206Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-08-26T23:21:57.3268298Z 2025-08-26T23:21:57.3268300Z 2025-08-26T23:21:57.3268392Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3268519Z 2025-08-26T23:21:57.3268723Z msg = Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-08-26T23:21:57.3269040Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.3269243Z Context manager that resets warning registry for catching warnings 2025-08-26T23:21:57.3269355Z 2025-08-26T23:21:57.3269441Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-08-26T23:21:57.3269640Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-08-26T23:21:57.3269835Z it impossible to retrigger the warning in this module, whatever you put in 2025-08-26T23:21:57.3270036Z the warnings filters. This context manager accepts a sequence of `modules` 2025-08-26T23:21:57.3270207Z as a keyword argument to its constructor and: 2025-08-26T23:21:57.3270294Z 2025-08-26T23:21:57.3271437Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-08-26T23:21:57.3271589Z on entry; 2025-08-26T23:21:57.3271707Z * resets ``__warningregistry__`` to its previous state on exit. 2025-08-26T23:21:57.3271811Z 2025-08-26T23:21:57.3271891Z This makes it possible to trigger any warning afresh inside the context 2025-08-26T23:21:57.3272073Z manager without disturbing the state of warnings outside. 2025-08-26T23:21:57.3272226Z 2025-08-26T23:21:57.3272312Z For compatibility with Python 3.0, please consider all arguments to be 2025-08-26T23:21:57.3272462Z keyword-only. 2025-08-26T23:21:57.3272515Z 2025-08-26T23:21:57.3272550Z Parameters 2025-08-26T23:21:57.3272631Z ---------- 2025-08-26T23:21:57.3272719Z record : bool, optional 2025-08-26T23:21:57.3272853Z Specifies whether warnings should be captured by a custom 2025-08-26T23:21:57.3274035Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-08-26T23:21:57.3274231Z returned by the context manager. Otherwise None is returned by the 2025-08-26T23:21:57.3274482Z context manager. The objects appended to the list are arguments whose 2025-08-26T23:21:57.3274659Z attributes mirror the arguments to ``showwarning()``. 2025-08-26T23:21:57.3274820Z modules : sequence, optional 2025-08-26T23:21:57.3274968Z Sequence of modules for which to reset warnings registry on entry and 2025-08-26T23:21:57.3275154Z restore on exit. To work correctly, all 'ignore' filters should 2025-08-26T23:21:57.3275298Z filter by one of these modules. 2025-08-26T23:21:57.3275373Z 2025-08-26T23:21:57.3275407Z Examples 2025-08-26T23:21:57.3275487Z -------- 2025-08-26T23:21:57.3275570Z >>> import warnings 2025-08-26T23:21:57.3276671Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-08-26T23:21:57.3276822Z ... modules=[np.core.fromnumeric] 2025-08-26T23:21:57.3276933Z ... ): 2025-08-26T23:21:57.3277023Z ... warnings.simplefilter("always") 2025-08-26T23:21:57.3277183Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-08-26T23:21:57.3277363Z ... # do something that raises a warning but ignore those in 2025-08-26T23:21:57.3277502Z ... # np.core.fromnumeric 2025-08-26T23:21:57.3277604Z 2025-08-26T23:21:57.3277732Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.3277857Z 2025-08-26T23:21:57.4309906Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/device_mesh.py line=721. 2025-08-26T23:21:57.4311044Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:21:57.4311410Z 2025-08-26T23:21:57.4311688Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-08-26T23:21:57.4312327Z The submesh created consists of the dimensions and the communicators indicated by 2025-08-26T23:21:57.4312786Z ``mesh_dim_names`` 2025-08-26T23:21:57.4312950Z 2025-08-26T23:21:57.4313039Z Args: 2025-08-26T23:21:57.4313407Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-08-26T23:21:57.4313940Z mesh dimension of the DeviceMesh to create the submesh for. 2025-08-26T23:21:57.4314332Z Returns: 2025-08-26T23:21:57.4314672Z A :class:`DeviceMesh` object 2025-08-26T23:21:57.4314879Z 2025-08-26T23:21:57.4315164Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-08-26T23:21:57.4315650Z In the first example: 2025-08-26T23:21:57.4316073Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-08-26T23:21:57.4316666Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-08-26T23:21:57.4317232Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-08-26T23:21:57.4317769Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-08-26T23:21:57.4318295Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-08-26T23:21:57.4318817Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-08-26T23:21:57.4319141Z 2025-08-26T23:21:57.4319246Z In the second example: 2025-08-26T23:21:57.4319674Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-08-26T23:21:57.4320070Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-08-26T23:21:57.4320292Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-08-26T23:21:57.4320610Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-08-26T23:21:57.4320743Z 2025-08-26T23:21:57.4320815Z Example:: 2025-08-26T23:21:57.4320871Z 2025-08-26T23:21:57.4320917Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:21:57.4321066Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-08-26T23:21:57.4321203Z >>> 2025-08-26T23:21:57.4321326Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-08-26T23:21:57.4321650Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-08-26T23:21:57.4321832Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T23:21:57.4322007Z >>> tp_mesh = mesh_2d["tp"] 2025-08-26T23:21:57.4322118Z >>> dp_mesh = mesh_2d["dp"] 2025-08-26T23:21:57.4324755Z >>> 2025-08-26T23:21:57.4324853Z >>> # Initialize a 3D mesh. 2025-08-26T23:21:57.4325028Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-08-26T23:21:57.4325270Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-08-26T23:21:57.4325452Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-08-26T23:21:57.4325571Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-08-26T23:21:57.4325650Z 2025-08-26T23:21:57.4325881Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-08-26T23:21:57.4326141Z 2025-08-26T23:21:57.4326229Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T23:21:57.4326455Z ^ 2025-08-26T23:21:57.4469767Z msg = Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2710. 2025-08-26T23:21:57.4477168Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4477642Z 2025-08-26T23:21:57.4477965Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-08-26T23:21:57.4478327Z 2025-08-26T23:21:57.4478576Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-08-26T23:21:57.4479134Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-08-26T23:21:57.4479454Z 2025-08-26T23:21:57.4479566Z Args: 2025-08-26T23:21:57.4479941Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-08-26T23:21:57.4480311Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-08-26T23:21:57.4480732Z matters and it needs to match with corresponding isend/irecv on the 2025-08-26T23:21:57.4480966Z remote end. 2025-08-26T23:21:57.4481051Z 2025-08-26T23:21:57.4481113Z Returns: 2025-08-26T23:21:57.4481317Z A list of distributed request objects returned by calling the corresponding 2025-08-26T23:21:57.4481553Z op in the op_list. 2025-08-26T23:21:57.4481644Z 2025-08-26T23:21:57.4481702Z Examples: 2025-08-26T23:21:57.4487639Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:21:57.4487887Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-08-26T23:21:57.4488132Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-08-26T23:21:57.4488370Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-08-26T23:21:57.4488600Z >>> recv_op = dist.P2POp( 2025-08-26T23:21:57.4488815Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-08-26T23:21:57.4489230Z ... ) 2025-08-26T23:21:57.4489380Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-08-26T23:21:57.4489569Z >>> for req in reqs: 2025-08-26T23:21:57.4489701Z >>> req.wait() 2025-08-26T23:21:57.4489834Z >>> recv_tensor 2025-08-26T23:21:57.4491744Z tensor([2, 3]) # Rank 0 2025-08-26T23:21:57.4491873Z tensor([0, 1]) # Rank 1 2025-08-26T23:21:57.4491948Z 2025-08-26T23:21:57.4492184Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-08-26T23:21:57.4492411Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-08-26T23:21:57.4492592Z lead to unexpected hang issues. 2025-08-26T23:21:57.4492675Z 2025-08-26T23:21:57.4492763Z In addition, if this API is the first collective call in the ``group`` 2025-08-26T23:21:57.4493055Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-08-26T23:21:57.4493273Z this API call; otherwise, the behavior is undefined. If this API call is 2025-08-26T23:21:57.4493487Z not the first collective call in the ``group``, batched P2P operations 2025-08-26T23:21:57.4493696Z involving only a subset of ranks of the ``group`` are allowed. 2025-08-26T23:21:57.4493819Z 2025-08-26T23:21:57.4493919Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4494054Z 2025-08-26T23:21:57.4495672Z msg = Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2842. 2025-08-26T23:21:57.4496031Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4496176Z 2025-08-26T23:21:57.4496283Z Reduces the tensor data across all machines in a way that all get the final result. 2025-08-26T23:21:57.4496455Z 2025-08-26T23:21:57.4496551Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-08-26T23:21:57.4496690Z 2025-08-26T23:21:57.4496740Z Complex tensors are supported. 2025-08-26T23:21:57.4496888Z 2025-08-26T23:21:57.4496921Z Args: 2025-08-26T23:21:57.4497055Z tensor (Tensor): Input and output of the collective. The function 2025-08-26T23:21:57.4497221Z operates in-place. 2025-08-26T23:21:57.4497348Z op (optional): One of the values from 2025-08-26T23:21:57.4497485Z ``torch.distributed.ReduceOp`` 2025-08-26T23:21:57.4497664Z enum. Specifies an operation used for element-wise reductions. 2025-08-26T23:21:57.4499288Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.4499478Z the default process group will be used. 2025-08-26T23:21:57.4499657Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T23:21:57.4499777Z 2025-08-26T23:21:57.4499821Z Returns: 2025-08-26T23:21:57.4499929Z Async work handle, if async_op is set to True. 2025-08-26T23:21:57.4500088Z None, if not async_op or if not part of the group 2025-08-26T23:21:57.4500192Z 2025-08-26T23:21:57.4500230Z Examples: 2025-08-26T23:21:57.4500430Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:21:57.4500572Z >>> # All tensors below are of torch.int64 type. 2025-08-26T23:21:57.4500713Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.4500848Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T23:21:57.4502094Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T23:21:57.4502242Z >>> tensor 2025-08-26T23:21:57.4502335Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4502453Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4502577Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T23:21:57.4502691Z >>> tensor 2025-08-26T23:21:57.4502780Z tensor([4, 6], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4502896Z tensor([4, 6], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4502973Z 2025-08-26T23:21:57.4503084Z >>> # All tensors below are of torch.cfloat type. 2025-08-26T23:21:57.4503213Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.4503329Z >>> tensor = torch.tensor( 2025-08-26T23:21:57.4504495Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T23:21:57.4504623Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T23:21:57.4504719Z >>> tensor 2025-08-26T23:21:57.4504820Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4505000Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4505134Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T23:21:57.4505247Z >>> tensor 2025-08-26T23:21:57.4505344Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4505476Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4505560Z 2025-08-26T23:21:57.4505581Z 2025-08-26T23:21:57.4505671Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4505798Z 2025-08-26T23:21:57.4506027Z msg = Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3202. 2025-08-26T23:21:57.4507382Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4507512Z 2025-08-26T23:21:57.4507593Z Gathers picklable objects from the whole group in a single process. 2025-08-26T23:21:57.4507709Z 2025-08-26T23:21:57.4507793Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-08-26T23:21:57.4507966Z object must be picklable in order to be gathered. 2025-08-26T23:21:57.4508056Z 2025-08-26T23:21:57.4508087Z Args: 2025-08-26T23:21:57.4508180Z obj (Any): Input object. Must be picklable. 2025-08-26T23:21:57.4508337Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-08-26T23:21:57.4508518Z should be correctly sized as the size of the group for this 2025-08-26T23:21:57.4508700Z collective and will contain the output. Must be ``None`` on non-dst 2025-08-26T23:21:57.4508876Z ranks. (default is ``None``) 2025-08-26T23:21:57.4510038Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-08-26T23:21:57.4510257Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-08-26T23:21:57.4510536Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.4510723Z the default process group will be used. Default is ``None``. 2025-08-26T23:21:57.4510941Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-08-26T23:21:57.4511097Z 2025-08-26T23:21:57.4511130Z Returns: 2025-08-26T23:21:57.4511242Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-08-26T23:21:57.4511385Z output of the collective. 2025-08-26T23:21:57.4511456Z 2025-08-26T23:21:57.4511535Z .. note:: Note that this API differs slightly from the gather collective 2025-08-26T23:21:57.4511722Z since it does not provide an async_op handle and thus will be a blocking 2025-08-26T23:21:57.4511866Z call. 2025-08-26T23:21:57.4511911Z 2025-08-26T23:21:57.4513034Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-08-26T23:21:57.4513228Z of objects must be moved to the GPU device before communication takes 2025-08-26T23:21:57.4513393Z place. In this case, the device used is given by 2025-08-26T23:21:57.4513560Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-08-26T23:21:57.4513743Z ensure that this is set so that each rank has an individual GPU, via 2025-08-26T23:21:57.4513893Z ``torch.cuda.set_device()``. 2025-08-26T23:21:57.4513964Z 2025-08-26T23:21:57.4513999Z .. warning:: 2025-08-26T23:21:57.4514129Z Object collectives have a number of serious performance and scalability 2025-08-26T23:21:57.4514312Z limitations. See :ref:`object_collectives` for details. 2025-08-26T23:21:57.4514523Z 2025-08-26T23:21:57.4514559Z .. warning:: 2025-08-26T23:21:57.4514676Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-08-26T23:21:57.4515832Z known to be insecure. It is possible to construct malicious pickle data 2025-08-26T23:21:57.4516022Z which will execute arbitrary code during unpickling. Only call this 2025-08-26T23:21:57.4516173Z function with data you trust. 2025-08-26T23:21:57.4516247Z 2025-08-26T23:21:57.4516305Z .. warning:: 2025-08-26T23:21:57.4516429Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-08-26T23:21:57.4516620Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-08-26T23:21:57.4516797Z pickled. Please consider using :func:`gather` instead. 2025-08-26T23:21:57.4516895Z 2025-08-26T23:21:57.4516948Z Example:: 2025-08-26T23:21:57.4517047Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T23:21:57.4517201Z >>> # Note: Process group initialization omitted on each rank. 2025-08-26T23:21:57.4517346Z >>> import torch.distributed as dist 2025-08-26T23:21:57.4518427Z >>> # Assumes world_size of 3. 2025-08-26T23:21:57.4518565Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-08-26T23:21:57.4518711Z >>> output = [None for _ in gather_objects] 2025-08-26T23:21:57.4518830Z >>> dist.gather_object( 2025-08-26T23:21:57.4518937Z ... gather_objects[dist.get_rank()], 2025-08-26T23:21:57.4519069Z ... output if dist.get_rank() == 0 else None, 2025-08-26T23:21:57.4519185Z ... dst=0 2025-08-26T23:21:57.4519267Z ... ) 2025-08-26T23:21:57.4519342Z >>> # On rank 0 2025-08-26T23:21:57.4519426Z >>> output 2025-08-26T23:21:57.4519507Z ['foo', 12, {1: 2}] 2025-08-26T23:21:57.4520601Z 2025-08-26T23:21:57.4520696Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4520822Z 2025-08-26T23:21:57.4521042Z msg = Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3798. 2025-08-26T23:21:57.4521359Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4521486Z 2025-08-26T23:21:57.4521541Z Gathers tensors from the whole group in a list. 2025-08-26T23:21:57.4521627Z 2025-08-26T23:21:57.4521681Z Complex and uneven sized tensors are supported. 2025-08-26T23:21:57.4521767Z 2025-08-26T23:21:57.4521799Z Args: 2025-08-26T23:21:57.4521911Z tensor_list (list[Tensor]): Output list. It should contain 2025-08-26T23:21:57.4522099Z correctly-sized tensors to be used for output of the collective. 2025-08-26T23:21:57.4522256Z Uneven sized tensors are supported. 2025-08-26T23:21:57.4522406Z tensor (Tensor): Tensor to be broadcast from current process. 2025-08-26T23:21:57.4525186Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.4525428Z the default process group will be used. 2025-08-26T23:21:57.4525582Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T23:21:57.4525691Z 2025-08-26T23:21:57.4525725Z Returns: 2025-08-26T23:21:57.4525824Z Async work handle, if async_op is set to True. 2025-08-26T23:21:57.4525967Z None, if not async_op or if not part of the group 2025-08-26T23:21:57.4526057Z 2025-08-26T23:21:57.4526092Z Examples: 2025-08-26T23:21:57.4526191Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T23:21:57.4526335Z >>> # All tensors below are of torch.int64 dtype. 2025-08-26T23:21:57.4526464Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.4526591Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T23:21:57.4526714Z >>> tensor_list = [ 2025-08-26T23:21:57.4526848Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-08-26T23:21:57.4527001Z ... ] 2025-08-26T23:21:57.4527084Z >>> tensor_list 2025-08-26T23:21:57.4527272Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-08-26T23:21:57.4527463Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-08-26T23:21:57.4527661Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T23:21:57.4527823Z >>> tensor 2025-08-26T23:21:57.4527928Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4529894Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4530048Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T23:21:57.4530157Z >>> tensor_list 2025-08-26T23:21:57.4530278Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-08-26T23:21:57.4530529Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-08-26T23:21:57.4530634Z 2025-08-26T23:21:57.4530710Z >>> # All tensors below are of torch.cfloat dtype. 2025-08-26T23:21:57.4530840Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.4530952Z >>> tensor_list = [ 2025-08-26T23:21:57.4531087Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-08-26T23:21:57.4531228Z ... ] 2025-08-26T23:21:57.4531303Z >>> tensor_list 2025-08-26T23:21:57.4533539Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-08-26T23:21:57.4533758Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-08-26T23:21:57.4533922Z >>> tensor = torch.tensor( 2025-08-26T23:21:57.4534050Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T23:21:57.4534180Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T23:21:57.4534280Z >>> tensor 2025-08-26T23:21:57.4534383Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T23:21:57.4534519Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T23:21:57.4534651Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T23:21:57.4534765Z >>> tensor_list 2025-08-26T23:21:57.4534940Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-08-26T23:21:57.4536126Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-08-26T23:21:57.4536251Z 2025-08-26T23:21:57.4536253Z 2025-08-26T23:21:57.4536344Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4536473Z 2025-08-26T23:21:57.4536697Z msg = Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4504. 2025-08-26T23:21:57.4537021Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4537151Z 2025-08-26T23:21:57.4537240Z Split input tensor and then scatter the split list to all processes in a group. 2025-08-26T23:21:57.4537367Z 2025-08-26T23:21:57.4537458Z Later the received tensors are concatenated from all the processes in the group 2025-08-26T23:21:57.4537634Z and returned as a single output tensor. 2025-08-26T23:21:57.4537714Z 2025-08-26T23:21:57.4537758Z Complex tensors are supported. 2025-08-26T23:21:57.4537829Z 2025-08-26T23:21:57.4537862Z Args: 2025-08-26T23:21:57.4537970Z output (Tensor): Gathered concatenated output tensor. 2025-08-26T23:21:57.4538115Z input (Tensor): Input tensor to scatter. 2025-08-26T23:21:57.4539238Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-08-26T23:21:57.4539430Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-08-26T23:21:57.4539581Z equally by ``world_size``. 2025-08-26T23:21:57.4539734Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-08-26T23:21:57.4539918Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-08-26T23:21:57.4540064Z equally by ``world_size``. 2025-08-26T23:21:57.4540216Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.4540508Z the default process group will be used. 2025-08-26T23:21:57.4540663Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T23:21:57.4540772Z 2025-08-26T23:21:57.4540805Z Returns: 2025-08-26T23:21:57.4540901Z Async work handle, if async_op is set to True. 2025-08-26T23:21:57.4541997Z None, if not async_op or if not part of the group. 2025-08-26T23:21:57.4542090Z 2025-08-26T23:21:57.4542126Z .. warning:: 2025-08-26T23:21:57.4542271Z `all_to_all_single` is experimental and subject to change. 2025-08-26T23:21:57.4542371Z 2025-08-26T23:21:57.4542405Z Examples: 2025-08-26T23:21:57.4542500Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T23:21:57.4542621Z >>> input = torch.arange(4) + rank * 4 2025-08-26T23:21:57.4542729Z >>> input 2025-08-26T23:21:57.4542835Z tensor([0, 1, 2, 3]) # Rank 0 2025-08-26T23:21:57.4542944Z tensor([4, 5, 6, 7]) # Rank 1 2025-08-26T23:21:57.4543052Z tensor([8, 9, 10, 11]) # Rank 2 2025-08-26T23:21:57.4543158Z tensor([12, 13, 14, 15]) # Rank 3 2025-08-26T23:21:57.4544205Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T23:21:57.4544344Z >>> dist.all_to_all_single(output, input) 2025-08-26T23:21:57.4544455Z >>> output 2025-08-26T23:21:57.4544540Z tensor([0, 4, 8, 12]) # Rank 0 2025-08-26T23:21:57.4544645Z tensor([1, 5, 9, 13]) # Rank 1 2025-08-26T23:21:57.4544750Z tensor([2, 6, 10, 14]) # Rank 2 2025-08-26T23:21:57.4544854Z tensor([3, 7, 11, 15]) # Rank 3 2025-08-26T23:21:57.4544923Z 2025-08-26T23:21:57.4544986Z >>> # Essentially, it is similar to following operation: 2025-08-26T23:21:57.4545133Z >>> scatter_list = list(input.chunk(world_size)) 2025-08-26T23:21:57.4545272Z >>> gather_list = list(output.chunk(world_size)) 2025-08-26T23:21:57.4546305Z >>> for i in range(world_size): 2025-08-26T23:21:57.4546463Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-08-26T23:21:57.4546585Z 2025-08-26T23:21:57.4546657Z >>> # Another example with uneven split 2025-08-26T23:21:57.4546769Z >>> input 2025-08-26T23:21:57.4546877Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T23:21:57.4547028Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T23:21:57.4547176Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T23:21:57.4547326Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T23:21:57.4547453Z >>> input_splits 2025-08-26T23:21:57.4547557Z [2, 2, 1, 1] # Rank 0 2025-08-26T23:21:57.4547684Z [3, 2, 2, 2] # Rank 1 2025-08-26T23:21:57.4548998Z [2, 1, 1, 1] # Rank 2 2025-08-26T23:21:57.4549154Z [2, 2, 2, 1] # Rank 3 2025-08-26T23:21:57.4549276Z >>> output_splits 2025-08-26T23:21:57.4549382Z [2, 3, 2, 2] # Rank 0 2025-08-26T23:21:57.4549513Z [2, 2, 1, 2] # Rank 1 2025-08-26T23:21:57.4549636Z [1, 2, 1, 2] # Rank 2 2025-08-26T23:21:57.4549761Z [1, 2, 1, 1] # Rank 3 2025-08-26T23:21:57.4549881Z >>> output = ... 2025-08-26T23:21:57.4550013Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-08-26T23:21:57.4550158Z >>> output 2025-08-26T23:21:57.4551902Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-08-26T23:21:57.4552066Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-08-26T23:21:57.4552216Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-08-26T23:21:57.4552415Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-08-26T23:21:57.4552506Z 2025-08-26T23:21:57.4552513Z 2025-08-26T23:21:57.4552579Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T23:21:57.4552717Z >>> input = torch.tensor( 2025-08-26T23:21:57.4552841Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T23:21:57.4552971Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T23:21:57.4553092Z >>> input 2025-08-26T23:21:57.4553206Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-08-26T23:21:57.4553363Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-08-26T23:21:57.4553526Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-08-26T23:21:57.4553711Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-08-26T23:21:57.4553868Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T23:21:57.4554010Z >>> dist.all_to_all_single(output, input) 2025-08-26T23:21:57.4554126Z >>> output 2025-08-26T23:21:57.4554239Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-08-26T23:21:57.4554497Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-08-26T23:21:57.4555704Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-08-26T23:21:57.4555867Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-08-26T23:21:57.4555966Z 2025-08-26T23:21:57.4556056Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4556179Z 2025-08-26T23:21:57.4556373Z msg = Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4646. 2025-08-26T23:21:57.4556688Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4556819Z 2025-08-26T23:21:57.4556973Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-08-26T23:21:57.4557134Z 2025-08-26T23:21:57.4557180Z Complex tensors are supported. 2025-08-26T23:21:57.4557252Z 2025-08-26T23:21:57.4557284Z Args: 2025-08-26T23:21:57.4557407Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-08-26T23:21:57.4557555Z per rank. 2025-08-26T23:21:57.4557689Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-08-26T23:21:57.4558830Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.4558995Z the default process group will be used. 2025-08-26T23:21:57.4559149Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T23:21:57.4559259Z 2025-08-26T23:21:57.4559291Z Returns: 2025-08-26T23:21:57.4559387Z Async work handle, if async_op is set to True. 2025-08-26T23:21:57.4559531Z None, if not async_op or if not part of the group. 2025-08-26T23:21:57.4559624Z 2025-08-26T23:21:57.4559659Z .. warning:: 2025-08-26T23:21:57.4559763Z `all_to_all` is experimental and subject to change. 2025-08-26T23:21:57.4559855Z 2025-08-26T23:21:57.4559888Z Examples: 2025-08-26T23:21:57.4559979Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T23:21:57.4560100Z >>> input = torch.arange(4) + rank * 4 2025-08-26T23:21:57.4561251Z >>> input = list(input.chunk(4)) 2025-08-26T23:21:57.4561361Z >>> input 2025-08-26T23:21:57.4561472Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-08-26T23:21:57.4561628Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-08-26T23:21:57.4561782Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-08-26T23:21:57.4561937Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-08-26T23:21:57.4562101Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T23:21:57.4562289Z >>> dist.all_to_all(output, input) 2025-08-26T23:21:57.4562397Z >>> output 2025-08-26T23:21:57.4562506Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-08-26T23:21:57.4562658Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-08-26T23:21:57.4563749Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-08-26T23:21:57.4563927Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-08-26T23:21:57.4564025Z 2025-08-26T23:21:57.4564088Z >>> # Essentially, it is similar to following operation: 2025-08-26T23:21:57.4564226Z >>> scatter_list = input 2025-08-26T23:21:57.4564330Z >>> gather_list = output 2025-08-26T23:21:57.4564435Z >>> for i in range(world_size): 2025-08-26T23:21:57.4564589Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-08-26T23:21:57.4564722Z 2025-08-26T23:21:57.4564755Z >>> input 2025-08-26T23:21:57.4564865Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T23:21:57.4565014Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T23:21:57.4566123Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T23:21:57.4566276Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T23:21:57.4566404Z >>> input_splits 2025-08-26T23:21:57.4566509Z [2, 2, 1, 1] # Rank 0 2025-08-26T23:21:57.4566635Z [3, 2, 2, 2] # Rank 1 2025-08-26T23:21:57.4566760Z [2, 1, 1, 1] # Rank 2 2025-08-26T23:21:57.4566883Z [2, 2, 2, 1] # Rank 3 2025-08-26T23:21:57.4567000Z >>> output_splits 2025-08-26T23:21:57.4567102Z [2, 3, 2, 2] # Rank 0 2025-08-26T23:21:57.4567251Z [2, 2, 1, 2] # Rank 1 2025-08-26T23:21:57.4567376Z [1, 2, 1, 2] # Rank 2 2025-08-26T23:21:57.4568435Z [1, 2, 1, 1] # Rank 3 2025-08-26T23:21:57.4568568Z >>> input = list(input.split(input_splits)) 2025-08-26T23:21:57.4568683Z >>> input 2025-08-26T23:21:57.4568807Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-08-26T23:21:57.4568987Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-08-26T23:21:57.4569164Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-08-26T23:21:57.4569338Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-08-26T23:21:57.4569480Z >>> output = ... 2025-08-26T23:21:57.4569580Z >>> dist.all_to_all(output, input) 2025-08-26T23:21:57.4569690Z >>> output 2025-08-26T23:21:57.4569809Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-08-26T23:21:57.4570991Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-08-26T23:21:57.4571171Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-08-26T23:21:57.4571347Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-08-26T23:21:57.4571454Z 2025-08-26T23:21:57.4571515Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T23:21:57.4571649Z >>> input = torch.tensor( 2025-08-26T23:21:57.4571771Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T23:21:57.4571896Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T23:21:57.4572006Z >>> input = list(input.chunk(4)) 2025-08-26T23:21:57.4572112Z >>> input 2025-08-26T23:21:57.4572271Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-08-26T23:21:57.4572453Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-08-26T23:21:57.4573576Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-08-26T23:21:57.4573767Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-08-26T23:21:57.4573971Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T23:21:57.4574117Z >>> dist.all_to_all(output, input) 2025-08-26T23:21:57.4574225Z >>> output 2025-08-26T23:21:57.4574348Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-08-26T23:21:57.4574528Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-08-26T23:21:57.4574728Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-08-26T23:21:57.4574911Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-08-26T23:21:57.4575022Z 2025-08-26T23:21:57.4575024Z 2025-08-26T23:21:57.4575115Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4575241Z 2025-08-26T23:21:57.4575426Z msg = Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/launch.py line=2. 2025-08-26T23:21:57.4576681Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4576809Z 2025-08-26T23:21:57.4576856Z Module ``torch.distributed.launch``. 2025-08-26T23:21:57.4576934Z 2025-08-26T23:21:57.4577023Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-08-26T23:21:57.4577201Z training processes on each of the training nodes. 2025-08-26T23:21:57.4577296Z 2025-08-26T23:21:57.4577330Z .. warning:: 2025-08-26T23:21:57.4577379Z 2025-08-26T23:21:57.4577473Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-08-26T23:21:57.4577633Z 2025-08-26T23:21:57.4577717Z The utility can be used for single-node distributed training, in which one or 2025-08-26T23:21:57.4577919Z more processes per node will be spawned. The utility can be used for either 2025-08-26T23:21:57.4578114Z CPU training or GPU training. If the utility is used for GPU training, 2025-08-26T23:21:57.4578311Z each distributed process will be operating on a single GPU. This can achieve 2025-08-26T23:21:57.4578513Z well-improved single-node training performance. It can also be used in 2025-08-26T23:21:57.4579671Z multi-node distributed training, by spawning up multiple processes on each node 2025-08-26T23:21:57.4579879Z for well-improved multi-node distributed training performance as well. 2025-08-26T23:21:57.4580075Z This will especially be beneficial for systems with multiple Infiniband 2025-08-26T23:21:57.4580280Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-08-26T23:21:57.4580523Z aggregated communication bandwidth. 2025-08-26T23:21:57.4580599Z 2025-08-26T23:21:57.4580682Z In both cases of single-node distributed training or multi-node distributed 2025-08-26T23:21:57.4580883Z training, this utility will launch the given number of processes per node 2025-08-26T23:21:57.4581082Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-08-26T23:21:57.4581277Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-08-26T23:21:57.4581465Z and each process will be operating on a single GPU from *GPU 0 to 2025-08-26T23:21:57.4582562Z GPU (nproc_per_node - 1)*. 2025-08-26T23:21:57.4582634Z 2025-08-26T23:21:57.4582676Z **How to use this module:** 2025-08-26T23:21:57.4582742Z 2025-08-26T23:21:57.4582800Z 1. Single-Node multi-process distributed training 2025-08-26T23:21:57.4582893Z 2025-08-26T23:21:57.4582927Z :: 2025-08-26T23:21:57.4582970Z 2025-08-26T23:21:57.4583098Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:21:57.4583289Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-08-26T23:21:57.4583440Z arguments of your training script) 2025-08-26T23:21:57.4583522Z 2025-08-26T23:21:57.4583599Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-08-26T23:21:57.4583710Z 2025-08-26T23:21:57.4583712Z 2025-08-26T23:21:57.4583769Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-08-26T23:21:57.4583880Z 2025-08-26T23:21:57.4583912Z :: 2025-08-26T23:21:57.4583955Z 2025-08-26T23:21:57.4584038Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:21:57.4585157Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-08-26T23:21:57.4585331Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T23:21:57.4585526Z and all other arguments of your training script) 2025-08-26T23:21:57.4585623Z 2025-08-26T23:21:57.4585656Z Node 2: 2025-08-26T23:21:57.4585700Z 2025-08-26T23:21:57.4585733Z :: 2025-08-26T23:21:57.4585774Z 2025-08-26T23:21:57.4585858Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:21:57.4586033Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-08-26T23:21:57.4586198Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T23:21:57.4586364Z and all other arguments of your training script) 2025-08-26T23:21:57.4586456Z 2025-08-26T23:21:57.4586518Z 3. To look up what optional arguments this module offers: 2025-08-26T23:21:57.4586612Z 2025-08-26T23:21:57.4586644Z :: 2025-08-26T23:21:57.4586684Z 2025-08-26T23:21:57.4587669Z python -m torch.distributed.launch --help 2025-08-26T23:21:57.4587757Z 2025-08-26T23:21:57.4587758Z 2025-08-26T23:21:57.4587800Z **Important Notices:** 2025-08-26T23:21:57.4587861Z 2025-08-26T23:21:57.4587933Z 1. This utility and multi-process distributed (single-node or 2025-08-26T23:21:57.4588294Z multi-node) GPU training currently only achieves the best performance using 2025-08-26T23:21:57.4588503Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-08-26T23:21:57.4588662Z use for GPU training. 2025-08-26T23:21:57.4588722Z 2025-08-26T23:21:57.4588799Z 2. In your training program, you must parse the command-line argument: 2025-08-26T23:21:57.4588992Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-08-26T23:21:57.4589188Z If your training program uses GPUs, you should ensure that your code only 2025-08-26T23:21:57.4589374Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-08-26T23:21:57.4589481Z 2025-08-26T23:21:57.4589523Z Parsing the local_rank argument 2025-08-26T23:21:57.4590623Z 2025-08-26T23:21:57.4590658Z :: 2025-08-26T23:21:57.4590703Z 2025-08-26T23:21:57.4590742Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.4590841Z >>> import argparse 2025-08-26T23:21:57.4590952Z >>> parser = argparse.ArgumentParser() 2025-08-26T23:21:57.4591107Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-08-26T23:21:57.4591254Z >>> args = parser.parse_args() 2025-08-26T23:21:57.4591328Z 2025-08-26T23:21:57.4591376Z Set your device to local rank using either 2025-08-26T23:21:57.4591456Z 2025-08-26T23:21:57.4591487Z :: 2025-08-26T23:21:57.4591527Z 2025-08-26T23:21:57.4591603Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-08-26T23:21:57.4591710Z 2025-08-26T23:21:57.4591741Z or 2025-08-26T23:21:57.4591780Z 2025-08-26T23:21:57.4591811Z :: 2025-08-26T23:21:57.4592798Z 2025-08-26T23:21:57.4592853Z >>> with torch.cuda.device(args.local_rank): 2025-08-26T23:21:57.4592975Z >>> # your code to run 2025-08-26T23:21:57.4593073Z >>> ... 2025-08-26T23:21:57.4593126Z 2025-08-26T23:21:57.4593166Z .. versionchanged:: 2.0.0 2025-08-26T23:21:57.4593230Z 2025-08-26T23:21:57.4593353Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-08-26T23:21:57.4593564Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-08-26T23:21:57.4593735Z previously used underscored ``--local_rank``. 2025-08-26T23:21:57.4593823Z 2025-08-26T23:21:57.4593907Z For backward compatibility, it may be necessary for users to handle both 2025-08-26T23:21:57.4594119Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-08-26T23:21:57.4594343Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-08-26T23:21:57.4594604Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-08-26T23:21:57.4595769Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-08-26T23:21:57.4595943Z including ``"--local-rank"`` should be sufficient. 2025-08-26T23:21:57.4596057Z 2025-08-26T23:21:57.4596141Z 3. In your training program, you are supposed to call the following function 2025-08-26T23:21:57.4596344Z at the beginning to start the distributed backend. It is strongly recommended 2025-08-26T23:21:57.4596556Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-08-26T23:21:57.4596739Z but ``env://`` is the one that is officially supported by this module. 2025-08-26T23:21:57.4596842Z 2025-08-26T23:21:57.4596875Z :: 2025-08-26T23:21:57.4596917Z 2025-08-26T23:21:57.4596996Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-08-26T23:21:57.4597171Z >>> init_method='env://') 2025-08-26T23:21:57.4597259Z 2025-08-26T23:21:57.4597344Z 4. In your training program, you can either use regular distributed functions 2025-08-26T23:21:57.4598500Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-08-26T23:21:57.4598700Z training program uses GPUs for training and you would like to use 2025-08-26T23:21:57.4598881Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-08-26T23:21:57.4599057Z here is how to configure it. 2025-08-26T23:21:57.4599127Z 2025-08-26T23:21:57.4599158Z :: 2025-08-26T23:21:57.4599201Z 2025-08-26T23:21:57.4599273Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-08-26T23:21:57.4599431Z >>> device_ids=[args.local_rank], 2025-08-26T23:21:57.4599573Z >>> output_device=args.local_rank) 2025-08-26T23:21:57.4599664Z 2025-08-26T23:21:57.4599748Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-08-26T23:21:57.4599949Z that your code will be operating on. This is generally the local rank of the 2025-08-26T23:21:57.4600147Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-08-26T23:21:57.4601636Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-08-26T23:21:57.4601791Z utility 2025-08-26T23:21:57.4601836Z 2025-08-26T23:21:57.4601925Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-08-26T23:21:57.4602125Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-08-26T23:21:57.4602315Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-08-26T23:21:57.4602501Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-08-26T23:21:57.4602670Z will not pass ``--local-rank`` when you specify this flag. 2025-08-26T23:21:57.4602770Z 2025-08-26T23:21:57.4602807Z .. warning:: 2025-08-26T23:21:57.4602856Z 2025-08-26T23:21:57.4602931Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-08-26T23:21:57.4603107Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-08-26T23:21:57.4603252Z write to a networked filesystem. See 2025-08-26T23:21:57.4604479Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-08-26T23:21:57.4604702Z how things can go wrong if you don't do this correctly. 2025-08-26T23:21:57.4604799Z 2025-08-26T23:21:57.4604802Z 2025-08-26T23:21:57.4604804Z 2025-08-26T23:21:57.4604805Z 2025-08-26T23:21:57.4604896Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4605019Z 2025-08-26T23:21:57.4984526Z msg = Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-08-26T23:21:57.4984944Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.4985091Z 2025-08-26T23:21:57.4985178Z Custom reducer class that can be used to specify a custom operation that 2025-08-26T23:21:57.4985363Z reduces losses of multiple microbatches into one value. 2025-08-26T23:21:57.4985462Z 2025-08-26T23:21:57.4985499Z Example: 2025-08-26T23:21:57.4985606Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.4985710Z >>> sum_reducer = _CustomReducer( 2025-08-26T23:21:57.4985826Z >>> torch.tensor(0.0), 2025-08-26T23:21:57.4987922Z >>> lambda a, b: a + b 2025-08-26T23:21:57.4988030Z >>> ) 2025-08-26T23:21:57.4988076Z 2025-08-26T23:21:57.4988172Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.4988306Z 2025-08-26T23:21:57.5007310Z msg = Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/options.py line=113. 2025-08-26T23:21:57.5007701Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5007835Z 2025-08-26T23:21:57.5007912Z Set device mapping between each RPC caller and callee pair. This 2025-08-26T23:21:57.5008089Z function can be called multiple times to incrementally add 2025-08-26T23:21:57.5008238Z device placement configurations. 2025-08-26T23:21:57.5008316Z 2025-08-26T23:21:57.5008347Z Args: 2025-08-26T23:21:57.5008431Z to (str): Callee name. 2025-08-26T23:21:57.5010545Z device_map (Dict of int, str, or torch.device): Device placement 2025-08-26T23:21:57.5010786Z mappings from this worker to the callee. This map must be 2025-08-26T23:21:57.5010924Z invertible. 2025-08-26T23:21:57.5010981Z 2025-08-26T23:21:57.5011016Z Example: 2025-08-26T23:21:57.5011111Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.5011227Z >>> # both workers 2025-08-26T23:21:57.5011319Z >>> def add(x, y): 2025-08-26T23:21:57.5011431Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-08-26T23:21:57.5011564Z >>> return x + y, (x + y).to(2) 2025-08-26T23:21:57.5011671Z >>> 2025-08-26T23:21:57.5011748Z >>> # on worker 0 2025-08-26T23:21:57.5011859Z >>> options = TensorPipeRpcBackendOptions( 2025-08-26T23:21:57.5011990Z >>> num_worker_threads=8, 2025-08-26T23:21:57.5012106Z >>> device_maps={"worker1": {0: 1}} 2025-08-26T23:21:57.5012238Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-08-26T23:21:57.5012360Z >>> ) 2025-08-26T23:21:57.5012455Z >>> options.set_device_map("worker1", {1: 2}) 2025-08-26T23:21:57.5013795Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-08-26T23:21:57.5013923Z >>> 2025-08-26T23:21:57.5014001Z >>> rpc.init_rpc( 2025-08-26T23:21:57.5014094Z >>> "worker0", 2025-08-26T23:21:57.5014183Z >>> rank=0, 2025-08-26T23:21:57.5014270Z >>> world_size=2, 2025-08-26T23:21:57.5014383Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-08-26T23:21:57.5014519Z >>> rpc_backend_options=options 2025-08-26T23:21:57.5014630Z >>> ) 2025-08-26T23:21:57.5016827Z >>> 2025-08-26T23:21:57.5016918Z >>> x = torch.ones(2) 2025-08-26T23:21:57.5017050Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-08-26T23:21:57.5017216Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-08-26T23:21:57.5017389Z >>> # sending the return value back, it will follow the invert of 2025-08-26T23:21:57.5017608Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-08-26T23:21:57.5017746Z >>> # cuda:1 on worker0 2025-08-26T23:21:57.5017865Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-08-26T23:21:57.5018018Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-08-26T23:21:57.5018113Z 2025-08-26T23:21:57.5018210Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5018336Z 2025-08-26T23:21:57.5018576Z msg = Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/functions.py line=6. 2025-08-26T23:21:57.5018894Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5019023Z 2025-08-26T23:21:57.5019109Z A decorator for a function indicating that the return value of the function 2025-08-26T23:21:57.5019324Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-08-26T23:21:57.5019520Z function can run asynchronously on the RPC callee. More specifically, the 2025-08-26T23:21:57.5019725Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-08-26T23:21:57.5021194Z function and installs subsequent processing steps as a callback to that 2025-08-26T23:21:57.5021395Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-08-26T23:21:57.5021584Z from the :class:`~torch.futures.Future` when completed and send the 2025-08-26T23:21:57.5021764Z value back as the RPC response. That also means the returned 2025-08-26T23:21:57.5021946Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-08-26T23:21:57.5022143Z sent through RPC. This decorator is useful when the wrapped function's 2025-08-26T23:21:57.5022328Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-08-26T23:21:57.5022518Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-08-26T23:21:57.5022635Z 2025-08-26T23:21:57.5022718Z .. note:: To enable asynchronous execution, applications must pass the 2025-08-26T23:21:57.5022946Z function object returned by this decorator to RPC APIs. If RPC detected 2025-08-26T23:21:57.5024130Z attributes installed by this decorator, it knows that this function 2025-08-26T23:21:57.5024318Z returns a ``Future`` object and will handle that accordingly. 2025-08-26T23:21:57.5024496Z However, this does not mean this decorator has to be outmost one when 2025-08-26T23:21:57.5024690Z defining a function. For example, when combined with ``@staticmethod`` 2025-08-26T23:21:57.5024880Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-08-26T23:21:57.5025068Z inner decorator to allow the target function be recognized as a static 2025-08-26T23:21:57.5025258Z or class function. This target function can still execute asynchronously 2025-08-26T23:21:57.5025454Z because, when accessed, the static or class method preserves attributes 2025-08-26T23:21:57.5025631Z installed by ``@rpc.functions.async_execution``. 2025-08-26T23:21:57.5025725Z 2025-08-26T23:21:57.5025728Z 2025-08-26T23:21:57.5025764Z Example:: 2025-08-26T23:21:57.5025885Z The returned :class:`~torch.futures.Future` object can come from 2025-08-26T23:21:57.5026984Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-08-26T23:21:57.5027156Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-08-26T23:21:57.5027337Z constructor. The example below shows directly using the 2025-08-26T23:21:57.5027487Z :class:`~torch.futures.Future` returned by 2025-08-26T23:21:57.5027618Z :meth:`~torch.futures.Future.then`. 2025-08-26T23:21:57.5027700Z 2025-08-26T23:21:57.5027748Z >>> from torch.distributed import rpc 2025-08-26T23:21:57.5027858Z >>> 2025-08-26T23:21:57.5027943Z >>> # omitting setup and shutdown RPC 2025-08-26T23:21:57.5028051Z >>> 2025-08-26T23:21:57.5028129Z >>> # On all workers 2025-08-26T23:21:57.5028234Z >>> @rpc.functions.async_execution 2025-08-26T23:21:57.5029725Z >>> def async_add_chained(to, x, y, z): 2025-08-26T23:21:57.5029883Z >>> # This function runs on "worker1" and returns immediately when 2025-08-26T23:21:57.5030056Z >>> # the callback is installed through the `then(cb)` API. In the 2025-08-26T23:21:57.5030225Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-08-26T23:21:57.5030479Z >>> # When the return value of that `rpc_async` arrives at 2025-08-26T23:21:57.5030671Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-08-26T23:21:57.5030840Z >>> # and set the value for the previously returned `Future`, which 2025-08-26T23:21:57.5031008Z >>> # will then trigger RPC to send the result back to "worker0". 2025-08-26T23:21:57.5031172Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:21:57.5031340Z >>> lambda fut: fut.wait() + z 2025-08-26T23:21:57.5031448Z >>> ) 2025-08-26T23:21:57.5032518Z >>> 2025-08-26T23:21:57.5032601Z >>> # On worker0 2025-08-26T23:21:57.5032697Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5032801Z >>> ret = rpc.rpc_sync( 2025-08-26T23:21:57.5032900Z >>> "worker1", 2025-08-26T23:21:57.5032997Z >>> async_add_chained, 2025-08-26T23:21:57.5033112Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-08-26T23:21:57.5033223Z >>> ) 2025-08-26T23:21:57.5033315Z >>> print(ret) # prints tensor([3., 3.]) 2025-08-26T23:21:57.5033394Z 2025-08-26T23:21:57.5033480Z When combined with TorchScript decorators, this decorator must be the 2025-08-26T23:21:57.5033628Z outmost one. 2025-08-26T23:21:57.5033681Z 2025-08-26T23:21:57.5034750Z >>> from torch import Tensor 2025-08-26T23:21:57.5034869Z >>> from torch.futures import Future 2025-08-26T23:21:57.5034993Z >>> from torch.distributed import rpc 2025-08-26T23:21:57.5035104Z >>> 2025-08-26T23:21:57.5035189Z >>> # omitting setup and shutdown RPC 2025-08-26T23:21:57.5035298Z >>> 2025-08-26T23:21:57.5035376Z >>> # On all workers 2025-08-26T23:21:57.5035505Z >>> @torch.jit.script 2025-08-26T23:21:57.5035627Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T23:21:57.5035751Z >>> return x + y 2025-08-26T23:21:57.5035841Z >>> 2025-08-26T23:21:57.5036836Z >>> @rpc.functions.async_execution 2025-08-26T23:21:57.5036956Z >>> @torch.jit.script 2025-08-26T23:21:57.5037089Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-08-26T23:21:57.5037245Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-08-26T23:21:57.5037363Z >>> 2025-08-26T23:21:57.5037437Z >>> # On worker0 2025-08-26T23:21:57.5037530Z >>> ret = rpc.rpc_sync( 2025-08-26T23:21:57.5037628Z >>> "worker1", 2025-08-26T23:21:57.5037717Z >>> async_add, 2025-08-26T23:21:57.5037819Z >>> args=("worker2", torch.ones(2), 1) 2025-08-26T23:21:57.5037929Z >>> ) 2025-08-26T23:21:57.5038936Z >>> print(ret) # prints tensor([2., 2.]) 2025-08-26T23:21:57.5039018Z 2025-08-26T23:21:57.5039098Z When combined with static or class method, this decorator must be the 2025-08-26T23:21:57.5039244Z inner one. 2025-08-26T23:21:57.5039294Z 2025-08-26T23:21:57.5039340Z >>> from torch.distributed import rpc 2025-08-26T23:21:57.5039448Z >>> 2025-08-26T23:21:57.5039531Z >>> # omitting setup and shutdown RPC 2025-08-26T23:21:57.5039637Z >>> 2025-08-26T23:21:57.5039712Z >>> # On all workers 2025-08-26T23:21:57.5039816Z >>> class AsyncExecutionClass: 2025-08-26T23:21:57.5039921Z >>> 2025-08-26T23:21:57.5039997Z >>> @staticmethod 2025-08-26T23:21:57.5041109Z >>> @rpc.functions.async_execution 2025-08-26T23:21:57.5041233Z >>> def static_async_add(to, x, y, z): 2025-08-26T23:21:57.5041375Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:21:57.5041520Z >>> lambda fut: fut.wait() + z 2025-08-26T23:21:57.5041663Z >>> ) 2025-08-26T23:21:57.5041745Z >>> 2025-08-26T23:21:57.5041821Z >>> @classmethod 2025-08-26T23:21:57.5041923Z >>> @rpc.functions.async_execution 2025-08-26T23:21:57.5042049Z >>> def class_async_add(cls, to, x, y, z): 2025-08-26T23:21:57.5042178Z >>> ret_fut = torch.futures.Future() 2025-08-26T23:21:57.5042317Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:21:57.5043387Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-08-26T23:21:57.5043536Z >>> ) 2025-08-26T23:21:57.5043625Z >>> return ret_fut 2025-08-26T23:21:57.5043720Z >>> 2025-08-26T23:21:57.5043806Z >>> @rpc.functions.async_execution 2025-08-26T23:21:57.5043930Z >>> def bound_async_add(self, to, x, y, z): 2025-08-26T23:21:57.5044075Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:21:57.5044244Z >>> lambda fut: fut.wait() + z 2025-08-26T23:21:57.5044352Z >>> ) 2025-08-26T23:21:57.5044431Z >>> 2025-08-26T23:21:57.5044507Z >>> # On worker0 2025-08-26T23:21:57.5045525Z >>> ret = rpc.rpc_sync( 2025-08-26T23:21:57.5045627Z >>> "worker1", 2025-08-26T23:21:57.5045732Z >>> AsyncExecutionClass.static_async_add, 2025-08-26T23:21:57.5045861Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T23:21:57.5045971Z >>> ) 2025-08-26T23:21:57.5046060Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:21:57.5046169Z >>> 2025-08-26T23:21:57.5046250Z >>> ret = rpc.rpc_sync( 2025-08-26T23:21:57.5046345Z >>> "worker1", 2025-08-26T23:21:57.5046448Z >>> AsyncExecutionClass.class_async_add, 2025-08-26T23:21:57.5046574Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T23:21:57.5047589Z >>> ) 2025-08-26T23:21:57.5047682Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:21:57.5047764Z 2025-08-26T23:21:57.5047825Z This decorator also works with RRef helpers, i.e., . 2025-08-26T23:21:57.5047974Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-08-26T23:21:57.5048144Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-08-26T23:21:57.5048291Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-08-26T23:21:57.5048379Z 2025-08-26T23:21:57.5048423Z >>> from torch.distributed import rpc 2025-08-26T23:21:57.5048532Z >>> 2025-08-26T23:21:57.5048625Z >>> # reuse the AsyncExecutionClass class above 2025-08-26T23:21:57.5048771Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:21:57.5048938Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-08-26T23:21:57.5050163Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:21:57.5050275Z >>> 2025-08-26T23:21:57.5050442Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:21:57.5050619Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-08-26T23:21:57.5050787Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:21:57.5050897Z >>> 2025-08-26T23:21:57.5050996Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:21:57.5051169Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-08-26T23:21:57.5051332Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:21:57.5051412Z 2025-08-26T23:21:57.5051502Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5051629Z 2025-08-26T23:21:57.5091611Z msg = Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-08-26T23:21:57.5092088Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5092221Z 2025-08-26T23:21:57.5092299Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-08-26T23:21:57.5092508Z except that it enables profiling on all threads running RPC server request callbacks. 2025-08-26T23:21:57.5092696Z 2025-08-26T23:21:57.5092797Z Context manager that manages autograd profiler state and holds a summary of results. 2025-08-26T23:21:57.5093014Z Under the hood it just records events of functions being executed in C++ and 2025-08-26T23:21:57.5093214Z exposes those events to Python. You can wrap any code into it and it will 2025-08-26T23:21:57.5093378Z only report runtime of PyTorch functions. 2025-08-26T23:21:57.5093572Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-08-26T23:21:57.5093706Z 2025-08-26T23:21:57.5093740Z Args: 2025-08-26T23:21:57.5095408Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-08-26T23:21:57.5095589Z Default: ``True``. 2025-08-26T23:21:57.5095655Z 2025-08-26T23:21:57.5095757Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-08-26T23:21:57.5096001Z Adds approximately 4us of overhead to each tensor operation. 2025-08-26T23:21:57.5096148Z Default: ``False`` 2025-08-26T23:21:57.5096211Z 2025-08-26T23:21:57.5096293Z record_shapes (bool, optional): If shapes recording is set, information 2025-08-26T23:21:57.5096490Z about input dimensions will be collected. This allows one to see which 2025-08-26T23:21:57.5096682Z dimensions have been used under the hood and further group by them 2025-08-26T23:21:57.5096870Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-08-26T23:21:57.5097064Z shape recording might skew your profiling data. It is recommended to 2025-08-26T23:21:57.5097261Z use separate runs with and without shape recording to validate the timing. 2025-08-26T23:21:57.5097461Z Most likely the skew will be negligible for bottom most events (in a case 2025-08-26T23:21:57.5098737Z of nested function calls). But for higher level functions the total 2025-08-26T23:21:57.5098922Z self cpu time might be artificially increased because of the shape 2025-08-26T23:21:57.5099089Z collection. 2025-08-26T23:21:57.5099146Z 2025-08-26T23:21:57.5099243Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-08-26T23:21:57.5099377Z 2025-08-26T23:21:57.5099414Z .. warning:: 2025-08-26T23:21:57.5099538Z Enabling memory profiling incurs additional profiler overhead 2025-08-26T23:21:57.5099646Z 2025-08-26T23:21:57.5099680Z .. warning:: 2025-08-26T23:21:57.5099831Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-08-26T23:21:57.5100042Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-08-26T23:21:57.5100234Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-08-26T23:21:57.5100507Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-08-26T23:21:57.5100608Z 2025-08-26T23:21:57.5101657Z Example: 2025-08-26T23:21:57.5101747Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5101846Z >>> # On worker 0: 2025-08-26T23:21:57.5101939Z >>> import torch 2025-08-26T23:21:57.5102044Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.5102181Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:21:57.5102317Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-08-26T23:21:57.5102442Z >>> outer_profile_rref = rpc.remote( 2025-08-26T23:21:57.5102583Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T23:21:57.5102711Z ... ) 2025-08-26T23:21:57.5102804Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-08-26T23:21:57.5103904Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-08-26T23:21:57.5104035Z >>> inner_profile_rref = rpc.remote( 2025-08-26T23:21:57.5104171Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T23:21:57.5104299Z ... ) 2025-08-26T23:21:57.5104391Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-08-26T23:21:57.5104566Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-08-26T23:21:57.5104720Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T23:21:57.5104881Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T23:21:57.5105036Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-08-26T23:21:57.5105223Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5105479Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T23:21:57.5106660Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5106854Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-08-26T23:21:57.5107052Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-08-26T23:21:57.5107245Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5107408Z Self CPU time total: 89.667us 2025-08-26T23:21:57.5107540Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-08-26T23:21:57.5107715Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5107939Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T23:21:57.5108160Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5108343Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-08-26T23:21:57.5108512Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-08-26T23:21:57.5109659Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-08-26T23:21:57.5109842Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:21:57.5110004Z Self CPU time total: 213.926us 2025-08-26T23:21:57.5110116Z >>> rpc.shutdown() 2025-08-26T23:21:57.5110177Z 2025-08-26T23:21:57.5110213Z >>> # On worker 1: 2025-08-26T23:21:57.5110319Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.5110535Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:21:57.5110685Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-08-26T23:21:57.5110815Z >>> rpc.shutdown() 2025-08-26T23:21:57.5110873Z 2025-08-26T23:21:57.5110963Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5111092Z 2025-08-26T23:21:57.5154669Z msg = Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-08-26T23:21:57.5155154Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5155283Z 2025-08-26T23:21:57.5155426Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-08-26T23:21:57.5155600Z 2025-08-26T23:21:57.5155699Z The sharing is done as described by `ZeRO `_. 2025-08-26T23:21:57.5155824Z 2025-08-26T23:21:57.5155881Z The local optimizer instance in each rank is only 2025-08-26T23:21:57.5156056Z responsible for updating approximately ``1 / world_size`` parameters and 2025-08-26T23:21:57.5156252Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-08-26T23:21:57.5156444Z parameters are updated locally, each rank will broadcast its parameters to 2025-08-26T23:21:57.5156638Z all other peers to keep all model replicas in the same state. 2025-08-26T23:21:57.5156858Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-08-26T23:21:57.5158547Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-08-26T23:21:57.5158724Z memory consumption. 2025-08-26T23:21:57.5158782Z 2025-08-26T23:21:57.5158873Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-08-26T23:21:57.5159082Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-08-26T23:21:57.5159311Z not divided among ranks. The partition is arbitrary and might not match the 2025-08-26T23:21:57.5159478Z the parameter registration or usage order. 2025-08-26T23:21:57.5159559Z 2025-08-26T23:21:57.5159593Z Arguments: 2025-08-26T23:21:57.5159714Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-08-26T23:21:57.5159888Z or :class:`dict` s giving all parameters, which will be sharded 2025-08-26T23:21:57.5160047Z across ranks. 2025-08-26T23:21:57.5160106Z 2025-08-26T23:21:57.5160141Z Keyword Args: 2025-08-26T23:21:57.5160274Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-08-26T23:21:57.5161599Z optimizer. 2025-08-26T23:21:57.5161736Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-08-26T23:21:57.5161921Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-08-26T23:21:57.5162087Z :meth:`torch.distributed.init_process_group`). 2025-08-26T23:21:57.5162261Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-08-26T23:21:57.5162452Z packed into buckets to speed up communication, and ``param.data`` 2025-08-26T23:21:57.5162633Z fields point to bucket views at different offsets; if ``False``, 2025-08-26T23:21:57.5162815Z each individual parameter is communicated separately, and each 2025-08-26T23:21:57.5162982Z ``params.data`` stays intact (default: ``False``). 2025-08-26T23:21:57.5163147Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-08-26T23:21:57.5163360Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-08-26T23:21:57.5163544Z synchronization; this requires (1) either a functional optimizer 2025-08-26T23:21:57.5164742Z for the ``optimizer_class`` argument or one with a functional 2025-08-26T23:21:57.5164995Z equivalent and (2) registering a DDP communication hook 2025-08-26T23:21:57.5165168Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-08-26T23:21:57.5165338Z parameters are packed into buckets matching those in 2025-08-26T23:21:57.5165494Z :class:`DistributedDataParallel`, meaning that the 2025-08-26T23:21:57.5165644Z ``parameters_as_bucket_view`` argument is ignored. 2025-08-26T23:21:57.5165803Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-08-26T23:21:57.5165947Z (per normal). 2025-08-26T23:21:57.5166045Z (default: ``False``) 2025-08-26T23:21:57.5166187Z **defaults: any trailing arguments, which are forwarded to the local 2025-08-26T23:21:57.5166331Z optimizer. 2025-08-26T23:21:57.5167368Z 2025-08-26T23:21:57.5167408Z Example:: 2025-08-26T23:21:57.5167455Z 2025-08-26T23:21:57.5167496Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5167599Z >>> import torch.nn as nn 2025-08-26T23:21:57.5167743Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-08-26T23:21:57.5167928Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T23:21:57.5168117Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-08-26T23:21:57.5168279Z >>> ddp = DDP(model, device_ids=[rank]) 2025-08-26T23:21:57.5168405Z >>> opt = ZeroRedundancyOptimizer( 2025-08-26T23:21:57.5168526Z >>> ddp.parameters(), 2025-08-26T23:21:57.5168640Z >>> optimizer_class=torch.optim.Adam, 2025-08-26T23:21:57.5168754Z >>> lr=0.01 2025-08-26T23:21:57.5169813Z >>> ) 2025-08-26T23:21:57.5169902Z >>> ddp(inputs).sum().backward() 2025-08-26T23:21:57.5170010Z >>> opt.step() 2025-08-26T23:21:57.5170064Z 2025-08-26T23:21:57.5170100Z .. warning:: 2025-08-26T23:21:57.5170224Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-08-26T23:21:57.5170479Z passed-in parameters are the same dense type. 2025-08-26T23:21:57.5170568Z 2025-08-26T23:21:57.5170602Z .. warning:: 2025-08-26T23:21:57.5170758Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-08-26T23:21:57.5170944Z the way that overlapping :class:`DistributedDataParallel` with 2025-08-26T23:21:57.5171132Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-08-26T23:21:57.5171326Z two or three training iterations do not perform parameter updates in 2025-08-26T23:21:57.5172477Z the optimizer step, depending on if ``static_graph=False`` or 2025-08-26T23:21:57.5172683Z ``static_graph=True``, respectively. This is because it needs 2025-08-26T23:21:57.5172858Z information about the gradient bucketing strategy used by 2025-08-26T23:21:57.5173037Z :class:`DistributedDataParallel`, which is not finalized until the 2025-08-26T23:21:57.5173223Z second forward pass if ``static_graph=False`` or until the third 2025-08-26T23:21:57.5173404Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-08-26T23:21:57.5173556Z is to prepend dummy inputs. 2025-08-26T23:21:57.5173627Z 2025-08-26T23:21:57.5173720Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-08-26T23:21:57.5173844Z 2025-08-26T23:21:57.5173936Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5174060Z 2025-08-26T23:21:57.5179933Z msg = Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-08-26T23:21:57.5182007Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5182141Z 2025-08-26T23:21:57.5182323Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-08-26T23:21:57.5182549Z This optimizer runs local optimizer at every step. 2025-08-26T23:21:57.5182758Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-08-26T23:21:57.5182910Z 2025-08-26T23:21:57.5182942Z Args: 2025-08-26T23:21:57.5183030Z optim: The local optimizer. 2025-08-26T23:21:57.5183110Z averager: A model averager instance to run post-localSGD algorithm. 2025-08-26T23:21:57.5183115Z 2025-08-26T23:21:57.5183149Z Example:: 2025-08-26T23:21:57.5183152Z 2025-08-26T23:21:57.5183202Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.5183239Z >>> import torch 2025-08-26T23:21:57.5183287Z >>> import torch.distributed as dist 2025-08-26T23:21:57.5183385Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T23:21:57.5183433Z >>> import torch.nn as nn 2025-08-26T23:21:57.5183509Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-08-26T23:21:57.5183605Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T23:21:57.5184833Z >>> PostLocalSGDState, 2025-08-26T23:21:57.5184886Z >>> post_localSGD_hook, 2025-08-26T23:21:57.5184919Z >>> ) 2025-08-26T23:21:57.5184951Z >>> 2025-08-26T23:21:57.5185015Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:21:57.5185072Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:21:57.5185105Z >>> ) 2025-08-26T23:21:57.5185136Z >>> 2025-08-26T23:21:57.5185193Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:21:57.5185300Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T23:21:57.5185365Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:21:57.5185425Z >>> 2025-08-26T23:21:57.5185502Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-08-26T23:21:57.5185593Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-08-26T23:21:57.5185657Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:21:57.5185735Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-08-26T23:21:57.5185801Z >>> opt = PostLocalSGDOptimizer( 2025-08-26T23:21:57.5185843Z >>> optim=local_optim, 2025-08-26T23:21:57.5185933Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T23:21:57.5185965Z >>> ) 2025-08-26T23:21:57.5186000Z >>> 2025-08-26T23:21:57.5186082Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-08-26T23:21:57.5187218Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-08-26T23:21:57.5187356Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-08-26T23:21:57.5187399Z >>> for step in range(0, 200): 2025-08-26T23:21:57.5187439Z >>> opt.zero_grad() 2025-08-26T23:21:57.5187483Z >>> loss = loss_fn(output, labels) 2025-08-26T23:21:57.5187522Z >>> loss.backward() 2025-08-26T23:21:57.5187558Z >>> opt.step() 2025-08-26T23:21:57.5187560Z 2025-08-26T23:21:57.5187652Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5187655Z 2025-08-26T23:21:57.5214384Z msg = Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-08-26T23:21:57.5215452Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5215508Z 2025-08-26T23:21:57.5215656Z DistributedOptimizer takes remote references to parameters scattered 2025-08-26T23:21:57.5216085Z across workers and applies the given optimizer locally for each parameter. 2025-08-26T23:21:57.5216092Z 2025-08-26T23:21:57.5216215Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-08-26T23:21:57.5216291Z to retrieve the gradients for specific parameters. 2025-08-26T23:21:57.5216295Z 2025-08-26T23:21:57.5216352Z Concurrent calls to 2025-08-26T23:21:57.5216468Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-08-26T23:21:57.5216548Z either from the same or different clients, will 2025-08-26T23:21:57.5216673Z be serialized on each worker -- as each worker's optimizer can only work 2025-08-26T23:21:57.5216776Z on one set of gradients at a time. However, there is no guarantee that 2025-08-26T23:21:57.5221888Z the full forward-backward-optimizer sequence will execute for one client 2025-08-26T23:21:57.5222012Z at a time. This means that the gradients being applied may not correspond 2025-08-26T23:21:57.5222112Z to the latest forward pass executed on a given worker. Also, there is no 2025-08-26T23:21:57.5222179Z guaranteed ordering across workers. 2025-08-26T23:21:57.5222183Z 2025-08-26T23:21:57.5222306Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-08-26T23:21:57.5222415Z by default, so that optimizer updates are not blocked by the Python Global 2025-08-26T23:21:57.5222521Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-08-26T23:21:57.5222634Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-08-26T23:21:57.5222743Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-08-26T23:21:57.5222807Z for your own custom optimizers. 2025-08-26T23:21:57.5222813Z 2025-08-26T23:21:57.5222850Z Args: 2025-08-26T23:21:57.5222946Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-08-26T23:21:57.5222998Z instantiate on each worker. 2025-08-26T23:21:57.5223092Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-08-26T23:21:57.5223244Z to optimize. 2025-08-26T23:21:57.5223337Z args: arguments to pass to the optimizer constructor on each worker. 2025-08-26T23:21:57.5223433Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-08-26T23:21:57.5223435Z 2025-08-26T23:21:57.5223501Z Example:: 2025-08-26T23:21:57.5223558Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.5223638Z >>> import torch.distributed.autograd as dist_autograd 2025-08-26T23:21:57.5223762Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.5223815Z >>> from torch import optim 2025-08-26T23:21:57.5225440Z >>> from torch.distributed.optim import DistributedOptimizer 2025-08-26T23:21:57.5225483Z >>> 2025-08-26T23:21:57.5225545Z >>> with dist_autograd.context() as context_id: 2025-08-26T23:21:57.5225670Z >>> # Forward pass. 2025-08-26T23:21:57.5225761Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-08-26T23:21:57.5225850Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-08-26T23:21:57.5225908Z >>> loss = rref1.to_here() + rref2.to_here() 2025-08-26T23:21:57.5225947Z >>> 2025-08-26T23:21:57.5225995Z >>> # Backward pass. 2025-08-26T23:21:57.5226060Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-08-26T23:21:57.5226100Z >>> 2025-08-26T23:21:57.5226142Z >>> # Optimizer. 2025-08-26T23:21:57.5226205Z >>> dist_optim = DistributedOptimizer( 2025-08-26T23:21:57.5226249Z >>> optim.SGD, 2025-08-26T23:21:57.5226294Z >>> [rref1, rref2], 2025-08-26T23:21:57.5226330Z >>> lr=0.05, 2025-08-26T23:21:57.5226371Z >>> ) 2025-08-26T23:21:57.5226423Z >>> dist_optim.step(context_id) 2025-08-26T23:21:57.5226426Z 2025-08-26T23:21:57.5226511Z __ https://github.com/pytorch/tutorials/pull/1465 2025-08-26T23:21:57.5226516Z 2025-08-26T23:21:57.5226622Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5226626Z 2025-08-26T23:21:57.5235004Z msg = Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-08-26T23:21:57.5235183Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5235187Z 2025-08-26T23:21:57.5235330Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-08-26T23:21:57.5235453Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-08-26T23:21:57.5235456Z 2025-08-26T23:21:57.5235542Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-08-26T23:21:57.5235545Z 2025-08-26T23:21:57.5235595Z .. warning:: 2025-08-26T23:21:57.5235686Z Current implementation only supports loading Tensors. 2025-08-26T23:21:57.5235691Z 2025-08-26T23:21:57.5235752Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5235808Z >>> sd = {"mode": model} 2025-08-26T23:21:57.5235856Z >>> dcp.load( 2025-08-26T23:21:57.5235904Z >>> sd, 2025-08-26T23:21:57.5235984Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T23:21:57.5236049Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T23:21:57.5236109Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T23:21:57.5236154Z >>> ) 2025-08-26T23:21:57.5236157Z 2025-08-26T23:21:57.5236278Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5236282Z 2025-08-26T23:21:57.5236594Z msg = Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-08-26T23:21:57.5236733Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5236735Z 2025-08-26T23:21:57.5236869Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-08-26T23:21:57.5237007Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-08-26T23:21:57.5237060Z metadata file, like Torch Save files. 2025-08-26T23:21:57.5237063Z 2025-08-26T23:21:57.5238374Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-08-26T23:21:57.5238382Z 2025-08-26T23:21:57.5238419Z .. warning:: 2025-08-26T23:21:57.5238483Z Current implementation only supports loading Tensors. 2025-08-26T23:21:57.5238486Z 2025-08-26T23:21:57.5238553Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5238591Z >>> sd = {"mode": model} 2025-08-26T23:21:57.5238625Z >>> dcp.load( 2025-08-26T23:21:57.5238657Z >>> sd, 2025-08-26T23:21:57.5238716Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T23:21:57.5238761Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T23:21:57.5238805Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T23:21:57.5238855Z >>> ) 2025-08-26T23:21:57.5238857Z 2025-08-26T23:21:57.5238949Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5238953Z 2025-08-26T23:21:57.5253785Z msg = Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97. 2025-08-26T23:21:57.5253888Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5253999Z 2025-08-26T23:21:57.5254172Z Save a distributed model in SPMD style. 2025-08-26T23:21:57.5254179Z 2025-08-26T23:21:57.5254290Z This function is different from ``torch.save()`` as it handles 2025-08-26T23:21:57.5254395Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-08-26T23:21:57.5254399Z 2025-08-26T23:21:57.5254505Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T23:21:57.5254576Z save will call ``state_dict`` before serialization. 2025-08-26T23:21:57.5254578Z 2025-08-26T23:21:57.5257091Z .. warning:: 2025-08-26T23:21:57.5257309Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-08-26T23:21:57.5257371Z for saved state_dicts. 2025-08-26T23:21:57.5257374Z 2025-08-26T23:21:57.5257414Z .. warning:: 2025-08-26T23:21:57.5257504Z If using the `process_group` argument, make sure that only its ranks 2025-08-26T23:21:57.5257584Z call `save_state_dict` and that all data in state_dict belong to it. 2025-08-26T23:21:57.5257586Z 2025-08-26T23:21:57.5257629Z .. note:: 2025-08-26T23:21:57.5257733Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-08-26T23:21:57.5257835Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-08-26T23:21:57.5257885Z group needs to be passed in. 2025-08-26T23:21:57.5257888Z 2025-08-26T23:21:57.5257931Z .. note:: 2025-08-26T23:21:57.5258032Z If no process group is available, this function assumes the intention is to save the 2025-08-26T23:21:57.5258088Z state_dict in the local process. 2025-08-26T23:21:57.5258093Z 2025-08-26T23:21:57.5258131Z .. note: 2025-08-26T23:21:57.5258194Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T23:21:57.5258196Z 2025-08-26T23:21:57.5258198Z 2025-08-26T23:21:57.5258248Z Args: 2025-08-26T23:21:57.5258310Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T23:21:57.5258365Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:21:57.5258445Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:21:57.5258520Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:21:57.5260045Z It can also be a key if the storage is a key-value store. 2025-08-26T23:21:57.5260092Z (Default: ``None``) 2025-08-26T23:21:57.5260155Z storage_writer (Optional[StorageWriter]): 2025-08-26T23:21:57.5260238Z Instance of StorageWriter used to perform writes. If this is not 2025-08-26T23:21:57.5260318Z specified, DCP will automatically infer the writer based on the 2025-08-26T23:21:57.5260546Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:21:57.5260590Z be raised. (Default: ``None``) 2025-08-26T23:21:57.5260635Z planner (Optional[SavePlanner]): 2025-08-26T23:21:57.5260709Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T23:21:57.5260758Z planner will be used. (Default: ``None``) 2025-08-26T23:21:57.5260849Z process_group (Optional[ProcessGroup]): 2025-08-26T23:21:57.5260919Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:21:57.5260958Z (Default: ``None``) 2025-08-26T23:21:57.5260993Z no_dist (bool): 2025-08-26T23:21:57.5261059Z If ``True``, this function will assume the intent is to load 2025-08-26T23:21:57.5261108Z a checkpoint on a single rank/process. 2025-08-26T23:21:57.5261193Z (Default: ``False``) 2025-08-26T23:21:57.5261285Z use_collectives (bool): If ``False``, this function will assume the intent is to save 2025-08-26T23:21:57.5261352Z a checkpoint without using cross-rank synchronization. 2025-08-26T23:21:57.5261391Z (Default: ``True``) 2025-08-26T23:21:57.5261470Z This configuration is experimental and should be used with caution. 2025-08-26T23:21:57.5261567Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T23:21:57.5261570Z 2025-08-26T23:21:57.5261603Z Returns: 2025-08-26T23:21:57.5261674Z Metadata: Metadata object for the saved checkpoint. 2025-08-26T23:21:57.5261676Z 2025-08-26T23:21:57.5261713Z Example: 2025-08-26T23:21:57.5261762Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5261807Z >>> my_model = MyModule() 2025-08-26T23:21:57.5261809Z 2025-08-26T23:21:57.5261862Z >>> state_dict = {"model": my_model} 2025-08-26T23:21:57.5261865Z 2025-08-26T23:21:57.5261957Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T23:21:57.5262006Z ... "/checkpoint/1" 2025-08-26T23:21:57.5262043Z ... ) 2025-08-26T23:21:57.5262120Z >>> torch.distributed.checkpoint.save( 2025-08-26T23:21:57.5262166Z >>> state_dict=state_dict, 2025-08-26T23:21:57.5263330Z >>> storage_writer=fs_storage_writer, 2025-08-26T23:21:57.5263365Z >>> ) 2025-08-26T23:21:57.5263367Z 2025-08-26T23:21:57.5263401Z .. note:: 2025-08-26T23:21:57.5263481Z save_state_dict uses collectives to coordinate writes across ranks. 2025-08-26T23:21:57.5263560Z For NCCL-based process groups, internal tensor representations of 2025-08-26T23:21:57.5263641Z objects must be moved to the GPU device before communication takes place. 2025-08-26T23:21:57.5263722Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T23:21:57.5263795Z and it is the user's responsibility to ensure that this is set so that 2025-08-26T23:21:57.5263870Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T23:21:57.5263874Z 2025-08-26T23:21:57.5263962Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5263964Z 2025-08-26T23:21:57.5264184Z msg = Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230. 2025-08-26T23:21:57.5264277Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5264373Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-08-26T23:21:57.5264475Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-08-26T23:21:57.5264478Z 2025-08-26T23:21:57.5264514Z .. warning:: 2025-08-26T23:21:57.5264574Z This feature is experimental and subject to change. 2025-08-26T23:21:57.5264631Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-08-26T23:21:57.5264635Z 2025-08-26T23:21:57.5264666Z Args: 2025-08-26T23:21:57.5264748Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T23:21:57.5264804Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:21:57.5264880Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:21:57.5265915Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:21:57.5265983Z It can also be a key if the storage is a key-value store. 2025-08-26T23:21:57.5266041Z (Default: ``None``) 2025-08-26T23:21:57.5266094Z storage_writer (Optional[StorageWriter]): 2025-08-26T23:21:57.5266169Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-08-26T23:21:57.5266254Z this is not specified, DCP will automatically infer the writer based on the 2025-08-26T23:21:57.5266326Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:21:57.5266387Z be raised. (Default: ``None``) 2025-08-26T23:21:57.5266435Z planner (Optional[SavePlanner]): 2025-08-26T23:21:57.5266507Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T23:21:57.5266558Z planner will be used. (Default: ``None``) 2025-08-26T23:21:57.5266608Z process_group (Optional[ProcessGroup]): 2025-08-26T23:21:57.5266677Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:21:57.5266715Z (Default: ``None``) 2025-08-26T23:21:57.5266780Z async_checkpointer_type (AsyncCheckpointerType): 2025-08-26T23:21:57.5266843Z whether to do checkpoint in separate thread or process 2025-08-26T23:21:57.5266903Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-08-26T23:21:57.5266946Z async_stager (AsyncStager): 2025-08-26T23:21:57.5267037Z provides staging implementation. If storage_writer implements AsyncStager 2025-08-26T23:21:57.5267114Z and async_stager is provided, async_stager will be used for staging 2025-08-26T23:21:57.5267153Z no_dist (bool): 2025-08-26T23:21:57.5267229Z If ``True``, this function will assume the intent is to save 2025-08-26T23:21:57.5268214Z a checkpoint on a single rank/process. 2025-08-26T23:21:57.5268256Z (Default: ``False``) 2025-08-26T23:21:57.5268366Z use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``) 2025-08-26T23:21:57.5268448Z This configuration is experimental and should be used with caution. 2025-08-26T23:21:57.5268544Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T23:21:57.5268546Z 2025-08-26T23:21:57.5268579Z Returns: 2025-08-26T23:21:57.5268654Z Future: A future holding the resultant Metadata object from `save`. 2025-08-26T23:21:57.5268657Z 2025-08-26T23:21:57.5268692Z Example: 2025-08-26T23:21:57.5268733Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5268774Z >>> my_model = MyModule() 2025-08-26T23:21:57.5268776Z 2025-08-26T23:21:57.5268823Z >>> state_dict = {"model": my_model} 2025-08-26T23:21:57.5268826Z 2025-08-26T23:21:57.5268909Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T23:21:57.5268949Z ... "/checkpoint/1" 2025-08-26T23:21:57.5268980Z ... ) 2025-08-26T23:21:57.5269057Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-08-26T23:21:57.5269099Z >>> state_dict=state_dict, 2025-08-26T23:21:57.5269147Z >>> storage_writer=fs_storage_writer, 2025-08-26T23:21:57.5269178Z >>> ) 2025-08-26T23:21:57.5269209Z >>> 2025-08-26T23:21:57.5269249Z >>> # ... do some work ... 2025-08-26T23:21:57.5269281Z >>> 2025-08-26T23:21:57.5270239Z >>> checkpoint_future.result() 2025-08-26T23:21:57.5270243Z 2025-08-26T23:21:57.5270276Z 2025-08-26T23:21:57.5270451Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5270494Z 2025-08-26T23:21:57.5327205Z msg = Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-08-26T23:21:57.5327320Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5327356Z 2025-08-26T23:21:57.5327630Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-08-26T23:21:57.5327639Z 2025-08-26T23:21:57.5327822Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-08-26T23:21:57.5327827Z 2025-08-26T23:21:57.5327933Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T23:21:57.5327992Z will be visible to the whole process. 2025-08-26T23:21:57.5327996Z 2025-08-26T23:21:57.5328173Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-08-26T23:21:57.5328182Z 2025-08-26T23:21:57.5328242Z 1) set_up_planner - called on all ranks. 2025-08-26T23:21:57.5328299Z Signals the start of a checkpoint save. 2025-08-26T23:21:57.5328302Z 2025-08-26T23:21:57.5328357Z 2) create_local_plan - called on all ranks. 2025-08-26T23:21:57.5328467Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-08-26T23:21:57.5328469Z 2025-08-26T23:21:57.5328552Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T23:21:57.5328633Z Takes the SavePlan from all ranks and make any global decision. 2025-08-26T23:21:57.5328635Z 2025-08-26T23:21:57.5328687Z 4) finish_plan - called on all ranks. 2025-08-26T23:21:57.5328770Z This gives each rank a chance to adjust to global planning decisions. 2025-08-26T23:21:57.5328772Z 2025-08-26T23:21:57.5328839Z 5) resolve_data - called multiple times on each rank 2025-08-26T23:21:57.5331093Z Lookups a value on the `state_dict` for the storage layer to write. 2025-08-26T23:21:57.5331098Z 2025-08-26T23:21:57.5331283Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-08-26T23:21:57.5331366Z most changes can be expressed by changes in a single method. 2025-08-26T23:21:57.5331369Z 2025-08-26T23:21:57.5331420Z There are 3 usual patterns of extension: 2025-08-26T23:21:57.5331422Z 2025-08-26T23:21:57.5331520Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-08-26T23:21:57.5331603Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-08-26T23:21:57.5331606Z 2025-08-26T23:21:57.5331651Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5331704Z >>> class RenamePlanner(DefaultSavePlanner): 2025-08-26T23:21:57.5331751Z >>> def set_up_planner( 2025-08-26T23:21:57.5331785Z >>> self, 2025-08-26T23:21:57.5331827Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T23:21:57.5331879Z >>> storage_meta: Optional[StorageMeta], 2025-08-26T23:21:57.5331922Z >>> is_coordinator: bool, 2025-08-26T23:21:57.5331958Z >>> ) -> None: 2025-08-26T23:21:57.5332004Z >>> # prefix all keys with `foo_`` 2025-08-26T23:21:57.5332113Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-08-26T23:21:57.5332115Z 2025-08-26T23:21:57.5332233Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-08-26T23:21:57.5332236Z 2025-08-26T23:21:57.5332281Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5332331Z >>> class FP16Planner(DefaultSavePlanner): 2025-08-26T23:21:57.5332379Z >>> def create_local_plan(self): 2025-08-26T23:21:57.5333872Z >>> plan = super().create_local_plan() 2025-08-26T23:21:57.5333920Z >>> for p in plan: 2025-08-26T23:21:57.5333974Z >>> if p.tensor_data is not None: 2025-08-26T23:21:57.5334049Z >>> p.tensor_data.properties.dtype = torch.float16 2025-08-26T23:21:57.5334091Z >>> return plan 2025-08-26T23:21:57.5334169Z >>> 2025-08-26T23:21:57.5334216Z >>> def resolve_data(self, write_item): 2025-08-26T23:21:57.5334265Z >>> item = super().resolve_data(write_item) 2025-08-26T23:21:57.5334366Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-08-26T23:21:57.5334369Z 2025-08-26T23:21:57.5334488Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-08-26T23:21:57.5334490Z 2025-08-26T23:21:57.5334552Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5334597Z >>> from itertools import zip_longest 2025-08-26T23:21:57.5334640Z >>> from dataclasses import replace 2025-08-26T23:21:57.5334706Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-08-26T23:21:57.5334803Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-08-26T23:21:57.5334874Z >>> # This sample doesn't handle ShardedTensors 2025-08-26T23:21:57.5334923Z >>> def create_global_plan(self, all_plans): 2025-08-26T23:21:57.5334984Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-08-26T23:21:57.5335023Z >>> items_per_rank = [ 2025-08-26T23:21:57.5335078Z >>> [item for item in items if item is not None] 2025-08-26T23:21:57.5335139Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-08-26T23:21:57.5335172Z >>> ] 2025-08-26T23:21:57.5335213Z >>> all_plans = [ 2025-08-26T23:21:57.5335262Z >>> replace(plan, items=items) 2025-08-26T23:21:57.5335342Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-08-26T23:21:57.5335379Z >>> ] 2025-08-26T23:21:57.5335442Z >>> return super().create_global_plan(all_plans) 2025-08-26T23:21:57.5335445Z 2025-08-26T23:21:57.5335541Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-08-26T23:21:57.5335648Z accomplished by having each rank contribute their data items in the local plan and 2025-08-26T23:21:57.5335697Z the global planner aggregate them: 2025-08-26T23:21:57.5335736Z 2025-08-26T23:21:57.5335787Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5336919Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-08-26T23:21:57.5336974Z >>> def create_local_plan(self) -> SavePlan: 2025-08-26T23:21:57.5337022Z >>> plan = super().create_local_plan() 2025-08-26T23:21:57.5337086Z >>> return replace(plan, planner_data="per-rank-data") 2025-08-26T23:21:57.5337119Z >>> 2025-08-26T23:21:57.5337234Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-08-26T23:21:57.5337308Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-08-26T23:21:57.5337368Z >>> merged_data = [p.planner_data for p in global_plan] 2025-08-26T23:21:57.5337436Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-08-26T23:21:57.5337479Z >>> return global_plan, metadata 2025-08-26T23:21:57.5337483Z 2025-08-26T23:21:57.5337573Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5337576Z 2025-08-26T23:21:57.5337786Z msg = Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-08-26T23:21:57.5337878Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5337880Z 2025-08-26T23:21:57.5337980Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-08-26T23:21:57.5337982Z 2025-08-26T23:21:57.5338082Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-08-26T23:21:57.5338084Z 2025-08-26T23:21:57.5338180Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T23:21:57.5338226Z will be visible to the whole process. 2025-08-26T23:21:57.5338228Z 2025-08-26T23:21:57.5338346Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-08-26T23:21:57.5338349Z 2025-08-26T23:21:57.5338395Z 1) set_up_planner - called on all ranks. 2025-08-26T23:21:57.5338445Z Signals the start of loading a checkpoint. 2025-08-26T23:21:57.5338448Z 2025-08-26T23:21:57.5338494Z 2) create_local_plan - called on all ranks. 2025-08-26T23:21:57.5339606Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-08-26T23:21:57.5339609Z 2025-08-26T23:21:57.5339698Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T23:21:57.5339772Z Takes the LoadPlan from all ranks and make any global decision. 2025-08-26T23:21:57.5339775Z 2025-08-26T23:21:57.5339829Z 4) load_bytes - called multiple times on each rank 2025-08-26T23:21:57.5339893Z This is called once per non-tensor value in state_dict. 2025-08-26T23:21:57.5339911Z 2025-08-26T23:21:57.5339990Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-08-26T23:21:57.5340062Z They are called in pair for each Tensor value in state_dict. 2025-08-26T23:21:57.5340064Z 2025-08-26T23:21:57.5340169Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-08-26T23:21:57.5340236Z most changes can be expressed by changes in a single method. 2025-08-26T23:21:57.5340239Z 2025-08-26T23:21:57.5340287Z There are two usual patterns of extension: 2025-08-26T23:21:57.5340289Z 2025-08-26T23:21:57.5340478Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-08-26T23:21:57.5340566Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-08-26T23:21:57.5340647Z to keep a reference to the original state_dict as load happens in place so 2025-08-26T23:21:57.5340695Z we need to be able to perform it in place 2025-08-26T23:21:57.5340699Z 2025-08-26T23:21:57.5340749Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5340799Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-08-26T23:21:57.5340841Z >>> def set_up_planner( 2025-08-26T23:21:57.5340896Z >>> self, 2025-08-26T23:21:57.5340940Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T23:21:57.5340979Z >>> metadata: Metadata, 2025-08-26T23:21:57.5341020Z >>> is_coordinator: bool, 2025-08-26T23:21:57.5342038Z >>> ) -> None: 2025-08-26T23:21:57.5342090Z >>> self.original_state_dict = state_dict 2025-08-26T23:21:57.5342158Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-08-26T23:21:57.5342188Z >>> 2025-08-26T23:21:57.5342235Z >>> if self.flatten_sharded_tensors: 2025-08-26T23:21:57.5342295Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-08-26T23:21:57.5342326Z >>> 2025-08-26T23:21:57.5342367Z >>> if self.flatten_state_dict: 2025-08-26T23:21:57.5342435Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-08-26T23:21:57.5342466Z >>> 2025-08-26T23:21:57.5342509Z >>> self.state_dict = state_dict 2025-08-26T23:21:57.5342550Z >>> self.metadata = metadata 2025-08-26T23:21:57.5342597Z >>> self.is_coordinator = is_coordinator 2025-08-26T23:21:57.5342626Z >>> 2025-08-26T23:21:57.5342673Z >>> def load_bytes(self, read_item, value): 2025-08-26T23:21:57.5342714Z >>> # Remove the "foo_" prefix 2025-08-26T23:21:57.5342829Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-08-26T23:21:57.5342832Z 2025-08-26T23:21:57.5342835Z 2025-08-26T23:21:57.5342928Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-08-26T23:21:57.5342931Z 2025-08-26T23:21:57.5342974Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:21:57.5343030Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-08-26T23:21:57.5343076Z >>> def resolve_tensor(self, read_item): 2025-08-26T23:21:57.5343129Z >>> tensor = super().resolve_tensor(read_item) 2025-08-26T23:21:57.5344168Z >>> return torch.empty_like(tensor, device="cpu") 2025-08-26T23:21:57.5344203Z >>> 2025-08-26T23:21:57.5344253Z >>> def commit_tensor(self, read_item, tensor): 2025-08-26T23:21:57.5344313Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-08-26T23:21:57.5344315Z 2025-08-26T23:21:57.5344405Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5344407Z 2025-08-26T23:21:57.5401760Z msg = Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-08-26T23:21:57.5401874Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5401996Z 2025-08-26T23:21:57.5402239Z Return the model state_dict and optimizers state_dict. 2025-08-26T23:21:57.5402247Z 2025-08-26T23:21:57.5402570Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-08-26T23:21:57.5402702Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-08-26T23:21:57.5402846Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-08-26T23:21:57.5402955Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-08-26T23:21:57.5403068Z with a different number of trainers and/or different parallelisms. 2025-08-26T23:21:57.5403199Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-08-26T23:21:57.5403259Z these APIs. 2025-08-26T23:21:57.5403328Z 3.) sanity checking the result state_dict. 2025-08-26T23:21:57.5403331Z 2025-08-26T23:21:57.5403444Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-08-26T23:21:57.5403563Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-08-26T23:21:57.5403678Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-08-26T23:21:57.5406727Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-08-26T23:21:57.5406923Z ``module.named_buffers()`` when the module is not distributed by any 2025-08-26T23:21:57.5407050Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-08-26T23:21:57.5407164Z a parameter, there will be a conversion from the parameter IDs to the 2025-08-26T23:21:57.5407228Z canonical FQNs when calling this API. 2025-08-26T23:21:57.5407235Z 2025-08-26T23:21:57.5407354Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-08-26T23:21:57.5407464Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-08-26T23:21:57.5407545Z optimizer parameter IDs to the canonical FQNs. 2025-08-26T23:21:57.5407550Z 2025-08-26T23:21:57.5407599Z Example: 2025-08-26T23:21:57.5407660Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5407704Z >>> import torch 2025-08-26T23:21:57.5407819Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:21:57.5407919Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T23:21:57.5408024Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-08-26T23:21:57.5408028Z 2025-08-26T23:21:57.5408089Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-08-26T23:21:57.5408184Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T23:21:57.5408244Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-08-26T23:21:57.5408334Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T23:21:57.5408339Z 2025-08-26T23:21:57.5408341Z 2025-08-26T23:21:57.5408450Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-08-26T23:21:57.5408537Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-08-26T23:21:57.5408597Z ... fsdp_model, fsdp_optim 2025-08-26T23:21:57.5410238Z ... ) 2025-08-26T23:21:57.5410242Z 2025-08-26T23:21:57.5410529Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-08-26T23:21:57.5410631Z >>> # the asserts will fail. 2025-08-26T23:21:57.5410688Z >>> assert ddp_state_dict == fsdp_state_dict 2025-08-26T23:21:57.5410753Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-08-26T23:21:57.5410756Z 2025-08-26T23:21:57.5410757Z 2025-08-26T23:21:57.5410795Z Args: 2025-08-26T23:21:57.5410855Z model (nn.Module): the nn.Module to the model. 2025-08-26T23:21:57.5410937Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-08-26T23:21:57.5411050Z The optimizers that are used to optimize ``model``. 2025-08-26T23:21:57.5411163Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-08-26T23:21:57.5411214Z that belong to the submodules. 2025-08-26T23:21:57.5411288Z options (StateDictOptions): the options to control how 2025-08-26T23:21:57.5411371Z model state_dict and optimizer state_dict should be returned. See 2025-08-26T23:21:57.5411450Z `StateDictOptions` for the details. 2025-08-26T23:21:57.5411453Z 2025-08-26T23:21:57.5411486Z Returns: 2025-08-26T23:21:57.5411573Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-08-26T23:21:57.5411575Z 2025-08-26T23:21:57.5411671Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-08-26T23:21:57.5411674Z 2025-08-26T23:21:57.5411776Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5411778Z 2025-08-26T23:21:57.5482336Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69. 2025-08-26T23:21:57.5484441Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5484446Z 2025-08-26T23:21:57.5484549Z Load a checkpoint into a distributed state dict in SPMD style. 2025-08-26T23:21:57.5484557Z 2025-08-26T23:21:57.5484650Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-08-26T23:21:57.5484743Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-08-26T23:21:57.5484893Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-08-26T23:21:57.5484931Z costs). 2025-08-26T23:21:57.5484934Z 2025-08-26T23:21:57.5485007Z Each rank will try to read the least amount of data necessary 2025-08-26T23:21:57.5485098Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-08-26T23:21:57.5485196Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-08-26T23:21:57.5485198Z 2025-08-26T23:21:57.5485300Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T23:21:57.5485398Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-08-26T23:21:57.5485467Z ``load_state_dict`` once the deserialization is complete. 2025-08-26T23:21:57.5485569Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-08-26T23:21:57.5485632Z it in the ``state_dict`` with the deserialized object. 2025-08-26T23:21:57.5485636Z 2025-08-26T23:21:57.5485678Z .. warning:: 2025-08-26T23:21:57.5485748Z All tensors in ``state_dict`` must be allocated on their 2025-08-26T23:21:57.5485813Z destination device *prior to* calling this function. 2025-08-26T23:21:57.5485820Z 2025-08-26T23:21:57.5485912Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-08-26T23:21:57.5485956Z on state_dict. 2025-08-26T23:21:57.5485960Z 2025-08-26T23:21:57.5486003Z .. warning:: 2025-08-26T23:21:57.5486081Z Users must call `load_state_dict` on the root module to ensure load 2025-08-26T23:21:57.5486160Z pos-processing and non-tensor data properly propagates. 2025-08-26T23:21:57.5486162Z 2025-08-26T23:21:57.5487436Z .. note: 2025-08-26T23:21:57.5487528Z If no process group is initialized, this function will assume the intent 2025-08-26T23:21:57.5487614Z is to load a checkpoint into the local process. This can be useful in the 2025-08-26T23:21:57.5487743Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-08-26T23:21:57.5487784Z or ShardedTensor) 2025-08-26T23:21:57.5487789Z 2025-08-26T23:21:57.5487821Z .. note: 2025-08-26T23:21:57.5487877Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T23:21:57.5487879Z 2025-08-26T23:21:57.5487914Z Args: 2025-08-26T23:21:57.5487995Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-08-26T23:21:57.5488074Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:21:57.5488153Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:21:57.5488230Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:21:57.5488300Z It can also be a key if the storage is a key-value store. 2025-08-26T23:21:57.5488363Z (Default: ``None``) 2025-08-26T23:21:57.5488417Z storage_reader (Optional[StorageReader]): 2025-08-26T23:21:57.5488497Z Instance of StorageWriter used to perform reads. If this is not 2025-08-26T23:21:57.5488575Z specified, DCP will automatically infer the reader based on the 2025-08-26T23:21:57.5488648Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:21:57.5488693Z be raised. (Default: ``None``) 2025-08-26T23:21:57.5488742Z planner (Optional[LoadPlanner]): 2025-08-26T23:21:57.5488819Z Instance of LoadPlanner. If this is not specified, the default 2025-08-26T23:21:57.5489932Z planner will be used. (Default: ``None``) 2025-08-26T23:21:57.5489992Z process_group (Optional[ProcessGroup]): 2025-08-26T23:21:57.5490066Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:21:57.5490107Z (Default: ``None``) 2025-08-26T23:21:57.5490189Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-08-26T23:21:57.5490286Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-08-26T23:21:57.5490428Z Returns: 2025-08-26T23:21:57.5490486Z None. 2025-08-26T23:21:57.5490489Z 2025-08-26T23:21:57.5490523Z Examples 2025-08-26T23:21:57.5490562Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5490604Z >>> my_model = MyModule() 2025-08-26T23:21:57.5490656Z >>> optimizer = Adagrad(my_model.parameters()) 2025-08-26T23:21:57.5490704Z >>> model_state_dict = my_model.state_dict() 2025-08-26T23:21:57.5490793Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-08-26T23:21:57.5490832Z ... "/checkpoint/1" 2025-08-26T23:21:57.5490864Z ... ) 2025-08-26T23:21:57.5490867Z 2025-08-26T23:21:57.5490927Z >>> torch.distributed.checkpoint.load_state_dict( 2025-08-26T23:21:57.5490973Z >>> state_dict=model_state_dict, 2025-08-26T23:21:57.5491018Z >>> storage_reader=fs_storage_reader, 2025-08-26T23:21:57.5491051Z >>> ) 2025-08-26T23:21:57.5491053Z 2025-08-26T23:21:57.5491124Z >>> # module.load_state_dict() function might have customized steps 2025-08-26T23:21:57.5491173Z >>> # to flush the state_dict, must call it to 2025-08-26T23:21:57.5492192Z >>> # ensure correct behavior. 2025-08-26T23:21:57.5492246Z >>> my_model.load_state_dict(model_state_dict) 2025-08-26T23:21:57.5492248Z 2025-08-26T23:21:57.5492281Z .. note:: 2025-08-26T23:21:57.5492360Z load_state_dict uses collectives to coordinate reads across ranks. 2025-08-26T23:21:57.5492438Z For NCCL-based process groups, internal tensor representations of 2025-08-26T23:21:57.5492520Z objects must be moved to the GPU device before communication takes place. 2025-08-26T23:21:57.5492599Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T23:21:57.5492679Z and it is the user's responsibility to ensure that this is set so that each 2025-08-26T23:21:57.5492749Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T23:21:57.5492751Z 2025-08-26T23:21:57.5492874Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5492878Z 2025-08-26T23:21:57.5552287Z msg = Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-08-26T23:21:57.5552395Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5552527Z 2025-08-26T23:21:57.5552877Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-08-26T23:21:57.5552883Z 2025-08-26T23:21:57.5552966Z This is the current recommended way to checkpoint FSDP. 2025-08-26T23:21:57.5553012Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.5553089Z >>> import torch.distributed.checkpoint as dist_cp 2025-08-26T23:21:57.5553131Z >>> # Save 2025-08-26T23:21:57.5553179Z >>> model: torch.nn.Model 2025-08-26T23:21:57.5553287Z >>> optim_params = model.parameters() 2025-08-26T23:21:57.5555841Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-08-26T23:21:57.5555920Z >>> # Save 2025-08-26T23:21:57.5556058Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-08-26T23:21:57.5556122Z >>> state_dict = { 2025-08-26T23:21:57.5556192Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-08-26T23:21:57.5556245Z >>> "model": model.state_dict() 2025-08-26T23:21:57.5556281Z >>> } 2025-08-26T23:21:57.5556336Z >>> dist_cp.save_state_dict( 2025-08-26T23:21:57.5556385Z >>> state_dict=optim_state, 2025-08-26T23:21:57.5556470Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-08-26T23:21:57.5556528Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-08-26T23:21:57.5556570Z >>> ) 2025-08-26T23:21:57.5556606Z >>> 2025-08-26T23:21:57.5556648Z >>> # Load 2025-08-26T23:21:57.5556733Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-08-26T23:21:57.5556789Z >>> model_state_dict = model_tp.state_dict() 2025-08-26T23:21:57.5556826Z >>> checkpoint = { 2025-08-26T23:21:57.5556928Z >>> "model": model_state_dict 2025-08-26T23:21:57.5556959Z >>> } 2025-08-26T23:21:57.5556999Z >>> dist_cp.load_state_dict( 2025-08-26T23:21:57.5557040Z >>> state_dict=checkpoint, 2025-08-26T23:21:57.5557109Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-08-26T23:21:57.5558453Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-08-26T23:21:57.5558488Z >>> ) 2025-08-26T23:21:57.5558552Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-08-26T23:21:57.5558582Z >>> 2025-08-26T23:21:57.5558649Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-08-26T23:21:57.5558689Z >>> model_state_dict, 2025-08-26T23:21:57.5558734Z >>> optimizer_key="optimizer", 2025-08-26T23:21:57.5558800Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-08-26T23:21:57.5558832Z >>> ) 2025-08-26T23:21:57.5558862Z >>> 2025-08-26T23:21:57.5558923Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-08-26T23:21:57.5558973Z >>> model, optim, optim_state["optimizer"] 2025-08-26T23:21:57.5559005Z >>> ) 2025-08-26T23:21:57.5559034Z >>> 2025-08-26T23:21:57.5559082Z >>> optim.load_state_dict(flattened_osd) 2025-08-26T23:21:57.5559085Z 2025-08-26T23:21:57.5559178Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5559180Z 2025-08-26T23:21:57.5918868Z msg = Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=114. 2025-08-26T23:21:57.5920589Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5920629Z 2025-08-26T23:21:57.5920852Z This configures FSDP-native mixed precision training. 2025-08-26T23:21:57.5920859Z 2025-08-26T23:21:57.5929180Z Attributes: 2025-08-26T23:21:57.5929487Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-08-26T23:21:57.5930080Z parameters during forward and backward and thus the dtype for 2025-08-26T23:21:57.5930195Z forward and backward computation. Outside forward and backward, the 2025-08-26T23:21:57.5930297Z *sharded* parameters are kept in full precision (e.g. for the 2025-08-26T23:21:57.5930556Z optimizer step), and for model checkpointing, the parameters are 2025-08-26T23:21:57.5930644Z always saved in full precision. (Default: ``None``) 2025-08-26T23:21:57.5930845Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T23:21:57.5930951Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-08-26T23:21:57.5931052Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-08-26T23:21:57.5931149Z the ``param_dtype`` value, still running gradient reduction in low 2025-08-26T23:21:57.5931335Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-08-26T23:21:57.5931440Z to force gradient reduction to run in full precision. (Default: 2025-08-26T23:21:57.5931499Z ``None``) 2025-08-26T23:21:57.5931605Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T23:21:57.5931711Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-08-26T23:21:57.5931809Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-08-26T23:21:57.5931919Z dtype thereafter. For model checkpointing, the buffers are saved 2025-08-26T23:21:57.5932008Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-08-26T23:21:57.5932046Z ``None``) 2025-08-26T23:21:57.5932150Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-08-26T23:21:57.5932265Z gradients to full precision after the backward pass in preparation 2025-08-26T23:21:57.5934475Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-08-26T23:21:57.5934586Z in the dtype used for gradient reduction, which can save memory if 2025-08-26T23:21:57.5934757Z using a custom optimizer that supports running in low precision. 2025-08-26T23:21:57.5934817Z (Default: ``False``) 2025-08-26T23:21:57.5934921Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-08-26T23:21:57.5935017Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-08-26T23:21:57.5935117Z that parameter and input dtypes match for forward computation, as 2025-08-26T23:21:57.5935214Z required by many ops. This may need to be set to ``True`` when only 2025-08-26T23:21:57.5935316Z applying mixed precision to some but not all FSDP modules, in which 2025-08-26T23:21:57.5935414Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-08-26T23:21:57.5935467Z (Default: ``False``) 2025-08-26T23:21:57.5935569Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-08-26T23:21:57.5935668Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-08-26T23:21:57.5935759Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-08-26T23:21:57.5935829Z this does not do anything. (Default: ``True``) 2025-08-26T23:21:57.5935951Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-08-26T23:21:57.5936036Z module classes to ignore for mixed precision when using an 2025-08-26T23:21:57.5936129Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-08-26T23:21:57.5936229Z applied to them separately with mixed precision disabled (meaning 2025-08-26T23:21:57.5936325Z that the final FSDP construction would deviate from the specified 2025-08-26T23:21:57.5936416Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-08-26T23:21:57.5936503Z not do anything. This API is experimental and subject to change. 2025-08-26T23:21:57.5936590Z (Default: ``(_BatchNorm,)``) 2025-08-26T23:21:57.5936594Z 2025-08-26T23:21:57.5936705Z .. note:: This API is experimental and subject to change. 2025-08-26T23:21:57.5936715Z 2025-08-26T23:21:57.5936821Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-08-26T23:21:57.5936825Z 2025-08-26T23:21:57.5936920Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-08-26T23:21:57.5936984Z precision, but buffers are not. 2025-08-26T23:21:57.5936987Z 2025-08-26T23:21:57.5937109Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-08-26T23:21:57.5937213Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-08-26T23:21:57.5937335Z Disabling FSDP's mixed precision for those norm modules only means that 2025-08-26T23:21:57.5937442Z the affine parameters are kept in ``float32``. However, this incurs 2025-08-26T23:21:57.5937571Z separate all-gathers and reduce-scatters for those norm modules, which 2025-08-26T23:21:57.5937688Z may be inefficient, so if the workload permits, the user should prefer 2025-08-26T23:21:57.5939863Z to still apply mixed precision to those modules. 2025-08-26T23:21:57.5939866Z 2025-08-26T23:21:57.5940016Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-08-26T23:21:57.5940135Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-08-26T23:21:57.5940221Z modules will have FSDP applied to them separately with mixed precision 2025-08-26T23:21:57.5940291Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-08-26T23:21:57.5940294Z 2025-08-26T23:21:57.5940527Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-08-26T23:21:57.5940605Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-08-26T23:21:57.5940675Z its ``cast_root_forward_inputs`` takes precedence over its 2025-08-26T23:21:57.5940745Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-08-26T23:21:57.5940865Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-08-26T23:21:57.5940949Z sufficient for the typical case where each FSDP instance has the same 2025-08-26T23:21:57.5941031Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-08-26T23:21:57.5941102Z ``param_dtype`` at the beginning of the model's forward pass. 2025-08-26T23:21:57.5941104Z 2025-08-26T23:21:57.5941183Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-08-26T23:21:57.5941268Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-08-26T23:21:57.5941345Z values to configure casting inputs or not before each instance's 2025-08-26T23:21:57.5941419Z forward. In such a case, since the casts happen before each FSDP 2025-08-26T23:21:57.5941501Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-08-26T23:21:57.5941589Z submodules run before its FSDP submodules to avoid the activation dtype 2025-08-26T23:21:57.5941665Z being changed due to a different ``MixedPrecision`` configuration. 2025-08-26T23:21:57.5941667Z 2025-08-26T23:21:57.5941707Z Example:: 2025-08-26T23:21:57.5941709Z 2025-08-26T23:21:57.5942840Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.5942910Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-08-26T23:21:57.5942952Z >>> model[1] = FSDP( 2025-08-26T23:21:57.5942994Z >>> model[1], 2025-08-26T23:21:57.5943109Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-08-26T23:21:57.5943145Z >>> ) 2025-08-26T23:21:57.5943184Z >>> model = FSDP( 2025-08-26T23:21:57.5943218Z >>> model, 2025-08-26T23:21:57.5943331Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-08-26T23:21:57.5943363Z >>> ) 2025-08-26T23:21:57.5943366Z 2025-08-26T23:21:57.5943476Z The above shows a working example. On the other hand, if ``model[1]`` 2025-08-26T23:21:57.5943557Z were replaced with ``model[0]``, meaning that the submodule using 2025-08-26T23:21:57.5943640Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-08-26T23:21:57.5943719Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-08-26T23:21:57.5943753Z ones. 2025-08-26T23:21:57.5943755Z 2025-08-26T23:21:57.5943757Z 2025-08-26T23:21:57.5943872Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5943874Z 2025-08-26T23:21:57.5944087Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=295. 2025-08-26T23:21:57.5944185Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.5944208Z 2025-08-26T23:21:57.5944284Z ``FullStateDictConfig`` is a config class meant to be used with 2025-08-26T23:21:57.5944363Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-08-26T23:21:57.5944438Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-08-26T23:21:57.5944524Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-08-26T23:21:57.5945583Z is meant to be used via the :func:`state_dict_type` context manager as 2025-08-26T23:21:57.5945618Z follows: 2025-08-26T23:21:57.5945620Z 2025-08-26T23:21:57.5945675Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.5945766Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:21:57.5945816Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-08-26T23:21:57.5945894Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-08-26T23:21:57.5945974Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-08-26T23:21:57.5946022Z >>> state = fsdp.state_dict() 2025-08-26T23:21:57.5946105Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-08-26T23:21:57.5946213Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-08-26T23:21:57.5946303Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-08-26T23:21:57.5946345Z >>> if dist.get_rank() == 0: 2025-08-26T23:21:57.5946417Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-08-26T23:21:57.5946476Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-08-26T23:21:57.5946527Z >>> model.load_state_dict(state_dict) 2025-08-26T23:21:57.5946614Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-08-26T23:21:57.5946699Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-08-26T23:21:57.5946738Z >>> fsdp = FSDP( 2025-08-26T23:21:57.5946774Z ... model, 2025-08-26T23:21:57.5946828Z ... device_id=torch.cuda.current_device(), 2025-08-26T23:21:57.5946874Z ... auto_wrap_policy=..., 2025-08-26T23:21:57.5947869Z ... sync_module_states=True, 2025-08-26T23:21:57.5947904Z ... ) 2025-08-26T23:21:57.5947983Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-08-26T23:21:57.5947985Z 2025-08-26T23:21:57.5948020Z Attributes: 2025-08-26T23:21:57.5948098Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-08-26T23:21:57.5948172Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-08-26T23:21:57.5948235Z ranks save the full state dict. (Default: ``False``) 2025-08-26T23:21:57.5948237Z 2025-08-26T23:21:57.5948330Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.5948332Z 2025-08-26T23:21:57.6012657Z msg = Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634. 2025-08-26T23:21:57.6012828Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6013300Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T23:21:57.6013319Z 2025-08-26T23:21:57.6013505Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-08-26T23:21:57.6013641Z The target module does not have to be a FSDP module. If the target 2025-08-26T23:21:57.6013956Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-08-26T23:21:57.6013963Z 2025-08-26T23:21:57.6014101Z .. note:: This API should be called for only the top-level (root) 2025-08-26T23:21:57.6014175Z module. 2025-08-26T23:21:57.6014181Z 2025-08-26T23:21:57.6014313Z .. note:: This API enables users to transparently use the conventional 2025-08-26T23:21:57.6014504Z ``state_dict`` API to take model checkpoints in cases where the 2025-08-26T23:21:57.6014636Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-08-26T23:21:57.6014772Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-08-26T23:21:57.6018386Z instances, while dispatching into `sharded_state_dict` implementation 2025-08-26T23:21:57.6018471Z for FSDP: 2025-08-26T23:21:57.6018477Z 2025-08-26T23:21:57.6018549Z Example:: 2025-08-26T23:21:57.6018553Z 2025-08-26T23:21:57.6018659Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.6018733Z >>> model = DDP(FSDP(...)) 2025-08-26T23:21:57.6018822Z >>> FSDP.set_state_dict_type( 2025-08-26T23:21:57.6018884Z >>> model, 2025-08-26T23:21:57.6018989Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T23:21:57.6019131Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-08-26T23:21:57.6019278Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-08-26T23:21:57.6019401Z >>> ) 2025-08-26T23:21:57.6019492Z >>> param_state_dict = model.state_dict() 2025-08-26T23:21:57.6019601Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T23:21:57.6019606Z 2025-08-26T23:21:57.6019663Z Args: 2025-08-26T23:21:57.6019745Z module (torch.nn.Module): Root module. 2025-08-26T23:21:57.6019891Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T23:21:57.6020034Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-08-26T23:21:57.6020099Z target ``state_dict_type``. 2025-08-26T23:21:57.6020225Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-08-26T23:21:57.6020297Z for the optimizer state dict. 2025-08-26T23:21:57.6020304Z 2025-08-26T23:21:57.6020508Z Returns: 2025-08-26T23:21:57.6022289Z A StateDictSettings that include the previous state_dict type and 2025-08-26T23:21:57.6022358Z configuration for the module. 2025-08-26T23:21:57.6022407Z 2025-08-26T23:21:57.6022536Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6022541Z 2025-08-26T23:21:57.6022945Z msg = Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792. 2025-08-26T23:21:57.6023077Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6023201Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T23:21:57.6023207Z 2025-08-26T23:21:57.6023370Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-08-26T23:21:57.6023440Z :meth:`set_state_dict_type` for the detail. 2025-08-26T23:21:57.6023529Z 2025-08-26T23:21:57.6023581Z Example:: 2025-08-26T23:21:57.6023585Z 2025-08-26T23:21:57.6023661Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.6023726Z >>> model = DDP(FSDP(...)) 2025-08-26T23:21:57.6023789Z >>> with FSDP.state_dict_type( 2025-08-26T23:21:57.6023842Z >>> model, 2025-08-26T23:21:57.6023916Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T23:21:57.6023960Z >>> ): 2025-08-26T23:21:57.6024057Z >>> checkpoint = model.state_dict() 2025-08-26T23:21:57.6024060Z 2025-08-26T23:21:57.6024108Z Args: 2025-08-26T23:21:57.6024180Z module (torch.nn.Module): Root module. 2025-08-26T23:21:57.6024301Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T23:21:57.6024448Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-08-26T23:21:57.6024536Z configuration for the target ``state_dict_type``. 2025-08-26T23:21:57.6026093Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-08-26T23:21:57.6026200Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-08-26T23:21:57.6026249Z 2025-08-26T23:21:57.6026378Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6026383Z 2025-08-26T23:21:57.6038290Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805. 2025-08-26T23:21:57.6038431Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6038434Z 2025-08-26T23:21:57.6038540Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-08-26T23:21:57.6038546Z 2025-08-26T23:21:57.6038631Z The given state-dict can be transformed to one of three types: 2025-08-26T23:21:57.6038812Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-08-26T23:21:57.6038815Z 2025-08-26T23:21:57.6038911Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-08-26T23:21:57.6039003Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-08-26T23:21:57.6039044Z avoid OOM. 2025-08-26T23:21:57.6039048Z 2025-08-26T23:21:57.6039143Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-08-26T23:21:57.6039224Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-08-26T23:21:57.6039264Z memory. 2025-08-26T23:21:57.6039266Z 2025-08-26T23:21:57.6039358Z For local state_dict, no transformation will be performed. But a state 2025-08-26T23:21:57.6039459Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-08-26T23:21:57.6039515Z nature (this is not supported yet). 2025-08-26T23:21:57.6039519Z 2025-08-26T23:21:57.6041911Z Example:: 2025-08-26T23:21:57.6041914Z 2025-08-26T23:21:57.6041982Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.6042088Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:21:57.6042165Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T23:21:57.6042241Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T23:21:57.6042331Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T23:21:57.6042387Z >>> # Save a checkpoint 2025-08-26T23:21:57.6042433Z >>> model, optim = ... 2025-08-26T23:21:57.6042483Z >>> FSDP.set_state_dict_type( 2025-08-26T23:21:57.6042522Z >>> model, 2025-08-26T23:21:57.6042576Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:21:57.6042633Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6042697Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6042784Z >>> ) 2025-08-26T23:21:57.6042835Z >>> state_dict = model.state_dict() 2025-08-26T23:21:57.6042906Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T23:21:57.6042967Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T23:21:57.6043012Z >>> # Load a checkpoint 2025-08-26T23:21:57.6043060Z >>> model, optim = ... 2025-08-26T23:21:57.6043130Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T23:21:57.6043183Z >>> FSDP.set_state_dict_type( 2025-08-26T23:21:57.6043246Z >>> model, 2025-08-26T23:21:57.6043304Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:21:57.6043367Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6043430Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6043475Z >>> ) 2025-08-26T23:21:57.6043530Z >>> model.load_state_dict(state_dict) 2025-08-26T23:21:57.6043626Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T23:21:57.6044978Z >>> model, optim, optim_state_dict 2025-08-26T23:21:57.6045011Z >>> ) 2025-08-26T23:21:57.6045067Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T23:21:57.6045070Z 2025-08-26T23:21:57.6045106Z Args: 2025-08-26T23:21:57.6045193Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T23:21:57.6045274Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T23:21:57.6045337Z were passed into the optimizer ``optim``. 2025-08-26T23:21:57.6045415Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T23:21:57.6045457Z parameters. 2025-08-26T23:21:57.6045545Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-08-26T23:21:57.6045628Z transform. If the value is None, optim.state_dict() will be used. ( 2025-08-26T23:21:57.6045672Z Default: ``None``) 2025-08-26T23:21:57.6045772Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T23:21:57.6045854Z are sharded or ``None`` if using the default process group. ( 2025-08-26T23:21:57.6045920Z Default: ``None``) 2025-08-26T23:21:57.6045923Z 2025-08-26T23:21:57.6045961Z Returns: 2025-08-26T23:21:57.6046039Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-08-26T23:21:57.6046113Z ``model``. The sharding of the optimizer state is based on 2025-08-26T23:21:57.6046157Z ``state_dict_type``. 2025-08-26T23:21:57.6046160Z 2025-08-26T23:21:57.6046262Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6046264Z 2025-08-26T23:21:57.6046590Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903. 2025-08-26T23:21:57.6047794Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6047799Z 2025-08-26T23:21:57.6047945Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-08-26T23:21:57.6047951Z 2025-08-26T23:21:57.6048024Z Given a ``optim_state_dict`` that is transformed through 2025-08-26T23:21:57.6048112Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-08-26T23:21:57.6048195Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-08-26T23:21:57.6048279Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-08-26T23:21:57.6048283Z 2025-08-26T23:21:57.6048339Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.6048436Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:21:57.6048501Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T23:21:57.6048576Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T23:21:57.6048658Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T23:21:57.6048730Z >>> # Save a checkpoint 2025-08-26T23:21:57.6048775Z >>> model, optim = ... 2025-08-26T23:21:57.6048824Z >>> FSDP.set_state_dict_type( 2025-08-26T23:21:57.6048857Z >>> model, 2025-08-26T23:21:57.6048910Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:21:57.6048965Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6049032Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6049063Z >>> ) 2025-08-26T23:21:57.6049132Z >>> state_dict = model.state_dict() 2025-08-26T23:21:57.6049183Z >>> original_osd = optim.state_dict() 2025-08-26T23:21:57.6050269Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-08-26T23:21:57.6050417Z >>> model, 2025-08-26T23:21:57.6050452Z >>> optim, 2025-08-26T23:21:57.6050494Z >>> optim_state_dict=original_osd 2025-08-26T23:21:57.6050556Z >>> ) 2025-08-26T23:21:57.6050611Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T23:21:57.6050653Z >>> # Load a checkpoint 2025-08-26T23:21:57.6050690Z >>> model, optim = ... 2025-08-26T23:21:57.6050751Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T23:21:57.6050792Z >>> FSDP.set_state_dict_type( 2025-08-26T23:21:57.6050825Z >>> model, 2025-08-26T23:21:57.6050870Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:21:57.6050919Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6050972Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:21:57.6051005Z >>> ) 2025-08-26T23:21:57.6051049Z >>> model.load_state_dict(state_dict) 2025-08-26T23:21:57.6051105Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T23:21:57.6051150Z >>> model, optim, optim_state_dict 2025-08-26T23:21:57.6051181Z >>> ) 2025-08-26T23:21:57.6051230Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T23:21:57.6051234Z 2025-08-26T23:21:57.6051264Z Args: 2025-08-26T23:21:57.6051338Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T23:21:57.6052373Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T23:21:57.6052429Z were passed into the optimizer ``optim``. 2025-08-26T23:21:57.6052498Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T23:21:57.6052534Z parameters. 2025-08-26T23:21:57.6052610Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-08-26T23:21:57.6052686Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-08-26T23:21:57.6052756Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-08-26T23:21:57.6052821Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-08-26T23:21:57.6052894Z load_directly (bool): If this is set to True, this API will also 2025-08-26T23:21:57.6052968Z call optim.load_state_dict(result) before returning the result. 2025-08-26T23:21:57.6053050Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-08-26T23:21:57.6053093Z (Default: ``False``) 2025-08-26T23:21:57.6053178Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T23:21:57.6053246Z are sharded or ``None`` if using the default process group. ( 2025-08-26T23:21:57.6053284Z Default: ``None``) 2025-08-26T23:21:57.6053287Z 2025-08-26T23:21:57.6053375Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6053378Z 2025-08-26T23:21:57.6337884Z msg = Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-08-26T23:21:57.6338040Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6338045Z 2025-08-26T23:21:57.6338185Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-08-26T23:21:57.6338287Z 2025-08-26T23:21:57.6340663Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-08-26T23:21:57.6340767Z by using different periods concurrently after the warm-up stage. 2025-08-26T23:21:57.6340915Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-08-26T23:21:57.6341043Z that supports `post-local SGD `_, which essentially only supports 2025-08-26T23:21:57.6341204Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-08-26T23:21:57.6341330Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-08-26T23:21:57.6341435Z Similarly, the process groups within this class do not have such an intra-machine process 2025-08-26T23:21:57.6341562Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-08-26T23:21:57.6341568Z 2025-08-26T23:21:57.6341601Z Args: 2025-08-26T23:21:57.6341698Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-08-26T23:21:57.6341772Z process group size, used for initializing process groups of 2025-08-26T23:21:57.6341855Z different sizes in a hierarchy to average parameters concurrently. 2025-08-26T23:21:57.6341931Z Particularly, at each iteration, there will be at most a single 2025-08-26T23:21:57.6342020Z process group that runs averaging -- the period of such group should 2025-08-26T23:21:57.6342101Z have the largest period which the current step can be divided by. 2025-08-26T23:21:57.6342173Z For example, if the dict has three keys: 2, 4, and 8, 2025-08-26T23:21:57.6342251Z then this means totally three process groups will be created to 2025-08-26T23:21:57.6342336Z average parameters every 2, 4, and 8 iterations, respectively. 2025-08-26T23:21:57.6342436Z At the 4th iteration, only the second process group will run 2025-08-26T23:21:57.6342502Z averaging, because the first process group should be a 2025-08-26T23:21:57.6342582Z subset of the second process group, and no need to execute the first 2025-08-26T23:21:57.6343838Z process group redundantly. 2025-08-26T23:21:57.6343921Z On the other hand, the third process group can only be triggered 2025-08-26T23:21:57.6344003Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-08-26T23:21:57.6344111Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-08-26T23:21:57.6344267Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-08-26T23:21:57.6344334Z If ``None``, the default process group, which is created 2025-08-26T23:21:57.6344413Z by :func:`torch.distributed.init_process_group`, will be used. 2025-08-26T23:21:57.6344463Z (default: ``None``) 2025-08-26T23:21:57.6344466Z 2025-08-26T23:21:57.6344506Z Example:: 2025-08-26T23:21:57.6344555Z >>> # xdoctest: +SKIP('undefined rank') 2025-08-26T23:21:57.6344601Z >>> from collections import OrderedDict 2025-08-26T23:21:57.6344637Z >>> import torch 2025-08-26T23:21:57.6344683Z >>> import torch.distributed as dist 2025-08-26T23:21:57.6344779Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T23:21:57.6344823Z >>> PostLocalSGDState, 2025-08-26T23:21:57.6344865Z >>> post_localSGD_hook, 2025-08-26T23:21:57.6344898Z >>> ) 2025-08-26T23:21:57.6345057Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-08-26T23:21:57.6345099Z >>> import torch.nn as nn 2025-08-26T23:21:57.6345130Z >>> 2025-08-26T23:21:57.6345197Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T23:21:57.6345242Z >>> torch.cuda.set_device(rank) 2025-08-26T23:21:57.6346299Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T23:21:57.6346366Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:21:57.6346461Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:21:57.6346493Z >>> ) 2025-08-26T23:21:57.6346550Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:21:57.6346648Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-08-26T23:21:57.6346695Z >>> subgroup, _ = dist.new_subgroups() 2025-08-26T23:21:57.6346823Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-08-26T23:21:57.6346887Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:21:57.6346919Z >>> 2025-08-26T23:21:57.6347018Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-08-26T23:21:57.6347067Z >>> # the 16 processes every 16 iterations. 2025-08-26T23:21:57.6347139Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-08-26T23:21:57.6347227Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-08-26T23:21:57.6347335Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:21:57.6347430Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T23:21:57.6347488Z >>> # After 100 steps, run model averaging at two levels. 2025-08-26T23:21:57.6347531Z >>> for step in range(0, 200): 2025-08-26T23:21:57.6347574Z >>> optimizer.zero_grad() 2025-08-26T23:21:57.6347633Z >>> loss = loss_fn(output, labels) 2025-08-26T23:21:57.6347674Z >>> loss.backward() 2025-08-26T23:21:57.6348736Z >>> optimizer.step() 2025-08-26T23:21:57.6348804Z >>> # Average parameters after ``optimizer.step()``. 2025-08-26T23:21:57.6348912Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-08-26T23:21:57.6348972Z >>> averager.average_parameters(model.parameters()) 2025-08-26T23:21:57.6348977Z 2025-08-26T23:21:57.6349012Z .. warning :: 2025-08-26T23:21:57.6349104Z The last group size in the dict must be the size of the provided ``process_group``, 2025-08-26T23:21:57.6349188Z which indicates model averaging at the highest level of the hierarchy. 2025-08-26T23:21:57.6349298Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-08-26T23:21:57.6349302Z 2025-08-26T23:21:57.6349337Z .. warning :: 2025-08-26T23:21:57.6349420Z `HierarchicalModelAverager` is experimental and subject to change. 2025-08-26T23:21:57.6349424Z 2025-08-26T23:21:57.6349514Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6349517Z 2025-08-26T23:21:57.6349785Z msg = Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-08-26T23:21:57.6349879Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6349882Z 2025-08-26T23:21:57.6349952Z Averages parameters periodically after the warm-up stage. 2025-08-26T23:21:57.6349955Z 2025-08-26T23:21:57.6350048Z This can be used for running `post-local SGD `_, 2025-08-26T23:21:57.6350120Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-08-26T23:21:57.6350209Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-08-26T23:21:57.6350238Z 2025-08-26T23:21:57.6350269Z Args: 2025-08-26T23:21:57.6350458Z period (int): The number of steps per model averaging. 2025-08-26T23:21:57.6350609Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-08-26T23:21:57.6351901Z Otherwise, only DDP needs to be used. 2025-08-26T23:21:57.6351994Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-08-26T23:21:57.6352081Z model averaging is skipped. 2025-08-26T23:21:57.6352155Z process_group: The process group to be used for all-reduce. 2025-08-26T23:21:57.6352211Z If ``None``, the default process group, which 2025-08-26T23:21:57.6352282Z is created by :func:`torch.distributed.init_process_group`, 2025-08-26T23:21:57.6352330Z will be used. (default: ``None``) 2025-08-26T23:21:57.6352352Z 2025-08-26T23:21:57.6352396Z Example:: 2025-08-26T23:21:57.6352401Z 2025-08-26T23:21:57.6352449Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:21:57.6352485Z >>> import torch 2025-08-26T23:21:57.6352531Z >>> import torch.distributed as dist 2025-08-26T23:21:57.6352640Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-08-26T23:21:57.6352736Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T23:21:57.6352777Z >>> import torch.nn as nn 2025-08-26T23:21:57.6352809Z >>> 2025-08-26T23:21:57.6352878Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T23:21:57.6352922Z >>> torch.cuda.set_device(rank) 2025-08-26T23:21:57.6352972Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-08-26T23:21:57.6353032Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:21:57.6353087Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:21:57.6353121Z >>> ) 2025-08-26T23:21:57.6353177Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:21:57.6354290Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T23:21:57.6354354Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:21:57.6354499Z >>> 2025-08-26T23:21:57.6354595Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T23:21:57.6354655Z >>> # After 100 steps, run model averaging every 4 steps. 2025-08-26T23:21:57.6354766Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:21:57.6354858Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T23:21:57.6354900Z >>> for step in range(0, 200): 2025-08-26T23:21:57.6354943Z >>> optimizer.zero_grad() 2025-08-26T23:21:57.6354989Z >>> loss = loss_fn(output, labels) 2025-08-26T23:21:57.6355029Z >>> loss.backward() 2025-08-26T23:21:57.6355069Z >>> optimizer.step() 2025-08-26T23:21:57.6355142Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-08-26T23:21:57.6355215Z >>> # inter-node communication only occurs every 4 iterations after 2025-08-26T23:21:57.6355264Z >>> # the initial ``warmup_steps`` period. 2025-08-26T23:21:57.6355324Z >>> averager.average_parameters(model.parameters()) 2025-08-26T23:21:57.6355326Z 2025-08-26T23:21:57.6355417Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6355419Z 2025-08-26T23:21:57.6374407Z msg = Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-08-26T23:21:57.6374515Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6374519Z 2025-08-26T23:21:57.6374565Z Run post-localSGD algorithm. 2025-08-26T23:21:57.6374616Z 2025-08-26T23:21:57.6376008Z This DDP communication hook is used for running post-localSGD algorithm, 2025-08-26T23:21:57.6376083Z by combining with a model averaging component (e.g., 2025-08-26T23:21:57.6376206Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-08-26T23:21:57.6376250Z that runs after the optimizer step. 2025-08-26T23:21:57.6376252Z 2025-08-26T23:21:57.6376284Z Args: 2025-08-26T23:21:57.6376366Z state (PostLocalSGDState): State information to run post-localSGD. 2025-08-26T23:21:57.6376516Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-08-26T23:21:57.6376663Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T23:21:57.6376753Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T23:21:57.6376828Z only exactly one tensor is stored in this bucket. 2025-08-26T23:21:57.6376833Z 2025-08-26T23:21:57.6376867Z Returns: 2025-08-26T23:21:57.6376952Z Future handler of the communication, which updates the gradients in place. 2025-08-26T23:21:57.6376955Z 2025-08-26T23:21:57.6376990Z Example:: 2025-08-26T23:21:57.6377029Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.6377118Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-08-26T23:21:57.6377166Z start_localSGD_iter=10) 2025-08-26T23:21:57.6377232Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:21:57.6377353Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-08-26T23:21:57.6377484Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-08-26T23:21:57.6377486Z 2025-08-26T23:21:57.6377577Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6377582Z 2025-08-26T23:21:57.6400074Z msg = Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-08-26T23:21:57.6400189Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6400194Z 2025-08-26T23:21:57.6400236Z Implement PowerSGD algorithm. 2025-08-26T23:21:57.6400238Z 2025-08-26T23:21:57.6400433Z This DDP communication hook implements PowerSGD gradient compression 2025-08-26T23:21:57.6400533Z algorithm described in the `paper `_. 2025-08-26T23:21:57.6400621Z Once gradient tensors are aggregated across all workers, this hook applies 2025-08-26T23:21:57.6400660Z compression as follows: 2025-08-26T23:21:57.6400662Z 2025-08-26T23:21:57.6400815Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-08-26T23:21:57.6400820Z 2025-08-26T23:21:57.6400966Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-08-26T23:21:57.6400968Z 2025-08-26T23:21:57.6401108Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-08-26T23:21:57.6401111Z 2025-08-26T23:21:57.6401153Z 2. Handles uncompressed tensors: 2025-08-26T23:21:57.6401155Z 2025-08-26T23:21:57.6401327Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-08-26T23:21:57.6401330Z 2025-08-26T23:21:57.6401447Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-08-26T23:21:57.6401449Z 2025-08-26T23:21:57.6401534Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-08-26T23:21:57.6401538Z 2025-08-26T23:21:57.6401623Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-08-26T23:21:57.6401802Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-08-26T23:21:57.6401805Z 2025-08-26T23:21:57.6401862Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-08-26T23:21:57.6401864Z 2025-08-26T23:21:57.6401907Z 3.3. Allreduces Ps as a batch; 2025-08-26T23:21:57.6401909Z 2025-08-26T23:21:57.6401953Z 3.4. Orthogonalizes each P in Ps; 2025-08-26T23:21:57.6401955Z 2025-08-26T23:21:57.6402055Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-08-26T23:21:57.6402057Z 2025-08-26T23:21:57.6402101Z 3.6. Allreduces Qs as a batch; 2025-08-26T23:21:57.6402103Z 2025-08-26T23:21:57.6403273Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-08-26T23:21:57.6403276Z 2025-08-26T23:21:57.6403450Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-08-26T23:21:57.6403552Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-08-26T23:21:57.6403700Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-08-26T23:21:57.6403703Z 2025-08-26T23:21:57.6403734Z Args: 2025-08-26T23:21:57.6403881Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-08-26T23:21:57.6404006Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-08-26T23:21:57.6404050Z and ``min_compression_rate``. 2025-08-26T23:21:57.6404191Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T23:21:57.6404280Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T23:21:57.6404339Z only exactly one tensor is stored in this bucket. 2025-08-26T23:21:57.6404342Z 2025-08-26T23:21:57.6404393Z Returns: 2025-08-26T23:21:57.6404479Z Future handler of the communication, which updates the gradients in place. 2025-08-26T23:21:57.6404481Z 2025-08-26T23:21:57.6404517Z Example:: 2025-08-26T23:21:57.6404555Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.6404653Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-08-26T23:21:57.6404712Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-08-26T23:21:57.6404771Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-08-26T23:21:57.6404774Z 2025-08-26T23:21:57.6404863Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6404865Z 2025-08-26T23:21:57.6466048Z msg = Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-08-26T23:21:57.6466162Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6466166Z 2025-08-26T23:21:57.6467789Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-08-26T23:21:57.6467855Z Needs to be called on all ranks in an SPMD fashion. 2025-08-26T23:21:57.6467857Z 2025-08-26T23:21:57.6467889Z Args: 2025-08-26T23:21:57.6467988Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-08-26T23:21:57.6468053Z of shards that represent the local shards on this rank. 2025-08-26T23:21:57.6468136Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-08-26T23:21:57.6468183Z shape of the overall sharded tensor. 2025-08-26T23:21:57.6468186Z 2025-08-26T23:21:57.6468220Z Keyword args: 2025-08-26T23:21:57.6468314Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:21:57.6468365Z the default process group will be used. 2025-08-26T23:21:57.6468483Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T23:21:57.6468559Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T23:21:57.6468631Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T23:21:57.6468669Z Default: ``False``. 2025-08-26T23:21:57.6468672Z 2025-08-26T23:21:57.6468704Z Returns: 2025-08-26T23:21:57.6468761Z A :class:`ShardedTensor` object handle on this rank 2025-08-26T23:21:57.6468781Z 2025-08-26T23:21:57.6468783Z 2025-08-26T23:21:57.6468820Z Examples: 2025-08-26T23:21:57.6468916Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-08-26T23:21:57.6468994Z each shard have a (5, 5) local tensor, we can do it like below: 2025-08-26T23:21:57.6468996Z 2025-08-26T23:21:57.6469033Z on rank 0: 2025-08-26T23:21:57.6470182Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T23:21:57.6470237Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T23:21:57.6470286Z >>> shard_offsets=[0, 0], 2025-08-26T23:21:57.6470433Z >>> shard_lengths=[5, 5], 2025-08-26T23:21:57.6470477Z >>> placement="rank:0/cuda:0" 2025-08-26T23:21:57.6470509Z >>> ) 2025-08-26T23:21:57.6470581Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T23:21:57.6470652Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T23:21:57.6470655Z 2025-08-26T23:21:57.6470688Z on rank 1: 2025-08-26T23:21:57.6470735Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T23:21:57.6470787Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T23:21:57.6470825Z >>> shard_offsets=[5, 0], 2025-08-26T23:21:57.6470862Z >>> shard_lengths=[5, 5], 2025-08-26T23:21:57.6470903Z >>> placement="rank:1/cuda:1" 2025-08-26T23:21:57.6470937Z >>> ) 2025-08-26T23:21:57.6471005Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T23:21:57.6471077Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T23:21:57.6471106Z 2025-08-26T23:21:57.6471196Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6471199Z 2025-08-26T23:21:57.6540529Z msg = Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-08-26T23:21:57.6540645Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6540647Z 2025-08-26T23:21:57.6542113Z Representation of a sharding plan, describes how to shard a module 2025-08-26T23:21:57.6542221Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-08-26T23:21:57.6542323Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-08-26T23:21:57.6542412Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-08-26T23:21:57.6542416Z 2025-08-26T23:21:57.6542448Z Args: 2025-08-26T23:21:57.6542544Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-08-26T23:21:57.6542610Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-08-26T23:21:57.6542706Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-08-26T23:21:57.6542797Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-08-26T23:21:57.6542851Z a parameter to a `ShardingSpec`. 2025-08-26T23:21:57.6542944Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-08-26T23:21:57.6542984Z to a `Sharder` object. 2025-08-26T23:21:57.6543099Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-08-26T23:21:57.6543190Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-08-26T23:21:57.6543323Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-08-26T23:21:57.6543360Z Default: `None` 2025-08-26T23:21:57.6543452Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-08-26T23:21:57.6543540Z a module's sharded output to be returned as a Tensor from its local shards to 2025-08-26T23:21:57.6543639Z ensure further processing in a data parallel fashion. ("" in list means the 2025-08-26T23:21:57.6543694Z root module). 2025-08-26T23:21:57.6543730Z Default: None 2025-08-26T23:21:57.6543762Z Example: 2025-08-26T23:21:57.6544870Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-08-26T23:21:57.6544974Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-08-26T23:21:57.6544999Z 2025-08-26T23:21:57.6545065Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-08-26T23:21:57.6545110Z >>> class MyModule(nn.Module): 2025-08-26T23:21:57.6545155Z >>> def __init__(self) -> None: 2025-08-26T23:21:57.6545193Z >>> super().__init__() 2025-08-26T23:21:57.6545234Z >>> self.fc1 = nn.Linear() 2025-08-26T23:21:57.6545273Z >>> self.gelu = nn.GELU() 2025-08-26T23:21:57.6545312Z >>> self.fc2 = nn.Linear() 2025-08-26T23:21:57.6545353Z >>> self.relu = nn.Linear() 2025-08-26T23:21:57.6545384Z >>> 2025-08-26T23:21:57.6545426Z >>> def forward(self, input): 2025-08-26T23:21:57.6545491Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-08-26T23:21:57.6545495Z 2025-08-26T23:21:57.6545497Z 2025-08-26T23:21:57.6545548Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-08-26T23:21:57.6545590Z >>> sharding_plan = ShardingPlan( 2025-08-26T23:21:57.6545624Z >>> plan={ 2025-08-26T23:21:57.6545664Z >>> "fc1.weight": spec1, 2025-08-26T23:21:57.6545705Z >>> "fc2.weight": spec2 2025-08-26T23:21:57.6545737Z >>> }, 2025-08-26T23:21:57.6545793Z >>> output_plan={ 2025-08-26T23:21:57.6545832Z >>> "fc2": output_spec 2025-08-26T23:21:57.6546778Z >>> }, 2025-08-26T23:21:57.6546824Z >>> return_local_tensor=["fc2"] 2025-08-26T23:21:57.6546856Z >>> ) 2025-08-26T23:21:57.6546858Z 2025-08-26T23:21:57.6546948Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6546950Z 2025-08-26T23:21:57.6585032Z msg = Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-08-26T23:21:57.6585144Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6585146Z 2025-08-26T23:21:57.6585244Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-08-26T23:21:57.6585290Z size and sharding spec on each rank. 2025-08-26T23:21:57.6585294Z 2025-08-26T23:21:57.6585326Z Args: 2025-08-26T23:21:57.6585408Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-08-26T23:21:57.6585501Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-08-26T23:21:57.6585564Z The specification describing how to shard the Tensor. 2025-08-26T23:21:57.6585631Z global_size (Sequence[int]): Size of the sharded tensor. 2025-08-26T23:21:57.6585741Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-08-26T23:21:57.6585776Z Default: None 2025-08-26T23:21:57.6585842Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T23:21:57.6585918Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T23:21:57.6585992Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T23:21:57.6586033Z Default: ``False``. 2025-08-26T23:21:57.6586092Z 2025-08-26T23:21:57.6586123Z Returns: 2025-08-26T23:21:57.6587688Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-08-26T23:21:57.6587747Z tensor stored in the current rank. 2025-08-26T23:21:57.6587750Z 2025-08-26T23:21:57.6587789Z Examples: 2025-08-26T23:21:57.6587833Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.6587892Z >>> # All tensors below are of torch.int64 type. 2025-08-26T23:21:57.6587942Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.6588069Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T23:21:57.6588152Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-08-26T23:21:57.6588188Z >>> local_tensor 2025-08-26T23:21:57.6588227Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-08-26T23:21:57.6588266Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-08-26T23:21:57.6588303Z >>> sharding_dim = 0 2025-08-26T23:21:57.6588375Z >>> sharding_spec = ChunkShardingSpec( 2025-08-26T23:21:57.6588416Z dim=sharding_dim, 2025-08-26T23:21:57.6588459Z placements=[ 2025-08-26T23:21:57.6588501Z "rank:0/cuda:0", 2025-08-26T23:21:57.6588539Z "rank:1/cuda:1", 2025-08-26T23:21:57.6588572Z ], 2025-08-26T23:21:57.6588604Z ) 2025-08-26T23:21:57.6588655Z >>> st = ShardedTensor._init_from_local_tensor( 2025-08-26T23:21:57.6590013Z ... local_tensor, sharding_spec, [2, 4] 2025-08-26T23:21:57.6590048Z ... ) 2025-08-26T23:21:57.6590084Z >>> st 2025-08-26T23:21:57.6590121Z ShardedTensor( 2025-08-26T23:21:57.6590164Z ShardedTensorMetadata( 2025-08-26T23:21:57.6590203Z shards_metadata=[ 2025-08-26T23:21:57.6590304Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-08-26T23:21:57.6590498Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-08-26T23:21:57.6590532Z ], 2025-08-26T23:21:57.6590575Z size=torch.Size([2, 4]) 2025-08-26T23:21:57.6590606Z ) 2025-08-26T23:21:57.6590671Z >>> st.local_tensor() 2025-08-26T23:21:57.6590710Z tensor([1, 2, 3, 4]) # Rank 0 2025-08-26T23:21:57.6590746Z tensor([3, 4, 5, 6]) # Rank 1 2025-08-26T23:21:57.6590749Z 2025-08-26T23:21:57.6590850Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-08-26T23:21:57.6590938Z rank validations, and we only validate the local shard on the current rank. 2025-08-26T23:21:57.6591015Z We fully rely on the user to ensure local tensor is sharded based on the 2025-08-26T23:21:57.6591052Z sharding spec. 2025-08-26T23:21:57.6591054Z 2025-08-26T23:21:57.6591144Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6591146Z 2025-08-26T23:21:57.6591385Z msg = Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-08-26T23:21:57.6591479Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.6591482Z 2025-08-26T23:21:57.6591574Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-08-26T23:21:57.6592617Z single local shard. 2025-08-26T23:21:57.6592620Z 2025-08-26T23:21:57.6592704Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-08-26T23:21:57.6592793Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-08-26T23:21:57.6592835Z we swap local shards directly. 2025-08-26T23:21:57.6592930Z For more generic cases, we merge different shards across different ranks and split 2025-08-26T23:21:57.6593018Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-08-26T23:21:57.6593020Z 2025-08-26T23:21:57.6593051Z Args: 2025-08-26T23:21:57.6593155Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-08-26T23:21:57.6593256Z specification describing how the tensor is sharded. 2025-08-26T23:21:57.6593261Z 2025-08-26T23:21:57.6593292Z Returns: 2025-08-26T23:21:57.6593368Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-08-26T23:21:57.6593370Z 2025-08-26T23:21:57.6593402Z Examples: 2025-08-26T23:21:57.6593441Z >>> # xdoctest: +SKIP 2025-08-26T23:21:57.6593488Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:21:57.6593573Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T23:21:57.6593620Z >>> tensor = torch.stack([tensor, tensor]) 2025-08-26T23:21:57.6593653Z >>> tensor 2025-08-26T23:21:57.6593699Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-08-26T23:21:57.6593744Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-08-26T23:21:57.6593787Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-08-26T23:21:57.6593850Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-08-26T23:21:57.6594920Z >>> sharding_dim = 0 2025-08-26T23:21:57.6594966Z >>> spec = ChunkShardingSpec( 2025-08-26T23:21:57.6595008Z dim=sharding_dim, 2025-08-26T23:21:57.6595045Z placements=[ 2025-08-26T23:21:57.6595084Z "rank:0/cuda:0", 2025-08-26T23:21:57.6595121Z "rank:1/cuda:1", 2025-08-26T23:21:57.6595157Z "rank:2/cuda:2", 2025-08-26T23:21:57.6595191Z "rank:3/cuda:3", 2025-08-26T23:21:57.6595223Z ], 2025-08-26T23:21:57.6595253Z ) 2025-08-26T23:21:57.6595295Z >>> current_offsets = [0] * 2 2025-08-26T23:21:57.6595337Z >>> current_offsets[0] = rank * 2 2025-08-26T23:21:57.6595381Z >>> shard_metadata = ShardMetadata( 2025-08-26T23:21:57.6595439Z shard_offsets=copy.deepcopy(current_offsets), 2025-08-26T23:21:57.6595482Z shard_sizes=tensor.size(), 2025-08-26T23:21:57.6595530Z placement=spec.placements[rank], 2025-08-26T23:21:57.6595561Z ) 2025-08-26T23:21:57.6595600Z >>> local_shards = [ 2025-08-26T23:21:57.6595632Z Shard( 2025-08-26T23:21:57.6595690Z tensor=tensor, 2025-08-26T23:21:57.6595732Z metadata=shard_metadata, 2025-08-26T23:21:57.6595764Z ) 2025-08-26T23:21:57.6596718Z ] 2025-08-26T23:21:57.6596804Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-08-26T23:21:57.6596840Z >>> sharding_dim = 1 2025-08-26T23:21:57.6596887Z >>> resharding_spec = ChunkShardingSpec( 2025-08-26T23:21:57.6596928Z dim=sharding_dim, 2025-08-26T23:21:57.6596964Z placements=[ 2025-08-26T23:21:57.6597001Z "rank:0/cuda:0", 2025-08-26T23:21:57.6597037Z "rank:1/cuda:1", 2025-08-26T23:21:57.6597071Z "rank:2/cuda:2", 2025-08-26T23:21:57.6597107Z "rank:3/cuda:3", 2025-08-26T23:21:57.6597138Z ], 2025-08-26T23:21:57.6597169Z ) 2025-08-26T23:21:57.6597211Z >>> st.reshard(resharding_spec) 2025-08-26T23:21:57.6597257Z >>> tensor = st.local_shards()[0].tensor 2025-08-26T23:21:57.6597291Z >>> tensor 2025-08-26T23:21:57.6597347Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-08-26T23:21:57.6597400Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-08-26T23:21:57.6597450Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-08-26T23:21:57.6597504Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-08-26T23:21:57.6597506Z 2025-08-26T23:21:57.6597597Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.6597599Z 2025-08-26T23:21:57.7056806Z msg = Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-08-26T23:21:57.7056947Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.7056956Z 2025-08-26T23:21:57.7057143Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-08-26T23:21:57.7057235Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-08-26T23:21:57.7057327Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-08-26T23:21:57.7057417Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-08-26T23:21:57.7057538Z when users would like to overwrite default sharding strategies of existing operators. 2025-08-26T23:21:57.7057542Z 2025-08-26T23:21:57.7057578Z Args: 2025-08-26T23:21:57.7057634Z op (Union[OpOverload, List[OpOverload]]): 2025-08-26T23:21:57.7057705Z An op or a list of ops to register the customized sharding function. 2025-08-26T23:21:57.7057708Z 2025-08-26T23:21:57.7057742Z Returns: 2025-08-26T23:21:57.7057837Z A function decorator which can be used to wrap a function that defines the sharding 2025-08-26T23:21:57.7058004Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-08-26T23:21:57.7058156Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-08-26T23:21:57.7058283Z already implemented the operator. The customized sharding function takes the same inputs 2025-08-26T23:21:57.7058372Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-08-26T23:21:57.7058482Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-08-26T23:21:57.7058635Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-08-26T23:21:57.7058705Z corresponding input placements. 2025-08-26T23:21:57.7058708Z 2025-08-26T23:21:57.7058762Z Example: 2025-08-26T23:21:57.7058830Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.7061028Z >>> @register_sharding(aten._softmax.default) 2025-08-26T23:21:57.7061106Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-08-26T23:21:57.7061167Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-08-26T23:21:57.7061260Z >>> acceptable_shardings = [] 2025-08-26T23:21:57.7061293Z >>> 2025-08-26T23:21:57.7061365Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-08-26T23:21:57.7061422Z >>> acceptable_shardings.append(all_replicate) 2025-08-26T23:21:57.7061454Z >>> 2025-08-26T23:21:57.7061500Z >>> for sharding_dim in range(x.ndim): 2025-08-26T23:21:57.7061550Z >>> if sharding_dim != softmax_dim: 2025-08-26T23:21:57.7061590Z >>> all_sharded = ( 2025-08-26T23:21:57.7061634Z >>> [Shard(sharding_dim)], 2025-08-26T23:21:57.7061682Z >>> [Shard(sharding_dim), None, None], 2025-08-26T23:21:57.7061718Z >>> ) 2025-08-26T23:21:57.7061774Z >>> acceptable_shardings.append(all_sharded) 2025-08-26T23:21:57.7061808Z >>> 2025-08-26T23:21:57.7061851Z >>> return acceptable_shardings 2025-08-26T23:21:57.7061854Z 2025-08-26T23:21:57.7061936Z .. note:: This API is currently experimental and subject to change 2025-08-26T23:21:57.7061939Z 2025-08-26T23:21:57.7062030Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.7062032Z 2025-08-26T23:21:57.7066240Z msg = Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-08-26T23:21:57.7068198Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.7068204Z 2025-08-26T23:21:57.7068317Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-08-26T23:21:57.7068423Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-08-26T23:21:57.7068522Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-08-26T23:21:57.7068638Z :class:`DTensor` according to the ``out_placements``. 2025-08-26T23:21:57.7068640Z 2025-08-26T23:21:57.7068673Z Args: 2025-08-26T23:21:57.7068751Z func (Callable): the function to be applied on each local shard of 2025-08-26T23:21:57.7068791Z :class:`DTensor` s. 2025-08-26T23:21:57.7068874Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-08-26T23:21:57.7068966Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-08-26T23:21:57.7069070Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-08-26T23:21:57.7069159Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-08-26T23:21:57.7069246Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-08-26T23:21:57.7069296Z mapping to the flattened ``output``. 2025-08-26T23:21:57.7069388Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-08-26T23:21:57.7069491Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-08-26T23:21:57.7069530Z should be `None`. 2025-08-26T23:21:57.7069621Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-08-26T23:21:57.7069704Z in. In this case, even if `out_placements` is not `None`, the result function 2025-08-26T23:21:57.7069802Z should ignore the desired placements because the function is not running with 2025-08-26T23:21:57.7069841Z :class:`DTensor` s. 2025-08-26T23:21:57.7071288Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T23:21:57.7071400Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-08-26T23:21:57.7071488Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-08-26T23:21:57.7071572Z placements of each :class:`DTensor` argument is the same as the required 2025-08-26T23:21:57.7071644Z placements or not. If the placements are not the same and 2025-08-26T23:21:57.7071771Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-08-26T23:21:57.7071857Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-08-26T23:21:57.7071946Z the required sharding placements before passing its local tensor to ``func``. 2025-08-26T23:21:57.7072027Z The only exception is when required placements are not ``None`` and the 2025-08-26T23:21:57.7072112Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-08-26T23:21:57.7072190Z will be skipped and the argument will be directly passed to ``func``. 2025-08-26T23:21:57.7072268Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-08-26T23:21:57.7072307Z Default: None 2025-08-26T23:21:57.7072375Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T23:21:57.7072454Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-08-26T23:21:57.7072528Z to the flattened input DTensor. This argument is the hint that user 2025-08-26T23:21:57.7072596Z can give to :meth:`to_local` in case the gradient layout of the 2025-08-26T23:21:57.7072672Z local tensor input does not match its :class:`DTensor` input layout. 2025-08-26T23:21:57.7072743Z If not specified, we will assume the gradient layout of the local 2025-08-26T23:21:57.7072821Z tensor input remains the same as the original :class:`DTensor` input 2025-08-26T23:21:57.7072883Z and use that for gradient computation. Default: None. 2025-08-26T23:21:57.7072936Z device_mesh (:class:`DeviceMesh`, optional): 2025-08-26T23:21:57.7074017Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-08-26T23:21:57.7074113Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-08-26T23:21:57.7074182Z mesh. Default: None. 2025-08-26T23:21:57.7074185Z 2025-08-26T23:21:57.7074221Z Keyword Args: 2025-08-26T23:21:57.7074342Z redistribute_inputs (bool, optional): 2025-08-26T23:21:57.7074560Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-08-26T23:21:57.7074648Z their placements are different from the required input placements. If this 2025-08-26T23:21:57.7074729Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-08-26T23:21:57.7074806Z an exception will be raised. Default: False. 2025-08-26T23:21:57.7074809Z 2025-08-26T23:21:57.7074841Z Returns: 2025-08-26T23:21:57.7074935Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-08-26T23:21:57.7075019Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-08-26T23:21:57.7075040Z 2025-08-26T23:21:57.7075073Z Raises: 2025-08-26T23:21:57.7075159Z AssertionError: For any non-DTensor output, we require its corresponding 2025-08-26T23:21:57.7075252Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-08-26T23:21:57.7075301Z if this is not the case. 2025-08-26T23:21:57.7075303Z 2025-08-26T23:21:57.7075395Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-08-26T23:21:57.7075452Z a redistribution according to ``in_placements``. 2025-08-26T23:21:57.7075455Z 2025-08-26T23:21:57.7075490Z Example: 2025-08-26T23:21:57.7075535Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.7075589Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-08-26T23:21:57.7076625Z >>> partial_sum_tensor = torch.mm(W, X) 2025-08-26T23:21:57.7076717Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-08-26T23:21:57.7076761Z >>> return reduced_tensor 2025-08-26T23:21:57.7076793Z >>> 2025-08-26T23:21:57.7076843Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-08-26T23:21:57.7076909Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-08-26T23:21:57.7076948Z >>> Y = torch.mm(W, X) 2025-08-26T23:21:57.7077020Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-08-26T23:21:57.7077087Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-08-26T23:21:57.7077119Z >>> 2025-08-26T23:21:57.7077217Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion 2025-08-26T23:21:57.7077266Z >>> local_mm_allreduce_forward = local_map( 2025-08-26T23:21:57.7077306Z >>> mm_allreduce_forward, 2025-08-26T23:21:57.7077353Z >>> out_placements=[Replicate()], 2025-08-26T23:21:57.7077398Z >>> in_placements=[col_wise, row_wise], 2025-08-26T23:21:57.7077439Z >>> device_mesh=device_mesh, 2025-08-26T23:21:57.7077473Z >>> ) 2025-08-26T23:21:57.7077504Z >>> 2025-08-26T23:21:57.7077544Z >>> W_dt = distribute_tensor( 2025-08-26T23:21:57.7077587Z ... W, device_mesh, (col_wise) 2025-08-26T23:21:57.7077631Z ... ) # col-wisely sharded W tensor 2025-08-26T23:21:57.7077669Z >>> X_dt = distribute_tensor( 2025-08-26T23:21:57.7078644Z ... X, device_mesh, (row_wise) 2025-08-26T23:21:57.7078689Z ... ) # row-wisely sharded X tensor 2025-08-26T23:21:57.7078734Z >>> Y_dt = local_mm_allreduce_forward( 2025-08-26T23:21:57.7078773Z ... device_mesh, W_dt, X_dt 2025-08-26T23:21:57.7078832Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-08-26T23:21:57.7078834Z 2025-08-26T23:21:57.7078910Z .. note:: This API is currently experimental and subject to change 2025-08-26T23:21:57.7078912Z 2025-08-26T23:21:57.7079003Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.7079005Z 2025-08-26T23:21:57.8502127Z msg = Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-08-26T23:21:57.8502662Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.8502675Z 2025-08-26T23:21:57.8503055Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-08-26T23:21:57.8503372Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-08-26T23:21:57.8503380Z 2025-08-26T23:21:57.8503480Z Keyword Args: 2025-08-26T23:21:57.8503763Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:21:57.8504085Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T23:21:57.8504448Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T23:21:57.8504674Z as a placeholder. default: None. 2025-08-26T23:21:57.8504905Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:21:57.8505273Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:21:57.8510799Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T23:21:57.8510868Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T23:21:57.8511019Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T23:21:57.8511063Z default: None 2025-08-26T23:21:57.8511129Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T23:21:57.8511263Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:21:57.8511325Z have the desired DTensor layouts. default: None. 2025-08-26T23:21:57.8511380Z use_local_output (bool, optional): 2025-08-26T23:21:57.8511569Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T23:21:57.8511614Z Returns: 2025-08-26T23:21:57.8511736Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-08-26T23:21:57.8511740Z 2025-08-26T23:21:57.8511781Z Example:: 2025-08-26T23:21:57.8511826Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:21:57.8511946Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-08-26T23:21:57.8512025Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:21:57.8512058Z >>> ... 2025-08-26T23:21:57.8512172Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:21:57.8512229Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:21:57.8512262Z >>> 2025-08-26T23:21:57.8512388Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-08-26T23:21:57.8512448Z >>> # and then redistributed to Replicated DTensor. 2025-08-26T23:21:57.8512492Z >>> parallelize_module( 2025-08-26T23:21:57.8512553Z >>> block, # this can be a submodule or module 2025-08-26T23:21:57.8512592Z >>> tp_mesh, 2025-08-26T23:21:57.8512643Z >>> parallelize_plan={ 2025-08-26T23:21:57.8512695Z >>> "attn": PrepareModuleInput( 2025-08-26T23:21:57.8512759Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T23:21:57.8512827Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-08-26T23:21:57.8512870Z >>> ), 2025-08-26T23:21:57.8512908Z >>> } 2025-08-26T23:21:57.8512951Z >>> ) 2025-08-26T23:21:57.8512954Z 2025-08-26T23:21:57.8513052Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.8513056Z 2025-08-26T23:21:57.8513299Z msg = Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-08-26T23:21:57.8513422Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.8513424Z 2025-08-26T23:21:57.8513574Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-08-26T23:21:57.8513716Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-08-26T23:21:57.8513719Z 2025-08-26T23:21:57.8513758Z Keyword Args: 2025-08-26T23:21:57.8513823Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:21:57.8515429Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T23:21:57.8515574Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T23:21:57.8515665Z ``None`` need to be specified as a placeholder. 2025-08-26T23:21:57.8515741Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:21:57.8515882Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T23:21:57.8515930Z have the desired DTensor layouts. 2025-08-26T23:21:57.8515978Z use_local_output (bool, optional): 2025-08-26T23:21:57.8516109Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T23:21:57.8516143Z Returns: 2025-08-26T23:21:57.8516251Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-08-26T23:21:57.8516254Z 2025-08-26T23:21:57.8516291Z Example:: 2025-08-26T23:21:57.8516334Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:21:57.8516453Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-08-26T23:21:57.8516529Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:21:57.8516586Z >>> ... 2025-08-26T23:21:57.8516698Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:21:57.8516751Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:21:57.8516784Z >>> 2025-08-26T23:21:57.8516924Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-08-26T23:21:57.8516983Z >>> # and then redistributed to Sharded DTensor. 2025-08-26T23:21:57.8517024Z >>> parallelize_module( 2025-08-26T23:21:57.8518129Z >>> block, # this can be a submodule or module 2025-08-26T23:21:57.8518170Z >>> tp_mesh, 2025-08-26T23:21:57.8518228Z >>> parallelize_plan = PrepareModuleOutput( 2025-08-26T23:21:57.8518278Z >>> output_layouts=Replicate(), 2025-08-26T23:21:57.8518326Z >>> desired_output_layouts=Shard(0) 2025-08-26T23:21:57.8518359Z >>> ) 2025-08-26T23:21:57.8518394Z >>> ) 2025-08-26T23:21:57.8518396Z 2025-08-26T23:21:57.8518491Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.8518494Z 2025-08-26T23:21:57.8518749Z msg = Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-08-26T23:21:57.8518848Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.8518851Z 2025-08-26T23:21:57.8519007Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-08-26T23:21:57.8519158Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-08-26T23:21:57.8519297Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-08-26T23:21:57.8519406Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-08-26T23:21:57.8519408Z 2025-08-26T23:21:57.8519443Z Keyword Args: 2025-08-26T23:21:57.8519520Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:21:57.8519638Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T23:21:57.8519785Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T23:21:57.8519833Z as a placeholder. default: None. 2025-08-26T23:21:57.8519921Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:21:57.8520049Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:21:57.8521267Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T23:21:57.8521326Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T23:21:57.8521455Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T23:21:57.8521491Z default: None 2025-08-26T23:21:57.8521553Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T23:21:57.8521678Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:21:57.8521734Z have the desired DTensor layouts. default: None. 2025-08-26T23:21:57.8521779Z use_local_input (bool, optional): 2025-08-26T23:21:57.8521905Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T23:21:57.8521964Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:21:57.8522081Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T23:21:57.8522261Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T23:21:57.8522316Z ``None`` need to be specified as a placeholder. 2025-08-26T23:21:57.8522387Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:21:57.8522517Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T23:21:57.8522561Z have the desired DTensor layouts. 2025-08-26T23:21:57.8522606Z use_local_output (bool, optional): 2025-08-26T23:21:57.8522728Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T23:21:57.8522760Z Returns: 2025-08-26T23:21:57.8522885Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-08-26T23:21:57.8522890Z 2025-08-26T23:21:57.8522924Z Example:: 2025-08-26T23:21:57.8522966Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:21:57.8524020Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-08-26T23:21:57.8524095Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:21:57.8524127Z >>> ... 2025-08-26T23:21:57.8524235Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:21:57.8524286Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:21:57.8524317Z >>> 2025-08-26T23:21:57.8524432Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-08-26T23:21:57.8524551Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-08-26T23:21:57.8524628Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-08-26T23:21:57.8524694Z >>> parallelize_module( 2025-08-26T23:21:57.8524748Z >>> block, # this can be a submodule or module 2025-08-26T23:21:57.8524781Z >>> tp_mesh, 2025-08-26T23:21:57.8524822Z >>> parallelize_plan={ 2025-08-26T23:21:57.8524876Z >>> "attn": PrepareModuleInputOutput( 2025-08-26T23:21:57.8524929Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T23:21:57.8524993Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-08-26T23:21:57.8525054Z >>> output_layouts=Replicate(), 2025-08-26T23:21:57.8525105Z >>> desired_output_layouts=Shard(0), 2025-08-26T23:21:57.8525138Z >>> ), 2025-08-26T23:21:57.8525169Z >>> } 2025-08-26T23:21:57.8525200Z >>> ) 2025-08-26T23:21:57.8525202Z 2025-08-26T23:21:57.8526202Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.8526226Z 2025-08-26T23:21:57.8754580Z msg = Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-08-26T23:21:57.8754969Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.8755103Z 2025-08-26T23:21:57.8755184Z Initialize rendezvous event object and record its operations. 2025-08-26T23:21:57.8755294Z 2025-08-26T23:21:57.8755327Z Args: 2025-08-26T23:21:57.8755425Z run_id (str): The run id of the rendezvous. 2025-08-26T23:21:57.8755572Z message (str): The message describing the event. 2025-08-26T23:21:57.8755754Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-08-26T23:21:57.8755954Z name (str): Event name. (E.g. Current action being performed). 2025-08-26T23:21:57.8758172Z hostname (str): Hostname of the node. 2025-08-26T23:21:57.8758325Z pid (Optional[int]): The process id of the node. 2025-08-26T23:21:57.8758506Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-08-26T23:21:57.8758805Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-08-26T23:21:57.8758997Z rank (Optional[int]): The rank of the node, if known. 2025-08-26T23:21:57.8759123Z Returns: 2025-08-26T23:21:57.8759198Z None 2025-08-26T23:21:57.8759271Z Example: 2025-08-26T23:21:57.8759361Z >>> # See DynamicRendezvousHandler class 2025-08-26T23:21:57.8759477Z >>> def _record( 2025-08-26T23:21:57.8759564Z ... self, 2025-08-26T23:21:57.8759652Z ... message: str, 2025-08-26T23:21:57.8759768Z ... node_state: NodeState = NodeState.RUNNING, 2025-08-26T23:21:57.8759898Z ... rank: Optional[int] = None, 2025-08-26T23:21:57.8760013Z ... ) -> None: 2025-08-26T23:21:57.8760112Z ... construct_and_record_rdzv_event( 2025-08-26T23:21:57.8760255Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-08-26T23:21:57.8760498Z ... run_id=self._settings.run_id, 2025-08-26T23:21:57.8760618Z ... message=message, 2025-08-26T23:21:57.8760735Z ... node_state=node_state, 2025-08-26T23:21:57.8760861Z ... hostname=self._this_node.addr, 2025-08-26T23:21:57.8760992Z ... pid=self._this_node.pid, 2025-08-26T23:21:57.8761120Z ... local_id=self._this_node.local_id, 2025-08-26T23:21:57.8761248Z ... rank=rank, 2025-08-26T23:21:57.8761351Z ... ) 2025-08-26T23:21:57.8761408Z 2025-08-26T23:21:57.8762733Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.8762867Z 2025-08-26T23:21:57.9146578Z msg = Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-08-26T23:21:57.9147607Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.9147990Z 2025-08-26T23:21:57.9148348Z RemoteModule instance can only be created after RPC initialization. 2025-08-26T23:21:57.9148679Z 2025-08-26T23:21:57.9148890Z It creates a user-specified module on a specified remote node. 2025-08-26T23:21:57.9149411Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T23:21:57.9149862Z executed on the remote node. 2025-08-26T23:21:57.9150044Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T23:21:57.9150221Z gradients back to the corresponding remote module. 2025-08-26T23:21:57.9150568Z It can be shared across processors using `RPC framework `__, 2025-08-26T23:21:57.9152795Z without incurring any overheads of copying the actual module, 2025-08-26T23:21:57.9152988Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-08-26T23:21:57.9153140Z pointing to the remote module. 2025-08-26T23:21:57.9153251Z 2025-08-26T23:21:57.9153326Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-08-26T23:21:57.9153512Z the ``forward`` method of the module returned by the ``module_cls``. 2025-08-26T23:21:57.9153620Z 2025-08-26T23:21:57.9153730Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-08-26T23:21:57.9153875Z 2025-08-26T23:21:57.9153965Z Particularly, to create a hybrid model, typically the local modules should be 2025-08-26T23:21:57.9154213Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-08-26T23:21:57.9154480Z Hybrid Example: 2025-08-26T23:21:57.9154579Z >>> class HybridModel(nn.Module): 2025-08-26T23:21:57.9154706Z >>> def __init__(self) -> None: 2025-08-26T23:21:57.9154828Z >>> nn.Module.__init__(self) 2025-08-26T23:21:57.9154959Z >>> self.remote_embedding = RemoteModule(...) 2025-08-26T23:21:57.9155099Z >>> self.local_linear = nn.Linear(...) 2025-08-26T23:21:57.9155182Z 2025-08-26T23:21:57.9155259Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T23:21:57.9155479Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T23:21:57.9155679Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-08-26T23:21:57.9157143Z ``def forward(input: Tensor) -> Tensor:`` and 2025-08-26T23:21:57.9157304Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-08-26T23:21:57.9157400Z 2025-08-26T23:21:57.9157437Z .. note:: 2025-08-26T23:21:57.9157539Z If the remote module is placed on a cuda device, 2025-08-26T23:21:57.9157708Z any input CPU tensors will be automatically moved to the same cuda device, 2025-08-26T23:21:57.9157959Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-08-26T23:21:57.9158130Z 2025-08-26T23:21:57.9158163Z Args: 2025-08-26T23:21:57.9158313Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:21:57.9158554Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T23:21:57.9158721Z formats: 2025-08-26T23:21:57.9158774Z 2025-08-26T23:21:57.9158831Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T23:21:57.9160042Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T23:21:57.9160137Z 2025-08-26T23:21:57.9160229Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:21:57.9160490Z module_cls (nn.Module): For example, 2025-08-26T23:21:57.9160610Z >>> class MyModule(nn.Module): 2025-08-26T23:21:57.9160725Z >>> def forward(input): 2025-08-26T23:21:57.9160837Z >>> return input + 1 2025-08-26T23:21:57.9160938Z >>> 2025-08-26T23:21:57.9161025Z >>> module_cls = MyModule 2025-08-26T23:21:57.9161167Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T23:21:57.9161382Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T23:21:57.9161584Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T23:21:57.9162828Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T23:21:57.9163028Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T23:21:57.9163249Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T23:21:57.9163370Z 2025-08-26T23:21:57.9163403Z Returns: 2025-08-26T23:21:57.9163533Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:21:57.9163736Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T23:21:57.9163949Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:21:57.9164154Z on the user-provided module on the remote side. 2025-08-26T23:21:57.9164244Z 2025-08-26T23:21:57.9164279Z Example:: 2025-08-26T23:21:57.9164382Z Run the following code in two different processes: 2025-08-26T23:21:57.9164473Z 2025-08-26T23:21:57.9164518Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.9165608Z >>> # On worker 0: 2025-08-26T23:21:57.9165699Z >>> import torch 2025-08-26T23:21:57.9165804Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9165927Z >>> from torch import nn, Tensor 2025-08-26T23:21:57.9166082Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:21:57.9166227Z >>> 2025-08-26T23:21:57.9166323Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:21:57.9166457Z >>> remote_linear_module = RemoteModule( 2025-08-26T23:21:57.9166585Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:21:57.9166702Z >>> ) 2025-08-26T23:21:57.9166784Z >>> input = torch.randn(128, 20) 2025-08-26T23:21:57.9167880Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T23:21:57.9168040Z >>> ret = ret_fut.wait() 2025-08-26T23:21:57.9168142Z >>> rpc.shutdown() 2025-08-26T23:21:57.9168202Z 2025-08-26T23:21:57.9168236Z >>> # On worker 1: 2025-08-26T23:21:57.9168324Z >>> import torch 2025-08-26T23:21:57.9168426Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9168536Z >>> 2025-08-26T23:21:57.9168629Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:21:57.9168750Z >>> rpc.shutdown() 2025-08-26T23:21:57.9168806Z 2025-08-26T23:21:57.9168896Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.9169021Z 2025-08-26T23:21:57.9170285Z msg = Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-08-26T23:21:57.9170739Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.9170868Z 2025-08-26T23:21:57.9170981Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-08-26T23:21:57.9171128Z 2025-08-26T23:21:57.9171240Z This alternate initialization method can be particularly useful if we want to create multiple 2025-08-26T23:21:57.9171494Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-08-26T23:21:57.9171639Z 2025-08-26T23:21:57.9171738Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-08-26T23:21:57.9171934Z which is not supported. The recommended way is as follows: 2025-08-26T23:21:57.9172033Z 2025-08-26T23:21:57.9172078Z 1. the sender creates a RemoteModule; 2025-08-26T23:21:57.9172210Z 2. the sender sends its ``module_rref`` over RPC; 2025-08-26T23:21:57.9172413Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-08-26T23:21:57.9172566Z 2025-08-26T23:21:57.9172636Z Example:: 2025-08-26T23:21:57.9173726Z Run the following code in two different processes: 2025-08-26T23:21:57.9173823Z 2025-08-26T23:21:57.9173866Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.9173977Z >>> # On worker 0: 2025-08-26T23:21:57.9174066Z >>> import torch 2025-08-26T23:21:57.9174169Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9174290Z >>> from torch import nn, Tensor 2025-08-26T23:21:57.9174469Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:21:57.9174614Z >>> 2025-08-26T23:21:57.9174708Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:21:57.9174834Z >>> remote_module = RemoteModule( 2025-08-26T23:21:57.9174958Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:21:57.9176072Z >>> ) 2025-08-26T23:21:57.9176150Z >>> 2025-08-26T23:21:57.9176257Z >>> remote_module1 = rpc.rpc_sync( 2025-08-26T23:21:57.9176371Z >>> "worker1/cpu", 2025-08-26T23:21:57.9176483Z >>> RemoteModule.init_from_module_rref, 2025-08-26T23:21:57.9176624Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-08-26T23:21:57.9176748Z >>> ) 2025-08-26T23:21:57.9176827Z >>> rpc.shutdown() 2025-08-26T23:21:57.9176885Z 2025-08-26T23:21:57.9176918Z >>> # On worker 1: 2025-08-26T23:21:57.9177006Z >>> import torch 2025-08-26T23:21:57.9177105Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9177214Z >>> 2025-08-26T23:21:57.9178258Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:21:57.9178383Z >>> rpc.shutdown() 2025-08-26T23:21:57.9178440Z 2025-08-26T23:21:57.9178471Z Args: 2025-08-26T23:21:57.9178618Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:21:57.9178857Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T23:21:57.9179028Z formats: 2025-08-26T23:21:57.9179081Z 2025-08-26T23:21:57.9179137Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T23:21:57.9179306Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T23:21:57.9179399Z 2025-08-26T23:21:57.9179488Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:21:57.9179699Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-08-26T23:21:57.9179863Z the created remote module. 2025-08-26T23:21:57.9181055Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T23:21:57.9181277Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T23:21:57.9181474Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T23:21:57.9181667Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T23:21:57.9181788Z 2025-08-26T23:21:57.9181822Z Returns: 2025-08-26T23:21:57.9181951Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:21:57.9182155Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-08-26T23:21:57.9182368Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:21:57.9182554Z on the user-provided module on the remote side. 2025-08-26T23:21:57.9182643Z 2025-08-26T23:21:57.9182731Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.9182855Z 2025-08-26T23:21:57.9183062Z msg = Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-08-26T23:21:57.9184318Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:57.9184448Z 2025-08-26T23:21:57.9184528Z A RemoteModule instance can only be created after RPC initialization. 2025-08-26T23:21:57.9184680Z 2025-08-26T23:21:57.9184753Z It creates a user-specified module on a specified remote node. 2025-08-26T23:21:57.9184939Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T23:21:57.9185096Z executed on the remote node. 2025-08-26T23:21:57.9185249Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T23:21:57.9185423Z gradients back to the corresponding remote module. 2025-08-26T23:21:57.9185516Z 2025-08-26T23:21:57.9185611Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-08-26T23:21:57.9185799Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-08-26T23:21:57.9185996Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-08-26T23:21:57.9186188Z and ``forward`` are the same as the ``forward`` method of the module 2025-08-26T23:21:57.9187292Z returned by the ``module_cls``. 2025-08-26T23:21:57.9187369Z 2025-08-26T23:21:57.9187444Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T23:21:57.9187639Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T23:21:57.9187845Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-08-26T23:21:57.9187960Z 2025-08-26T23:21:57.9188010Z | ``def forward(input: Tensor) -> Tensor:`` 2025-08-26T23:21:57.9188152Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-08-26T23:21:57.9188250Z 2025-08-26T23:21:57.9188282Z Args: 2025-08-26T23:21:57.9188428Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:21:57.9188685Z The format should be "/", where the device field can be parsed as torch.device type. 2025-08-26T23:21:57.9188892Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-08-26T23:21:57.9189066Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:21:57.9190255Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-08-26T23:21:57.9190447Z 2025-08-26T23:21:57.9190490Z >>> class MyModule(nn.Module): 2025-08-26T23:21:57.9190605Z >>> def forward(input): 2025-08-26T23:21:57.9190716Z >>> return input + 1 2025-08-26T23:21:57.9190818Z >>> 2025-08-26T23:21:57.9190903Z >>> module_cls = MyModule 2025-08-26T23:21:57.9190974Z 2025-08-26T23:21:57.9191047Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T23:21:57.9191223Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T23:21:57.9191328Z 2025-08-26T23:21:57.9191360Z Returns: 2025-08-26T23:21:57.9191490Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:21:57.9192633Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T23:21:57.9192851Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:21:57.9193037Z on the user-provided module on the remote side. 2025-08-26T23:21:57.9193124Z 2025-08-26T23:21:57.9193158Z Example:: 2025-08-26T23:21:57.9193259Z Run the following code in two different processes: 2025-08-26T23:21:57.9193352Z 2025-08-26T23:21:57.9193395Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:57.9193506Z >>> # On worker 0: 2025-08-26T23:21:57.9193596Z >>> import torch 2025-08-26T23:21:57.9193699Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9193819Z >>> from torch import nn, Tensor 2025-08-26T23:21:57.9193972Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:21:57.9195141Z >>> 2025-08-26T23:21:57.9195239Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:21:57.9195372Z >>> remote_linear_module = RemoteModule( 2025-08-26T23:21:57.9195498Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:21:57.9195653Z >>> ) 2025-08-26T23:21:57.9195739Z >>> input = torch.randn(128, 20) 2025-08-26T23:21:57.9195868Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T23:21:57.9195998Z >>> ret = ret_fut.wait() 2025-08-26T23:21:57.9196097Z >>> rpc.shutdown() 2025-08-26T23:21:57.9196155Z 2025-08-26T23:21:57.9196189Z >>> # On worker 1: 2025-08-26T23:21:57.9196276Z >>> import torch 2025-08-26T23:21:57.9197321Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:21:57.9197462Z >>> 2025-08-26T23:21:57.9197556Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:21:57.9197676Z >>> rpc.shutdown() 2025-08-26T23:21:57.9197732Z 2025-08-26T23:21:57.9197803Z Furthermore, a more practical example that is combined with 2025-08-26T23:21:57.9198080Z `DistributedDataParallel `__ (DDP) 2025-08-26T23:21:57.9198420Z can be found in this `tutorial `__. 2025-08-26T23:21:57.9198573Z 2025-08-26T23:21:57.9198665Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:57.9198788Z 2025-08-26T23:21:58.6461357Z msg = Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py line=142. 2025-08-26T23:21:58.6461796Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.6462057Z Return the recommended gain value for the given nonlinearity function. 2025-08-26T23:21:58.6462187Z 2025-08-26T23:21:58.6462238Z The values are as follows: 2025-08-26T23:21:58.6462317Z 2025-08-26T23:21:58.6462374Z ================= ==================================================== 2025-08-26T23:21:58.6462518Z nonlinearity gain 2025-08-26T23:21:58.6462645Z ================= ==================================================== 2025-08-26T23:21:58.6462791Z Linear / Identity :math:`1` 2025-08-26T23:21:58.6462908Z Conv{1,2,3}D :math:`1` 2025-08-26T23:21:58.6463171Z Sigmoid :math:`1` 2025-08-26T23:21:58.6463291Z Tanh :math:`\frac{5}{3}` 2025-08-26T23:21:58.6463422Z ReLU :math:`\sqrt{2}` 2025-08-26T23:21:58.6463580Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-08-26T23:21:58.6463740Z SELU :math:`\frac{3}{4}` 2025-08-26T23:21:58.6463871Z ================= ==================================================== 2025-08-26T23:21:58.6463965Z 2025-08-26T23:21:58.6464033Z .. warning:: 2025-08-26T23:21:58.6464170Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-08-26T23:21:58.6464375Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-08-26T23:21:58.6464576Z This gives the initial weights a variance of ``1 / N``, 2025-08-26T23:21:58.6464773Z which is necessary to induce a stable fixed point in the forward pass. 2025-08-26T23:21:58.6464989Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-08-26T23:21:58.6465187Z effect for more stable gradient flow in rectangular layers. 2025-08-26T23:21:58.6465296Z 2025-08-26T23:21:58.6465339Z Args: 2025-08-26T23:21:58.6465471Z nonlinearity: the non-linear function (`nn.functional` name) 2025-08-26T23:21:58.6465654Z param: optional parameter for the non-linear function 2025-08-26T23:21:58.6465761Z 2025-08-26T23:21:58.6465802Z Examples: 2025-08-26T23:21:58.6465908Z >>> gain = nn.init.calculate_gain( 2025-08-26T23:21:58.6466035Z ... "leaky_relu", 0.2 2025-08-26T23:21:58.6466164Z ... ) # leaky_relu with negative_slope=0.2 2025-08-26T23:21:58.6466256Z 2025-08-26T23:21:58.6466450Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-08-26T23:21:58.6468318Z 2025-08-26T23:21:58.6468524Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.6468657Z 2025-08-26T23:21:58.6806809Z msg = Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-08-26T23:21:58.6807438Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.6807678Z 2025-08-26T23:21:58.6807980Z Context manager for training with uneven inputs across processes in DDP. 2025-08-26T23:21:58.6808198Z 2025-08-26T23:21:58.6808339Z This context manager will keep track of already-joined DDP processes, 2025-08-26T23:21:58.6808692Z and "shadow" the forward and backward passes by inserting collective 2025-08-26T23:21:58.6809004Z communication operations to match with the ones created by non-joined 2025-08-26T23:21:58.6809441Z DDP processes. This will ensure each collective call has a corresponding 2025-08-26T23:21:58.6813262Z call by already-joined DDP processes, preventing hangs or errors that 2025-08-26T23:21:58.6813635Z would otherwise happen when training with uneven inputs across 2025-08-26T23:21:58.6813958Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-08-26T23:21:58.6814280Z specified to be ``True``, all trainers will throw an error once one rank 2025-08-26T23:21:58.6814581Z runs out of inputs, allowing these errors to be caught and handled 2025-08-26T23:21:58.6814830Z according to application logic. 2025-08-26T23:21:58.6814952Z 2025-08-26T23:21:58.6815079Z Once all DDP processes have joined, the context manager will broadcast 2025-08-26T23:21:58.6815386Z the model corresponding to the last joined process to all processes to 2025-08-26T23:21:58.6815647Z ensure the model is the same across all processes 2025-08-26T23:21:58.6815862Z (which is guaranteed by DDP). 2025-08-26T23:21:58.6815980Z 2025-08-26T23:21:58.6816103Z To use this to enable training with uneven inputs across processes, 2025-08-26T23:21:58.6816416Z simply wrap this context manager around your training loop. No further 2025-08-26T23:21:58.6816841Z modifications to the model or data loading is required. 2025-08-26T23:21:58.6819643Z 2025-08-26T23:21:58.6819737Z .. warning:: 2025-08-26T23:21:58.6819941Z If the model or training loop this context manager is wrapped around 2025-08-26T23:21:58.6820228Z has additional distributed collective operations, such as 2025-08-26T23:21:58.6820639Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-08-26T23:21:58.6820909Z ``throw_on_early_termination`` must be enabled. This is because this 2025-08-26T23:21:58.6821187Z context manager is not aware of non-DDP collective communication. 2025-08-26T23:21:58.6821462Z This flag will cause all ranks to throw when any one rank 2025-08-26T23:21:58.6821726Z exhausts inputs, allowing these errors to be caught and recovered 2025-08-26T23:21:58.6821955Z from across all ranks. 2025-08-26T23:21:58.6822058Z 2025-08-26T23:21:58.6822109Z Args: 2025-08-26T23:21:58.6825061Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-08-26T23:21:58.6825394Z gradients by the initial ``world_size`` DDP training was launched 2025-08-26T23:21:58.6825663Z with. If ``False``, will compute the effective world size 2025-08-26T23:21:58.6825920Z (number of ranks that have not depleted their inputs yet) and 2025-08-26T23:21:58.6826169Z divide gradients by that during allreduce. Set 2025-08-26T23:21:58.6826424Z ``divide_by_initial_world_size=True`` to ensure every input 2025-08-26T23:21:58.6826700Z sample including the uneven inputs have equal weight in terms of 2025-08-26T23:21:58.6826983Z how much they contribute to the global gradient. This is 2025-08-26T23:21:58.6827246Z achieved by always dividing the gradient by the initial 2025-08-26T23:21:58.6827521Z ``world_size`` even when we encounter uneven inputs. If you set 2025-08-26T23:21:58.6827790Z this to ``False``, we divide the gradient by the remaining 2025-08-26T23:21:58.6830609Z number of nodes. This ensures parity with training on a smaller 2025-08-26T23:21:58.6830914Z ``world_size`` although it also means the uneven inputs would 2025-08-26T23:21:58.6831180Z contribute more towards the global gradient. Typically, you 2025-08-26T23:21:58.6831456Z would want to set this to ``True`` for cases where the last few 2025-08-26T23:21:58.6831834Z inputs of your training job are uneven. In extreme cases, where 2025-08-26T23:21:58.6832116Z there is a large discrepancy in the number of inputs, setting 2025-08-26T23:21:58.6832369Z this to ``False`` might provide better results. 2025-08-26T23:21:58.6832646Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-08-26T23:21:58.6832924Z in ``enable=False`` to disable in cases where you know that 2025-08-26T23:21:58.6833235Z inputs are even across participating processes. Default is 2025-08-26T23:21:58.6833465Z ``True``. 2025-08-26T23:21:58.6835934Z throw_on_early_termination (bool): Whether to throw an error 2025-08-26T23:21:58.6836221Z or continue training when at least one rank has exhausted 2025-08-26T23:21:58.6836495Z inputs. If ``True``, will throw upon the first rank reaching end 2025-08-26T23:21:58.6836748Z of data. If ``False``, will continue training with a smaller 2025-08-26T23:21:58.6837006Z effective world size until all ranks are joined. Note that if 2025-08-26T23:21:58.6837247Z this flag is specified, then the flag 2025-08-26T23:21:58.6837477Z ``divide_by_initial_world_size`` would be ignored. Default 2025-08-26T23:21:58.6837690Z is ``False``. 2025-08-26T23:21:58.6837784Z 2025-08-26T23:21:58.6837788Z 2025-08-26T23:21:58.6837848Z Example:: 2025-08-26T23:21:58.6837927Z 2025-08-26T23:21:58.6837999Z >>> # xdoctest: +SKIP("Distributed") 2025-08-26T23:21:58.6838181Z >>> import torch 2025-08-26T23:21:58.6840629Z >>> import torch.distributed as dist 2025-08-26T23:21:58.6840913Z >>> import os 2025-08-26T23:21:58.6841076Z >>> import torch.multiprocessing as mp 2025-08-26T23:21:58.6841268Z >>> import torch.nn as nn 2025-08-26T23:21:58.6841442Z >>> # On each spawned worker 2025-08-26T23:21:58.6841610Z >>> def worker(rank): 2025-08-26T23:21:58.6841814Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-08-26T23:21:58.6842043Z >>> torch.cuda.set_device(rank) 2025-08-26T23:21:58.6842248Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T23:21:58.6842494Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-08-26T23:21:58.6842743Z >>> model, device_ids=[rank], output_device=rank 2025-08-26T23:21:58.6845053Z >>> ) 2025-08-26T23:21:58.6845223Z >>> # Rank 1 gets one more input than rank 0. 2025-08-26T23:21:58.6845482Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-08-26T23:21:58.6845723Z >>> with model.join(): 2025-08-26T23:21:58.6845894Z >>> for _ in range(5): 2025-08-26T23:21:58.6846074Z >>> for inp in inputs: 2025-08-26T23:21:58.6846257Z >>> loss = model(inp).sum() 2025-08-26T23:21:58.6846443Z >>> loss.backward() 2025-08-26T23:21:58.6846673Z >>> # Without the join() API, the below synchronization will hang 2025-08-26T23:21:58.6846926Z >>> # blocking for rank 1's allreduce to complete. 2025-08-26T23:21:58.6847143Z >>> torch.cuda.synchronize(device=rank) 2025-08-26T23:21:58.6850176Z 2025-08-26T23:21:58.6850452Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.6850664Z 2025-08-26T23:21:58.6851072Z msg = Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-08-26T23:21:58.6851653Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.6851968Z 2025-08-26T23:21:58.6852140Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-08-26T23:21:58.6852377Z 2025-08-26T23:21:58.6852492Z Registers an optimizer with DDP such that the optimization for a 2025-08-26T23:21:58.6852777Z parameter will run immediately when that parameter's gradient is 2025-08-26T23:21:58.6853063Z finished with reduction, instead of waiting for all parameters' 2025-08-26T23:21:58.6853427Z gradients to finish reduction. This can result in a training speedup 2025-08-26T23:21:58.6853731Z depending on your workload since the optimizer can run while gradient 2025-08-26T23:21:58.6854042Z reduction for other parameters are still ongoing. In addition, this has 2025-08-26T23:21:58.6854360Z the potential to reduce peak memory consumption during training, as it 2025-08-26T23:21:58.6856957Z only needs to load the per-parameter optimizer states of a single 2025-08-26T23:21:58.6857257Z parameter at a time, instead of loading all per-parameter optimizer 2025-08-26T23:21:58.6857498Z states at once. 2025-08-26T23:21:58.6857582Z 2025-08-26T23:21:58.6857634Z Args: 2025-08-26T23:21:58.6857819Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-08-26T23:21:58.6858051Z as a fused optimizer. 2025-08-26T23:21:58.6858251Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-08-26T23:21:58.6858529Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-08-26T23:21:58.6858835Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-08-26T23:21:58.6859136Z Optimizers. If this is omitted, all DDP model parameters will be 2025-08-26T23:21:58.6859373Z optimized. 2025-08-26T23:21:58.6861832Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-08-26T23:21:58.6862009Z 2025-08-26T23:21:58.6862067Z .. warning :: 2025-08-26T23:21:58.6862269Z _register_fused_optim should only be called once on a DDP instance, 2025-08-26T23:21:58.6862755Z and registering multiple fused optimizers for the same DDP model 2025-08-26T23:21:58.6863011Z is not currently supported. Please ping 2025-08-26T23:21:58.6863287Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:21:58.6863545Z for your use case. 2025-08-26T23:21:58.6863642Z 2025-08-26T23:21:58.6863699Z .. warning :: 2025-08-26T23:21:58.6863894Z _register_fused_optim and register_comm_hook currently do not 2025-08-26T23:21:58.6864190Z compose together, meaning that custom DDP communication hooks are 2025-08-26T23:21:58.6866547Z not supported with overlapped optimizers. Please ping 2025-08-26T23:21:58.6866872Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:21:58.6867131Z for your use case. 2025-08-26T23:21:58.6867229Z 2025-08-26T23:21:58.6867292Z .. warning :: 2025-08-26T23:21:58.6867507Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-08-26T23:21:58.6867785Z with overlapped optimizer. Please ping 2025-08-26T23:21:58.6868063Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:21:58.6868312Z for your use case. 2025-08-26T23:21:58.6868408Z 2025-08-26T23:21:58.6868463Z Example:: 2025-08-26T23:21:58.6868539Z 2025-08-26T23:21:58.6868619Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-08-26T23:21:58.6868926Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-08-26T23:21:58.6871396Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-08-26T23:21:58.6871644Z >>> lr = 1e-2 2025-08-26T23:21:58.6871784Z >>> betas = (0.9, 0.99) 2025-08-26T23:21:58.6871936Z >>> eps = 1e-6 2025-08-26T23:21:58.6872140Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-08-26T23:21:58.6872404Z >>> # Example with subset of parameters 2025-08-26T23:21:58.6872612Z >>> params_to_opt = [list(net.parameters())[0]] 2025-08-26T23:21:58.6872923Z >>> net._register_fused_optim( 2025-08-26T23:21:58.6873174Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-08-26T23:21:58.6873413Z ... ) 2025-08-26T23:21:58.6873489Z 2025-08-26T23:21:58.6873631Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.6873826Z 2025-08-26T23:21:58.7246991Z msg = Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py line=272. 2025-08-26T23:21:58.7247362Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7247609Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-08-26T23:21:58.7247757Z 2025-08-26T23:21:58.7247880Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-08-26T23:21:58.7248134Z and with 2D inputs, this class 2025-08-26T23:21:58.7248212Z 2025-08-26T23:21:58.7248332Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-08-26T23:21:58.7248582Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-08-26T23:21:58.7248827Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-08-26T23:21:58.7248967Z 2025-08-26T23:21:58.7249092Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-08-26T23:21:58.7249285Z operations. 2025-08-26T23:21:58.7251757Z 2025-08-26T23:21:58.7251866Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-08-26T23:21:58.7252090Z pass. This scales the output of the Embedding before performing a weighted 2025-08-26T23:21:58.7252311Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-08-26T23:21:58.7252571Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-08-26T23:21:58.7252734Z :attr:`per_sample_weights`. 2025-08-26T23:21:58.7252808Z 2025-08-26T23:21:58.7252841Z Args: 2025-08-26T23:21:58.7252960Z num_embeddings (int): size of the dictionary of embeddings 2025-08-26T23:21:58.7253130Z embedding_dim (int): the size of each embedding vector 2025-08-26T23:21:58.7253337Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-08-26T23:21:58.7253538Z is renormalized to have norm :attr:`max_norm`. 2025-08-26T23:21:58.7253752Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-08-26T23:21:58.7254030Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-08-26T23:21:58.7254246Z the words in the mini-batch. Default ``False``. 2025-08-26T23:21:58.7254417Z Note: this option is not supported when ``mode="max"``. 2025-08-26T23:21:58.7255916Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-08-26T23:21:58.7256117Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-08-26T23:21:58.7256310Z into consideration. ``"mean"`` computes the average of the values 2025-08-26T23:21:58.7256487Z in the bag, ``"max"`` computes the max value over each bag. 2025-08-26T23:21:58.7256635Z Default: ``"mean"`` 2025-08-26T23:21:58.7256828Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-08-26T23:21:58.7257064Z Notes for more details regarding sparse gradients. Note: this option is not 2025-08-26T23:21:58.7257275Z supported when ``mode="max"``. 2025-08-26T23:21:58.7257489Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-08-26T23:21:58.7257731Z is equivalent to the size of `indices`. This matches the CSR format. 2025-08-26T23:21:58.7259061Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-08-26T23:21:58.7259318Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-08-26T23:21:58.7259538Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-08-26T23:21:58.7259770Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-08-26T23:21:58.7259986Z zeros, but can be updated to another value to be used as the padding vector. 2025-08-26T23:21:58.7260188Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-08-26T23:21:58.7260452Z reduction. 2025-08-26T23:21:58.7260532Z 2025-08-26T23:21:58.7260568Z Attributes: 2025-08-26T23:21:58.7260733Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-08-26T23:21:58.7260934Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-08-26T23:21:58.7261023Z 2025-08-26T23:21:58.7261065Z Examples:: 2025-08-26T23:21:58.7261117Z 2025-08-26T23:21:58.7262204Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-08-26T23:21:58.7262368Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-08-26T23:21:58.7262513Z >>> # a batch of 2 samples of 4 indices each 2025-08-26T23:21:58.7262718Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T23:21:58.7262878Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T23:21:58.7263023Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:21:58.7263154Z >>> embedding_sum(input, offsets) 2025-08-26T23:21:58.7263282Z tensor([[-0.8861, -5.4350, -0.0523], 2025-08-26T23:21:58.7263398Z [ 1.1306, -2.5798, -1.0044]]) 2025-08-26T23:21:58.7263475Z 2025-08-26T23:21:58.7263519Z >>> # Example with padding_idx 2025-08-26T23:21:58.7263666Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-08-26T23:21:58.7264815Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T23:21:58.7264978Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T23:21:58.7265110Z >>> embedding_sum(input, offsets) 2025-08-26T23:21:58.7265227Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-08-26T23:21:58.7265342Z [-0.7082, 3.2145, -2.6251]]) 2025-08-26T23:21:58.7265416Z 2025-08-26T23:21:58.7265481Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-08-26T23:21:58.7265634Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-08-26T23:21:58.7265781Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-08-26T23:21:58.7265914Z embedding.weight, 2025-08-26T23:21:58.7266035Z padding_idx=embedding.padding_idx, 2025-08-26T23:21:58.7266157Z mode='sum') 2025-08-26T23:21:58.7267209Z 2025-08-26T23:21:58.7267344Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7267468Z 2025-08-26T23:21:58.7272204Z msg = Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py line=186. 2025-08-26T23:21:58.7272610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7272795Z Take in and process masked source/target sequences. 2025-08-26T23:21:58.7272887Z 2025-08-26T23:21:58.7272929Z .. note:: 2025-08-26T23:21:58.7272981Z 2025-08-26T23:21:58.7273127Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-08-26T23:21:58.7273349Z not allowed to participate in the attention, 2025-08-26T23:21:58.7273538Z which is the opposite of the definition for :attr:`attn_mask` 2025-08-26T23:21:58.7273712Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-08-26T23:21:58.7275356Z 2025-08-26T23:21:58.7275394Z Args: 2025-08-26T23:21:58.7275499Z src: the sequence to the encoder (required). 2025-08-26T23:21:58.7275648Z tgt: the sequence to the decoder (required). 2025-08-26T23:21:58.7275851Z src_mask: the additive mask for the src sequence (optional). 2025-08-26T23:21:58.7276021Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-08-26T23:21:58.7276194Z memory_mask: the additive mask for the encoder output (optional). 2025-08-26T23:21:58.7276383Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-08-26T23:21:58.7276577Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-08-26T23:21:58.7276782Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-08-26T23:21:58.7276981Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-08-26T23:21:58.7277148Z Default: ``None``; try to detect a causal mask. 2025-08-26T23:21:58.7277276Z Warning: 2025-08-26T23:21:58.7277395Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-08-26T23:21:58.7277552Z the causal mask. Providing incorrect hints can result in 2025-08-26T23:21:58.7278818Z incorrect execution, including forward and backward 2025-08-26T23:21:58.7278957Z compatibility. 2025-08-26T23:21:58.7279098Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-08-26T23:21:58.7279262Z Default: ``None``; try to detect a causal mask. 2025-08-26T23:21:58.7279387Z Warning: 2025-08-26T23:21:58.7279504Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-08-26T23:21:58.7279660Z the causal mask. Providing incorrect hints can result in 2025-08-26T23:21:58.7279820Z incorrect execution, including forward and backward 2025-08-26T23:21:58.7279953Z compatibility. 2025-08-26T23:21:58.7280084Z memory_is_causal: If specified, applies a causal mask as 2025-08-26T23:21:58.7280222Z ``memory_mask``. 2025-08-26T23:21:58.7281413Z Default: ``False``. 2025-08-26T23:21:58.7281521Z Warning: 2025-08-26T23:21:58.7281631Z ``memory_is_causal`` provides a hint that 2025-08-26T23:21:58.7281779Z ``memory_mask`` is the causal mask. Providing incorrect 2025-08-26T23:21:58.7281931Z hints can result in incorrect execution, including 2025-08-26T23:21:58.7282072Z forward and backward compatibility. 2025-08-26T23:21:58.7282156Z 2025-08-26T23:21:58.7282190Z Shape: 2025-08-26T23:21:58.7282335Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-08-26T23:21:58.7282502Z `(N, S, E)` if `batch_first=True`. 2025-08-26T23:21:58.7282667Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T23:21:58.7282830Z `(N, T, E)` if `batch_first=True`. 2025-08-26T23:21:58.7283944Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-08-26T23:21:58.7284153Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-08-26T23:21:58.7284300Z - memory_mask: :math:`(T, S)`. 2025-08-26T23:21:58.7284464Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T23:21:58.7284667Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-08-26T23:21:58.7284892Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T23:21:58.7285018Z 2025-08-26T23:21:58.7285130Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-08-26T23:21:58.7285350Z positions. If a BoolTensor is provided, positions with ``True`` 2025-08-26T23:21:58.7285553Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-08-26T23:21:58.7285762Z is provided, it will be added to the attention weight. 2025-08-26T23:21:58.7286938Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-08-26T23:21:58.7287161Z the attention. If a BoolTensor is provided, the positions with the 2025-08-26T23:21:58.7287380Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-08-26T23:21:58.7287523Z 2025-08-26T23:21:58.7287617Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T23:21:58.7287787Z `(N, T, E)` if `batch_first=True`. 2025-08-26T23:21:58.7287867Z 2025-08-26T23:21:58.7287953Z Note: Due to the multi-head attention architecture in the transformer model, 2025-08-26T23:21:58.7288159Z the output sequence length of a transformer is same as the input sequence 2025-08-26T23:21:58.7288325Z (i.e. target) length of the decoder. 2025-08-26T23:21:58.7288405Z 2025-08-26T23:21:58.7288543Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-08-26T23:21:58.7288741Z batch size, :math:`E` is the feature number 2025-08-26T23:21:58.7288829Z 2025-08-26T23:21:58.7288863Z Examples: 2025-08-26T23:21:58.7289915Z >>> # xdoctest: +SKIP 2025-08-26T23:21:58.7290035Z >>> output = transformer_model( 2025-08-26T23:21:58.7290171Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-08-26T23:21:58.7290294Z ... ) 2025-08-26T23:21:58.7290477Z 2025-08-26T23:21:58.7290611Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7290737Z 2025-08-26T23:21:58.7349869Z msg = Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py line=410. 2025-08-26T23:21:58.7350202Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7350472Z Computes a partial inverse of :class:`MaxPool2d`. 2025-08-26T23:21:58.7350565Z 2025-08-26T23:21:58.7350657Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-08-26T23:21:58.7350787Z 2025-08-26T23:21:58.7352255Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-08-26T23:21:58.7352470Z including the indices of the maximal values and computes a partial inverse 2025-08-26T23:21:58.7352646Z in which all non-maximal values are set to zero. 2025-08-26T23:21:58.7352737Z 2025-08-26T23:21:58.7352769Z Note: 2025-08-26T23:21:58.7352924Z This operation may behave nondeterministically when the input indices has repeat values. 2025-08-26T23:21:58.7353208Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-08-26T23:21:58.7353385Z 2025-08-26T23:21:58.7353474Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-08-26T23:21:58.7353733Z sizes. Hence, the inversion process can get ambiguous. 2025-08-26T23:21:58.7353901Z To accommodate this, you can provide the needed output size 2025-08-26T23:21:58.7354077Z as an additional argument :attr:`output_size` in the forward call. 2025-08-26T23:21:58.7354230Z See the Inputs and Example below. 2025-08-26T23:21:58.7354309Z 2025-08-26T23:21:58.7355543Z Args: 2025-08-26T23:21:58.7355706Z kernel_size (int or tuple): Size of the max pooling window. 2025-08-26T23:21:58.7355871Z stride (int or tuple): Stride of the max pooling window. 2025-08-26T23:21:58.7356020Z It is set to :attr:`kernel_size` by default. 2025-08-26T23:21:58.7356173Z padding (int or tuple): Padding that was added to the input 2025-08-26T23:21:58.7356276Z 2025-08-26T23:21:58.7356309Z Inputs: 2025-08-26T23:21:58.7356424Z - `input`: the input Tensor to invert 2025-08-26T23:21:58.7356579Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-08-26T23:21:58.7356750Z - `output_size` (optional): the targeted output size 2025-08-26T23:21:58.7356845Z 2025-08-26T23:21:58.7356878Z Shape: 2025-08-26T23:21:58.7356991Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-08-26T23:21:58.7358205Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-08-26T23:21:58.7358319Z 2025-08-26T23:21:58.7358354Z .. math:: 2025-08-26T23:21:58.7358505Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-08-26T23:21:58.7358635Z 2025-08-26T23:21:58.7358667Z .. math:: 2025-08-26T23:21:58.7358806Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-08-26T23:21:58.7358931Z 2025-08-26T23:21:58.7358995Z or as given by :attr:`output_size` in the call operator 2025-08-26T23:21:58.7359093Z 2025-08-26T23:21:58.7359128Z Example:: 2025-08-26T23:21:58.7359178Z 2025-08-26T23:21:58.7359277Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-08-26T23:21:58.7359419Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-08-26T23:21:58.7359551Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-08-26T23:21:58.7359678Z [ 5., 6., 7., 8.], 2025-08-26T23:21:58.7360909Z [ 9., 10., 11., 12.], 2025-08-26T23:21:58.7361032Z [13., 14., 15., 16.]]]]) 2025-08-26T23:21:58.7361154Z >>> output, indices = pool(input) 2025-08-26T23:21:58.7361274Z >>> unpool(output, indices) 2025-08-26T23:21:58.7361387Z tensor([[[[ 0., 0., 0., 0.], 2025-08-26T23:21:58.7361497Z [ 0., 6., 0., 8.], 2025-08-26T23:21:58.7361605Z [ 0., 0., 0., 0.], 2025-08-26T23:21:58.7361714Z [ 0., 14., 0., 16.]]]]) 2025-08-26T23:21:58.7361862Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-08-26T23:21:58.7362026Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-08-26T23:21:58.7362157Z [ 6., 7., 8., 9., 10.], 2025-08-26T23:21:58.7363319Z [11., 12., 13., 14., 15.], 2025-08-26T23:21:58.7363446Z [16., 17., 18., 19., 20.]]]]) 2025-08-26T23:21:58.7363569Z >>> output, indices = pool(input) 2025-08-26T23:21:58.7363709Z >>> # This call will not work without specifying output_size 2025-08-26T23:21:58.7363864Z >>> unpool(output, indices, output_size=input.size()) 2025-08-26T23:21:58.7363998Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-08-26T23:21:58.7364109Z [ 0., 7., 0., 9., 0.], 2025-08-26T23:21:58.7364218Z [ 0., 0., 0., 0., 0.], 2025-08-26T23:21:58.7364327Z [ 0., 17., 0., 19., 0.]]]]) 2025-08-26T23:21:58.7364442Z 2025-08-26T23:21:58.7364445Z 2025-08-26T23:21:58.7364476Z 2025-08-26T23:21:58.7364606Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7364731Z 2025-08-26T23:21:58.7495019Z msg = Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1798. 2025-08-26T23:21:58.7497257Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7497456Z Creates a criterion that measures the triplet loss given input 2025-08-26T23:21:58.7497648Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-08-26T23:21:58.7497832Z positive, and negative examples, respectively), and a nonnegative, 2025-08-26T23:21:58.7498036Z real-valued function ("distance function") used to compute the relationship 2025-08-26T23:21:58.7498264Z between the anchor and positive example ("positive distance") and the 2025-08-26T23:21:58.7498440Z anchor and negative example ("negative distance"). 2025-08-26T23:21:58.7498535Z 2025-08-26T23:21:58.7498612Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-08-26T23:21:58.7498759Z can be described as: 2025-08-26T23:21:58.7498822Z 2025-08-26T23:21:58.7500292Z .. math:: 2025-08-26T23:21:58.7500586Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-08-26T23:21:58.7500740Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-08-26T23:21:58.7500839Z 2025-08-26T23:21:58.7500928Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-08-26T23:21:58.7501166Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-08-26T23:21:58.7501405Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-08-26T23:21:58.7501622Z between the positive and negative distances that is required for the loss to 2025-08-26T23:21:58.7501873Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-08-26T23:21:58.7502032Z that the distance function can handle. 2025-08-26T23:21:58.7502111Z 2025-08-26T23:21:58.7502161Z If :attr:`reduction` is not ``'none'`` 2025-08-26T23:21:58.7503728Z (default ``'mean'``), then: 2025-08-26T23:21:58.7503800Z 2025-08-26T23:21:58.7503834Z .. math:: 2025-08-26T23:21:58.7503916Z \ell(x, y) = 2025-08-26T23:21:58.7504007Z \begin{cases} 2025-08-26T23:21:58.7504141Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-08-26T23:21:58.7504315Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-08-26T23:21:58.7504455Z \end{cases} 2025-08-26T23:21:58.7504512Z 2025-08-26T23:21:58.7504598Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-08-26T23:21:58.7504815Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-08-26T23:21:58.7504941Z 2025-08-26T23:21:58.7504975Z Args: 2025-08-26T23:21:58.7505114Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-08-26T23:21:58.7505316Z quantifies the closeness of two tensors. If not specified, 2025-08-26T23:21:58.7505480Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-08-26T23:21:58.7505672Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-08-26T23:21:58.7505900Z between the positive and negative distances required for the loss to be 0. Larger 2025-08-26T23:21:58.7506132Z margins penalize cases where the negative examples are not distant enough from the 2025-08-26T23:21:58.7506336Z anchors, relative to the positives. Default: :math:`1`. 2025-08-26T23:21:58.7506532Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-08-26T23:21:58.7506788Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-08-26T23:21:58.7507007Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-08-26T23:21:58.7507229Z negative example than the anchor is, swaps the positive example and the anchor in 2025-08-26T23:21:58.7507417Z the loss computation. Default: ``False``. 2025-08-26T23:21:58.7507631Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-08-26T23:21:58.7507840Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T23:21:58.7508016Z ``'mean'``: the sum of the output will be divided by the number of 2025-08-26T23:21:58.7508207Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-08-26T23:21:58.7508348Z 2025-08-26T23:21:58.7508349Z 2025-08-26T23:21:58.7508389Z Shape: 2025-08-26T23:21:58.7508531Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-08-26T23:21:58.7508701Z as supported by the distance function. 2025-08-26T23:21:58.7509970Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-08-26T23:21:58.7510131Z otherwise. 2025-08-26T23:21:58.7510188Z 2025-08-26T23:21:58.7510224Z Examples: 2025-08-26T23:21:58.7510274Z 2025-08-26T23:21:58.7510318Z >>> # Initialize embeddings 2025-08-26T23:21:58.7510522Z >>> embedding = nn.Embedding(1000, 128) 2025-08-26T23:21:58.7510646Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:21:58.7510777Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:21:58.7510907Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:21:58.7511030Z >>> anchor = embedding(anchor_ids) 2025-08-26T23:21:58.7511153Z >>> positive = embedding(positive_ids) 2025-08-26T23:21:58.7511273Z >>> negative = embedding(negative_ids) 2025-08-26T23:21:58.7513038Z >>> 2025-08-26T23:21:58.7513169Z >>> # Built-in Distance Function 2025-08-26T23:21:58.7513281Z >>> triplet_loss = \ 2025-08-26T23:21:58.7513445Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-08-26T23:21:58.7513637Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:21:58.7513769Z >>> output.backward() 2025-08-26T23:21:58.7513861Z >>> 2025-08-26T23:21:58.7513944Z >>> # Custom Distance Function 2025-08-26T23:21:58.7514056Z >>> def l_infinity(x1, x2): 2025-08-26T23:21:58.7514181Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-08-26T23:21:58.7515413Z >>> 2025-08-26T23:21:58.7515533Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-08-26T23:21:58.7515674Z >>> triplet_loss = ( 2025-08-26T23:21:58.7515834Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-08-26T23:21:58.7516027Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:21:58.7516158Z >>> output.backward() 2025-08-26T23:21:58.7516248Z >>> 2025-08-26T23:21:58.7516335Z >>> # Custom Distance Function (Lambda) 2025-08-26T23:21:58.7516448Z >>> triplet_loss = ( 2025-08-26T23:21:58.7516559Z >>> nn.TripletMarginWithDistanceLoss( 2025-08-26T23:21:58.7516719Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-08-26T23:21:58.7517830Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:21:58.7517962Z >>> output.backward() 2025-08-26T23:21:58.7518023Z 2025-08-26T23:21:58.7518058Z Reference: 2025-08-26T23:21:58.7518214Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-08-26T23:21:58.7518440Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-08-26T23:21:58.7518586Z 2025-08-26T23:21:58.7518718Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-08-26T23:21:58.7518876Z 2025-08-26T23:21:58.7519064Z msg = Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1933. 2025-08-26T23:21:58.7519356Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7519535Z The Connectionist Temporal Classification loss. 2025-08-26T23:21:58.7519622Z 2025-08-26T23:21:58.7519770Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-08-26T23:21:58.7521154Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-08-26T23:21:58.7521431Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-08-26T23:21:58.7521688Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-08-26T23:21:58.7521858Z 2025-08-26T23:21:58.7521894Z Args: 2025-08-26T23:21:58.7522003Z blank (int, optional): blank label. Default :math:`0`. 2025-08-26T23:21:58.7522186Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-08-26T23:21:58.7522375Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T23:21:58.7522551Z ``'mean'``: the output losses will be divided by the target lengths and 2025-08-26T23:21:58.7522751Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-08-26T23:21:58.7522915Z Default: ``'mean'`` 2025-08-26T23:21:58.7523024Z zero_infinity (bool, optional): 2025-08-26T23:21:58.7524195Z Whether to zero infinite losses and the associated gradients. 2025-08-26T23:21:58.7524342Z Default: ``False`` 2025-08-26T23:21:58.7524479Z Infinite losses mainly occur when the inputs are too short 2025-08-26T23:21:58.7524623Z to be aligned to the targets. 2025-08-26T23:21:58.7524701Z 2025-08-26T23:21:58.7524735Z Shape: 2025-08-26T23:21:58.7524880Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-08-26T23:21:58.7525031Z where :math:`T = \text{input length}`, 2025-08-26T23:21:58.7525154Z :math:`N = \text{batch size}`, and 2025-08-26T23:21:58.7525292Z :math:`C = \text{number of classes (including blank)}`. 2025-08-26T23:21:58.7525463Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-08-26T23:21:58.7525626Z :func:`torch.nn.functional.log_softmax`). 2025-08-26T23:21:58.7526696Z - Targets: Tensor of size :math:`(N, S)` or 2025-08-26T23:21:58.7526841Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-08-26T23:21:58.7526980Z where :math:`N = \text{batch size}` and 2025-08-26T23:21:58.7527124Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-08-26T23:21:58.7527286Z It represents the target sequences. Each element in the target 2025-08-26T23:21:58.7527478Z sequence is a class index. And the target index cannot be blank (default=0). 2025-08-26T23:21:58.7527656Z In the :math:`(N, S)` form, targets are padded to the 2025-08-26T23:21:58.7527801Z length of the longest sequence, and stacked. 2025-08-26T23:21:58.7527955Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-08-26T23:21:58.7528110Z the targets are assumed to be un-padded and 2025-08-26T23:21:58.7528240Z concatenated within 1 dimension. 2025-08-26T23:21:58.7529321Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T23:21:58.7529503Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-08-26T23:21:58.7529682Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-08-26T23:21:58.7529871Z for each sequence to achieve masking under the assumption that sequences 2025-08-26T23:21:58.7530055Z are padded to equal lengths. 2025-08-26T23:21:58.7530205Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T23:21:58.7530481Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-08-26T23:21:58.7530670Z Lengths are specified for each sequence to achieve masking under the 2025-08-26T23:21:58.7530868Z assumption that sequences are padded to equal lengths. If target shape is 2025-08-26T23:21:58.7531079Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-08-26T23:21:58.7531265Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-08-26T23:21:58.7532412Z each target in a batch. Lengths must each be :math:`\leq S` 2025-08-26T23:21:58.7532598Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-08-26T23:21:58.7532826Z targets, the target_lengths must add up to the total length of the tensor. 2025-08-26T23:21:58.7533021Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-08-26T23:21:58.7533210Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-08-26T23:21:58.7533399Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-08-26T23:21:58.7533504Z 2025-08-26T23:21:58.7533540Z Examples: 2025-08-26T23:21:58.7533591Z 2025-08-26T23:21:58.7533636Z >>> # Target are to be padded 2025-08-26T23:21:58.7533754Z >>> T = 50 # Input sequence length 2025-08-26T23:21:58.7533882Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:21:58.7534939Z >>> N = 16 # Batch size 2025-08-26T23:21:58.7535090Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-08-26T23:21:58.7535274Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-08-26T23:21:58.7535406Z >>> 2025-08-26T23:21:58.7535548Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T23:21:58.7535729Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T23:21:58.7535869Z >>> 2025-08-26T23:21:58.7535981Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:21:58.7536162Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-08-26T23:21:58.7536304Z >>> 2025-08-26T23:21:58.7536425Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T23:21:58.7537536Z >>> target_lengths = torch.randint( 2025-08-26T23:21:58.7537654Z ... low=S_min, 2025-08-26T23:21:58.7537749Z ... high=S, 2025-08-26T23:21:58.7537841Z ... size=(N,), 2025-08-26T23:21:58.7537945Z ... dtype=torch.long, 2025-08-26T23:21:58.7538045Z ... ) 2025-08-26T23:21:58.7538133Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:21:58.7538274Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:21:58.7538414Z >>> loss.backward() 2025-08-26T23:21:58.7538506Z >>> 2025-08-26T23:21:58.7538579Z >>> 2025-08-26T23:21:58.7539599Z >>> # Target are to be un-padded 2025-08-26T23:21:58.7539720Z >>> T = 50 # Input sequence length 2025-08-26T23:21:58.7539846Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:21:58.7539970Z >>> N = 16 # Batch size 2025-08-26T23:21:58.7540066Z >>> 2025-08-26T23:21:58.7540179Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T23:21:58.7540441Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T23:21:58.7540626Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T23:21:58.7540769Z >>> 2025-08-26T23:21:58.7540880Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:21:58.7541096Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-08-26T23:21:58.7542204Z >>> target = torch.randint( 2025-08-26T23:21:58.7542313Z ... low=1, 2025-08-26T23:21:58.7542404Z ... high=C, 2025-08-26T23:21:58.7542504Z ... size=(sum(target_lengths),), 2025-08-26T23:21:58.7542620Z ... dtype=torch.long, 2025-08-26T23:21:58.7542720Z ... ) 2025-08-26T23:21:58.7542843Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:21:58.7542979Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:21:58.7543119Z >>> loss.backward() 2025-08-26T23:21:58.7543210Z >>> 2025-08-26T23:21:58.7543284Z >>> 2025-08-26T23:21:58.7544328Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-08-26T23:21:58.7544508Z >>> T = 50 # Input sequence length 2025-08-26T23:21:58.7544635Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:21:58.7544752Z >>> 2025-08-26T23:21:58.7544864Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-08-26T23:21:58.7545021Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-08-26T23:21:58.7545178Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-08-26T23:21:58.7545347Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-08-26T23:21:58.7545470Z >>> 2025-08-26T23:21:58.7545581Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:21:58.7545767Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-08-26T23:21:58.7546854Z >>> target = torch.randint( 2025-08-26T23:21:58.7546962Z ... low=1, 2025-08-26T23:21:58.7547051Z ... high=C, 2025-08-26T23:21:58.7547149Z ... size=(target_lengths,), 2025-08-26T23:21:58.7547263Z ... dtype=torch.long, 2025-08-26T23:21:58.7547361Z ... ) 2025-08-26T23:21:58.7547471Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:21:58.7547607Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:21:58.7547745Z >>> loss.backward() 2025-08-26T23:21:58.7547808Z 2025-08-26T23:21:58.7547842Z Reference: 2025-08-26T23:21:58.7547955Z A. Graves et al.: Connectionist Temporal Classification: 2025-08-26T23:21:58.7549059Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-08-26T23:21:58.7549238Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-08-26T23:21:58.7549331Z 2025-08-26T23:21:58.7549364Z Note: 2025-08-26T23:21:58.7549492Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-08-26T23:21:58.7549701Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-08-26T23:21:58.7549905Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-08-26T23:21:58.7550061Z dtype :attr:`torch.int32`. 2025-08-26T23:21:58.7550135Z 2025-08-26T23:21:58.7550230Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-08-26T23:21:58.7550449Z 2025-08-26T23:21:58.7550450Z 2025-08-26T23:21:58.7550482Z Note: 2025-08-26T23:21:58.7550612Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-08-26T23:21:58.7550822Z may select a nondeterministic algorithm to increase performance. If this is 2025-08-26T23:21:58.7551974Z undesirable, you can try to make the operation deterministic (potentially at 2025-08-26T23:21:58.7552185Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-08-26T23:21:58.7552337Z True``. 2025-08-26T23:21:58.7552460Z Please see the notes on :doc:`/notes/randomness` for background. 2025-08-26T23:21:58.7552596Z 2025-08-26T23:21:58.7552781Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7552905Z 2025-08-26T23:21:58.7651375Z msg = Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=603. 2025-08-26T23:21:58.7651697Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7652347Z Applies Batch Normalization over a N-Dimensional input. 2025-08-26T23:21:58.7652453Z 2025-08-26T23:21:58.7652650Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-08-26T23:21:58.7654658Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-08-26T23:21:58.7654856Z Internal Covariate Shift `__ . 2025-08-26T23:21:58.7654964Z 2025-08-26T23:21:58.7655034Z .. math:: 2025-08-26T23:21:58.7655105Z 2025-08-26T23:21:58.7655190Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-08-26T23:21:58.7655311Z 2025-08-26T23:21:58.7655402Z The mean and standard-deviation are calculated per-dimension over all 2025-08-26T23:21:58.7655613Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-08-26T23:21:58.7655818Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-08-26T23:21:58.7656007Z By default, the elements of :math:`\gamma` are sampled from 2025-08-26T23:21:58.7656187Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-08-26T23:21:58.7656393Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-08-26T23:21:58.7657859Z `torch.var(input, unbiased=False)`. 2025-08-26T23:21:58.7657940Z 2025-08-26T23:21:58.7658034Z Also by default, during training this layer keeps running estimates of its 2025-08-26T23:21:58.7658236Z computed mean and variance, which are then used for normalization during 2025-08-26T23:21:58.7658484Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-08-26T23:21:58.7658641Z of 0.1. 2025-08-26T23:21:58.7658687Z 2025-08-26T23:21:58.7658775Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-08-26T23:21:58.7658965Z keep running estimates, and batch statistics are instead used during 2025-08-26T23:21:58.7659119Z evaluation time as well. 2025-08-26T23:21:58.7659188Z 2025-08-26T23:21:58.7659221Z .. note:: 2025-08-26T23:21:58.7659349Z This :attr:`momentum` argument is different from one used in optimizer 2025-08-26T23:21:58.7659539Z classes and the conventional notion of momentum. Mathematically, the 2025-08-26T23:21:58.7659700Z update rule for running statistics here is 2025-08-26T23:21:58.7659879Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-08-26T23:21:58.7660084Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-08-26T23:21:58.7660232Z new observed value. 2025-08-26T23:21:58.7660298Z 2025-08-26T23:21:58.7660512Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-08-26T23:21:58.7660742Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-08-26T23:21:58.7660931Z Normalization or Spatio-temporal Batch Normalization. 2025-08-26T23:21:58.7662058Z 2025-08-26T23:21:58.7662120Z Currently :class:`SyncBatchNorm` only supports 2025-08-26T23:21:58.7662312Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-08-26T23:21:58.7662526Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-08-26T23:21:58.7662711Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-08-26T23:21:58.7662854Z Network with DDP. 2025-08-26T23:21:58.7662918Z 2025-08-26T23:21:58.7662949Z Args: 2025-08-26T23:21:58.7663125Z num_features: :math:`C` from an expected input of size 2025-08-26T23:21:58.7663261Z :math:`(N, C, +)` 2025-08-26T23:21:58.7663397Z eps: a value added to the denominator for numerical stability. 2025-08-26T23:21:58.7663537Z Default: ``1e-5`` 2025-08-26T23:21:58.7663672Z momentum: the value used for the running_mean and running_var 2025-08-26T23:21:58.7664877Z computation. Can be set to ``None`` for cumulative moving average 2025-08-26T23:21:58.7665066Z (i.e. simple average). Default: 0.1 2025-08-26T23:21:58.7665219Z affine: a boolean value that when set to ``True``, this module has 2025-08-26T23:21:58.7665384Z learnable affine parameters. Default: ``True`` 2025-08-26T23:21:58.7665548Z track_running_stats: a boolean value that when set to ``True``, this 2025-08-26T23:21:58.7665738Z module tracks the running mean and variance, and when set to ``False``, 2025-08-26T23:21:58.7665954Z this module does not track such statistics, and initializes statistics 2025-08-26T23:21:58.7666143Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-08-26T23:21:58.7666333Z When these buffers are ``None``, this module always uses batch statistics. 2025-08-26T23:21:58.7666506Z in both training and eval modes. Default: ``True`` 2025-08-26T23:21:58.7666683Z process_group: synchronization of stats happen within each process group 2025-08-26T23:21:58.7667847Z individually. Default behavior is synchronization across the whole 2025-08-26T23:21:58.7667992Z world 2025-08-26T23:21:58.7668043Z 2025-08-26T23:21:58.7668077Z Shape: 2025-08-26T23:21:58.7668166Z - Input: :math:`(N, C, +)` 2025-08-26T23:21:58.7668295Z - Output: :math:`(N, C, +)` (same shape as input) 2025-08-26T23:21:58.7668385Z 2025-08-26T23:21:58.7668420Z .. note:: 2025-08-26T23:21:58.7668553Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-08-26T23:21:58.7668767Z synchronization is disabled when ``model.eval()`` is set or if 2025-08-26T23:21:58.7668920Z ``self.training`` is otherwise ``False``. 2025-08-26T23:21:58.7669003Z 2025-08-26T23:21:58.7669038Z Examples:: 2025-08-26T23:21:58.7669090Z 2025-08-26T23:21:58.7669129Z >>> # xdoctest: +SKIP 2025-08-26T23:21:58.7670205Z >>> # With Learnable Parameters 2025-08-26T23:21:58.7670418Z >>> m = nn.SyncBatchNorm(100) 2025-08-26T23:21:58.7670541Z >>> # creating process group (optional) 2025-08-26T23:21:58.7670674Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T23:21:58.7670800Z >>> ranks = list(range(8)) 2025-08-26T23:21:58.7670910Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T23:21:58.7671039Z >>> # Note: every rank calls into new_group for every 2025-08-26T23:21:58.7671185Z >>> # process group created, even if that rank is not 2025-08-26T23:21:58.7671316Z >>> # part of the group. 2025-08-26T23:21:58.7671476Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T23:21:58.7672647Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T23:21:58.7672804Z >>> # Without Learnable Parameters 2025-08-26T23:21:58.7672951Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-08-26T23:21:58.7673108Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-08-26T23:21:58.7673229Z >>> output = m(input) 2025-08-26T23:21:58.7673296Z 2025-08-26T23:21:58.7673341Z >>> # network is nn.BatchNorm layer 2025-08-26T23:21:58.7673514Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-08-26T23:21:58.7673707Z >>> # only single gpu per process is currently supported 2025-08-26T23:21:58.7673881Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-08-26T23:21:58.7674039Z >>> sync_bn_network, 2025-08-26T23:21:58.7674208Z >>> device_ids=[args.local_rank], 2025-08-26T23:21:58.7675393Z >>> output_device=args.local_rank) 2025-08-26T23:21:58.7675513Z 2025-08-26T23:21:58.7675719Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7675904Z 2025-08-26T23:21:58.7676304Z msg = Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=830. 2025-08-26T23:21:58.7676840Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7677204Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-08-26T23:21:58.7677424Z 2025-08-26T23:21:58.7677473Z Args: 2025-08-26T23:21:58.7677725Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-08-26T23:21:58.7678042Z process_group (optional): process group to scope synchronization, 2025-08-26T23:21:58.7678285Z default is the whole world 2025-08-26T23:21:58.7678410Z 2025-08-26T23:21:58.7678464Z Returns: 2025-08-26T23:21:58.7680693Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-08-26T23:21:58.7681029Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-08-26T23:21:58.7681335Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-08-26T23:21:58.7681561Z instead. 2025-08-26T23:21:58.7681653Z 2025-08-26T23:21:58.7681711Z Example:: 2025-08-26T23:21:58.7681790Z 2025-08-26T23:21:58.7681859Z >>> # Network with nn.BatchNorm layer 2025-08-26T23:21:58.7682056Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:58.7682270Z >>> module = torch.nn.Sequential( 2025-08-26T23:21:58.7682465Z >>> torch.nn.Linear(20, 100), 2025-08-26T23:21:58.7682720Z >>> torch.nn.BatchNorm1d(100), 2025-08-26T23:21:58.7682916Z >>> ).cuda() 2025-08-26T23:21:58.7684984Z >>> # creating process group (optional) 2025-08-26T23:21:58.7685133Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T23:21:58.7685265Z >>> ranks = list(range(8)) 2025-08-26T23:21:58.7685385Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T23:21:58.7685522Z >>> # Note: every rank calls into new_group for every 2025-08-26T23:21:58.7685672Z >>> # process group created, even if that rank is not 2025-08-26T23:21:58.7685806Z >>> # part of the group. 2025-08-26T23:21:58.7685929Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:21:58.7686100Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T23:21:58.7686301Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T23:21:58.7686516Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-08-26T23:21:58.7687769Z 2025-08-26T23:21:58.7687805Z 2025-08-26T23:21:58.7687942Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7688068Z 2025-08-26T23:21:58.7719683Z msg = Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/flatten.py line=66. 2025-08-26T23:21:58.7720011Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7720141Z 2025-08-26T23:21:58.7720256Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-08-26T23:21:58.7720553Z 2025-08-26T23:21:58.7720699Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-08-26T23:21:58.7720915Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-08-26T23:21:58.7721116Z 2025-08-26T23:21:58.7721233Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-08-26T23:21:58.7721467Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-08-26T23:21:58.7721657Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-08-26T23:21:58.7723301Z 2025-08-26T23:21:58.7723337Z Shape: 2025-08-26T23:21:58.7723525Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-08-26T23:21:58.7723738Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-08-26T23:21:58.7723947Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-08-26T23:21:58.7724114Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-08-26T23:21:58.7724225Z 2025-08-26T23:21:58.7724257Z Args: 2025-08-26T23:21:58.7724361Z dim (Union[int, str]): Dimension to be unflattened 2025-08-26T23:21:58.7724575Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-08-26T23:21:58.7724729Z 2025-08-26T23:21:58.7724764Z Examples: 2025-08-26T23:21:58.7724852Z >>> input = torch.randn(2, 50) 2025-08-26T23:21:58.7724966Z >>> # With tuple of ints 2025-08-26T23:21:58.7726187Z >>> m = nn.Sequential( 2025-08-26T23:21:58.7726290Z >>> nn.Linear(50, 50), 2025-08-26T23:21:58.7726399Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-08-26T23:21:58.7726504Z >>> ) 2025-08-26T23:21:58.7726586Z >>> output = m(input) 2025-08-26T23:21:58.7726685Z >>> output.size() 2025-08-26T23:21:58.7726783Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:21:58.7726884Z >>> # With torch.Size 2025-08-26T23:21:58.7726980Z >>> m = nn.Sequential( 2025-08-26T23:21:58.7727080Z >>> nn.Linear(50, 50), 2025-08-26T23:21:58.7727192Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-08-26T23:21:58.7728316Z >>> ) 2025-08-26T23:21:58.7728397Z >>> output = m(input) 2025-08-26T23:21:58.7728523Z >>> output.size() 2025-08-26T23:21:58.7728618Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:21:58.7728728Z >>> # With namedshape (tuple of tuples) 2025-08-26T23:21:58.7728865Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-08-26T23:21:58.7729032Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-08-26T23:21:58.7729184Z >>> output = unflatten(input) 2025-08-26T23:21:58.7729293Z >>> output.size() 2025-08-26T23:21:58.7729386Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:21:58.7729450Z 2025-08-26T23:21:58.7729539Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7730856Z 2025-08-26T23:21:58.7842401Z msg = Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrize.py line=424. 2025-08-26T23:21:58.7843036Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7843356Z Register a parametrization to a tensor in a module. 2025-08-26T23:21:58.7843517Z 2025-08-26T23:21:58.7843682Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-08-26T23:21:58.7844072Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-08-26T23:21:58.7844476Z If the original tensor requires a gradient, the backward pass will differentiate 2025-08-26T23:21:58.7844852Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-08-26T23:21:58.7845084Z 2025-08-26T23:21:58.7845272Z The first time that a module registers a parametrization, this function will add an attribute 2025-08-26T23:21:58.7845658Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-08-26T23:21:58.7845872Z 2025-08-26T23:21:58.7848968Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-08-26T23:21:58.7849171Z ``module.parametrizations.weight``. 2025-08-26T23:21:58.7849175Z 2025-08-26T23:21:58.7849266Z The original tensor will be accessible under 2025-08-26T23:21:58.7849354Z ``module.parametrizations.weight.original``. 2025-08-26T23:21:58.7849358Z 2025-08-26T23:21:58.7849522Z Parametrizations may be concatenated by registering several parametrizations 2025-08-26T23:21:58.7849585Z on the same attribute. 2025-08-26T23:21:58.7849588Z 2025-08-26T23:21:58.7849756Z The training mode of a registered parametrization is updated on registration 2025-08-26T23:21:58.7849835Z to match the training mode of the host module 2025-08-26T23:21:58.7849839Z 2025-08-26T23:21:58.7850014Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-08-26T23:21:58.7850089Z using the context manager :func:`cached`. 2025-08-26T23:21:58.7850117Z 2025-08-26T23:21:58.7850259Z A :attr:`parametrization` may optionally implement a method with signature 2025-08-26T23:21:58.7850264Z 2025-08-26T23:21:58.7850446Z .. code-block:: python 2025-08-26T23:21:58.7850449Z 2025-08-26T23:21:58.7850581Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-08-26T23:21:58.7850584Z 2025-08-26T23:21:58.7850733Z This method is called on the unparametrized tensor when the first parametrization 2025-08-26T23:21:58.7850854Z is registered to compute the initial value of the original tensor. 2025-08-26T23:21:58.7851028Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-08-26T23:21:58.7851033Z 2025-08-26T23:21:58.7851209Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-08-26T23:21:58.7851379Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-08-26T23:21:58.7851384Z 2025-08-26T23:21:58.7851513Z It is possible for the first parametrization to depend on several inputs. 2025-08-26T23:21:58.7851690Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-08-26T23:21:58.7851825Z (see the example implementation of a ``RankOne`` parametrization below). 2025-08-26T23:21:58.7851828Z 2025-08-26T23:21:58.7852014Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-08-26T23:21:58.7852091Z with names ``original0``, ``original1``,... 2025-08-26T23:21:58.7852094Z 2025-08-26T23:21:58.7852151Z .. note:: 2025-08-26T23:21:58.7852154Z 2025-08-26T23:21:58.7852307Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-08-26T23:21:58.7852400Z once to perform a number of consistency checks. 2025-08-26T23:21:58.7852558Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-08-26T23:21:58.7852629Z and nothing will be called otherwise. 2025-08-26T23:21:58.7852634Z 2025-08-26T23:21:58.7852688Z .. note:: 2025-08-26T23:21:58.7852691Z 2025-08-26T23:21:58.7852808Z In most situations, ``right_inverse`` will be a function such that 2025-08-26T23:21:58.7852878Z ``forward(right_inverse(X)) == X`` (see 2025-08-26T23:21:58.7853031Z `right inverse `_). 2025-08-26T23:21:58.7853163Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-08-26T23:21:58.7853221Z to relax this. 2025-08-26T23:21:58.7853226Z 2025-08-26T23:21:58.7853279Z .. warning:: 2025-08-26T23:21:58.7853283Z 2025-08-26T23:21:58.7853430Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-08-26T23:21:58.7853569Z will register a number of new parameters. If such parametrization is registered 2025-08-26T23:21:58.7853718Z after the optimizer is created, these new parameters will need to be added manually 2025-08-26T23:21:58.7853862Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-08-26T23:21:58.7853867Z 2025-08-26T23:21:58.7853922Z Args: 2025-08-26T23:21:58.7854045Z module (nn.Module): module on which to register the parametrization 2025-08-26T23:21:58.7854171Z tensor_name (str): name of the parameter or buffer on which to register 2025-08-26T23:21:58.7854240Z the parametrization 2025-08-26T23:21:58.7854360Z parametrization (nn.Module): the parametrization to register 2025-08-26T23:21:58.7854450Z Keyword args: 2025-08-26T23:21:58.7854572Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-08-26T23:21:58.7854689Z may change the dtype and shape of the tensor. Default: `False` 2025-08-26T23:21:58.7854841Z Warning: the parametrization is not checked for consistency upon registration. 2025-08-26T23:21:58.7856909Z Enable this flag at your own risk. 2025-08-26T23:21:58.7856914Z 2025-08-26T23:21:58.7856975Z Raises: 2025-08-26T23:21:58.7857139Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-08-26T23:21:58.7857142Z 2025-08-26T23:21:58.7857194Z Examples: 2025-08-26T23:21:58.7857284Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T23:21:58.7857340Z >>> import torch 2025-08-26T23:21:58.7857404Z >>> import torch.nn as nn 2025-08-26T23:21:58.7857483Z >>> import torch.nn.utils.parametrize as P 2025-08-26T23:21:58.7857536Z >>> 2025-08-26T23:21:58.7857599Z >>> class Symmetric(nn.Module): 2025-08-26T23:21:58.7857661Z >>> def forward(self, X): 2025-08-26T23:21:58.7857760Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-08-26T23:21:58.7857809Z >>> 2025-08-26T23:21:58.7857873Z >>> def right_inverse(self, A): 2025-08-26T23:21:58.7857935Z >>> return A.triu() 2025-08-26T23:21:58.7857983Z >>> 2025-08-26T23:21:58.7858042Z >>> m = nn.Linear(5, 5) 2025-08-26T23:21:58.7858171Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-08-26T23:21:58.7858304Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-08-26T23:21:58.7858354Z True 2025-08-26T23:21:58.7858413Z >>> A = torch.rand(5, 5) 2025-08-26T23:21:58.7858478Z >>> A = A + A.T # A is now symmetric 2025-08-26T23:21:58.7860102Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-08-26T23:21:58.7860181Z >>> print(torch.allclose(m.weight, A)) 2025-08-26T23:21:58.7860230Z True 2025-08-26T23:21:58.7860233Z 2025-08-26T23:21:58.7860296Z >>> class RankOne(nn.Module): 2025-08-26T23:21:58.7860456Z >>> def forward(self, x, y): 2025-08-26T23:21:58.7860540Z >>> # Form a rank 1 matrix multiplying two vectors 2025-08-26T23:21:58.7860623Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-08-26T23:21:58.7860673Z >>> 2025-08-26T23:21:58.7860739Z >>> def right_inverse(self, Z): 2025-08-26T23:21:58.7860809Z >>> # Project Z onto the rank 1 matrices 2025-08-26T23:21:58.7860894Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-08-26T23:21:58.7860963Z >>> # Return rescaled singular vectors 2025-08-26T23:21:58.7861033Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-08-26T23:21:58.7861120Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-08-26T23:21:58.7861168Z >>> 2025-08-26T23:21:58.7861251Z >>> linear_rank_one = P.register_parametrization( 2025-08-26T23:21:58.7861325Z ... nn.Linear(4, 4), "weight", RankOne() 2025-08-26T23:21:58.7861372Z ... ) 2025-08-26T23:21:58.7861484Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-08-26T23:21:58.7861533Z 1 2025-08-26T23:21:58.7861536Z 2025-08-26T23:21:58.7861584Z 2025-08-26T23:21:58.7861772Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7863055Z 2025-08-26T23:21:58.7893893Z msg = Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=14. 2025-08-26T23:21:58.7894015Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7894104Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-08-26T23:21:58.7894164Z 2025-08-26T23:21:58.7894266Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T23:21:58.7894362Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T23:21:58.7894453Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T23:21:58.7894602Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T23:21:58.7894606Z 2025-08-26T23:21:58.7894643Z .. note:: 2025-08-26T23:21:58.7894728Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-08-26T23:21:58.7894809Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-08-26T23:21:58.7894883Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T23:21:58.7894963Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T23:21:58.7895043Z One place we are confident in is that NHWC(channels_last) conversion for 2025-08-26T23:21:58.7895119Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-08-26T23:21:58.7895190Z even in cases where we have to apply permutation to input tensors. 2025-08-26T23:21:58.7895193Z 2025-08-26T23:21:58.7895271Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T23:21:58.7895318Z channels_last. This ensures that; 2025-08-26T23:21:58.7895414Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T23:21:58.7895498Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T23:21:58.7897163Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T23:21:58.7897219Z from memory_format conversion. 2025-08-26T23:21:58.7897222Z 2025-08-26T23:21:58.7897313Z The optimal case is that, layers between convolution layers are channels 2025-08-26T23:21:58.7897401Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T23:21:58.7897481Z encounters the first convolution layer and stay in that memory format. 2025-08-26T23:21:58.7897572Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T23:21:58.7897576Z 2025-08-26T23:21:58.7897652Z In case where a channels last incompatible layer is between convolution 2025-08-26T23:21:58.7897730Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T23:21:58.7897809Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T23:21:58.7897888Z contiguous format and be permuted to channels last when it encounters 2025-08-26T23:21:58.7897964Z another convolution layer. There's no point in propagating that 2025-08-26T23:21:58.7898039Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T23:21:58.7898081Z ``memory_format``. 2025-08-26T23:21:58.7898083Z 2025-08-26T23:21:58.7898161Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T23:21:58.7898239Z there might have been a better spot to fuse the permutation other than 2025-08-26T23:21:58.7898284Z immediately before a convolution. 2025-08-26T23:21:58.7898288Z 2025-08-26T23:21:58.7898321Z Args: 2025-08-26T23:21:58.7898397Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-08-26T23:21:58.7898473Z ``nn.Module`` 2025-08-26T23:21:58.7898531Z memory_format: user specified ``memory_format``, 2025-08-26T23:21:58.7899948Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T23:21:58.7899951Z 2025-08-26T23:21:58.7899989Z Returns: 2025-08-26T23:21:58.7900054Z The original module with updated ``nn.Conv2d`` 2025-08-26T23:21:58.7900057Z 2025-08-26T23:21:58.7900089Z Example: 2025-08-26T23:21:58.7900170Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:58.7900235Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T23:21:58.7900279Z >>> input = torch.randint( 2025-08-26T23:21:58.7900428Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T23:21:58.7900503Z ... ) 2025-08-26T23:21:58.7900544Z >>> model = nn.Sequential( 2025-08-26T23:21:58.7900591Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-08-26T23:21:58.7900634Z >>> # This is identical to: 2025-08-26T23:21:58.7900723Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-08-26T23:21:58.7900785Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-08-26T23:21:58.7900829Z ... model, torch.channels_last 2025-08-26T23:21:58.7900860Z ... ) 2025-08-26T23:21:58.7900900Z >>> out = model(input) 2025-08-26T23:21:58.7900932Z 2025-08-26T23:21:58.7901025Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7901027Z 2025-08-26T23:21:58.7901253Z msg = Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=93. 2025-08-26T23:21:58.7901344Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7901423Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-08-26T23:21:58.7903077Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T23:21:58.7903181Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T23:21:58.7903273Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T23:21:58.7903381Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T23:21:58.7903387Z 2025-08-26T23:21:58.7903422Z .. note:: 2025-08-26T23:21:58.7903511Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-08-26T23:21:58.7903590Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-08-26T23:21:58.7903663Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T23:21:58.7903744Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T23:21:58.7903828Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-08-26T23:21:58.7903905Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-08-26T23:21:58.7903977Z even in cases where we have to apply permutation to input tensors. 2025-08-26T23:21:58.7903979Z 2025-08-26T23:21:58.7904056Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T23:21:58.7904104Z channels_last_3d. This ensures that; 2025-08-26T23:21:58.7904181Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T23:21:58.7904262Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T23:21:58.7904343Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T23:21:58.7904387Z from memory_format conversion. 2025-08-26T23:21:58.7904391Z 2025-08-26T23:21:58.7904469Z The optimal case is that, layers between convolution layers are channels 2025-08-26T23:21:58.7904575Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T23:21:58.7904653Z encounters the first convolution layer and stay in that memory format. 2025-08-26T23:21:58.7905721Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T23:21:58.7905723Z 2025-08-26T23:21:58.7905805Z In case where a channels last incompatible layer is between convolution 2025-08-26T23:21:58.7905906Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T23:21:58.7905985Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T23:21:58.7906062Z contiguous format and be permuted to channels last when it encounters 2025-08-26T23:21:58.7906137Z another convolution layer. There's no point in propagating that 2025-08-26T23:21:58.7906228Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T23:21:58.7906271Z ``memory_format``. 2025-08-26T23:21:58.7906274Z 2025-08-26T23:21:58.7906352Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T23:21:58.7906430Z there might have been a better spot to fuse the permutation other than 2025-08-26T23:21:58.7906475Z immediately before a convolution. 2025-08-26T23:21:58.7906477Z 2025-08-26T23:21:58.7906509Z Args: 2025-08-26T23:21:58.7906587Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-08-26T23:21:58.7906627Z ``nn.Module`` 2025-08-26T23:21:58.7906686Z memory_format: user specified ``memory_format``, 2025-08-26T23:21:58.7906752Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T23:21:58.7906756Z 2025-08-26T23:21:58.7906788Z Returns: 2025-08-26T23:21:58.7906843Z The original module with updated ``nn.Conv3d`` 2025-08-26T23:21:58.7906847Z 2025-08-26T23:21:58.7906880Z Example: 2025-08-26T23:21:58.7906949Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:21:58.7907009Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T23:21:58.7907966Z >>> input = torch.randint( 2025-08-26T23:21:58.7908027Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T23:21:58.7908059Z ... ) 2025-08-26T23:21:58.7908100Z >>> model = nn.Sequential( 2025-08-26T23:21:58.7908146Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-08-26T23:21:58.7908188Z >>> # This is identical to: 2025-08-26T23:21:58.7908278Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-08-26T23:21:58.7908342Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-08-26T23:21:58.7908387Z ... model, torch.channels_last_3d 2025-08-26T23:21:58.7908421Z ... ) 2025-08-26T23:21:58.7908461Z >>> out = model(input) 2025-08-26T23:21:58.7908493Z 2025-08-26T23:21:58.7908583Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7908585Z 2025-08-26T23:21:58.7919475Z msg = Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py line=350. 2025-08-26T23:21:58.7919593Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7919659Z Pad a packed batch of variable length sequences. 2025-08-26T23:21:58.7919664Z 2025-08-26T23:21:58.7919731Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-08-26T23:21:58.7919733Z 2025-08-26T23:21:58.7919834Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-08-26T23:21:58.7919926Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-08-26T23:21:58.7919972Z sequence and ``B`` is the batch size. 2025-08-26T23:21:58.7920020Z 2025-08-26T23:21:58.7921780Z Example: 2025-08-26T23:21:58.7921885Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-08-26T23:21:58.7921948Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-08-26T23:21:58.7921987Z >>> lens = [2, 1, 3] 2025-08-26T23:21:58.7922033Z >>> packed = pack_padded_sequence( 2025-08-26T23:21:58.7922092Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-08-26T23:21:58.7922165Z ... ) 2025-08-26T23:21:58.7922201Z >>> packed 2025-08-26T23:21:58.7922289Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-08-26T23:21:58.7922370Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-08-26T23:21:58.7922458Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-08-26T23:21:58.7922522Z >>> seq_unpacked 2025-08-26T23:21:58.7922565Z tensor([[1, 2, 0], 2025-08-26T23:21:58.7922612Z [3, 0, 0], 2025-08-26T23:21:58.7922649Z [4, 5, 6]]) 2025-08-26T23:21:58.7922692Z >>> lens_unpacked 2025-08-26T23:21:58.7922728Z tensor([2, 1, 3]) 2025-08-26T23:21:58.7922730Z 2025-08-26T23:21:58.7922764Z .. note:: 2025-08-26T23:21:58.7922822Z :attr:`total_length` is useful to implement the 2025-08-26T23:21:58.7922906Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-08-26T23:21:58.7922988Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-08-26T23:21:58.7923075Z See :ref:`this FAQ section ` for 2025-08-26T23:21:58.7924188Z details. 2025-08-26T23:21:58.7924190Z 2025-08-26T23:21:58.7924226Z Args: 2025-08-26T23:21:58.7924279Z sequence (PackedSequence): batch to pad 2025-08-26T23:21:58.7924367Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-08-26T23:21:58.7924413Z format, ``T x B x *`` otherwise. 2025-08-26T23:21:58.7924511Z padding_value (float, optional): values for padded elements. 2025-08-26T23:21:58.7924595Z total_length (int, optional): if not ``None``, the output will be padded to 2025-08-26T23:21:58.7924680Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-08-26T23:21:58.7924748Z if :attr:`total_length` is less than the max sequence length in 2025-08-26T23:21:58.7924790Z :attr:`sequence`. 2025-08-26T23:21:58.7924792Z 2025-08-26T23:21:58.7924824Z Returns: 2025-08-26T23:21:58.7924895Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-08-26T23:21:58.7924967Z containing the list of lengths of each sequence in the batch. 2025-08-26T23:21:58.7925046Z Batch elements will be re-ordered as they were ordered originally when 2025-08-26T23:21:58.7925124Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-08-26T23:21:58.7925156Z 2025-08-26T23:21:58.7925245Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7925247Z 2025-08-26T23:21:58.7978706Z msg = Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=979. 2025-08-26T23:21:58.7978829Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7978943Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-08-26T23:21:58.7978945Z 2025-08-26T23:21:58.7980536Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-08-26T23:21:58.7980632Z by removing the specified ``amount`` of (currently unpruned) channels 2025-08-26T23:21:58.7980699Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-08-26T23:21:58.7980774Z Modifies module in place (and also return the modified module) 2025-08-26T23:21:58.7980879Z by: 2025-08-26T23:21:58.7980881Z 2025-08-26T23:21:58.7980958Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:21:58.7981037Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:21:58.7981120Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:21:58.7981201Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:21:58.7981272Z ``name+'_orig'``. 2025-08-26T23:21:58.7981275Z 2025-08-26T23:21:58.7981311Z Args: 2025-08-26T23:21:58.7981379Z module (nn.Module): module containing the tensor to prune 2025-08-26T23:21:58.7981448Z name (str): parameter name within ``module`` on which pruning 2025-08-26T23:21:58.7981486Z will act. 2025-08-26T23:21:58.7981549Z amount (int or float): quantity of parameters to prune. 2025-08-26T23:21:58.7981642Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T23:21:58.7981717Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T23:21:58.7981774Z absolute number of parameters to prune. 2025-08-26T23:21:58.7981843Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-08-26T23:21:58.7981903Z entries for argument ``p`` in :func:`torch.norm`. 2025-08-26T23:21:58.7983203Z dim (int): index of the dim along which we define channels to prune. 2025-08-26T23:21:58.7983305Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-08-26T23:21:58.7983373Z shape as module parameter) used to compute mask for pruning. 2025-08-26T23:21:58.7983458Z The values in this tensor indicate the importance of the corresponding 2025-08-26T23:21:58.7983507Z elements in the parameter being pruned. 2025-08-26T23:21:58.7983595Z If unspecified or None, the module parameter will be used in its place. 2025-08-26T23:21:58.7983600Z 2025-08-26T23:21:58.7983635Z Returns: 2025-08-26T23:21:58.7983745Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T23:21:58.7983747Z 2025-08-26T23:21:58.7983800Z Examples: 2025-08-26T23:21:58.7983848Z >>> from torch.nn.utils import prune 2025-08-26T23:21:58.7983891Z >>> m = prune.ln_structured( 2025-08-26T23:21:58.7983960Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-08-26T23:21:58.7983996Z ... ) 2025-08-26T23:21:58.7984027Z 2025-08-26T23:21:58.7984116Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7984118Z 2025-08-26T23:21:58.7984303Z msg = Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1026. 2025-08-26T23:21:58.7984394Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7984397Z 2025-08-26T23:21:58.7984549Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-08-26T23:21:58.7984551Z 2025-08-26T23:21:58.7984595Z Modifies modules in place by: 2025-08-26T23:21:58.7984598Z 2025-08-26T23:21:58.7984674Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:21:58.7985838Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:21:58.7985924Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:21:58.7986002Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:21:58.7986037Z ``name+'_orig'``. 2025-08-26T23:21:58.7986040Z 2025-08-26T23:21:58.7986070Z Args: 2025-08-26T23:21:58.7986145Z parameters (Iterable of (module, name) tuples): parameters of 2025-08-26T23:21:58.7986215Z the model to prune in a global fashion, i.e. by aggregating all 2025-08-26T23:21:58.7986314Z weights prior to deciding which ones to prune. module must be of 2025-08-26T23:21:58.7986373Z type :class:`nn.Module`, and name must be a string. 2025-08-26T23:21:58.7986453Z pruning_method (function): a valid pruning function from this module, 2025-08-26T23:21:58.7986517Z or a custom one implemented by the user that satisfies the 2025-08-26T23:21:58.7986597Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-08-26T23:21:58.7986702Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-08-26T23:21:58.7986781Z the corresponding parameter's importance scores tensor. The tensor 2025-08-26T23:21:58.7986853Z should be the same shape as the parameter, and is used for computing 2025-08-26T23:21:58.7986893Z mask for pruning. 2025-08-26T23:21:58.7986965Z If unspecified or None, the parameter will be used in place of its 2025-08-26T23:21:58.7987020Z importance scores. 2025-08-26T23:21:58.7987069Z kwargs: other keyword arguments such as: 2025-08-26T23:21:58.7987142Z amount (int or float): quantity of parameters to prune across the 2025-08-26T23:21:58.7987183Z specified parameters. 2025-08-26T23:21:58.7987247Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T23:21:58.7988276Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T23:21:58.7988331Z absolute number of parameters to prune. 2025-08-26T23:21:58.7988333Z 2025-08-26T23:21:58.7988366Z Raises: 2025-08-26T23:21:58.7988426Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-08-26T23:21:58.7988428Z 2025-08-26T23:21:58.7988458Z Note: 2025-08-26T23:21:58.7988536Z Since global structured pruning doesn't make much sense unless the 2025-08-26T23:21:58.7988607Z norm is normalized by the size of the parameter, we now limit the 2025-08-26T23:21:58.7988666Z scope of global pruning to unstructured methods. 2025-08-26T23:21:58.7988668Z 2025-08-26T23:21:58.7988703Z Examples: 2025-08-26T23:21:58.7988769Z >>> from torch.nn.utils import prune 2025-08-26T23:21:58.7988815Z >>> from collections import OrderedDict 2025-08-26T23:21:58.7988857Z >>> net = nn.Sequential( 2025-08-26T23:21:58.7988893Z ... OrderedDict( 2025-08-26T23:21:58.7988926Z ... [ 2025-08-26T23:21:58.7988972Z ... ("first", nn.Linear(10, 4)), 2025-08-26T23:21:58.7989017Z ... ("second", nn.Linear(4, 1)), 2025-08-26T23:21:58.7989049Z ... ] 2025-08-26T23:21:58.7989081Z ... ) 2025-08-26T23:21:58.7989113Z ... ) 2025-08-26T23:21:58.7989154Z >>> parameters_to_prune = ( 2025-08-26T23:21:58.7989196Z ... (net.first, "weight"), 2025-08-26T23:21:58.7989236Z ... (net.second, "weight"), 2025-08-26T23:21:58.7990204Z ... ) 2025-08-26T23:21:58.7990248Z >>> prune.global_unstructured( 2025-08-26T23:21:58.7990291Z ... parameters_to_prune, 2025-08-26T23:21:58.7990440Z ... pruning_method=prune.L1Unstructured, 2025-08-26T23:21:58.7990492Z ... amount=10, 2025-08-26T23:21:58.7990525Z ... ) 2025-08-26T23:21:58.7990607Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-08-26T23:21:58.7990639Z tensor(10) 2025-08-26T23:21:58.7990642Z 2025-08-26T23:21:58.7990644Z 2025-08-26T23:21:58.7990734Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7990736Z 2025-08-26T23:21:58.7990913Z msg = Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1149. 2025-08-26T23:21:58.7991005Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:21:58.7991141Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-08-26T23:21:58.7991144Z 2025-08-26T23:21:58.7991221Z Modifies module in place (and also return the modified module) by: 2025-08-26T23:21:58.7991259Z 2025-08-26T23:21:58.7991333Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:21:58.7991409Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:21:58.7991485Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:21:58.7991560Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:21:58.7991596Z ``name+'_orig'``. 2025-08-26T23:21:58.7991599Z 2025-08-26T23:21:58.7991649Z Args: 2025-08-26T23:21:58.7991716Z module (nn.Module): module containing the tensor to prune 2025-08-26T23:21:58.7991783Z name (str): parameter name within ``module`` on which pruning 2025-08-26T23:21:58.7992767Z will act. 2025-08-26T23:21:58.7992838Z mask (Tensor): binary mask to be applied to the parameter. 2025-08-26T23:21:58.7992866Z 2025-08-26T23:21:58.7992898Z Returns: 2025-08-26T23:21:58.7992976Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T23:21:58.7992981Z 2025-08-26T23:21:58.7993015Z Examples: 2025-08-26T23:21:58.7993062Z >>> from torch.nn.utils import prune 2025-08-26T23:21:58.7993104Z >>> m = prune.custom_from_mask( 2025-08-26T23:21:58.7993169Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-08-26T23:21:58.7993200Z ... ) 2025-08-26T23:21:58.7993242Z >>> print(m.bias_mask) 2025-08-26T23:21:58.7993279Z tensor([0., 1., 0.]) 2025-08-26T23:21:58.7993283Z 2025-08-26T23:21:58.7993313Z 2025-08-26T23:21:58.7993401Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:21:58.7993403Z 2025-08-26T23:21:58.8132557Z gathering tests 2025-08-26T23:21:58.8139603Z running 731 test(s) 2025-08-26T23:21:58.8147249Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::typename:0, line 1082 <- wrt source file 2025-08-26T23:21:58.8152387Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::typename:0 2025-08-26T23:21:58.8152641Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::is_tensor:0, line 1118 <- wrt source file 2025-08-26T23:21:58.8154347Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::is_tensor:0 2025-08-26T23:21:58.8154707Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_device:0, line 1203 <- wrt source file 2025-08-26T23:21:58.8156819Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_device:0 2025-08-26T23:21:58.8157299Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1252 <- wrt source file 2025-08-26T23:21:58.8157530Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_tensor_type:0 2025-08-26T23:21:58.8157771Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_dtype:0, line 1289 <- wrt source file 2025-08-26T23:21:58.8157972Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::set_default_dtype:0 2025-08-26T23:21:58.8158230Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1444 <- wrt source file 2025-08-26T23:21:58.8158444Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::use_deterministic_algorithms:0 2025-08-26T23:21:58.8158660Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::compile:0, line 2567 <- wrt source file 2025-08-26T23:21:58.8158842Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::compile:0 2025-08-26T23:21:58.8159173Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2840 <- wrt source file 2025-08-26T23:21:58.8159402Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0 2025-08-26T23:21:58.8159652Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file 2025-08-26T23:21:58.8159841Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::custom_op:0 2025-08-26T23:21:58.8160058Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file 2025-08-26T23:21:58.8160257Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::impl:0 2025-08-26T23:21:58.8160587Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file 2025-08-26T23:21:58.8437213Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_custom_ops.py::impl_abstract:0 2025-08-26T23:21:58.8437515Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_C.cpython-312-x86_64-linux-gnu.so::Generator:0, line 15 <- wrt source file 2025-08-26T23:21:58.8437751Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_C.cpython-312-x86_64-linux-gnu.so::Generator:0 2025-08-26T23:21:58.8438020Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_C.cpython-312-x86_64-linux-gnu.so::_LinAlgError:0, line 5 <- wrt source file 2025-08-26T23:21:58.8440194Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_C.cpython-312-x86_64-linux-gnu.so::_LinAlgError:0 2025-08-26T23:21:58.8440647Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file 2025-08-26T23:21:58.8440843Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/quasirandom.py::SobolEngine:0 2025-08-26T23:21:58.8441050Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py::list:0, line 473 <- wrt source file 2025-08-26T23:21:58.8441223Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py::list:0 2025-08-26T23:21:58.8441425Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py::help:0, line 533 <- wrt source file 2025-08-26T23:21:58.8441587Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py::help:0 2025-08-26T23:21:58.8441824Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file 2025-08-26T23:21:58.8465230Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor_str.py::set_printoptions:0 2025-08-26T23:21:58.8465475Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 649 <- wrt source file 2025-08-26T23:21:58.8470655Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_hook:0 2025-08-26T23:21:58.8470936Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 706 <- wrt source file 2025-08-26T23:21:58.8475176Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0 2025-08-26T23:21:58.8475425Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1333 <- wrt source file 2025-08-26T23:21:58.8517219Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.refine_names:0 2025-08-26T23:21:58.8517468Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1378 <- wrt source file 2025-08-26T23:21:58.8518691Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.align_to:0 2025-08-26T23:21:58.8518985Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.rename:0, line 1451 <- wrt source file 2025-08-26T23:21:58.8520650Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.rename:0 2025-08-26T23:21:58.8520901Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1481 <- wrt source file 2025-08-26T23:21:58.8525487Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0 2025-08-26T23:21:58.8525756Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file 2025-08-26T23:21:58.8526664Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::broadcast_tensors:0 2025-08-26T23:21:58.8526908Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file 2025-08-26T23:21:58.8528038Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::broadcast_shapes:0 2025-08-26T23:21:58.8528262Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::split:0, line 144 <- wrt source file 2025-08-26T23:21:58.8532920Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::split:0 2025-08-26T23:21:58.8533154Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::einsum:0, line 258 <- wrt source file 2025-08-26T23:21:58.8540308Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::einsum:0 2025-08-26T23:21:58.8540679Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 992 <- wrt source file 2025-08-26T23:21:58.8545306Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::_unique_consecutive_impl:0 2025-08-26T23:21:58.8545537Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::tensordot:0, line 1267 <- wrt source file 2025-08-26T23:21:58.8551224Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::tensordot:0 2025-08-26T23:21:58.8551475Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::cartesian_prod:0, line 1351 <- wrt source file 2025-08-26T23:21:58.8554935Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::cartesian_prod:0 2025-08-26T23:21:58.8555178Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::block_diag:0, line 1385 <- wrt source file 2025-08-26T23:21:58.8558991Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::block_diag:0 2025-08-26T23:21:58.8559223Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::cdist:0, line 1441 <- wrt source file 2025-08-26T23:21:58.8564404Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::cdist:0 2025-08-26T23:21:58.8564681Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_1d:0, line 1482 <- wrt source file 2025-08-26T23:21:58.8574582Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_1d:0 2025-08-26T23:21:58.8574827Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_2d:0, line 1520 <- wrt source file 2025-08-26T23:21:58.8576091Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_2d:0 2025-08-26T23:21:58.8576324Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_3d:0, line 1560 <- wrt source file 2025-08-26T23:21:58.8582692Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::atleast_3d:0 2025-08-26T23:21:58.8582946Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::norm:0, line 1735 <- wrt source file 2025-08-26T23:21:58.8593306Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::norm:0 2025-08-26T23:21:58.8593548Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::unravel_index:0, line 1903 <- wrt source file 2025-08-26T23:21:58.8603712Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::unravel_index:0 2025-08-26T23:21:58.8604155Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::chain_matmul:0, line 2003 <- wrt source file 2025-08-26T23:21:58.8604493Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::chain_matmul:0 2025-08-26T23:21:58.8604787Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::_lu_impl:0, line 2104 <- wrt source file 2025-08-26T23:21:58.8605132Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py::_lu_impl:0 2025-08-26T23:21:58.8605417Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::add_safe_globals:0, line 299 <- wrt source file 2025-08-26T23:21:58.8605651Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::add_safe_globals:0 2025-08-26T23:21:58.8605995Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::safe_globals:0, line 324 <- wrt source file 2025-08-26T23:21:58.8606322Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::safe_globals:0 2025-08-26T23:21:58.8606579Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::skip_data:0, line 400 <- wrt source file 2025-08-26T23:21:58.8606795Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::skip_data:0 2025-08-26T23:21:58.8609871Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::register_package:0, line 472 <- wrt source file 2025-08-26T23:21:58.8610126Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::register_package:0 2025-08-26T23:21:58.8610488Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::save:0, line 950 <- wrt source file 2025-08-26T23:21:58.8610775Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py::save:0 2025-08-26T23:21:58.8611029Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library.define:0, line 153 <- wrt source file 2025-08-26T23:21:58.8611221Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library.define:0 2025-08-26T23:21:58.8611540Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 247 <- wrt source file 2025-08-26T23:21:58.8615453Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library._impl_with_aoti_compile:0 2025-08-26T23:21:58.8615926Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library.impl:0, line 307 <- wrt source file 2025-08-26T23:21:58.8617440Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::Library.impl:0 2025-08-26T23:21:58.8618010Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::define:0, line 512 <- wrt source file 2025-08-26T23:21:58.8624456Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::define:0 2025-08-26T23:21:58.8626998Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::impl:0, line 618 <- wrt source file 2025-08-26T23:21:58.8631625Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::impl:0 2025-08-26T23:21:58.8632100Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_kernel:0, line 799 <- wrt source file 2025-08-26T23:21:58.8632499Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_kernel:0 2025-08-26T23:21:58.8632886Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_autocast:0, line 867 <- wrt source file 2025-08-26T23:21:58.8633482Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_autocast:0 2025-08-26T23:21:58.8634109Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_torch_dispatch:0, line 1232 <- wrt source file 2025-08-26T23:21:58.8668414Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_torch_dispatch:0 2025-08-26T23:21:58.8668809Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_vmap:0, line 1321 <- wrt source file 2025-08-26T23:21:58.8737533Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py::register_vmap:0 2025-08-26T23:21:58.8737937Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::get_ignored_functions:0, line 116 <- wrt source file 2025-08-26T23:21:58.8740940Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::get_ignored_functions:0 2025-08-26T23:21:58.8741360Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::get_testing_overrides:0, line 422 <- wrt source file 2025-08-26T23:21:58.8757725Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::get_testing_overrides:0 2025-08-26T23:21:58.8758152Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::wrap_torch_function:0, line 1577 <- wrt source file 2025-08-26T23:21:58.8759186Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::wrap_torch_function:0 2025-08-26T23:21:58.8759603Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::handle_torch_function:0, line 1712 <- wrt source file 2025-08-26T23:21:58.8760509Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::handle_torch_function:0 2025-08-26T23:21:58.8761052Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1960 <- wrt source file 2025-08-26T23:21:58.8772757Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::is_tensor_method_or_property:0 2025-08-26T23:21:58.8773183Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::is_tensor_like:0, line 1979 <- wrt source file 2025-08-26T23:21:58.8778230Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/overrides.py::is_tensor_like:0 2025-08-26T23:21:58.8778741Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file 2025-08-26T23:21:58.8779190Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_namedtensor_internals.py::update_names:0 2025-08-26T23:21:58.8779602Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file 2025-08-26T23:21:58.8780033Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/torch_version.py::TorchVersion:0 2025-08-26T23:21:58.8780631Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0, line 475 <- wrt source file 2025-08-26T23:21:58.8783001Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0 2025-08-26T23:21:58.8783675Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1760 <- wrt source file 2025-08-26T23:21:58.8784322Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/__init__.py::_compile_kernel:0 2025-08-26T23:21:58.8784706Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::save:0, line 345 <- wrt source file 2025-08-26T23:21:58.8785130Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::save:0 2025-08-26T23:21:58.8787035Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::load:0, line 415 <- wrt source file 2025-08-26T23:21:58.8787418Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::load:0 2025-08-26T23:21:58.8787817Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::register_dataclass:0, line 572 <- wrt source file 2025-08-26T23:21:58.8788246Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/__init__.py::register_dataclass:0 2025-08-26T23:21:58.8788658Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::as_nested_tensor:0, line 61 <- wrt source file 2025-08-26T23:21:58.9019320Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::as_nested_tensor:0 2025-08-26T23:21:58.9020065Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor:0, line 240 <- wrt source file 2025-08-26T23:21:58.9126334Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor:0 2025-08-26T23:21:58.9126860Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::narrow:0, line 315 <- wrt source file 2025-08-26T23:21:58.9178329Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::narrow:0 2025-08-26T23:21:58.9183597Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0, line 405 <- wrt source file 2025-08-26T23:21:58.9190872Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0 2025-08-26T23:21:58.9191653Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::masked_select:0, line 481 <- wrt source file 2025-08-26T23:21:58.9205358Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py::masked_select:0 2025-08-26T23:21:58.9206016Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 125 <- wrt source file 2025-08-26T23:21:58.9206461Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::allow_in_graph:0 2025-08-26T23:21:58.9206901Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 181 <- wrt source file 2025-08-26T23:21:59.4342313Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::substitute_in_graph:0 2025-08-26T23:21:59.4342902Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 411 <- wrt source file 2025-08-26T23:21:59.4348775Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::wrap_numpy:0 2025-08-26T23:21:59.4349238Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_compiling:0, line 443 <- wrt source file 2025-08-26T23:21:59.4349699Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_compiling:0 2025-08-26T23:21:59.4350153Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0, line 464 <- wrt source file 2025-08-26T23:21:59.4350703Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0 2025-08-26T23:21:59.4351371Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_exporting:0, line 482 <- wrt source file 2025-08-26T23:21:59.4351810Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::is_exporting:0 2025-08-26T23:21:59.4352243Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 497 <- wrt source file 2025-08-26T23:21:59.4352686Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0 2025-08-26T23:21:59.4353123Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 512 <- wrt source file 2025-08-26T23:21:59.4353570Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0 2025-08-26T23:21:59.4353977Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/__init__.py::annotate:0, line 147 <- wrt source file 2025-08-26T23:21:59.4354369Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/__init__.py::annotate:0 2025-08-26T23:21:59.4354890Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 197 <- wrt source file 2025-08-26T23:21:59.4355350Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::Future.add_done_callback:0 2025-08-26T23:21:59.4355796Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 261 <- wrt source file 2025-08-26T23:21:59.4356250Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::Future.set_exception:0 2025-08-26T23:21:59.4356737Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::collect_all:0, line 295 <- wrt source file 2025-08-26T23:21:59.4357155Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py::collect_all:0 2025-08-26T23:21:59.4357631Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0, line 22 <- wrt source file 2025-08-26T23:21:59.4358103Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0 2025-08-26T23:21:59.4358556Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 113 <- wrt source file 2025-08-26T23:21:59.5693103Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py::current_accelerator:0 2025-08-26T23:21:59.5693675Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py::device_index:0, line 249 <- wrt source file 2025-08-26T23:21:59.5694134Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py::device_index:0 2025-08-26T23:21:59.5694586Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 320 <- wrt source file 2025-08-26T23:21:59.5695152Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_mode_options:0 2025-08-26T23:21:59.5695587Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_options:0, line 357 <- wrt source file 2025-08-26T23:21:59.5700673Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_options:0 2025-08-26T23:21:59.5701301Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/aot_autograd.py::aot_function:0, line 768 <- wrt source file 2025-08-26T23:21:59.5855748Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/aot_autograd.py::aot_function:0 2025-08-26T23:21:59.5856238Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0, line 184 <- wrt source file 2025-08-26T23:21:59.5856728Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0 2025-08-26T23:21:59.5857176Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::vjp:0, line 233 <- wrt source file 2025-08-26T23:21:59.5874788Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::vjp:0 2025-08-26T23:21:59.5875242Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacrev:0, line 475 <- wrt source file 2025-08-26T23:21:59.5907614Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacrev:0 2025-08-26T23:21:59.5908115Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jvp:0, line 1023 <- wrt source file 2025-08-26T23:21:59.6320798Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jvp:0 2025-08-26T23:21:59.6321280Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0, line 1181 <- wrt source file 2025-08-26T23:21:59.6348144Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0 2025-08-26T23:21:59.6348617Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::hessian:0, line 1341 <- wrt source file 2025-08-26T23:21:59.6356289Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::hessian:0 2025-08-26T23:21:59.6356847Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1505 <- wrt source file 2025-08-26T23:21:59.6357323Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::functionalize:0 2025-08-26T23:21:59.6357777Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1704 <- wrt source file 2025-08-26T23:21:59.6442429Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::linearize:0 2025-08-26T23:21:59.6442938Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file 2025-08-26T23:21:59.6443442Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/functional_call.py::functional_call:0 2025-08-26T23:21:59.6443887Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file 2025-08-26T23:21:59.6444319Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/fx_minifier.py::minifier:0 2025-08-26T23:21:59.6444798Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1131 <- wrt source file 2025-08-26T23:21:59.6445435Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0 2025-08-26T23:21:59.6445948Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0, line 1186 <- wrt source file 2025-08-26T23:21:59.6446473Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0 2025-08-26T23:21:59.6446945Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file 2025-08-26T23:21:59.6447394Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_args:0 2025-08-26T23:21:59.6448100Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file 2025-08-26T23:21:59.6451307Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0 2025-08-26T23:21:59.6451815Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 176 <- wrt source file 2025-08-26T23:21:59.6452282Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0 2025-08-26T23:21:59.6452745Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 31 <- wrt source file 2025-08-26T23:21:59.6453406Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0 2025-08-26T23:21:59.6454250Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 76 <- wrt source file 2025-08-26T23:21:59.6455038Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0 2025-08-26T23:21:59.6455686Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 130 <- wrt source file 2025-08-26T23:21:59.6456178Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0 2025-08-26T23:21:59.6456672Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 163 <- wrt source file 2025-08-26T23:21:59.6457229Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0 2025-08-26T23:21:59.6459395Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file 2025-08-26T23:21:59.6459837Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0 2025-08-26T23:21:59.6460292Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file 2025-08-26T23:21:59.6460839Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0 2025-08-26T23:21:59.6461286Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file 2025-08-26T23:21:59.6461801Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0 2025-08-26T23:21:59.6462243Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file 2025-08-26T23:21:59.6462686Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0 2025-08-26T23:21:59.6463144Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file 2025-08-26T23:21:59.6463631Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0 2025-08-26T23:21:59.6465559Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file 2025-08-26T23:21:59.6466100Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0 2025-08-26T23:21:59.6466582Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 172 <- wrt source file 2025-08-26T23:21:59.6467038Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0 2025-08-26T23:21:59.6467483Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 544 <- wrt source file 2025-08-26T23:21:59.6467939Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0 2025-08-26T23:21:59.6468397Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 566 <- wrt source file 2025-08-26T23:21:59.6468890Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0 2025-08-26T23:21:59.6469336Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 580 <- wrt source file 2025-08-26T23:21:59.6469814Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0 2025-08-26T23:21:59.6470258Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 602 <- wrt source file 2025-08-26T23:21:59.6470794Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0 2025-08-26T23:21:59.6471265Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 729 <- wrt source file 2025-08-26T23:21:59.6471718Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0 2025-08-26T23:21:59.6472182Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file 2025-08-26T23:21:59.6472657Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0 2025-08-26T23:21:59.6473126Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file 2025-08-26T23:21:59.6473613Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0 2025-08-26T23:21:59.6474100Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file 2025-08-26T23:21:59.6476984Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0 2025-08-26T23:21:59.6477575Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file 2025-08-26T23:21:59.6478415Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0 2025-08-26T23:21:59.6478930Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0, line 188 <- wrt source file 2025-08-26T23:21:59.6479445Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0 2025-08-26T23:21:59.6480162Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0, line 102 <- wrt source file 2025-08-26T23:21:59.6480851Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0 2025-08-26T23:21:59.6481499Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0, line 148 <- wrt source file 2025-08-26T23:21:59.6482144Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0 2025-08-26T23:21:59.6482822Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0, line 436 <- wrt source file 2025-08-26T23:21:59.6484981Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0 2025-08-26T23:21:59.6485676Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file 2025-08-26T23:21:59.6510308Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0 2025-08-26T23:21:59.6510948Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file 2025-08-26T23:21:59.6511788Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0 2025-08-26T23:21:59.6512633Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file 2025-08-26T23:21:59.6513330Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0 2025-08-26T23:21:59.6513874Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 30 <- wrt source file 2025-08-26T23:21:59.6992808Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0 2025-08-26T23:21:59.7012120Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file 2025-08-26T23:21:59.8744247Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0 2025-08-26T23:21:59.8745613Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 30 <- wrt source file 2025-08-26T23:21:59.8746417Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0 2025-08-26T23:21:59.8747224Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file 2025-08-26T23:21:59.8748067Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0 2025-08-26T23:21:59.8774103Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file 2025-08-26T23:21:59.8775093Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0 2025-08-26T23:21:59.8775918Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file 2025-08-26T23:21:59.8782954Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0 2025-08-26T23:21:59.8783791Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file 2025-08-26T23:21:59.8784608Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0 2025-08-26T23:21:59.8785548Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 211 <- wrt source file 2025-08-26T23:21:59.8786225Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0 2025-08-26T23:21:59.8787129Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0, line 283 <- wrt source file 2025-08-26T23:21:59.8787795Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0 2025-08-26T23:21:59.8788442Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 359 <- wrt source file 2025-08-26T23:21:59.8789185Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0 2025-08-26T23:21:59.8789845Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file 2025-08-26T23:21:59.8790630Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0 2025-08-26T23:21:59.8791324Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file 2025-08-26T23:21:59.8792042Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0 2025-08-26T23:21:59.8792737Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 515 <- wrt source file 2025-08-26T23:21:59.8793442Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0 2025-08-26T23:21:59.8794204Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 801 <- wrt source file 2025-08-26T23:21:59.8794994Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0 2025-08-26T23:21:59.8795696Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1206 <- wrt source file 2025-08-26T23:21:59.8796416Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0 2025-08-26T23:21:59.8797126Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1273 <- wrt source file 2025-08-26T23:21:59.8797858Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0 2025-08-26T23:21:59.8798563Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1326 <- wrt source file 2025-08-26T23:21:59.8799281Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0 2025-08-26T23:21:59.8799989Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file 2025-08-26T23:21:59.8800793Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0 2025-08-26T23:21:59.8803403Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file 2025-08-26T23:21:59.8804191Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0 2025-08-26T23:21:59.8804891Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 124 <- wrt source file 2025-08-26T23:21:59.8805642Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0 2025-08-26T23:21:59.8806338Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 209 <- wrt source file 2025-08-26T23:21:59.8807049Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0 2025-08-26T23:21:59.8807803Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 296 <- wrt source file 2025-08-26T23:21:59.8808577Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0 2025-08-26T23:21:59.8809328Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 378 <- wrt source file 2025-08-26T23:21:59.8810096Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0 2025-08-26T23:21:59.8810916Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 460 <- wrt source file 2025-08-26T23:21:59.8813184Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0 2025-08-26T23:21:59.8813927Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file 2025-08-26T23:21:59.8814606Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0 2025-08-26T23:21:59.8815291Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file 2025-08-26T23:21:59.9116092Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0 2025-08-26T23:21:59.9116853Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file 2025-08-26T23:21:59.9393357Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0 2025-08-26T23:21:59.9394166Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file 2025-08-26T23:21:59.9398145Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0 2025-08-26T23:21:59.9398950Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file 2025-08-26T23:21:59.9399744Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0 2025-08-26T23:21:59.9400562Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 138 <- wrt source file 2025-08-26T23:21:59.9401374Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0 2025-08-26T23:21:59.9402053Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 505 <- wrt source file 2025-08-26T23:21:59.9402738Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0 2025-08-26T23:21:59.9403451Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 635 <- wrt source file 2025-08-26T23:21:59.9404132Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0 2025-08-26T23:21:59.9404831Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 892 <- wrt source file 2025-08-26T23:21:59.9431271Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0 2025-08-26T23:21:59.9431982Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1014 <- wrt source file 2025-08-26T23:21:59.9432694Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0 2025-08-26T23:21:59.9433391Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1140 <- wrt source file 2025-08-26T23:21:59.9434102Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0 2025-08-26T23:21:59.9434820Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py::update_bn:0, line 337 <- wrt source file 2025-08-26T23:21:59.9435513Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py::update_bn:0 2025-08-26T23:21:59.9436103Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 280 <- wrt source file 2025-08-26T23:21:59.9436714Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0 2025-08-26T23:21:59.9437331Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 388 <- wrt source file 2025-08-26T23:21:59.9437988Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0 2025-08-26T23:21:59.9438603Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 491 <- wrt source file 2025-08-26T23:21:59.9439209Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::StepLR:0 2025-08-26T23:21:59.9441978Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 547 <- wrt source file 2025-08-26T23:21:59.9442623Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0 2025-08-26T23:21:59.9443228Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 608 <- wrt source file 2025-08-26T23:21:59.9443843Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0 2025-08-26T23:21:59.9444434Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 683 <- wrt source file 2025-08-26T23:21:59.9445082Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LinearLR:0 2025-08-26T23:21:59.9445689Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 773 <- wrt source file 2025-08-26T23:21:59.9446320Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0 2025-08-26T23:21:59.9446963Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0, line 971 <- wrt source file 2025-08-26T23:21:59.9447574Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0 2025-08-26T23:21:59.9448193Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1062 <- wrt source file 2025-08-26T23:21:59.9450473Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0 2025-08-26T23:21:59.9451095Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1134 <- wrt source file 2025-08-26T23:21:59.9451726Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0 2025-08-26T23:21:59.9452395Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 1803 <- wrt source file 2025-08-26T23:21:59.9453120Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0 2025-08-26T23:21:59.9453827Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 1819 <- wrt source file 2025-08-26T23:21:59.9454580Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1 2025-08-26T23:21:59.9455261Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0, line 339 <- wrt source file 2025-08-26T23:21:59.9455943Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0 2025-08-26T23:21:59.9456560Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file 2025-08-26T23:21:59.9457150Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_prims/context.py::TorchRefsMode:0 2025-08-26T23:21:59.9459230Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file 2025-08-26T23:21:59.9459853Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/package/glob_group.py::GlobGroup:0 2025-08-26T23:21:59.9460545Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file 2025-08-26T23:21:59.9461151Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0 2025-08-26T23:21:59.9461744Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file 2025-08-26T23:21:59.9462350Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1 2025-08-26T23:21:59.9462941Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file 2025-08-26T23:21:59.9463583Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2 2025-08-26T23:21:59.9464209Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file 2025-08-26T23:21:59.9464904Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0 2025-08-26T23:21:59.9466957Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file 2025-08-26T23:21:59.9467544Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/profiler.py::profile:0 2025-08-26T23:21:59.9468148Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 42 <- wrt source file 2025-08-26T23:21:59.9468748Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::gds_register_buffer:0 2025-08-26T23:21:59.9469339Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 58 <- wrt source file 2025-08-26T23:21:59.9469947Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0 2025-08-26T23:21:59.9470762Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::GdsFile:0, line 85 <- wrt source file 2025-08-26T23:21:59.9471225Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/gds.py::GdsFile:0 2025-08-26T23:21:59.9471607Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 103 <- wrt source file 2025-08-26T23:21:59.9472043Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::Dim:0 2025-08-26T23:21:59.9472459Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0, line 715 <- wrt source file 2025-08-26T23:21:59.9474138Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0 2025-08-26T23:21:59.9474667Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1, line 731 <- wrt source file 2025-08-26T23:21:59.9475115Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1 2025-08-26T23:21:59.9475549Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0, line 815 <- wrt source file 2025-08-26T23:21:59.9475997Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0 2025-08-26T23:21:59.9476444Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 230 <- wrt source file 2025-08-26T23:21:59.9476912Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0 2025-08-26T23:21:59.9477339Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::custom_op:0, line 98 <- wrt source file 2025-08-26T23:21:59.9730526Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::custom_op:0 2025-08-26T23:21:59.9730992Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 238 <- wrt source file 2025-08-26T23:21:59.9768427Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0 2025-08-26T23:21:59.9770865Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 307 <- wrt source file 2025-08-26T23:21:59.9771431Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0 2025-08-26T23:21:59.9771896Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0, line 541 <- wrt source file 2025-08-26T23:21:59.9844968Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0 2025-08-26T23:21:59.9845485Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 709 <- wrt source file 2025-08-26T23:21:59.9928138Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0 2025-08-26T23:21:59.9928707Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 795 <- wrt source file 2025-08-26T23:21:59.9929250Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0 2025-08-26T23:21:59.9929729Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 51 <- wrt source file 2025-08-26T23:21:59.9930189Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/infer_schema.py::infer_schema:0 2025-08-26T23:21:59.9931136Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file 2025-08-26T23:21:59.9965047Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0 2025-08-26T23:21:59.9965505Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::_snake_case:0, line 102 <- wrt source file 2025-08-26T23:21:59.9965919Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::_snake_case:0 2025-08-26T23:21:59.9966342Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0, line 1873 <- wrt source file 2025-08-26T23:21:59.9966788Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::Graph.eliminate_dead_code:0 2025-08-26T23:21:59.9967236Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::Graph.on_generate_code:0, line 1967 <- wrt source file 2025-08-26T23:21:59.9967661Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/graph.py::Graph.on_generate_code:0 2025-08-26T23:21:59.9968073Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::TensorType:0, line 12 <- wrt source file 2025-08-26T23:21:59.9968481Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::TensorType:0 2025-08-26T23:21:59.9968878Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::is_consistent:0, line 65 <- wrt source file 2025-08-26T23:21:59.9971252Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::is_consistent:0 2025-08-26T23:21:59.9971665Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::is_more_precise:0, line 93 <- wrt source file 2025-08-26T23:21:59.9972178Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/tensor_type.py::is_more_precise:0 2025-08-26T23:21:59.9972600Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/subgraph_rewriter.py::replace_pattern:0, line 125 <- wrt source file 2025-08-26T23:21:59.9973102Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/subgraph_rewriter.py::replace_pattern:0 2025-08-26T23:21:59.9973519Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/interpreter.py::Interpreter:0, line 49 <- wrt source file 2025-08-26T23:21:59.9973928Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/interpreter.py::Interpreter:0 2025-08-26T23:21:59.9974401Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/interpreter.py::Transformer:0, line 480 <- wrt source file 2025-08-26T23:21:59.9974810Z * SKIPPED: 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line 129 <- wrt source file 2025-08-26T23:22:00.0035457Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/graph_drawer.py::FxGraphDrawer.get_dot_graph:0 2025-08-26T23:22:00.0035918Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/split_module.py::split_module:0, line 89 <- wrt source file 2025-08-26T23:22:00.0037856Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/split_module.py::split_module:0 2025-08-26T23:22:00.0038297Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0, line 99 <- wrt source file 2025-08-26T23:22:00.0038724Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0 2025-08-26T23:22:00.0039232Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0, line 51 <- wrt 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SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_hook:0 2025-08-26T23:22:00.0050039Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 147 <- wrt source file 2025-08-26T23:22:00.0054639Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_prehook:0 2025-08-26T23:22:00.0055073Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 283 <- wrt source file 2025-08-26T23:22:00.0055507Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0 2025-08-26T23:22:00.0055917Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::save_on_cpu:0, line 353 <- wrt source file 2025-08-26T23:22:00.0056324Z * SKIPPED: 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/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0 2025-08-26T23:22:00.0070547Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file 2025-08-26T23:22:00.0070964Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::make_dual:0 2025-08-26T23:22:00.0071375Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::unpack_dual:0, line 151 <- wrt source file 2025-08-26T23:22:00.0071801Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::unpack_dual:0 2025-08-26T23:22:00.0072215Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::dual_level:0, line 187 <- wrt source file 2025-08-26T23:22:00.0072639Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/forward_ad.py::dual_level:0 2025-08-26T23:22:00.0073041Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::profile:0, line 182 <- wrt source file 2025-08-26T23:22:00.0073459Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::profile:0 2025-08-26T23:22:00.0075426Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::emit_itt:0, line 880 <- wrt source file 2025-08-26T23:22:00.0075839Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::emit_itt:0 2025-08-26T23:22:00.0076279Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::emit_nvtx:0, line 953 <- wrt source file 2025-08-26T23:22:00.0076693Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py::emit_nvtx:0 2025-08-26T23:22:00.0077090Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::vjp:0, line 293 <- wrt source file 2025-08-26T23:22:00.0077531Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::vjp:0 2025-08-26T23:22:00.0077923Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::jvp:0, line 395 <- wrt source file 2025-08-26T23:22:00.0078320Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::jvp:0 2025-08-26T23:22:00.0078721Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::jacobian:0, line 630 <- wrt source file 2025-08-26T23:22:00.0079139Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::jacobian:0 2025-08-26T23:22:00.0079542Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::hessian:0, line 894 <- wrt source file 2025-08-26T23:22:00.0079954Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::hessian:0 2025-08-26T23:22:00.0080463Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::vhp:0, line 1010 <- wrt source file 2025-08-26T23:22:00.0080862Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::vhp:0 2025-08-26T23:22:00.0081251Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::hvp:0, line 1109 <- wrt source file 2025-08-26T23:22:00.0083063Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/functional.py::hvp:0 2025-08-26T23:22:00.0083518Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0, line 71 <- wrt source file 2025-08-26T23:22:00.0083997Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0 2025-08-26T23:22:00.0084465Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0, line 115 <- wrt source file 2025-08-26T23:22:00.0084937Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0 2025-08-26T23:22:00.0085393Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0, line 167 <- wrt source file 2025-08-26T23:22:00.0085850Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0 2025-08-26T23:22:00.0086320Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0, line 214 <- wrt source file 2025-08-26T23:22:00.0086833Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0 2025-08-26T23:22:00.0087358Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0, line 243 <- wrt source file 2025-08-26T23:22:00.0087846Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0 2025-08-26T23:22:00.0093729Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::Function:0, line 485 <- wrt source file 2025-08-26T23:22:00.0094139Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/function.py::Function:0 2025-08-26T23:22:00.0094539Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::no_grad:0, line 50 <- wrt source file 2025-08-26T23:22:00.0094982Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::no_grad:0 2025-08-26T23:22:00.0095388Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::enable_grad:0, line 108 <- wrt source file 2025-08-26T23:22:00.0095805Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::enable_grad:0 2025-08-26T23:22:00.0096224Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0, line 166 <- wrt source file 2025-08-26T23:22:00.0096656Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0 2025-08-26T23:22:00.0097083Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::inference_mode:0, line 238 <- wrt source file 2025-08-26T23:22:00.0097513Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/grad_mode.py::inference_mode:0 2025-08-26T23:22:00.0097954Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 155 <- wrt source file 2025-08-26T23:22:00.0099813Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/cond.py::cond:0 2025-08-26T23:22:00.0100232Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/map.py::map:0, line 79 <- wrt source file 2025-08-26T23:22:00.0100719Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/map.py::map:0 2025-08-26T23:22:00.0101149Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file 2025-08-26T23:22:00.0101618Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0 2025-08-26T23:22:00.0102086Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 186 <- wrt source file 2025-08-26T23:22:00.0102568Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0 2025-08-26T23:22:00.0103056Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 322 <- wrt source file 2025-08-26T23:22:00.0103562Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0 2025-08-26T23:22:00.0104011Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 156 <- wrt source file 2025-08-26T23:22:00.0104463Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::scan:0 2025-08-26T23:22:00.0106057Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0, line 474 <- wrt source file 2025-08-26T23:22:00.0106503Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0 2025-08-26T23:22:00.0106941Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_logging/_internal.py::set_logs:0, line 459 <- wrt source file 2025-08-26T23:22:00.0107347Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_logging/_internal.py::set_logs:0 2025-08-26T23:22:00.0107748Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 277 <- wrt source file 2025-08-26T23:22:00.0108183Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0 2025-08-26T23:22:00.0108585Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 320 <- wrt source file 2025-08-26T23:22:00.0108995Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0 2025-08-26T23:22:00.0109400Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 357 <- wrt source file 2025-08-26T23:22:00.0109820Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0 2025-08-26T23:22:00.0111456Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 387 <- wrt source file 2025-08-26T23:22:00.0111883Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0 2025-08-26T23:22:00.0112331Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 422 <- wrt source file 2025-08-26T23:22:00.0112741Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0 2025-08-26T23:22:00.0113145Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 457 <- wrt source file 2025-08-26T23:22:00.0113566Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0 2025-08-26T23:22:00.0113964Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 494 <- wrt source file 2025-08-26T23:22:00.0114364Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_map:0 2025-08-26T23:22:00.0114870Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 893 <- wrt source file 2025-08-26T23:22:00.0115308Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0 2025-08-26T23:22:00.0116865Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0, line 547 <- wrt source file 2025-08-26T23:22:00.0117337Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0 2025-08-26T23:22:00.0117782Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0, line 749 <- wrt source file 2025-08-26T23:22:00.0118242Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0 2025-08-26T23:22:00.0118712Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 303 <- wrt source file 2025-08-26T23:22:00.0119134Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::register_dataclass:0 2025-08-26T23:22:00.0119563Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::register_constant:0, line 419 <- wrt source file 2025-08-26T23:22:00.0119985Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::register_constant:0 2025-08-26T23:22:00.0120469Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1026 <- wrt source file 2025-08-26T23:22:00.0120886Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_is_leaf:0 2025-08-26T23:22:00.0121274Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_map:0, line 1345 <- wrt source file 2025-08-26T23:22:00.0122946Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_map:0 2025-08-26T23:22:00.0123330Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/dlpack.py::from_dlpack:0, line 93 <- wrt source file 2025-08-26T23:22:00.0128429Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/dlpack.py::from_dlpack:0 2025-08-26T23:22:00.0128880Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 69 <- wrt source file 2025-08-26T23:22:00.0129383Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0 2025-08-26T23:22:00.0129963Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 375 <- wrt source file 2025-08-26T23:22:00.0130610Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0 2025-08-26T23:22:00.0131106Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0, line 410 <- wrt source file 2025-08-26T23:22:00.0131578Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0 2025-08-26T23:22:00.0132053Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 724 <- wrt source file 2025-08-26T23:22:00.0341767Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0 2025-08-26T23:22:00.0342244Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py::Sampler:0, line 40 <- wrt source file 2025-08-26T23:22:00.0342662Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py::Sampler:0 2025-08-26T23:22:00.0343095Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file 2025-08-26T23:22:00.0343538Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::IterableDataset:0 2025-08-26T23:22:00.0343962Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::StackDataset:0, line 219 <- wrt source file 2025-08-26T23:22:00.0344456Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::StackDataset:0 2025-08-26T23:22:00.0344872Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::random_split:0, line 441 <- wrt source file 2025-08-26T23:22:00.0345297Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/dataset.py::random_split:0 2025-08-26T23:22:00.0345762Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file 2025-08-26T23:22:00.0346221Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_convert:0 2025-08-26T23:22:00.0346658Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file 2025-08-26T23:22:00.0348427Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::collate:0 2025-08-26T23:22:00.0348882Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 364 <- wrt source file 2025-08-26T23:22:00.0349338Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_collate:0 2025-08-26T23:22:00.0349803Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 268 <- wrt source file 2025-08-26T23:22:00.0350275Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0 2025-08-26T23:22:00.0350860Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0, line 35 <- wrt source file 2025-08-26T23:22:00.0351405Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0 2025-08-26T23:22:00.0351907Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0, line 29 <- wrt source file 2025-08-26T23:22:00.0352419Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0 2025-08-26T23:22:00.0352921Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file 2025-08-26T23:22:00.0354731Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0 2025-08-26T23:22:00.0355255Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 73 <- wrt source file 2025-08-26T23:22:00.0355764Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0 2025-08-26T23:22:00.0356273Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0, line 29 <- wrt source file 2025-08-26T23:22:00.0356803Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0 2025-08-26T23:22:00.0357330Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file 2025-08-26T23:22:00.0357875Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0 2025-08-26T23:22:00.0358429Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file 2025-08-26T23:22:00.0358919Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0 2025-08-26T23:22:00.0359432Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0, line 37 <- wrt source file 2025-08-26T23:22:00.0359941Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0 2025-08-26T23:22:00.0361743Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 53 <- wrt source file 2025-08-26T23:22:00.0362317Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0 2025-08-26T23:22:00.0362823Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 201 <- wrt source file 2025-08-26T23:22:00.0363343Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0 2025-08-26T23:22:00.0363848Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0, line 53 <- wrt source file 2025-08-26T23:22:00.0364361Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0 2025-08-26T23:22:00.0364903Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 113 <- wrt source file 2025-08-26T23:22:00.0365428Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0 2025-08-26T23:22:00.0365954Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file 2025-08-26T23:22:00.0366488Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0 2025-08-26T23:22:00.0368535Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 88 <- wrt source file 2025-08-26T23:22:00.0369077Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0 2025-08-26T23:22:00.0369577Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0, line 304 <- wrt source file 2025-08-26T23:22:00.0370077Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0 2025-08-26T23:22:00.0370816Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0, line 30 <- wrt source file 2025-08-26T23:22:00.0371362Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0 2025-08-26T23:22:00.0371896Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file 2025-08-26T23:22:00.0372496Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0 2025-08-26T23:22:00.0373024Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 90 <- wrt source file 2025-08-26T23:22:00.0373604Z * SKIPPED: 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line 216 <- wrt source file 2025-08-26T23:22:00.0379548Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0 2025-08-26T23:22:00.0380037Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 314 <- wrt source file 2025-08-26T23:22:00.0380634Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0 2025-08-26T23:22:00.0381163Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0, line 362 <- wrt source file 2025-08-26T23:22:00.0381658Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0 2025-08-26T23:22:00.0382137Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0, line 394 <- wrt source file 2025-08-26T23:22:00.0382630Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0 2025-08-26T23:22:00.0383108Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0, line 441 <- wrt source file 2025-08-26T23:22:00.0383599Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0 2025-08-26T23:22:00.0384081Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 480 <- wrt source file 2025-08-26T23:22:00.0385832Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0 2025-08-26T23:22:00.0386330Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 533 <- wrt source file 2025-08-26T23:22:00.0386839Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0 2025-08-26T23:22:00.0387328Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 599 <- wrt source file 2025-08-26T23:22:00.0387861Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0 2025-08-26T23:22:00.0388337Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0, line 648 <- wrt source file 2025-08-26T23:22:00.0388854Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0 2025-08-26T23:22:00.0389326Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0, line 811 <- wrt source file 2025-08-26T23:22:00.0389804Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0 2025-08-26T23:22:00.0390316Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0, line 878 <- wrt source file 2025-08-26T23:22:00.0391961Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0 2025-08-26T23:22:00.0392460Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 989 <- wrt source file 2025-08-26T23:22:00.0392950Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0 2025-08-26T23:22:00.0393477Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1063 <- wrt source file 2025-08-26T23:22:00.0394075Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0 2025-08-26T23:22:00.0394685Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1084 <- wrt source file 2025-08-26T23:22:00.0395239Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0 2025-08-26T23:22:00.0395761Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1108 <- wrt source file 2025-08-26T23:22:00.0396279Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0 2025-08-26T23:22:00.0396770Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1154 <- wrt source file 2025-08-26T23:22:00.0397251Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0 2025-08-26T23:22:00.0398703Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file 2025-08-26T23:22:00.0399174Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0 2025-08-26T23:22:00.0399639Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file 2025-08-26T23:22:00.0400118Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0 2025-08-26T23:22:00.0400944Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0, line 349 <- wrt source file 2025-08-26T23:22:00.0401389Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0 2025-08-26T23:22:00.0401879Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0, line 322 <- wrt source file 2025-08-26T23:22:00.0402364Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0 2025-08-26T23:22:00.0402803Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_creation.py::make_tensor:0, line 114 <- wrt source file 2025-08-26T23:22:00.0403253Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_creation.py::make_tensor:0 2025-08-26T23:22:00.0403685Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::parametrize:0, line 615 <- wrt source file 2025-08-26T23:22:00.0405138Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::parametrize:0 2025-08-26T23:22:00.0405592Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0, line 736 <- wrt source file 2025-08-26T23:22:00.0406054Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0 2025-08-26T23:22:00.0406501Z * DOCTEST : 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2025-08-26T23:22:00.0409493Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0, line 4778 <- wrt source file 2025-08-26T23:22:00.0411506Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0 2025-08-26T23:22:00.0411983Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0, line 194 <- wrt source file 2025-08-26T23:22:00.0412453Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0 2025-08-26T23:22:00.0412924Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0, line 220 <- wrt source file 2025-08-26T23:22:00.0413418Z * SKIPPED: 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/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 295 <- wrt source file 2025-08-26T23:22:00.0417921Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0 2025-08-26T23:22:00.0418394Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/profiler/profiler.py::profile:0, line 617 <- wrt source file 2025-08-26T23:22:00.0418803Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/profiler/profiler.py::profile:0 2025-08-26T23:22:00.0419202Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file 2025-08-26T23:22:00.0419610Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/amp/grad_scaler.py::GradScaler:0 2025-08-26T23:22:00.0420016Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file 2025-08-26T23:22:00.0420576Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/poisson.py::Poisson:0 2025-08-26T23:22:00.0420991Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file 2025-08-26T23:22:00.0421410Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/laplace.py::Laplace:0 2025-08-26T23:22:00.0421842Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/constraints.py::is_dependent:0, line 166 <- wrt source file 2025-08-26T23:22:00.0422305Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/constraints.py::is_dependent:0 2025-08-26T23:22:00.0422762Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 187 <- wrt source file 2025-08-26T23:22:00.0423242Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/constraints.py::_DependentProperty:0 2025-08-26T23:22:00.0424973Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file 2025-08-26T23:22:00.0425394Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/gamma.py::Gamma:0 2025-08-26T23:22:00.0425814Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file 2025-08-26T23:22:00.0426264Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0 2025-08-26T23:22:00.0426701Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file 2025-08-26T23:22:00.0427186Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/geometric.py::Geometric:0 2025-08-26T23:22:00.0427640Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file 2025-08-26T23:22:00.0428135Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0 2025-08-26T23:22:00.0428657Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file 2025-08-26T23:22:00.0430597Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0 2025-08-26T23:22:00.0431095Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file 2025-08-26T23:22:00.0432869Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0 2025-08-26T23:22:00.0435503Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file 2025-08-26T23:22:00.0435948Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/log_normal.py::LogNormal:0 2025-08-26T23:22:00.0436386Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file 2025-08-26T23:22:00.0510739Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0 2025-08-26T23:22:00.0540331Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file 2025-08-26T23:22:00.0540958Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/normal.py::Normal:0 2025-08-26T23:22:00.0541356Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/beta.py::Beta:0, line 21 <- wrt source file 2025-08-26T23:22:00.0541755Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/beta.py::Beta:0 2025-08-26T23:22:00.0543902Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/uniform.py::Uniform:0, line 21 <- wrt source file 2025-08-26T23:22:00.0544344Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/uniform.py::Uniform:0 2025-08-26T23:22:00.0544827Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file 2025-08-26T23:22:00.0545347Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0 2025-08-26T23:22:00.0545805Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/binomial.py::Binomial:0, line 31 <- wrt source file 2025-08-26T23:22:00.0546235Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/binomial.py::Binomial:0 2025-08-26T23:22:00.0546672Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file 2025-08-26T23:22:00.0547133Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/independent.py::Independent:0 2025-08-26T23:22:00.0547570Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file 2025-08-26T23:22:00.0548067Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/exponential.py::Exponential:0 2025-08-26T23:22:00.0548510Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1065 <- wrt source file 2025-08-26T23:22:00.0548988Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::CatTransform:0 2025-08-26T23:22:00.0549431Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::StackTransform:0, line 1177 <- wrt source file 2025-08-26T23:22:00.0549889Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::StackTransform:0 2025-08-26T23:22:00.0550492Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0, line 1253 <- wrt source file 2025-08-26T23:22:00.0551025Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0 2025-08-26T23:22:00.0552733Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file 2025-08-26T23:22:00.0553215Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0 2025-08-26T23:22:00.0553646Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/weibull.py::Weibull:0, line 22 <- wrt source file 2025-08-26T23:22:00.0554071Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/weibull.py::Weibull:0 2025-08-26T23:22:00.0554707Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file 2025-08-26T23:22:00.0555221Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0 2025-08-26T23:22:00.0555658Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file 2025-08-26T23:22:00.0556056Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/chi2.py::Chi2:0 2025-08-26T23:22:00.0556474Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file 2025-08-26T23:22:00.0556923Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/multinomial.py::Multinomial:0 2025-08-26T23:22:00.0557351Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file 2025-08-26T23:22:00.0558769Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/studentT.py::StudentT:0 2025-08-26T23:22:00.0559193Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file 2025-08-26T23:22:00.0559634Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0 2025-08-26T23:22:00.0560056Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/utils.py::clamp_probs:0, line 114 <- wrt source file 2025-08-26T23:22:00.0560559Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/utils.py::clamp_probs:0 2025-08-26T23:22:00.0560983Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/bernoulli.py::Bernoulli:0, line 30 <- wrt source file 2025-08-26T23:22:00.0561457Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/bernoulli.py::Bernoulli:0 2025-08-26T23:22:00.0561868Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file 2025-08-26T23:22:00.0562327Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/gumbel.py::Gumbel:0 2025-08-26T23:22:00.0562761Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file 2025-08-26T23:22:00.0563229Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0 2025-08-26T23:22:00.0564718Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file 2025-08-26T23:22:00.0565158Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/half_normal.py::HalfNormal:0 2025-08-26T23:22:00.0565581Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 42 <- wrt source file 2025-08-26T23:22:00.0566013Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/dirichlet.py::Dirichlet:0 2025-08-26T23:22:00.0566425Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file 2025-08-26T23:22:00.0566836Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/pareto.py::Pareto:0 2025-08-26T23:22:00.0567286Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/von_mises.py::VonMises:0, line 117 <- wrt source file 2025-08-26T23:22:00.0567724Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/von_mises.py::VonMises:0 2025-08-26T23:22:00.0568129Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file 2025-08-26T23:22:00.0568539Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/cauchy.py::Cauchy:0 2025-08-26T23:22:00.0570148Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/categorical.py::Categorical:0, line 42 <- wrt source file 2025-08-26T23:22:00.0570722Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/categorical.py::Categorical:0 2025-08-26T23:22:00.0571145Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file 2025-08-26T23:22:00.0571560Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/wishart.py::Wishart:0 2025-08-26T23:22:00.0571970Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_equal:0, line 171 <- wrt source file 2025-08-26T23:22:00.0572399Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_equal:0 2025-08-26T23:22:00.0572822Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file 2025-08-26T23:22:00.0587642Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0 2025-08-26T23:22:00.0588099Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file 2025-08-26T23:22:00.0588590Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0 2025-08-26T23:22:00.0590334Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file 2025-08-26T23:22:00.0594866Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0 2025-08-26T23:22:00.0595329Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file 2025-08-26T23:22:00.0596461Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0 2025-08-26T23:22:00.0596967Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file 2025-08-26T23:22:00.0598168Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0 2025-08-26T23:22:00.0598600Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file 2025-08-26T23:22:00.0599028Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0 2025-08-26T23:22:00.0599440Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file 2025-08-26T23:22:00.0601545Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_warns:0 2025-08-26T23:22:00.0602042Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0, line 36 <- wrt source file 2025-08-26T23:22:00.0603932Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0 2025-08-26T23:22:00.0604408Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0, line 22 <- wrt source file 2025-08-26T23:22:00.0604874Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0 2025-08-26T23:22:00.0605342Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0, line 122 <- wrt source file 2025-08-26T23:22:00.0605832Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0 2025-08-26T23:22:00.0606296Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0, line 214 <- wrt source file 2025-08-26T23:22:00.0606747Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0 2025-08-26T23:22:00.0607161Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/masked/_ops.py::logaddexp:0, line 1530 <- wrt source file 2025-08-26T23:22:00.0613874Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/masked/_ops.py::logaddexp:0 2025-08-26T23:22:00.0614620Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0, line 25 <- wrt source file 2025-08-26T23:22:00.0620992Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0 2025-08-26T23:22:00.0622100Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0, line 158 <- wrt source file 2025-08-26T23:22:00.0622916Z * SKIPPED: 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SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0 2025-08-26T23:22:00.0628253Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0, line 1121 <- wrt source file 2025-08-26T23:22:00.0628947Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0 2025-08-26T23:22:00.0629647Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0, line 2578 <- wrt source file 2025-08-26T23:22:00.0630528Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0 2025-08-26T23:22:00.0631262Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2680 <- wrt source file 2025-08-26T23:22:00.0632027Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0 2025-08-26T23:22:00.0632736Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3147 <- wrt source file 2025-08-26T23:22:00.0633489Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0 2025-08-26T23:22:00.0634190Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3376 <- wrt source file 2025-08-26T23:22:00.0637650Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0 2025-08-26T23:22:00.0638350Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0, line 3478 <- wrt source file 2025-08-26T23:22:00.0639067Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0 2025-08-26T23:22:00.0639769Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0, line 3592 <- wrt source file 2025-08-26T23:22:00.0640619Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0 2025-08-26T23:22:00.0641387Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0, line 3715 <- wrt source file 2025-08-26T23:22:00.0642122Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0 2025-08-26T23:22:00.0642922Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0, line 3924 <- wrt source file 2025-08-26T23:22:00.0643654Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0 2025-08-26T23:22:00.0644364Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0, line 4062 <- wrt source file 2025-08-26T23:22:00.0645163Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0 2025-08-26T23:22:00.0645842Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::gather:0, line 4168 <- wrt source file 2025-08-26T23:22:00.0646550Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::gather:0 2025-08-26T23:22:00.0647219Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter:0, line 4253 <- wrt source file 2025-08-26T23:22:00.0647873Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter:0 2025-08-26T23:22:00.0648557Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0, line 4391 <- wrt source file 2025-08-26T23:22:00.0649345Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0 2025-08-26T23:22:00.0650056Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::monitored_barrier:0, line 4873 <- wrt source file 2025-08-26T23:22:00.0650885Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::monitored_barrier:0 2025-08-26T23:22:00.0651616Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0, line 5415 <- wrt source file 2025-08-26T23:22:00.0652315Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0 2025-08-26T23:22:00.0653036Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::new_subgroups_by_enumeration:0, line 5509 <- wrt source file 2025-08-26T23:22:00.0653812Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::new_subgroups_by_enumeration:0 2025-08-26T23:22:00.0654468Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/run.py::__doc__:0, line 57 <- wrt source file 2025-08-26T23:22:00.0657114Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/run.py::__doc__:0 2025-08-26T23:22:00.0657744Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/autograd/__init__.py::context:0, line 47 <- wrt source file 2025-08-26T23:22:00.0658428Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/autograd/__init__.py::context:0 2025-08-26T23:22:00.0659111Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::put:0, line 142 <- wrt source file 2025-08-26T23:22:00.0659905Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::put:0 2025-08-26T23:22:00.0660736Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::get:0, line 195 <- wrt source file 2025-08-26T23:22:00.0661498Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::get:0 2025-08-26T23:22:00.0662238Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_symmetric_memory/_nvshmem_triton.py::putmem_signal_block:0, line 268 <- wrt source file 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SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0 2025-08-26T23:22:00.0729777Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0, line 125 <- wrt source file 2025-08-26T23:22:00.0730697Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0 2025-08-26T23:22:00.0731583Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0, line 1490 <- wrt source file 2025-08-26T23:22:00.0733956Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0 2025-08-26T23:22:00.0734977Z * DOCTEST : 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2025-08-26T23:22:00.0739276Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/join.py::Join:0 2025-08-26T23:22:00.0739985Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0, line 107 <- wrt source file 2025-08-26T23:22:00.0740880Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/__init__.py::register_ddp_comm_hook:0 2025-08-26T23:22:00.0741726Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_pertensor_hook:0, line 64 <- wrt source file 2025-08-26T23:22:00.0742680Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_pertensor_hook:0 2025-08-26T23:22:00.0745035Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_perchannel_hook:0, line 145 <- wrt source file 2025-08-26T23:22:00.0745941Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/quantization_hooks.py::quantization_perchannel_hook:0 2025-08-26T23:22:00.0746768Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::allreduce_hook:0, line 49 <- wrt source file 2025-08-26T23:22:00.0747571Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::allreduce_hook:0 2025-08-26T23:22:00.0748363Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::fp16_compress_hook:0, line 104 <- wrt source file 2025-08-26T23:22:00.0749184Z * SKIPPED: 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/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_wrapper:0, line 182 <- wrt source file 2025-08-26T23:22:00.0755818Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/default_hooks.py::bf16_compress_wrapper:0 2025-08-26T23:22:00.0756601Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0, line 23 <- wrt source file 2025-08-26T23:22:00.0757389Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/debugging_hooks.py::noop_hook:0 2025-08-26T23:22:00.0758186Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py::batched_powerSGD_hook:0, line 708 <- wrt source file 2025-08-26T23:22:00.0759022Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py::batched_powerSGD_hook:0 2025-08-26T23:22:00.0759805Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py::custom_sharded_op_impl:0, line 457 <- wrt source file 2025-08-26T23:22:00.0760649Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py::custom_sharded_op_impl:0 2025-08-26T23:22:00.0761428Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0, line 31 <- wrt source file 2025-08-26T23:22:00.0762293Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_optim/__init__.py::named_params_with_sharded_tensor:0 2025-08-26T23:22:00.0763095Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/_ops/_common.py::_sharded_op_common:0, line 18 <- wrt source file 2025-08-26T23:22:00.0765246Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/_ops/_common.py::_sharded_op_common:0 2025-08-26T23:22:00.0765973Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_tools/memory_tracker.py::MemoryTracker:0, line 55 <- wrt source file 2025-08-26T23:22:00.0766675Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_tools/memory_tracker.py::MemoryTracker:0 2025-08-26T23:22:00.0767349Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/contract.py::contract:0, line 66 <- wrt source file 2025-08-26T23:22:00.0768024Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/contract.py::contract:0 2025-08-26T23:22:00.0768714Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/replicate_with_fsdp.py::replicate:0, line 247 <- wrt source file 2025-08-26T23:22:00.0769448Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/replicate_with_fsdp.py::replicate:0 2025-08-26T23:22:00.0770138Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/replicate.py::replicate:0, line 190 <- wrt source file 2025-08-26T23:22:00.0770911Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/replicate.py::replicate:0 2025-08-26T23:22:00.0771674Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0, line 53 <- wrt source file 2025-08-26T23:22:00.0772427Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_composable/checkpoint_activation.py::checkpoint:0 2025-08-26T23:22:00.0774804Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_random.py::OffsetBasedRNGTracker._set_pre_op_offset:0, line 294 <- wrt source file 2025-08-26T23:22:00.0775605Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_random.py::OffsetBasedRNGTracker._set_pre_op_offset:0 2025-08-26T23:22:00.0776312Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_api.py::_shard_tensor:0, line 837 <- wrt source file 2025-08-26T23:22:00.0776968Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_api.py::_shard_tensor:0 2025-08-26T23:22:00.0777663Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/api.py::parallelize_module:0, line 56 <- wrt source file 2025-08-26T23:22:00.0778401Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/api.py::parallelize_module:0 2025-08-26T23:22:00.0779112Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/loss.py::loss_parallel:0, line 56 <- wrt source file 2025-08-26T23:22:00.0779824Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/loss.py::loss_parallel:0 2025-08-26T23:22:00.0780664Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/ddp.py::_pre_dp_module_transform:0, line 88 <- wrt source file 2025-08-26T23:22:00.0781511Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/ddp.py::_pre_dp_module_transform:0 2025-08-26T23:22:00.0783751Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::ColwiseParallel:0, line 64 <- wrt source file 2025-08-26T23:22:00.0784493Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::ColwiseParallel:0 2025-08-26T23:22:00.0785221Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::RowwiseParallel:0, line 198 <- wrt source file 2025-08-26T23:22:00.0785965Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::RowwiseParallel:0 2025-08-26T23:22:00.0786492Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0, line 350 <- wrt source file 2025-08-26T23:22:00.0786996Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0 2025-08-26T23:22:00.0787474Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_ops/_common_rules.py::pointwise_rule:0, line 230 <- wrt source file 2025-08-26T23:22:00.0787964Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/_ops/_common_rules.py::pointwise_rule:0 2025-08-26T23:22:00.0788478Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/rendezvous/api.py::RendezvousHandler.shutdown:0, line 231 <- wrt source file 2025-08-26T23:22:00.0789018Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/rendezvous/api.py::RendezvousHandler.shutdown:0 2025-08-26T23:22:00.0789582Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/utils/distributed.py::get_free_port:0, line 141 <- wrt source file 2025-08-26T23:22:00.0791540Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/utils/distributed.py::get_free_port:0 2025-08-26T23:22:00.0792071Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0, line 134 <- wrt source file 2025-08-26T23:22:00.0792531Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0 2025-08-26T23:22:00.0792974Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/codecache.py::WritableTempFile:0, line 372 <- wrt source file 2025-08-26T23:22:00.0793419Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/codecache.py::WritableTempFile:0 2025-08-26T23:22:00.0793951Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0, line 45 <- wrt source file 2025-08-26T23:22:00.0794887Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0 2025-08-26T23:22:00.0795630Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1721 <- wrt source file 2025-08-26T23:22:00.0796382Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0 2025-08-26T23:22:00.0797107Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 3418 <- wrt source file 2025-08-26T23:22:00.0799488Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0 2025-08-26T23:22:00.0800111Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file 2025-08-26T23:22:00.0800768Z [W826 23:22:00.114966860 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0801128Z [W826 23:22:00.115089718 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0801479Z [W826 23:22:00.115174666 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0801955Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_input:0 2025-08-26T23:22:00.0802520Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file 2025-08-26T23:22:00.0802983Z [W826 23:22:00.115385043 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0803458Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_weight:0 2025-08-26T23:22:00.0804018Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file 2025-08-26T23:22:00.0804471Z [W826 23:22:00.115595660 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0806276Z [W826 23:22:00.126264549 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0806626Z [W826 23:22:00.126431167 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0807098Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_input:0 2025-08-26T23:22:00.0807718Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file 2025-08-26T23:22:00.0808173Z [W826 23:22:00.126935728 NNPACK.cpp:56] Could not initialize NNPACK! Reason: Unsupported hardware. 2025-08-26T23:22:00.0832841Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_weight:0 2025-08-26T23:22:00.0892042Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file 2025-08-26T23:22:00.1912312Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_input:0 2025-08-26T23:22:00.1916601Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file 2025-08-26T23:22:00.2873947Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_weight:0 2025-08-26T23:22:00.2874515Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::uniform_:0, line 230 <- wrt source file 2025-08-26T23:22:00.2874913Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::uniform_:0 2025-08-26T23:22:00.2875289Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::normal_:0, line 257 <- wrt source file 2025-08-26T23:22:00.2875688Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::normal_:0 2025-08-26T23:22:00.2876070Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::trunc_normal_:0, line 292 <- wrt source file 2025-08-26T23:22:00.2876467Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::trunc_normal_:0 2025-08-26T23:22:00.2877206Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::constant_:0, line 306 <- wrt source file 2025-08-26T23:22:00.2877676Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::constant_:0 2025-08-26T23:22:00.2878045Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::ones_:0, line 323 <- wrt source file 2025-08-26T23:22:00.2878423Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::ones_:0 2025-08-26T23:22:00.2878790Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::zeros_:0, line 336 <- wrt source file 2025-08-26T23:22:00.2879164Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::zeros_:0 2025-08-26T23:22:00.2879529Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::eye_:0, line 352 <- wrt source file 2025-08-26T23:22:00.2879906Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::eye_:0 2025-08-26T23:22:00.2880267Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::dirac_:0, line 374 <- wrt source file 2025-08-26T23:22:00.2880729Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::dirac_:0 2025-08-26T23:22:00.2881108Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::xavier_uniform_:0, line 460 <- wrt source file 2025-08-26T23:22:00.2881513Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::xavier_uniform_:0 2025-08-26T23:22:00.2881906Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::xavier_normal_:0, line 492 <- wrt source file 2025-08-26T23:22:00.2882301Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::xavier_normal_:0 2025-08-26T23:22:00.2882768Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 543 <- wrt source file 2025-08-26T23:22:00.2888589Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::kaiming_uniform_:0 2025-08-26T23:22:00.2889084Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::kaiming_normal_:0, line 608 <- wrt source file 2025-08-26T23:22:00.2889483Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::kaiming_normal_:0 2025-08-26T23:22:00.2889866Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::orthogonal_:0, line 647 <- wrt source file 2025-08-26T23:22:00.2890257Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::orthogonal_:0 2025-08-26T23:22:00.2890726Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::sparse_:0, line 700 <- wrt source file 2025-08-26T23:22:00.2891099Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py::sparse_:0 2025-08-26T23:22:00.2891524Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0, line 460 <- wrt source file 2025-08-26T23:22:00.3026849Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0 2025-08-26T23:22:00.3027345Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0, line 579 <- wrt source file 2025-08-26T23:22:00.3502397Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0 2025-08-26T23:22:00.3531616Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2174 <- wrt source file 2025-08-26T23:22:00.3853539Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::gumbel_softmax:0 2025-08-26T23:22:00.3854706Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::embedding:0, line 2478 <- wrt source file 2025-08-26T23:22:00.3855170Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::embedding:0 2025-08-26T23:22:00.3855590Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::embedding_bag:0, line 2618 <- wrt source file 2025-08-26T23:22:00.3891658Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::embedding_bag:0 2025-08-26T23:22:00.3892366Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::ctc_loss:0, line 3051 <- wrt source file 2025-08-26T23:22:00.4205899Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::ctc_loss:0 2025-08-26T23:22:00.4206579Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::nll_loss:0, line 3121 <- wrt source file 2025-08-26T23:22:00.4501658Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::nll_loss:0 2025-08-26T23:22:00.4502286Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::cross_entropy:0, line 3430 <- wrt source file 2025-08-26T23:22:00.5042310Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::cross_entropy:0 2025-08-26T23:22:00.5042861Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3495 <- wrt source file 2025-08-26T23:22:00.5043582Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy:0 2025-08-26T23:22:00.5044057Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3565 <- wrt source file 2025-08-26T23:22:00.5103111Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0 2025-08-26T23:22:00.5103626Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::pad:0, line 5263 <- wrt source file 2025-08-26T23:22:00.5107006Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/functional.py::pad:0 2025-08-26T23:22:00.5107520Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 120 <- wrt source file 2025-08-26T23:22:00.5108063Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0 2025-08-26T23:22:00.5108590Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 127 <- wrt source file 2025-08-26T23:22:00.5109075Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0 2025-08-26T23:22:00.5109637Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 642 <- wrt source file 2025-08-26T23:22:00.5110198Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0 2025-08-26T23:22:00.5110906Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1446 <- wrt source file 2025-08-26T23:22:00.5111597Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0 2025-08-26T23:22:00.5112161Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 1999 <- wrt source file 2025-08-26T23:22:00.5112795Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0 2025-08-26T23:22:00.5113359Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2009 <- wrt source file 2025-08-26T23:22:00.5113933Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1 2025-08-26T23:22:00.5114596Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2044 <- wrt source file 2025-08-26T23:22:00.5115257Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0 2025-08-26T23:22:00.5115754Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 95 <- wrt source file 2025-08-26T23:22:00.5116195Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/attention/bias.py::CausalBias:0 2025-08-26T23:22:00.5116637Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file 2025-08-26T23:22:00.5117156Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad1d:0 2025-08-26T23:22:00.5117615Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 122 <- wrt source file 2025-08-26T23:22:00.5128941Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad2d:0 2025-08-26T23:22:00.5129418Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 187 <- wrt source file 2025-08-26T23:22:00.9606619Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad3d:0 2025-08-26T23:22:00.9872819Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 241 <- wrt source file 2025-08-26T23:22:00.9881057Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0 2025-08-26T23:22:00.9881792Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 294 <- wrt source file 2025-08-26T23:22:00.9882598Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0 2025-08-26T23:22:00.9883299Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 350 <- wrt source file 2025-08-26T23:22:01.0282424Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0 2025-08-26T23:22:01.0321494Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 395 <- wrt source file 2025-08-26T23:22:01.0412630Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0 2025-08-26T23:22:01.0413408Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 439 <- wrt source file 2025-08-26T23:22:01.0552578Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0 2025-08-26T23:22:01.0553357Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 497 <- wrt source file 2025-08-26T23:22:01.0592929Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0 2025-08-26T23:22:01.0593603Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 556 <- wrt source file 2025-08-26T23:22:01.0762450Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0 2025-08-26T23:22:01.0763122Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 600 <- wrt source file 2025-08-26T23:22:01.0932957Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0 2025-08-26T23:22:01.0933631Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 658 <- wrt source file 2025-08-26T23:22:01.3267324Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0 2025-08-26T23:22:01.3504642Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 692 <- wrt source file 2025-08-26T23:22:01.3512615Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0 2025-08-26T23:22:01.3513299Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 750 <- wrt source file 2025-08-26T23:22:01.3515085Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0 2025-08-26T23:22:01.3515851Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 812 <- wrt source file 2025-08-26T23:22:01.3855493Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0 2025-08-26T23:22:01.3861465Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 551 <- wrt source file 2025-08-26T23:22:01.3862562Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.register_buffer:0 2025-08-26T23:22:01.3863013Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1039 <- wrt source file 2025-08-26T23:22:01.3863448Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.apply:0 2025-08-26T23:22:01.3863870Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.to:0, line 1290 <- wrt source file 2025-08-26T23:22:01.3864287Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.to:0 2025-08-26T23:22:01.3864709Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2229 <- wrt source file 2025-08-26T23:22:01.3865320Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.state_dict:0 2025-08-26T23:22:01.3865801Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2670 <- wrt source file 2025-08-26T23:22:01.3866243Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.parameters:0 2025-08-26T23:22:01.3866694Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2698 <- wrt source file 2025-08-26T23:22:01.3867154Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_parameters:0 2025-08-26T23:22:01.3867591Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2725 <- wrt source file 2025-08-26T23:22:01.3868024Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.buffers:0 2025-08-26T23:22:01.3868458Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2752 <- wrt source file 2025-08-26T23:22:01.3868908Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_buffers:0 2025-08-26T23:22:01.3869350Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2783 <- wrt source file 2025-08-26T23:22:01.3869802Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_children:0 2025-08-26T23:22:01.3870234Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2807 <- wrt source file 2025-08-26T23:22:01.3870836Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.modules:0 2025-08-26T23:22:01.3871264Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2845 <- wrt source file 2025-08-26T23:22:01.3871842Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_modules:0 2025-08-26T23:22:01.3872334Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file 2025-08-26T23:22:01.3872747Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout:0 2025-08-26T23:22:01.3873151Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 108 <- wrt source file 2025-08-26T23:22:01.3873569Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout1d:0 2025-08-26T23:22:01.3873977Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 163 <- wrt source file 2025-08-26T23:22:01.3912224Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout2d:0 2025-08-26T23:22:01.3912911Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 211 <- wrt source file 2025-08-26T23:22:01.4002239Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout3d:0 2025-08-26T23:22:01.4003118Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 257 <- wrt source file 2025-08-26T23:22:01.4005712Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0 2025-08-26T23:22:01.4006686Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 309 <- wrt source file 2025-08-26T23:22:01.4232556Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0 2025-08-26T23:22:01.4233749Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file 2025-08-26T23:22:01.4236483Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Threshold:0 2025-08-26T23:22:01.4237593Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU:0, line 120 <- wrt source file 2025-08-26T23:22:01.4241690Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU:0 2025-08-26T23:22:01.4242322Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::RReLU:0, line 185 <- wrt source file 2025-08-26T23:22:01.4246491Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::RReLU:0 2025-08-26T23:22:01.4246920Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 247 <- wrt source file 2025-08-26T23:22:01.4249250Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardtanh:0 2025-08-26T23:22:01.4249675Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 318 <- wrt source file 2025-08-26T23:22:01.4251556Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU6:0 2025-08-26T23:22:01.4252074Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 349 <- wrt source file 2025-08-26T23:22:01.4253919Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Sigmoid:0 2025-08-26T23:22:01.4254393Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 384 <- wrt source file 2025-08-26T23:22:01.4256242Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0 2025-08-26T23:22:01.4256667Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanh:0, line 420 <- wrt source file 2025-08-26T23:22:01.4258708Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanh:0 2025-08-26T23:22:01.4259125Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::SiLU:0, line 456 <- wrt source file 2025-08-26T23:22:01.4261570Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::SiLU:0 2025-08-26T23:22:01.4262354Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Mish:0, line 501 <- wrt source file 2025-08-26T23:22:01.4264570Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Mish:0 2025-08-26T23:22:01.4265202Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 552 <- wrt source file 2025-08-26T23:22:01.4265860Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardswish:0 2025-08-26T23:22:01.4266662Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ELU:0, line 598 <- wrt source file 2025-08-26T23:22:01.4268065Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::ELU:0 2025-08-26T23:22:01.4268754Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::CELU:0, line 646 <- wrt source file 2025-08-26T23:22:01.4270997Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::CELU:0 2025-08-26T23:22:01.4271879Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::SELU:0, line 705 <- wrt source file 2025-08-26T23:22:01.4272493Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::SELU:0 2025-08-26T23:22:01.4273355Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::GLU:0, line 751 <- wrt source file 2025-08-26T23:22:01.4274335Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::GLU:0 2025-08-26T23:22:01.4275067Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::GELU:0, line 799 <- wrt source file 2025-08-26T23:22:01.4332118Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::GELU:0 2025-08-26T23:22:01.4333333Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 848 <- wrt source file 2025-08-26T23:22:01.4334684Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardshrink:0 2025-08-26T23:22:01.4336663Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 903 <- wrt source file 2025-08-26T23:22:01.4338492Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LeakyReLU:0 2025-08-26T23:22:01.4339603Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 945 <- wrt source file 2025-08-26T23:22:01.4401928Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSigmoid:0 2025-08-26T23:22:01.4403599Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softplus:0, line 981 <- wrt source file 2025-08-26T23:22:01.4405155Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softplus:0 2025-08-26T23:22:01.4406539Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 1030 <- wrt source file 2025-08-26T23:22:01.4407186Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softshrink:0 2025-08-26T23:22:01.4407835Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1144 <- wrt source file 2025-08-26T23:22:01.4408700Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0 2025-08-26T23:22:01.4409326Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1609 <- wrt source file 2025-08-26T23:22:01.4409939Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::PReLU:0 2025-08-26T23:22:01.4411469Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1660 <- wrt source file 2025-08-26T23:22:01.4412164Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softsign:0 2025-08-26T23:22:01.4412786Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1686 <- wrt source file 2025-08-26T23:22:01.4414997Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanhshrink:0 2025-08-26T23:22:01.4415610Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1724 <- wrt source file 2025-08-26T23:22:01.4472099Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmin:0 2025-08-26T23:22:01.4472707Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1788 <- wrt source file 2025-08-26T23:22:01.4594044Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax:0 2025-08-26T23:22:01.4594760Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1835 <- wrt source file 2025-08-26T23:22:01.4692656Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax2d:0 2025-08-26T23:22:01.4693283Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1874 <- wrt source file 2025-08-26T23:22:01.4793132Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSoftmax:0 2025-08-26T23:22:01.4793748Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file 2025-08-26T23:22:01.4795001Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0 2025-08-26T23:22:01.4795699Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file 2025-08-26T23:22:01.4802619Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding:0 2025-08-26T23:22:01.4803259Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file 2025-08-26T23:22:01.4804929Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0 2025-08-26T23:22:01.4805639Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 521 <- wrt source file 2025-08-26T23:22:01.4808873Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0 2025-08-26T23:22:01.4809542Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 90 <- wrt source file 2025-08-26T23:22:08.3504003Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::Transformer:0 2025-08-26T23:22:08.3504840Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 336 <- wrt source file 2025-08-26T23:22:09.7835904Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0 2025-08-26T23:22:09.7924476Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 562 <- wrt source file 2025-08-26T23:22:12.8825968Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0 2025-08-26T23:22:12.8833279Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 686 <- wrt source file 2025-08-26T23:22:13.1163833Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0 2025-08-26T23:22:13.1165135Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 995 <- wrt source file 2025-08-26T23:22:13.6065419Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0 2025-08-26T23:22:13.6066771Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file 2025-08-26T23:22:13.6162775Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0 2025-08-26T23:22:13.6163411Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 99 <- wrt source file 2025-08-26T23:22:13.6262875Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0 2025-08-26T23:22:13.6270878Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file 2025-08-26T23:22:13.6276272Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::Upsample:0 2025-08-26T23:22:13.6277422Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 229 <- wrt source file 2025-08-26T23:22:13.6282152Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0 2025-08-26T23:22:13.6283203Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 279 <- wrt source file 2025-08-26T23:22:13.6286241Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0 2025-08-26T23:22:13.6287180Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file 2025-08-26T23:22:13.6341830Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0 2025-08-26T23:22:13.6343177Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 207 <- wrt source file 2025-08-26T23:22:13.6452555Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0 2025-08-26T23:22:13.6452991Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 291 <- wrt source file 2025-08-26T23:22:13.7212929Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0 2025-08-26T23:22:13.7213849Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 366 <- wrt source file 2025-08-26T23:22:13.7598958Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0 2025-08-26T23:22:13.7600783Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 550 <- wrt source file 2025-08-26T23:22:13.8161241Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0 2025-08-26T23:22:13.8162163Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 642 <- wrt source file 2025-08-26T23:22:13.8216709Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0 2025-08-26T23:22:13.8217502Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 738 <- wrt source file 2025-08-26T23:22:13.8292127Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0 2025-08-26T23:22:13.8292886Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 855 <- wrt source file 2025-08-26T23:22:13.9472897Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0 2025-08-26T23:22:13.9511290Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 946 <- wrt source file 2025-08-26T23:22:13.9512030Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0 2025-08-26T23:22:13.9512732Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1033 <- wrt source file 2025-08-26T23:22:13.9780133Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0 2025-08-26T23:22:13.9781279Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1152 <- wrt source file 2025-08-26T23:22:13.9971751Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool1d:0 2025-08-26T23:22:13.9972377Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1204 <- wrt source file 2025-08-26T23:22:14.0652918Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool2d:0 2025-08-26T23:22:14.0653542Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1264 <- wrt source file 2025-08-26T23:22:14.2433174Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool3d:0 2025-08-26T23:22:14.2433902Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1320 <- wrt source file 2025-08-26T23:22:14.2492671Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0 2025-08-26T23:22:14.2493356Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1355 <- wrt source file 2025-08-26T23:22:14.2702215Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0 2025-08-26T23:22:14.2702919Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1399 <- wrt source file 2025-08-26T23:22:14.2972369Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0 2025-08-26T23:22:14.2973329Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1447 <- wrt source file 2025-08-26T23:22:14.3042369Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0 2025-08-26T23:22:14.3043076Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1481 <- wrt source file 2025-08-26T23:22:14.3324590Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0 2025-08-26T23:22:14.3325295Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1521 <- wrt source file 2025-08-26T23:22:14.3563085Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0 2025-08-26T23:22:14.3563789Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file 2025-08-26T23:22:14.3670987Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0 2025-08-26T23:22:14.3671693Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 115 <- wrt source file 2025-08-26T23:22:14.3679633Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::L1Loss:0 2025-08-26T23:22:14.3680243Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 215 <- wrt source file 2025-08-26T23:22:14.4855496Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::NLLLoss:0 2025-08-26T23:22:14.4856192Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 329 <- wrt source file 2025-08-26T23:22:14.4863567Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0 2025-08-26T23:22:14.4864235Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 418 <- wrt source file 2025-08-26T23:22:14.4876681Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0 2025-08-26T23:22:14.4877212Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 535 <- wrt source file 2025-08-26T23:22:14.5122231Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::KLDivLoss:0 2025-08-26T23:22:14.5122690Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 617 <- wrt source file 2025-08-26T23:22:14.5123178Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MSELoss:0 2025-08-26T23:22:14.5123595Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 703 <- wrt source file 2025-08-26T23:22:14.5124017Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCELoss:0 2025-08-26T23:22:14.5124470Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 778 <- wrt source file 2025-08-26T23:22:14.5205361Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0 2025-08-26T23:22:14.5205815Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 826 <- wrt source file 2025-08-26T23:22:14.5273567Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1 2025-08-26T23:22:14.5274030Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 974 <- wrt source file 2025-08-26T23:22:14.5279199Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0 2025-08-26T23:22:14.5279659Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1306 <- wrt source file 2025-08-26T23:22:14.5732818Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0 2025-08-26T23:22:14.5733276Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1, line 1333 <- wrt source file 2025-08-26T23:22:14.5734591Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1 2025-08-26T23:22:14.5735424Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1495 <- wrt source file 2025-08-26T23:22:14.5742075Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0 2025-08-26T23:22:14.5743425Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1562 <- wrt source file 2025-08-26T23:22:14.5748274Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0 2025-08-26T23:22:14.5749728Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1643 <- wrt source file 2025-08-26T23:22:14.5755718Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0 2025-08-26T23:22:14.5757044Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1745 <- wrt source file 2025-08-26T23:22:14.5765289Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0 2025-08-26T23:22:14.5769760Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file 2025-08-26T23:22:14.5771557Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0 2025-08-26T23:22:14.5772865Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 81 <- wrt source file 2025-08-26T23:22:14.5777143Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0 2025-08-26T23:22:14.5778136Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNN:0, line 595 <- wrt source file 2025-08-26T23:22:14.6763278Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNN:0 2025-08-26T23:22:14.6781941Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 953 <- wrt source file 2025-08-26T23:22:14.8172500Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTM:0 2025-08-26T23:22:14.8172963Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1288 <- wrt source file 2025-08-26T23:22:14.9133182Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRU:0 2025-08-26T23:22:14.9138756Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1537 <- wrt source file 2025-08-26T23:22:15.0254541Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNNCell:0 2025-08-26T23:22:15.0255003Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1659 <- wrt source file 2025-08-26T23:22:15.0603400Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTMCell:0 2025-08-26T23:22:15.0603949Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1773 <- wrt source file 2025-08-26T23:22:15.1715342Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRUCell:0 2025-08-26T23:22:15.1715912Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 187 <- wrt source file 2025-08-26T23:22:15.1963016Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0 2025-08-26T23:22:15.1963512Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 303 <- wrt source file 2025-08-26T23:22:15.2284126Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0 2025-08-26T23:22:15.2290436Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 419 <- wrt source file 2025-08-26T23:22:15.3347735Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0 2025-08-26T23:22:15.3349270Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file 2025-08-26T23:22:15.3393421Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Identity:0 2025-08-26T23:22:15.3394195Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Linear:0, line 83 <- wrt source file 2025-08-26T23:22:15.3415443Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Linear:0 2025-08-26T23:22:15.3415878Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 191 <- wrt source file 2025-08-26T23:22:16.0156715Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/linear.py::Bilinear:0 2025-08-26T23:22:16.0157251Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 332 <- wrt source file 2025-08-26T23:22:16.0551839Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0 2025-08-26T23:22:16.0552336Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 443 <- wrt source file 2025-08-26T23:22:16.0915979Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0 2025-08-26T23:22:16.0916432Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 554 <- wrt source file 2025-08-26T23:22:16.2186383Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0 2025-08-26T23:22:16.2187261Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file 2025-08-26T23:22:16.3435114Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0 2025-08-26T23:22:16.3435631Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 163 <- wrt source file 2025-08-26T23:22:16.3642436Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LayerNorm:0 2025-08-26T23:22:16.3644149Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 274 <- wrt source file 2025-08-26T23:22:16.3744167Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::GroupNorm:0 2025-08-26T23:22:16.3745163Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 367 <- wrt source file 2025-08-26T23:22:16.3746828Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/normalization.py::RMSNorm:0 2025-08-26T23:22:16.3747966Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 30 <- wrt source file 2025-08-26T23:22:16.3750006Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/flatten.py::Flatten:0 2025-08-26T23:22:16.3751412Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file 2025-08-26T23:22:16.3752224Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential:0 2025-08-26T23:22:16.3752959Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 260 <- wrt source file 2025-08-26T23:22:16.3756050Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.append:0 2025-08-26T23:22:16.3762606Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 283 <- wrt source file 2025-08-26T23:22:16.3763109Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.insert:0 2025-08-26T23:22:16.3763583Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 314 <- wrt source file 2025-08-26T23:22:16.3766520Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.extend:0 2025-08-26T23:22:16.3767003Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleList:0, line 343 <- wrt source file 2025-08-26T23:22:16.3767734Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleList:0 2025-08-26T23:22:16.3768199Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 523 <- wrt source file 2025-08-26T23:22:16.3768670Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleDict:0 2025-08-26T23:22:16.3769438Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterList:0, line 653 <- wrt source file 2025-08-26T23:22:16.3770301Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterList:0 2025-08-26T23:22:16.3773477Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 808 <- wrt source file 2025-08-26T23:22:16.3773950Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterDict:0 2025-08-26T23:22:16.3774374Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file 2025-08-26T23:22:16.3774792Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/fold.py::Fold:0 2025-08-26T23:22:16.3775192Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/fold.py::Unfold:0, line 395 <- wrt source file 2025-08-26T23:22:16.4161091Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/fold.py::Unfold:0 2025-08-26T23:22:16.4162579Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file 2025-08-26T23:22:16.4167359Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0 2025-08-26T23:22:16.4168314Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 346 <- wrt source file 2025-08-26T23:22:16.4172808Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0 2025-08-26T23:22:16.4178769Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 265 <- wrt source file 2025-08-26T23:22:16.4179250Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0 2025-08-26T23:22:16.4179921Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 360 <- wrt source file 2025-08-26T23:22:16.4182257Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0 2025-08-26T23:22:16.4182966Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 591 <- wrt source file 2025-08-26T23:22:16.4183556Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0 2025-08-26T23:22:16.4184160Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file 2025-08-26T23:22:16.4196912Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/init.py::skip_init:0 2025-08-26T23:22:16.4197382Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file 2025-08-26T23:22:16.4197867Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0 2025-08-26T23:22:16.4198304Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 439 <- wrt source file 2025-08-26T23:22:16.4198763Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pad_sequence:0 2025-08-26T23:22:16.4199181Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 500 <- wrt source file 2025-08-26T23:22:16.4492813Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0 2025-08-26T23:22:16.4496266Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 556 <- wrt source file 2025-08-26T23:22:16.4496831Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pack_sequence:0 2025-08-26T23:22:16.4497319Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 584 <- wrt source file 2025-08-26T23:22:16.4497822Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0 2025-08-26T23:22:16.4498312Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::identity:0, line 849 <- wrt source file 2025-08-26T23:22:16.4498798Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::identity:0 2025-08-26T23:22:16.4499301Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 885 <- wrt source file 2025-08-26T23:22:16.4499826Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_unstructured:0 2025-08-26T23:22:16.4515161Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 928 <- wrt source file 2025-08-26T23:22:16.4517087Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::l1_unstructured:0 2025-08-26T23:22:16.4523669Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_structured:0, line 968 <- wrt source file 2025-08-26T23:22:16.4524376Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_structured:0 2025-08-26T23:22:16.4525027Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::remove:0, line 1197 <- wrt source file 2025-08-26T23:22:16.4525920Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::remove:0 2025-08-26T23:22:16.4526421Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1225 <- wrt source file 2025-08-26T23:22:16.4527683Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py::is_pruned:0 2025-08-26T23:22:16.4528132Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 196 <- wrt source file 2025-08-26T23:22:16.4530037Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/stateless.py::functional_call:0 2025-08-26T23:22:16.4530639Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file 2025-08-26T23:22:16.4574678Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0 2025-08-26T23:22:16.4611328Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file 2025-08-26T23:22:16.4773605Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0 2025-08-26T23:22:16.4774318Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file 2025-08-26T23:22:16.4775048Z * SKIPPED: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0 2025-08-26T23:22:16.4776012Z * DOCTEST : /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0, line 178 <- wrt source file 2025-08-26T23:22:16.4777215Z * SUCCESS: /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0 2025-08-26T23:22:16.4811421Z ============ 2025-08-26T23:22:16.4811676Z Finished doctests 2025-08-26T23:22:16.4811824Z 338 / 731 passed 2025-08-26T23:22:16.4816834Z  2025-08-26T23:22:16.4817022Z === Found 146 parse-time warnings === 2025-08-26T23:22:16.4817213Z --- Parse Warning: 1 / 146 --- 2025-08-26T23:22:16.4827404Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=565. 2025-08-26T23:22:16.4827854Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4828049Z 2025-08-26T23:22:16.4828186Z Load a model from a github repo or a local directory. 2025-08-26T23:22:16.4828327Z 2025-08-26T23:22:16.4828468Z Note: Loading a model is the typical use case, but this can also be used to 2025-08-26T23:22:16.4828682Z for loading other objects such as tokenizers, loss functions, etc. 2025-08-26T23:22:16.4828839Z 2025-08-26T23:22:16.4832602Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-08-26T23:22:16.4832803Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-08-26T23:22:16.4832961Z ref (a tag or a branch). 2025-08-26T23:22:16.4833071Z 2025-08-26T23:22:16.4833188Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-08-26T23:22:16.4833333Z path to a local directory. 2025-08-26T23:22:16.4833441Z 2025-08-26T23:22:16.4833523Z Args: 2025-08-26T23:22:16.4833634Z repo_or_dir (str): If ``source`` is 'github', 2025-08-26T23:22:16.4834037Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-08-26T23:22:16.4834294Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-08-26T23:22:16.4834653Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-08-26T23:22:16.4834876Z If ``source`` is 'local' then it should be a path to a local directory. 2025-08-26T23:22:16.4835138Z model (str): the name of a callable (entrypoint) defined in the 2025-08-26T23:22:16.4835306Z repo/dir's ``hubconf.py``. 2025-08-26T23:22:16.4835469Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T23:22:16.4835658Z source (str, optional): 'github' or 'local'. Specifies how 2025-08-26T23:22:16.4835855Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-08-26T23:22:16.4836045Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-08-26T23:22:16.4836270Z This parameter was introduced in v1.12 and helps ensuring that users 2025-08-26T23:22:16.4836454Z only run code from repos that they trust. 2025-08-26T23:22:16.4836585Z 2025-08-26T23:22:16.4836713Z - If ``False``, a prompt will ask the user whether the repo should 2025-08-26T23:22:16.4836875Z be trusted. 2025-08-26T23:22:16.4837019Z - If ``True``, the repo will be added to the trusted list and loaded 2025-08-26T23:22:16.4837186Z without requiring explicit confirmation. 2025-08-26T23:22:16.4840618Z - If ``"check"``, the repo will be checked against the list of 2025-08-26T23:22:16.4840833Z trusted repos in the cache. If it is not present in that list, the 2025-08-26T23:22:16.4841027Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-08-26T23:22:16.4841276Z - If ``None``: this will raise a warning, inviting the user to set 2025-08-26T23:22:16.4841583Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-08-26T23:22:16.4841769Z is only present for backward compatibility and will be removed in 2025-08-26T23:22:16.4841916Z v2.0. 2025-08-26T23:22:16.4842006Z 2025-08-26T23:22:16.4842133Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-08-26T23:22:16.4842336Z force_reload (bool, optional): whether to force a fresh download of 2025-08-26T23:22:16.4842524Z the github repo unconditionally. Does not have any effect if 2025-08-26T23:22:16.4842685Z ``source = 'local'``. Default is ``False``. 2025-08-26T23:22:16.4842846Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-08-26T23:22:16.4843042Z local caches. Note that the message about first download cannot be 2025-08-26T23:22:16.4843223Z muted. Does not have any effect if ``source = 'local'``. 2025-08-26T23:22:16.4843368Z Default is ``True``. 2025-08-26T23:22:16.4843554Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-08-26T23:22:16.4843799Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-08-26T23:22:16.4844048Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-08-26T23:22:16.4844254Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-08-26T23:22:16.4844444Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T23:22:16.4844608Z 2025-08-26T23:22:16.4844697Z Returns: 2025-08-26T23:22:16.4844821Z The output of the ``model`` callable when called with the given 2025-08-26T23:22:16.4844966Z ``*args`` and ``**kwargs``. 2025-08-26T23:22:16.4845086Z 2025-08-26T23:22:16.4845162Z Example: 2025-08-26T23:22:16.4845295Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:22:16.4845428Z >>> # from a github repo 2025-08-26T23:22:16.4845548Z >>> repo = "pytorch/vision" 2025-08-26T23:22:16.4845666Z >>> model = torch.hub.load( 2025-08-26T23:22:16.4845818Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-08-26T23:22:16.4845958Z ... ) 2025-08-26T23:22:16.4846050Z >>> # from a local directory 2025-08-26T23:22:16.4846206Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T23:22:16.4846342Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.4846502Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-08-26T23:22:16.4846659Z 2025-08-26T23:22:16.4846799Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4846961Z 2025-08-26T23:22:16.4847048Z warnings.warn(msg) 2025-08-26T23:22:16.4847143Z 2025-08-26T23:22:16.4847288Z --- Parse Warning: 2 / 146 --- 2025-08-26T23:22:16.4847661Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=657. 2025-08-26T23:22:16.4848071Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4848242Z 2025-08-26T23:22:16.4851175Z Load a model from a local directory with a ``hubconf.py``. 2025-08-26T23:22:16.4851352Z 2025-08-26T23:22:16.4851424Z Args: 2025-08-26T23:22:16.4851547Z hubconf_dir (str): path to a local directory that contains a 2025-08-26T23:22:16.4851694Z ``hubconf.py``. 2025-08-26T23:22:16.4851839Z model (str): name of an entrypoint defined in the directory's 2025-08-26T23:22:16.4851980Z ``hubconf.py``. 2025-08-26T23:22:16.4852115Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T23:22:16.4852360Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T23:22:16.4852525Z 2025-08-26T23:22:16.4852606Z Returns: 2025-08-26T23:22:16.4852718Z a single model with corresponding pretrained weights. 2025-08-26T23:22:16.4852861Z 2025-08-26T23:22:16.4852933Z Example: 2025-08-26T23:22:16.4853027Z >>> # xdoctest: +SKIP("stub local path") 2025-08-26T23:22:16.4853172Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T23:22:16.4853303Z >>> model = _load_local( 2025-08-26T23:22:16.4853408Z ... path, 2025-08-26T23:22:16.4853505Z ... "resnet50", 2025-08-26T23:22:16.4853621Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-08-26T23:22:16.4853742Z ... ) 2025-08-26T23:22:16.4853825Z 2025-08-26T23:22:16.4853961Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4854122Z 2025-08-26T23:22:16.4854200Z warnings.warn(msg) 2025-08-26T23:22:16.4854304Z 2025-08-26T23:22:16.4854427Z --- Parse Warning: 3 / 146 --- 2025-08-26T23:22:16.4854801Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=696. 2025-08-26T23:22:16.4855204Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4855394Z Download object at the given URL to a local path. 2025-08-26T23:22:16.4855520Z 2025-08-26T23:22:16.4855590Z Args: 2025-08-26T23:22:16.4855687Z url (str): URL of the object to download 2025-08-26T23:22:16.4855863Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-08-26T23:22:16.4856100Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-08-26T23:22:16.4856321Z Default: None 2025-08-26T23:22:16.4856481Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-08-26T23:22:16.4856649Z Default: True 2025-08-26T23:22:16.4856743Z 2025-08-26T23:22:16.4856816Z Example: 2025-08-26T23:22:16.4856926Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:22:16.4857062Z >>> # xdoctest: +REQUIRES(POSIX) 2025-08-26T23:22:16.4857185Z >>> torch.hub.download_url_to_file( 2025-08-26T23:22:16.4857393Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-08-26T23:22:16.4857551Z ... "/tmp/temporary_file", 2025-08-26T23:22:16.4857662Z ... ) 2025-08-26T23:22:16.4857746Z 2025-08-26T23:22:16.4857822Z 2025-08-26T23:22:16.4857957Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4858113Z 2025-08-26T23:22:16.4858194Z warnings.warn(msg) 2025-08-26T23:22:16.4858301Z 2025-08-26T23:22:16.4858420Z --- Parse Warning: 4 / 146 --- 2025-08-26T23:22:16.4858809Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/hub.py line=821. 2025-08-26T23:22:16.4859247Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4859438Z Loads the Torch serialized object at the given URL. 2025-08-26T23:22:16.4859566Z 2025-08-26T23:22:16.4859680Z If downloaded file is a zip file, it will be automatically 2025-08-26T23:22:16.4859826Z decompressed. 2025-08-26T23:22:16.4859921Z 2025-08-26T23:22:16.4860040Z If the object is already present in `model_dir`, it's deserialized and 2025-08-26T23:22:16.4860193Z returned. 2025-08-26T23:22:16.4860324Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-08-26T23:22:16.4860659Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-08-26T23:22:16.4860803Z 2025-08-26T23:22:16.4860876Z Args: 2025-08-26T23:22:16.4860976Z url (str): URL of the object to download 2025-08-26T23:22:16.4861139Z model_dir (str, optional): directory in which to save the object 2025-08-26T23:22:16.4861369Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-08-26T23:22:16.4861626Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-08-26T23:22:16.4861794Z Default: True 2025-08-26T23:22:16.4861980Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-08-26T23:22:16.4862212Z ``filename-.ext`` where ```` is the first eight or more 2025-08-26T23:22:16.4865523Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-08-26T23:22:16.4865730Z ensure unique names and to verify the contents of the file. 2025-08-26T23:22:16.4865882Z Default: False 2025-08-26T23:22:16.4866066Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-08-26T23:22:16.4866336Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-08-26T23:22:16.4866583Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-08-26T23:22:16.4866743Z 2025-08-26T23:22:16.4866821Z Example: 2025-08-26T23:22:16.4866931Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T23:22:16.4867076Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-08-26T23:22:16.4867260Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-08-26T23:22:16.4867456Z ... ) 2025-08-26T23:22:16.4867546Z 2025-08-26T23:22:16.4867619Z 2025-08-26T23:22:16.4867756Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4867916Z 2025-08-26T23:22:16.4867998Z warnings.warn(msg) 2025-08-26T23:22:16.4868094Z 2025-08-26T23:22:16.4868207Z --- Parse Warning: 5 / 146 --- 2025-08-26T23:22:16.4868607Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py line=1493. 2025-08-26T23:22:16.4869030Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4869193Z 2025-08-26T23:22:16.4869280Z dim_order(ambiguity_check=False) -> tuple 2025-08-26T23:22:16.4869393Z 2025-08-26T23:22:16.4869524Z Returns the uniquely determined tuple of int describing the dim order or 2025-08-26T23:22:16.4869693Z physical layout of :attr:`self`. 2025-08-26T23:22:16.4869803Z 2025-08-26T23:22:16.4869934Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-08-26T23:22:16.4870140Z starting from the outermost to the innermost dimension. 2025-08-26T23:22:16.4870273Z 2025-08-26T23:22:16.4870493Z Note that the dim order may not always be uniquely determined. 2025-08-26T23:22:16.4870745Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-08-26T23:22:16.4871055Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-08-26T23:22:16.4871329Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-08-26T23:22:16.4871565Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-08-26T23:22:16.4871762Z Otherwise, it will raise TypeError. 2025-08-26T23:22:16.4871911Z 2025-08-26T23:22:16.4872001Z Args: 2025-08-26T23:22:16.4872160Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-08-26T23:22:16.4872338Z 2025-08-26T23:22:16.4872427Z Examples:: 2025-08-26T23:22:16.4872508Z 2025-08-26T23:22:16.4872599Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-08-26T23:22:16.4872712Z (0, 1, 2, 3) 2025-08-26T23:22:16.4872830Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-08-26T23:22:16.4872956Z (0, 2, 1, 3) 2025-08-26T23:22:16.4873084Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-08-26T23:22:16.4873233Z (0, 2, 3, 1) 2025-08-26T23:22:16.4873338Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-08-26T23:22:16.4873451Z (0, 1, 2, 3) 2025-08-26T23:22:16.4873537Z >>> try: 2025-08-26T23:22:16.4873663Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-08-26T23:22:16.4873812Z ... except RuntimeError as e: 2025-08-26T23:22:16.4873956Z ... print(e) 2025-08-26T23:22:16.4874124Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-08-26T23:22:16.4874317Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-08-26T23:22:16.4874581Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-08-26T23:22:16.4874750Z ... ) # It can be mapped to contiguous format 2025-08-26T23:22:16.4874874Z (0, 1, 2, 3) 2025-08-26T23:22:16.4874965Z >>> try: 2025-08-26T23:22:16.4875081Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-08-26T23:22:16.4875234Z ... except TypeError as e: 2025-08-26T23:22:16.4875347Z ... print(e) 2025-08-26T23:22:16.4875497Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-08-26T23:22:16.4875689Z 2025-08-26T23:22:16.4875772Z .. warning:: 2025-08-26T23:22:16.4875909Z The dim_order tensor API is experimental and subject to change. 2025-08-26T23:22:16.4876060Z 2025-08-26T23:22:16.4876200Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4876357Z 2025-08-26T23:22:16.4876434Z warnings.warn(msg) 2025-08-26T23:22:16.4876529Z 2025-08-26T23:22:16.4876646Z --- Parse Warning: 6 / 146 --- 2025-08-26T23:22:16.4877069Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py line=397. 2025-08-26T23:22:16.4877475Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4877691Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-08-26T23:22:16.4877847Z 2025-08-26T23:22:16.4877971Z This is helpful when you want to visualize data over some 2025-08-26T23:22:16.4878147Z range of inputs. See below for a plotting example. 2025-08-26T23:22:16.4878282Z 2025-08-26T23:22:16.4878400Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-08-26T23:22:16.4878575Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-08-26T23:22:16.4878767Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-08-26T23:22:16.4878948Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-08-26T23:22:16.4879121Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-08-26T23:22:16.4879292Z to the result shape. 2025-08-26T23:22:16.4879411Z 2025-08-26T23:22:16.4879495Z .. note:: 2025-08-26T23:22:16.4879638Z 0D inputs are treated equivalently to 1D inputs of a 2025-08-26T23:22:16.4888031Z single element. 2025-08-26T23:22:16.4888209Z 2025-08-26T23:22:16.4888375Z .. warning:: 2025-08-26T23:22:16.4888506Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-08-26T23:22:16.4888675Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-08-26T23:22:16.4888807Z 2025-08-26T23:22:16.4888909Z In the future `torch.meshgrid` will transition to 2025-08-26T23:22:16.4889050Z `indexing='xy'` as the default. 2025-08-26T23:22:16.4889163Z 2025-08-26T23:22:16.4889271Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-08-26T23:22:16.4889442Z this issue with the goal of migrating to NumPy's behavior. 2025-08-26T23:22:16.4889576Z 2025-08-26T23:22:16.4889653Z .. seealso:: 2025-08-26T23:22:16.4889746Z 2025-08-26T23:22:16.4889854Z :func:`torch.cartesian_prod` has the same effect but it 2025-08-26T23:22:16.4890007Z collects the data in a tensor of vectors. 2025-08-26T23:22:16.4890124Z 2025-08-26T23:22:16.4890196Z Args: 2025-08-26T23:22:16.4890460Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-08-26T23:22:16.4890661Z treated as tensors of size :math:`(1,)` automatically 2025-08-26T23:22:16.4890788Z 2025-08-26T23:22:16.4890900Z indexing: (str, optional): the indexing mode, either "xy" 2025-08-26T23:22:16.4891072Z or "ij", defaults to "ij". See warning for future changes. 2025-08-26T23:22:16.4891199Z 2025-08-26T23:22:16.4891302Z If "xy" is selected, the first dimension corresponds 2025-08-26T23:22:16.4891452Z to the cardinality of the second input and the second 2025-08-26T23:22:16.4891620Z dimension corresponds to the cardinality of the first 2025-08-26T23:22:16.4891759Z input. 2025-08-26T23:22:16.4891903Z 2025-08-26T23:22:16.4892005Z If "ij" is selected, the dimensions are in the same 2025-08-26T23:22:16.4892159Z order as the cardinality of the inputs. 2025-08-26T23:22:16.4892289Z 2025-08-26T23:22:16.4892371Z Returns: 2025-08-26T23:22:16.4892504Z seq (sequence of Tensors): If the input has :math:`N` 2025-08-26T23:22:16.4892678Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-08-26T23:22:16.4892869Z output will also have :math:`N` tensors, where each tensor 2025-08-26T23:22:16.4893025Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-08-26T23:22:16.4893145Z 2025-08-26T23:22:16.4893236Z Example:: 2025-08-26T23:22:16.4893335Z 2025-08-26T23:22:16.4893427Z >>> x = torch.tensor([1, 2, 3]) 2025-08-26T23:22:16.4893571Z >>> y = torch.tensor([4, 5, 6]) 2025-08-26T23:22:16.4893713Z 2025-08-26T23:22:16.4893833Z Observe the element-wise pairings across the grid, (1, 4), 2025-08-26T23:22:16.4894038Z (1, 5), ..., (3, 6). This is the same thing as the 2025-08-26T23:22:16.4894181Z cartesian product. 2025-08-26T23:22:16.4894327Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-08-26T23:22:16.4894464Z >>> grid_x 2025-08-26T23:22:16.4894565Z tensor([[1, 1, 1], 2025-08-26T23:22:16.4894674Z [2, 2, 2], 2025-08-26T23:22:16.4894784Z [3, 3, 3]]) 2025-08-26T23:22:16.4894892Z >>> grid_y 2025-08-26T23:22:16.4894987Z tensor([[4, 5, 6], 2025-08-26T23:22:16.4895088Z [4, 5, 6], 2025-08-26T23:22:16.4895194Z [4, 5, 6]]) 2025-08-26T23:22:16.4895293Z 2025-08-26T23:22:16.4895399Z This correspondence can be seen when these grids are 2025-08-26T23:22:16.4895541Z stacked properly. 2025-08-26T23:22:16.4895691Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-08-26T23:22:16.4895911Z ... torch.cartesian_prod(x, y)) 2025-08-26T23:22:16.4896049Z True 2025-08-26T23:22:16.4896141Z 2025-08-26T23:22:16.4896250Z `torch.meshgrid` is commonly used to produce a grid for 2025-08-26T23:22:16.4896391Z plotting. 2025-08-26T23:22:16.4896509Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-08-26T23:22:16.4896647Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-08-26T23:22:16.4896783Z >>> import matplotlib.pyplot as plt 2025-08-26T23:22:16.4896918Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-08-26T23:22:16.4897048Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-08-26T23:22:16.4897182Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-08-26T23:22:16.4897325Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-08-26T23:22:16.4897459Z >>> ax = plt.axes(projection='3d') 2025-08-26T23:22:16.4897609Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-08-26T23:22:16.4897743Z >>> plt.show() 2025-08-26T23:22:16.4897860Z 2025-08-26T23:22:16.4897985Z .. image:: ../_static/img/meshgrid.png 2025-08-26T23:22:16.4898115Z :width: 512 2025-08-26T23:22:16.4898232Z 2025-08-26T23:22:16.4898323Z 2025-08-26T23:22:16.4898483Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4898657Z 2025-08-26T23:22:16.4898750Z warnings.warn(msg) 2025-08-26T23:22:16.4898886Z 2025-08-26T23:22:16.4899060Z --- Parse Warning: 7 / 146 --- 2025-08-26T23:22:16.4899443Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/functional.py line=793. 2025-08-26T23:22:16.4899876Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4900145Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-08-26T23:22:16.4900437Z 2025-08-26T23:22:16.4900539Z Returns the unique elements of the input tensor. 2025-08-26T23:22:16.4900664Z 2025-08-26T23:22:16.4900871Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-08-26T23:22:16.4901090Z this function also eliminates non-consecutive duplicate values. 2025-08-26T23:22:16.4901237Z 2025-08-26T23:22:16.4901362Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-08-26T23:22:16.4901581Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-08-26T23:22:16.4901818Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-08-26T23:22:16.4902029Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-08-26T23:22:16.4902169Z 2025-08-26T23:22:16.4902244Z Args: 2025-08-26T23:22:16.4902342Z input (Tensor): the input tensor 2025-08-26T23:22:16.4902501Z sorted (bool): Whether to sort the unique elements in ascending order 2025-08-26T23:22:16.4902662Z before returning as output. 2025-08-26T23:22:16.4902822Z return_inverse (bool): Whether to also return the indices for where 2025-08-26T23:22:16.4903013Z elements in the original input ended up in the returned unique list. 2025-08-26T23:22:16.4903212Z return_counts (bool): Whether to also return the counts for each unique 2025-08-26T23:22:16.4903364Z element. 2025-08-26T23:22:16.4903503Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-08-26T23:22:16.4903692Z unique of the flattened input is returned. Otherwise, each of the 2025-08-26T23:22:16.4903926Z tensors indexed by the given dimension is treated as one of the 2025-08-26T23:22:16.4904112Z elements to apply the unique operation upon. See examples for more 2025-08-26T23:22:16.4904276Z details. Default: ``None`` 2025-08-26T23:22:16.4904385Z 2025-08-26T23:22:16.4904461Z Returns: 2025-08-26T23:22:16.4904619Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-08-26T23:22:16.4904790Z 2025-08-26T23:22:16.4904904Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-08-26T23:22:16.4905070Z - **inverse_indices** (*Tensor*): (optional) if 2025-08-26T23:22:16.4905232Z :attr:`return_inverse` is True, there will be an additional 2025-08-26T23:22:16.4905410Z returned tensor (same shape as input) representing the indices 2025-08-26T23:22:16.4905596Z for where elements in the original input map to in the output; 2025-08-26T23:22:16.4905773Z otherwise, this function will only return a single tensor. 2025-08-26T23:22:16.4905929Z - **counts** (*Tensor*): (optional) if 2025-08-26T23:22:16.4906087Z :attr:`return_counts` is True, there will be an additional 2025-08-26T23:22:16.4906257Z returned tensor (same shape as output or output.size(dim), 2025-08-26T23:22:16.4906429Z if dim was specified) representing the number of occurrences 2025-08-26T23:22:16.4906581Z for each unique value or tensor. 2025-08-26T23:22:16.4906695Z 2025-08-26T23:22:16.4906774Z Example:: 2025-08-26T23:22:16.4906863Z 2025-08-26T23:22:16.4906984Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-08-26T23:22:16.4907135Z >>> output 2025-08-26T23:22:16.4907261Z tensor([1, 2, 3]) 2025-08-26T23:22:16.4907363Z 2025-08-26T23:22:16.4907462Z >>> output, inverse_indices = torch.unique( 2025-08-26T23:22:16.4907639Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T23:22:16.4907799Z >>> output 2025-08-26T23:22:16.4907895Z tensor([1, 2, 3]) 2025-08-26T23:22:16.4908003Z >>> inverse_indices 2025-08-26T23:22:16.4908151Z tensor([0, 2, 1, 2]) 2025-08-26T23:22:16.4908481Z 2025-08-26T23:22:16.4908613Z >>> output, inverse_indices = torch.unique( 2025-08-26T23:22:16.4908879Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T23:22:16.4909077Z >>> output 2025-08-26T23:22:16.4909207Z tensor([1, 2, 3]) 2025-08-26T23:22:16.4909390Z >>> inverse_indices 2025-08-26T23:22:16.4909538Z tensor([[0, 2], 2025-08-26T23:22:16.4909704Z [1, 2]]) 2025-08-26T23:22:16.4909850Z 2025-08-26T23:22:16.4909975Z >>> a = torch.tensor([ 2025-08-26T23:22:16.4910125Z ... [ 2025-08-26T23:22:16.4910271Z ... [1, 1, 0, 0], 2025-08-26T23:22:16.4910547Z ... [1, 1, 0, 0], 2025-08-26T23:22:16.4910754Z ... [0, 0, 1, 1], 2025-08-26T23:22:16.4910895Z ... ], 2025-08-26T23:22:16.4911043Z ... [ 2025-08-26T23:22:16.4911186Z ... [0, 0, 1, 1], 2025-08-26T23:22:16.4911338Z ... [0, 0, 1, 1], 2025-08-26T23:22:16.4911505Z ... [1, 1, 1, 1], 2025-08-26T23:22:16.4911649Z ... ], 2025-08-26T23:22:16.4911777Z ... [ 2025-08-26T23:22:16.4911928Z ... [1, 1, 0, 0], 2025-08-26T23:22:16.4912064Z ... [1, 1, 0, 0], 2025-08-26T23:22:16.4912207Z ... [0, 0, 1, 1], 2025-08-26T23:22:16.4912374Z ... ], 2025-08-26T23:22:16.4912548Z ... ]) 2025-08-26T23:22:16.4912702Z 2025-08-26T23:22:16.4912887Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-08-26T23:22:16.4913119Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-08-26T23:22:16.4913360Z >>> # each other, so one of them will be removed. 2025-08-26T23:22:16.4913538Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-08-26T23:22:16.4913711Z tensor(True) 2025-08-26T23:22:16.4913870Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-08-26T23:22:16.4914042Z >>> a_unique_dim0 2025-08-26T23:22:16.4914203Z tensor([[[0, 0, 1, 1], 2025-08-26T23:22:16.4914344Z [0, 0, 1, 1], 2025-08-26T23:22:16.4914605Z [1, 1, 1, 1]], 2025-08-26T23:22:16.4914787Z [[1, 1, 0, 0], 2025-08-26T23:22:16.4914935Z [1, 1, 0, 0], 2025-08-26T23:22:16.4915090Z [0, 0, 1, 1]]]) 2025-08-26T23:22:16.4915250Z 2025-08-26T23:22:16.4915414Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-08-26T23:22:16.4915623Z >>> # `a_unique_dim0`: 2025-08-26T23:22:16.4915791Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-08-26T23:22:16.4915946Z tensor(True) 2025-08-26T23:22:16.4916124Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-08-26T23:22:16.4916286Z tensor(True) 2025-08-26T23:22:16.4916429Z 2025-08-26T23:22:16.4916614Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-08-26T23:22:16.4916837Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-08-26T23:22:16.4917051Z >>> # them will be removed. 2025-08-26T23:22:16.4917219Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-08-26T23:22:16.4917367Z tensor(True) 2025-08-26T23:22:16.4917568Z >>> torch.unique(a, dim=1) 2025-08-26T23:22:16.4917724Z tensor([[[0, 0, 1, 1], 2025-08-26T23:22:16.4917878Z [1, 1, 0, 0]], 2025-08-26T23:22:16.4918040Z [[1, 1, 1, 1], 2025-08-26T23:22:16.4918180Z [0, 0, 1, 1]], 2025-08-26T23:22:16.4918343Z [[0, 0, 1, 1], 2025-08-26T23:22:16.4918485Z [1, 1, 0, 0]]]) 2025-08-26T23:22:16.4918614Z 2025-08-26T23:22:16.4918829Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-08-26T23:22:16.4919048Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-08-26T23:22:16.4919266Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-08-26T23:22:16.4919466Z >>> # sub-tensors will be removed. 2025-08-26T23:22:16.4919626Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-08-26T23:22:16.4919801Z tensor(True) 2025-08-26T23:22:16.4919945Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-08-26T23:22:16.4920091Z tensor(True) 2025-08-26T23:22:16.4920264Z >>> torch.unique(a, dim=2) 2025-08-26T23:22:16.4920536Z tensor([[[0, 1], 2025-08-26T23:22:16.4920697Z [0, 1], 2025-08-26T23:22:16.4920897Z [1, 0]], 2025-08-26T23:22:16.4921030Z [[1, 0], 2025-08-26T23:22:16.4921189Z [1, 0], 2025-08-26T23:22:16.4921391Z [1, 1]], 2025-08-26T23:22:16.4921520Z [[0, 1], 2025-08-26T23:22:16.4921676Z [0, 1], 2025-08-26T23:22:16.4921805Z [1, 0]]]) 2025-08-26T23:22:16.4921949Z 2025-08-26T23:22:16.4922130Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4922326Z 2025-08-26T23:22:16.4922463Z warnings.warn(msg) 2025-08-26T23:22:16.4922591Z 2025-08-26T23:22:16.4922746Z --- Parse Warning: 8 / 146 --- 2025-08-26T23:22:16.4934314Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/serialization.py line=1285. 2025-08-26T23:22:16.4934751Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4935009Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-08-26T23:22:16.4935193Z 2025-08-26T23:22:16.4935304Z Loads an object saved with :func:`torch.save` from a file. 2025-08-26T23:22:16.4935435Z 2025-08-26T23:22:16.4935565Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-08-26T23:22:16.4935771Z which underlie tensors, specially. They are first deserialized on the 2025-08-26T23:22:16.4935968Z CPU and are then moved to the device they were saved from. If this fails 2025-08-26T23:22:16.4936171Z (e.g. because the run time system doesn't have certain devices), an exception 2025-08-26T23:22:16.4936376Z is raised. However, storages can be dynamically remapped to an alternative 2025-08-26T23:22:16.4936561Z set of devices using the :attr:`map_location` argument. 2025-08-26T23:22:16.4936689Z 2025-08-26T23:22:16.4936815Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-08-26T23:22:16.4937021Z storage with two arguments: storage and location. The storage argument 2025-08-26T23:22:16.4937224Z will be the initial deserialization of the storage, residing on the CPU. 2025-08-26T23:22:16.4937419Z Each serialized storage has a location tag associated with it which 2025-08-26T23:22:16.4937607Z identifies the device it was saved from, and this tag is the second 2025-08-26T23:22:16.4937810Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-08-26T23:22:16.4938047Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-08-26T23:22:16.4938237Z :attr:`map_location` should return either ``None`` or a storage. If 2025-08-26T23:22:16.4938436Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-08-26T23:22:16.4938650Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-08-26T23:22:16.4938885Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-08-26T23:22:16.4939043Z 2025-08-26T23:22:16.4939167Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-08-26T23:22:16.4939377Z a device tag, it indicates the location where all tensors should be loaded. 2025-08-26T23:22:16.4939529Z 2025-08-26T23:22:16.4939665Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-08-26T23:22:16.4939880Z appearing in the file (keys), to ones that specify where to put the 2025-08-26T23:22:16.4940038Z storages (values). 2025-08-26T23:22:16.4940133Z 2025-08-26T23:22:16.4940260Z User extensions can register their own location tags and tagging and 2025-08-26T23:22:16.4940607Z deserialization methods using :func:`torch.serialization.register_package`. 2025-08-26T23:22:16.4940774Z 2025-08-26T23:22:16.4940911Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-08-26T23:22:16.4941071Z 2025-08-26T23:22:16.4941142Z Args: 2025-08-26T23:22:16.4941309Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-08-26T23:22:16.4941533Z or a string or os.PathLike object containing a file name 2025-08-26T23:22:16.4941756Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-08-26T23:22:16.4941974Z locations 2025-08-26T23:22:16.4942144Z pickle_module: module used for unpickling metadata and objects (has to 2025-08-26T23:22:16.4942335Z match the :attr:`pickle_module` used to serialize file) 2025-08-26T23:22:16.4942514Z weights_only: Indicates whether unpickler should be restricted to 2025-08-26T23:22:16.4942694Z loading only tensors, primitive types, dictionaries 2025-08-26T23:22:16.4942877Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-08-26T23:22:16.4943051Z See :ref:`weights-only` for more details. 2025-08-26T23:22:16.4943258Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-08-26T23:22:16.4943536Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-08-26T23:22:16.4943816Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-08-26T23:22:16.4944088Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-08-26T23:22:16.4944358Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-08-26T23:22:16.4944572Z will be lazily loaded when their data is accessed. 2025-08-26T23:22:16.4944761Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-08-26T23:22:16.4944971Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-08-26T23:22:16.4945134Z :attr:`errors=...`. 2025-08-26T23:22:16.4945246Z 2025-08-26T23:22:16.4945332Z .. warning:: 2025-08-26T23:22:16.4945469Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-08-26T23:22:16.4945678Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-08-26T23:22:16.4945889Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-08-26T23:22:16.4946109Z during unpickling. Never load data that could have come from an untrusted 2025-08-26T23:22:16.4946335Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-08-26T23:22:16.4946499Z 2025-08-26T23:22:16.4946572Z .. note:: 2025-08-26T23:22:16.4946741Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-08-26T23:22:16.4946961Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-08-26T23:22:16.4947184Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-08-26T23:22:16.4947353Z 2025-08-26T23:22:16.4947428Z .. note:: 2025-08-26T23:22:16.4947581Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-08-26T23:22:16.4947792Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-08-26T23:22:16.4947988Z when loading files saved by Python 2 in Python 3. If this default 2025-08-26T23:22:16.4948192Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-08-26T23:22:16.4948407Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-08-26T23:22:16.4948614Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-08-26T23:22:16.4948817Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-08-26T23:22:16.4948966Z 2025-08-26T23:22:16.4949041Z Example: 2025-08-26T23:22:16.4949148Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-08-26T23:22:16.4949290Z >>> torch.load("tensors.pt", weights_only=True) 2025-08-26T23:22:16.4949475Z # Load all tensors onto the CPU 2025-08-26T23:22:16.4949594Z >>> torch.load( 2025-08-26T23:22:16.4949705Z ... "tensors.pt", 2025-08-26T23:22:16.4949827Z ... map_location=torch.device("cpu"), 2025-08-26T23:22:16.4949955Z ... weights_only=True, 2025-08-26T23:22:16.4950065Z ... ) 2025-08-26T23:22:16.4950179Z # Load all tensors onto the CPU, using a function 2025-08-26T23:22:16.4950315Z >>> torch.load( 2025-08-26T23:22:16.4950571Z ... "tensors.pt", 2025-08-26T23:22:16.4950700Z ... map_location=lambda storage, loc: storage, 2025-08-26T23:22:16.4950834Z ... weights_only=True, 2025-08-26T23:22:16.4950940Z ... ) 2025-08-26T23:22:16.4951035Z # Load all tensors onto GPU 1 2025-08-26T23:22:16.4951150Z >>> torch.load( 2025-08-26T23:22:16.4951253Z ... "tensors.pt", 2025-08-26T23:22:16.4951387Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-08-26T23:22:16.4951529Z ... weights_only=True, 2025-08-26T23:22:16.4951653Z ... ) # type: ignore[attr-defined] 2025-08-26T23:22:16.4951779Z # Map tensors from GPU 1 to GPU 0 2025-08-26T23:22:16.4951897Z >>> torch.load( 2025-08-26T23:22:16.4951995Z ... "tensors.pt", 2025-08-26T23:22:16.4952116Z ... map_location={"cuda:1": "cuda:0"}, 2025-08-26T23:22:16.4952247Z ... weights_only=True, 2025-08-26T23:22:16.4952353Z ... ) 2025-08-26T23:22:16.4952452Z # Load tensor from io.BytesIO object 2025-08-26T23:22:16.4952634Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-08-26T23:22:16.4952810Z >>> with open("tensor.pt", "rb") as f: 2025-08-26T23:22:16.4952940Z ... buffer = io.BytesIO(f.read()) 2025-08-26T23:22:16.4953103Z >>> torch.load(buffer, weights_only=False) 2025-08-26T23:22:16.4953255Z # Load a module with 'ascii' encoding for unpickling 2025-08-26T23:22:16.4953439Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-08-26T23:22:16.4953635Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-08-26T23:22:16.4953778Z 2025-08-26T23:22:16.4953914Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.4954099Z 2025-08-26T23:22:16.4954179Z warnings.warn(msg) 2025-08-26T23:22:16.4954277Z 2025-08-26T23:22:16.4954408Z --- Parse Warning: 9 / 146 --- 2025-08-26T23:22:16.4954895Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=375. 2025-08-26T23:22:16.4955305Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.4955519Z Registers the function implementation as the fallback for the given key. 2025-08-26T23:22:16.4955672Z 2025-08-26T23:22:16.4955792Z This function only works for a library with global namespace ("_"). 2025-08-26T23:22:16.4955939Z 2025-08-26T23:22:16.4956016Z Args: 2025-08-26T23:22:16.4956170Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-08-26T23:22:16.4956352Z to register a fallthrough. 2025-08-26T23:22:16.4956546Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-08-26T23:22:16.4956760Z the dispatch key that the library was created with. 2025-08-26T23:22:16.4956987Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-08-26T23:22:16.4957289Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-08-26T23:22:16.4957486Z 2025-08-26T23:22:16.4957566Z Example:: 2025-08-26T23:22:16.4957656Z 2025-08-26T23:22:16.4957743Z >>> my_lib = Library("_", "IMPL") 2025-08-26T23:22:16.4957883Z >>> def fallback_kernel(op, *args, **kwargs): 2025-08-26T23:22:16.4958022Z >>> # Handle all autocast ops generically 2025-08-26T23:22:16.4958148Z >>> # ... 2025-08-26T23:22:16.4958270Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T23:22:16.4958393Z 2025-08-26T23:22:16.4958654Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-08-26T23:22:16.4958928Z 2025-08-26T23:22:16.4959018Z my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T23:22:16.4959138Z ^ 2025-08-26T23:22:16.4959223Z warnings.warn(msg) 2025-08-26T23:22:16.4959320Z 2025-08-26T23:22:16.4959435Z --- Parse Warning: 10 / 146 --- 2025-08-26T23:22:16.4959799Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=948. 2025-08-26T23:22:16.4960205Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.4960532Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-08-26T23:22:16.4960683Z 2025-08-26T23:22:16.4960792Z Also sometimes known as a "meta kernel", "abstract impl". 2025-08-26T23:22:16.4960925Z 2025-08-26T23:22:16.4961051Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-08-26T23:22:16.4961252Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-08-26T23:22:16.4961485Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-08-26T23:22:16.4961664Z what the properties of the output Tensors are. 2025-08-26T23:22:16.4961785Z 2025-08-26T23:22:16.4961910Z The FakeTensor implementation has the same signature as the operator. 2025-08-26T23:22:16.4962101Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-08-26T23:22:16.4962309Z implementation, assume that all Tensor inputs to the operator are 2025-08-26T23:22:16.4962509Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-08-26T23:22:16.4962694Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-08-26T23:22:16.4962887Z The FakeTensor implementation must consist of only PyTorch operations 2025-08-26T23:22:16.4963078Z (and may not directly access the storage or data of any input or 2025-08-26T23:22:16.4963238Z intermediate Tensors). 2025-08-26T23:22:16.4963341Z 2025-08-26T23:22:16.4963443Z This API may be used as a decorator (see examples). 2025-08-26T23:22:16.4963567Z 2025-08-26T23:22:16.4963662Z For a detailed guide on custom ops, please see 2025-08-26T23:22:16.4963836Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-08-26T23:22:16.4963985Z 2025-08-26T23:22:16.4964058Z Args: 2025-08-26T23:22:16.4964192Z op_name: Operator name (along with the overload) or OpOverload object. 2025-08-26T23:22:16.4964356Z func: Fake tensor implementation. 2025-08-26T23:22:16.4964508Z lib (Optional[Library]): Library to register the fake tensor to. 2025-08-26T23:22:16.4964683Z allow_override: Flag controlling if we want to override an 2025-08-26T23:22:16.4964851Z existing registered fake impl. This is by default off, 2025-08-26T23:22:16.4965019Z and will error you're trying to register a fake impl to 2025-08-26T23:22:16.4965229Z an operator that already has a fake impl. This also only 2025-08-26T23:22:16.4965392Z applies if the custom operator was not created via 2025-08-26T23:22:16.4965558Z torch.library.custom_op, as overriding and existing fake 2025-08-26T23:22:16.4965712Z impl is already allowed. 2025-08-26T23:22:16.4965822Z 2025-08-26T23:22:16.4965897Z Examples: 2025-08-26T23:22:16.4965988Z >>> import torch 2025-08-26T23:22:16.4966097Z >>> import numpy as np 2025-08-26T23:22:16.4966212Z >>> from torch import Tensor 2025-08-26T23:22:16.4966320Z >>> 2025-08-26T23:22:16.4966441Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T23:22:16.4966624Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-08-26T23:22:16.4966817Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T23:22:16.4967002Z >>> raise NotImplementedError("Implementation goes here") 2025-08-26T23:22:16.4967141Z >>> 2025-08-26T23:22:16.4967257Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-08-26T23:22:16.4967395Z >>> def _(x, weight, bias): 2025-08-26T23:22:16.4967516Z >>> assert x.dim() == 2 2025-08-26T23:22:16.4967636Z >>> assert weight.dim() == 2 2025-08-26T23:22:16.4967758Z >>> assert bias.dim() == 1 2025-08-26T23:22:16.4967887Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T23:22:16.4968024Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T23:22:16.4968160Z >>> assert x.device == weight.device 2025-08-26T23:22:16.4968276Z >>> 2025-08-26T23:22:16.4968373Z >>> return (x @ weight.t()) + bias 2025-08-26T23:22:16.4968505Z >>> 2025-08-26T23:22:16.4968622Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-08-26T23:22:16.4968762Z >>> x = torch.randn(2, 3) 2025-08-26T23:22:16.4968879Z >>> w = torch.randn(3, 3) 2025-08-26T23:22:16.4968994Z >>> b = torch.randn(3) 2025-08-26T23:22:16.4969120Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-08-26T23:22:16.4969241Z >>> 2025-08-26T23:22:16.4969348Z >>> assert y.shape == (2, 3) 2025-08-26T23:22:16.4969456Z >>> 2025-08-26T23:22:16.4969570Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T23:22:16.4969749Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-08-26T23:22:16.4969918Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-08-26T23:22:16.4970047Z >>> x_np = x.numpy(force=True) 2025-08-26T23:22:16.4970177Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T23:22:16.4970322Z >>> return torch.tensor(res, device=x.device) 2025-08-26T23:22:16.4970503Z >>> 2025-08-26T23:22:16.4970618Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-08-26T23:22:16.4970754Z >>> def _(x): 2025-08-26T23:22:16.4970875Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T23:22:16.4971026Z >>> # Since we cannot peek at the data in an fake impl, 2025-08-26T23:22:16.4971183Z >>> # we use the ctx object to construct a new symint that 2025-08-26T23:22:16.4971329Z >>> # represents the data-dependent size. 2025-08-26T23:22:16.4971461Z >>> ctx = torch.library.get_ctx() 2025-08-26T23:22:16.4971588Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T23:22:16.4971712Z >>> shape = [nnz, x.dim()] 2025-08-26T23:22:16.4971850Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T23:22:16.4971983Z >>> return result 2025-08-26T23:22:16.4972134Z >>> 2025-08-26T23:22:16.4972252Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T23:22:16.4972384Z >>> 2025-08-26T23:22:16.4972479Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-08-26T23:22:16.4972646Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-08-26T23:22:16.4972814Z >>> trace.print_readable() 2025-08-26T23:22:16.4972920Z >>> 2025-08-26T23:22:16.4973048Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-08-26T23:22:16.4973194Z 2025-08-26T23:22:16.4973268Z 2025-08-26T23:22:16.4973491Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-08-26T23:22:16.4973733Z 2025-08-26T23:22:16.4973804Z _._ = None 2025-08-26T23:22:16.4973887Z ^ 2025-08-26T23:22:16.4973970Z warnings.warn(msg) 2025-08-26T23:22:16.4974064Z 2025-08-26T23:22:16.4974179Z --- Parse Warning: 11 / 146 --- 2025-08-26T23:22:16.4974550Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1083. 2025-08-26T23:22:16.4974964Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.4975151Z Register a backward formula for this custom op. 2025-08-26T23:22:16.4975271Z 2025-08-26T23:22:16.4988247Z In order for an operator to work with autograd, you need to register 2025-08-26T23:22:16.4988429Z a backward formula: 2025-08-26T23:22:16.4988588Z 1. You must tell us how to compute gradients during the backward pass 2025-08-26T23:22:16.4988755Z by providing us a "backward" function. 2025-08-26T23:22:16.4988970Z 2. If you need any values from the forward to compute gradients, you can 2025-08-26T23:22:16.4989151Z use `setup_context` to save values for backward. 2025-08-26T23:22:16.4989273Z 2025-08-26T23:22:16.4989398Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-08-26T23:22:16.4989590Z - ``grads`` is one or more gradients. The number of gradients matches 2025-08-26T23:22:16.4989744Z the number of outputs of the operator. 2025-08-26T23:22:16.4989930Z The ``ctx`` object is `the same ctx object `_ used by 2025-08-26T23:22:16.4990134Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-08-26T23:22:16.4990320Z same as :meth:`torch.autograd.Function.backward`. 2025-08-26T23:22:16.4990522Z 2025-08-26T23:22:16.4990640Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-08-26T23:22:16.4990834Z Please save quantities needed for backward onto the ``ctx`` object via 2025-08-26T23:22:16.4991042Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-08-26T23:22:16.4991235Z or assigning them as attributes of ``ctx``. If your custom op has 2025-08-26T23:22:16.4991421Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-08-26T23:22:16.4991610Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-08-26T23:22:16.4991745Z 2025-08-26T23:22:16.4991867Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-08-26T23:22:16.4992062Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-08-26T23:22:16.4992263Z not depend on or mutate global state. If you need a non-traceable backward, 2025-08-26T23:22:16.4992462Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-08-26T23:22:16.4992608Z 2025-08-26T23:22:16.4992725Z If you need different autograd behavior on different devices, then we 2025-08-26T23:22:16.4992963Z recommend creating two different custom operators, one for each device 2025-08-26T23:22:16.4993158Z that needs different behavior, and switching between them at runtime. 2025-08-26T23:22:16.4993303Z 2025-08-26T23:22:16.4993378Z Examples: 2025-08-26T23:22:16.4993473Z >>> import torch 2025-08-26T23:22:16.4993580Z >>> import numpy as np 2025-08-26T23:22:16.4993697Z >>> from torch import Tensor 2025-08-26T23:22:16.4993807Z >>> 2025-08-26T23:22:16.4993934Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-08-26T23:22:16.4994090Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-08-26T23:22:16.4994217Z >>> x_np = x.cpu().numpy() 2025-08-26T23:22:16.4994332Z >>> y_np = np.sin(x_np) 2025-08-26T23:22:16.4994528Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T23:22:16.4994657Z >>> 2025-08-26T23:22:16.4994768Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-08-26T23:22:16.4994901Z >>> x, = inputs 2025-08-26T23:22:16.4995017Z >>> ctx.save_for_backward(x) 2025-08-26T23:22:16.4995126Z >>> 2025-08-26T23:22:16.4995215Z >>> def backward(ctx, grad): 2025-08-26T23:22:16.4995330Z >>> x, = ctx.saved_tensors 2025-08-26T23:22:16.4995444Z >>> return grad * x.cos() 2025-08-26T23:22:16.4995551Z >>> 2025-08-26T23:22:16.4995646Z >>> torch.library.register_autograd( 2025-08-26T23:22:16.4995795Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-08-26T23:22:16.4995928Z ... ) 2025-08-26T23:22:16.4996008Z >>> 2025-08-26T23:22:16.4998019Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T23:22:16.4998152Z >>> y = numpy_sin(x) 2025-08-26T23:22:16.4998320Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T23:22:16.4998477Z >>> assert torch.allclose(grad_x, x.cos()) 2025-08-26T23:22:16.4998593Z >>> 2025-08-26T23:22:16.4998691Z >>> # Example with a keyword-only arg 2025-08-26T23:22:16.4998848Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T23:22:16.4999016Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-08-26T23:22:16.4999174Z >>> x_np = x.cpu().numpy() 2025-08-26T23:22:16.4999290Z >>> y_np = x_np * val 2025-08-26T23:22:16.4999422Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T23:22:16.5000913Z >>> 2025-08-26T23:22:16.5001053Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-08-26T23:22:16.5001224Z >>> ctx.val = keyword_only_inputs["val"] 2025-08-26T23:22:16.5001339Z >>> 2025-08-26T23:22:16.5001432Z >>> def backward(ctx, grad): 2025-08-26T23:22:16.5001551Z >>> return grad * ctx.val 2025-08-26T23:22:16.5001656Z >>> 2025-08-26T23:22:16.5001751Z >>> torch.library.register_autograd( 2025-08-26T23:22:16.5001900Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-08-26T23:22:16.5002032Z ... ) 2025-08-26T23:22:16.5002113Z >>> 2025-08-26T23:22:16.5003369Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T23:22:16.5003498Z >>> y = numpy_mul(x, val=3.14) 2025-08-26T23:22:16.5003635Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T23:22:16.5003800Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-08-26T23:22:16.5003929Z 2025-08-26T23:22:16.5004002Z 2025-08-26T23:22:16.5004135Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5004292Z 2025-08-26T23:22:16.5004370Z warnings.warn(msg) 2025-08-26T23:22:16.5004515Z 2025-08-26T23:22:16.5006473Z --- Parse Warning: 12 / 146 --- 2025-08-26T23:22:16.5006850Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1482. 2025-08-26T23:22:16.5007249Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5007456Z Returns the computed kernel for a given operator and dispatch key. 2025-08-26T23:22:16.5007597Z 2025-08-26T23:22:16.5007717Z This function retrieves the kernel that would be executed for a given 2025-08-26T23:22:16.5007914Z operator and dispatch key combination. The returned SafeKernelFunction 2025-08-26T23:22:16.5008102Z can be used to call the kernel in a boxed fashion. The intended use 2025-08-26T23:22:16.5008281Z case for this function is to retrieve the original kernel for a given 2025-08-26T23:22:16.5008472Z dispatch key and then register another kernel to the same dispatch key 2025-08-26T23:22:16.5008648Z that calls into the original kernel for certain cases. 2025-08-26T23:22:16.5008774Z 2025-08-26T23:22:16.5008846Z Args: 2025-08-26T23:22:16.5008969Z op: Operator name (along with the overload) or OpOverload object 2025-08-26T23:22:16.5010547Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-08-26T23:22:16.5010764Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-08-26T23:22:16.5010964Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-08-26T23:22:16.5011099Z 2025-08-26T23:22:16.5011171Z Returns: 2025-08-26T23:22:16.5011310Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-08-26T23:22:16.5011513Z call the kernel. 2025-08-26T23:22:16.5011615Z 2025-08-26T23:22:16.5011690Z Raises: 2025-08-26T23:22:16.5011797Z RuntimeError: If the operator does not exist. 2025-08-26T23:22:16.5011916Z 2025-08-26T23:22:16.5013128Z Example: 2025-08-26T23:22:16.5013229Z >>> # Get the CPU kernel for torch.add 2025-08-26T23:22:16.5013384Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-08-26T23:22:16.5013521Z >>> 2025-08-26T23:22:16.5013641Z >>> # You can also use DispatchKey enum 2025-08-26T23:22:16.5013819Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-08-26T23:22:16.5013981Z >>> 2025-08-26T23:22:16.5014071Z >>> # Or use an OpOverload directly 2025-08-26T23:22:16.5014232Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-08-26T23:22:16.5014380Z >>> 2025-08-26T23:22:16.5014510Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-08-26T23:22:16.5015778Z >>> # Get the original kernel for torch.sin 2025-08-26T23:22:16.5015941Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-08-26T23:22:16.5016087Z >>> 2025-08-26T23:22:16.5016216Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-08-26T23:22:16.5016387Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-08-26T23:22:16.5016519Z >>> if (x < 0).any(): 2025-08-26T23:22:16.5016658Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-08-26T23:22:16.5016797Z >>> else: 2025-08-26T23:22:16.5016902Z >>> return torch.zeros_like(x) 2025-08-26T23:22:16.5017012Z >>> 2025-08-26T23:22:16.5018182Z >>> lib = torch.library.Library("aten", "IMPL") 2025-08-26T23:22:16.5018369Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-08-26T23:22:16.5018620Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T23:22:16.5018796Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-08-26T23:22:16.5018931Z >>> 2025-08-26T23:22:16.5019023Z >>> # Test the conditional behavior 2025-08-26T23:22:16.5019152Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-08-26T23:22:16.5019283Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-08-26T23:22:16.5019405Z >>> torch.sin(x_positive) 2025-08-26T23:22:16.5019518Z tensor([0., 0.]) 2025-08-26T23:22:16.5019621Z >>> torch.sin(x_mixed) 2025-08-26T23:22:16.5020896Z tensor([-0.8415, 0.9093]) 2025-08-26T23:22:16.5021015Z 2025-08-26T23:22:16.5021228Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-08-26T23:22:16.5021467Z 2025-08-26T23:22:16.5021577Z which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T23:22:16.5021712Z ^ 2025-08-26T23:22:16.5021795Z warnings.warn(msg) 2025-08-26T23:22:16.5021888Z 2025-08-26T23:22:16.5022004Z --- Parse Warning: 13 / 146 --- 2025-08-26T23:22:16.5022372Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py line=1571. 2025-08-26T23:22:16.5022775Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5024390Z Given an operator and some sample arguments, tests if the operator is 2025-08-26T23:22:16.5024563Z registered correctly. 2025-08-26T23:22:16.5024661Z 2025-08-26T23:22:16.5024780Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-08-26T23:22:16.5025031Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-08-26T23:22:16.5025235Z and these APIs require that the functions you pass them satisfy certain 2025-08-26T23:22:16.5025432Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-08-26T23:22:16.5025607Z ``opcheck`` tests these metadata and properties. 2025-08-26T23:22:16.5025727Z 2025-08-26T23:22:16.5025812Z Concretely, we test the following: 2025-08-26T23:22:16.5027886Z 2025-08-26T23:22:16.5028008Z - test_schema: If the schema matches the implementation of 2025-08-26T23:22:16.5028194Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-08-26T23:22:16.5028384Z then we check the implementation mutates the Tensor. If the schema 2025-08-26T23:22:16.5028564Z specifies that we return a new Tensor, then we check that the 2025-08-26T23:22:16.5028745Z implementation returns a new Tensor (instead of an existing one or 2025-08-26T23:22:16.5028909Z a view of an existing one). 2025-08-26T23:22:16.5029056Z - test_autograd_registration: If the operator supports training 2025-08-26T23:22:16.5029232Z (autograd): we check that its autograd formula is registered via 2025-08-26T23:22:16.5029414Z torch.library.register_autograd or a manual registration to one 2025-08-26T23:22:16.5029603Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-08-26T23:22:16.5030988Z registrations may lead to undefined behavior. 2025-08-26T23:22:16.5031149Z - test_faketensor: If the operator has a FakeTensor kernel 2025-08-26T23:22:16.5031315Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-08-26T23:22:16.5031491Z but not sufficient) for the operator to work with PyTorch compilation 2025-08-26T23:22:16.5031681Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-08-26T23:22:16.5031915Z (also sometimes known as a meta kernel) was registered for the 2025-08-26T23:22:16.5032090Z operator and that it is correct. This test takes the result of 2025-08-26T23:22:16.5032264Z running the operator on real tensors and the result of running 2025-08-26T23:22:16.5032436Z the operator on FakeTensors and checks that they have the same 2025-08-26T23:22:16.5032598Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-08-26T23:22:16.5032765Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-08-26T23:22:16.5034002Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-08-26T23:22:16.5034182Z This checks that the outputs (and gradients, if applicable) are the 2025-08-26T23:22:16.5034349Z same under eager-mode PyTorch and torch.compile. 2025-08-26T23:22:16.5034602Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-08-26T23:22:16.5034772Z other things it tests are that the operator supports 2025-08-26T23:22:16.5034950Z functionalization and that the backward pass (if it exists) also 2025-08-26T23:22:16.5035115Z supports FakeTensor and functionalization. 2025-08-26T23:22:16.5035232Z 2025-08-26T23:22:16.5035347Z For best results, please call ``opcheck`` multiple times with a 2025-08-26T23:22:16.5035521Z representative set of inputs. If your operator supports 2025-08-26T23:22:16.5035709Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-08-26T23:22:16.5036945Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-08-26T23:22:16.5037124Z use ``opcheck`` with inputs on all supported devices. 2025-08-26T23:22:16.5037249Z 2025-08-26T23:22:16.5037321Z Args: 2025-08-26T23:22:16.5037440Z op: The operator. Must either be a function decorated with 2025-08-26T23:22:16.5037618Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-08-26T23:22:16.5037847Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-08-26T23:22:16.5038005Z args: The args to the operator 2025-08-26T23:22:16.5038128Z kwargs: The kwargs to the operator 2025-08-26T23:22:16.5038275Z test_utils: Tests that we should run. Default: all of them. 2025-08-26T23:22:16.5038430Z Example: ("test_schema", "test_faketensor") 2025-08-26T23:22:16.5039735Z raise_exception: If we should raise an exception on the first 2025-08-26T23:22:16.5039904Z error. If False, we will return a dict with information 2025-08-26T23:22:16.5040046Z on if each test passed or not. 2025-08-26T23:22:16.5040210Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-08-26T23:22:16.5040454Z If specified ``atol`` must also be specified. 2025-08-26T23:22:16.5040614Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T23:22:16.5040787Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T23:22:16.5040966Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-08-26T23:22:16.5041138Z If specified ``rtol`` must also be specified. 2025-08-26T23:22:16.5041295Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T23:22:16.5041461Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T23:22:16.5042647Z 2025-08-26T23:22:16.5042725Z .. warning:: 2025-08-26T23:22:16.5042815Z 2025-08-26T23:22:16.5042937Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-08-26T23:22:16.5043124Z opcheck tests if your usage of torch.library APIs is correct while 2025-08-26T23:22:16.5043309Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-08-26T23:22:16.5043549Z mathematically correct. Use both to test custom ops that support 2025-08-26T23:22:16.5043704Z gradient computation. 2025-08-26T23:22:16.5043806Z 2025-08-26T23:22:16.5043878Z Example: 2025-08-26T23:22:16.5043959Z 2025-08-26T23:22:16.5045099Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5045176Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T23:22:16.5045236Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-08-26T23:22:16.5045284Z >>> x_np = x.numpy(force=True) 2025-08-26T23:22:16.5045323Z >>> z_np = x_np * y 2025-08-26T23:22:16.5045379Z >>> return torch.from_numpy(z_np).to(x.device) 2025-08-26T23:22:16.5045411Z >>> 2025-08-26T23:22:16.5045453Z >>> @numpy_mul.register_fake 2025-08-26T23:22:16.5045492Z >>> def _(x, y): 2025-08-26T23:22:16.5045539Z >>> return torch.empty_like(x) 2025-08-26T23:22:16.5045573Z >>> 2025-08-26T23:22:16.5045626Z >>> def setup_context(ctx, inputs, output): 2025-08-26T23:22:16.5045663Z >>> y, = inputs 2025-08-26T23:22:16.5045703Z >>> ctx.y = y 2025-08-26T23:22:16.5045734Z >>> 2025-08-26T23:22:16.5045775Z >>> def backward(ctx, grad): 2025-08-26T23:22:16.5045820Z >>> return grad * ctx.y, None 2025-08-26T23:22:16.5045852Z >>> 2025-08-26T23:22:16.5045933Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-08-26T23:22:16.5045964Z >>> 2025-08-26T23:22:16.5046005Z >>> sample_inputs = [ 2025-08-26T23:22:16.5047051Z >>> (torch.randn(3), 3.14), 2025-08-26T23:22:16.5047105Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-08-26T23:22:16.5047164Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-08-26T23:22:16.5047268Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-08-26T23:22:16.5047304Z >>> ] 2025-08-26T23:22:16.5047336Z >>> 2025-08-26T23:22:16.5047379Z >>> for args in sample_inputs: 2025-08-26T23:22:16.5047433Z >>> torch.library.opcheck(numpy_mul, args) 2025-08-26T23:22:16.5047463Z 2025-08-26T23:22:16.5047495Z 2025-08-26T23:22:16.5047624Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5047656Z 2025-08-26T23:22:16.5047693Z warnings.warn(msg) 2025-08-26T23:22:16.5047723Z 2025-08-26T23:22:16.5047806Z --- Parse Warning: 14 / 146 --- 2025-08-26T23:22:16.5048141Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_prims_common/__init__.py line=1877. 2025-08-26T23:22:16.5048239Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5048320Z Computes the minimum storage size to hold the given tensor geometry. 2025-08-26T23:22:16.5048351Z 2025-08-26T23:22:16.5048383Z Example 2025-08-26T23:22:16.5048415Z ======= 2025-08-26T23:22:16.5049477Z 2025-08-26T23:22:16.5049563Z This is the size of a newly allocated tensor's storage, in units of elements 2025-08-26T23:22:16.5049593Z 2025-08-26T23:22:16.5049638Z >>> t = torch.empty((10, 20)) 2025-08-26T23:22:16.5049723Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-08-26T23:22:16.5049756Z 200 2025-08-26T23:22:16.5049786Z 2025-08-26T23:22:16.5049829Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:22:16.5049883Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-08-26T23:22:16.5049933Z >>> size = compute_required_storage_length( 2025-08-26T23:22:16.5049987Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-08-26T23:22:16.5050055Z ... ) 2025-08-26T23:22:16.5050097Z >>> size == t.storage().size() 2025-08-26T23:22:16.5050130Z True 2025-08-26T23:22:16.5050160Z 2025-08-26T23:22:16.5050232Z A valid tensor may have a larger storage size, but never smaller 2025-08-26T23:22:16.5050263Z 2025-08-26T23:22:16.5050307Z >>> slice = torch.empty(100)[20:40] 2025-08-26T23:22:16.5050424Z >>> slice.storage().size() 2025-08-26T23:22:16.5050455Z 100 2025-08-26T23:22:16.5050486Z 2025-08-26T23:22:16.5050532Z >>> compute_required_storage_length( 2025-08-26T23:22:16.5051610Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-08-26T23:22:16.5051643Z ... ) 2025-08-26T23:22:16.5051674Z 40 2025-08-26T23:22:16.5051704Z 2025-08-26T23:22:16.5051735Z 2025-08-26T23:22:16.5051824Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5051857Z 2025-08-26T23:22:16.5051897Z warnings.warn(msg) 2025-08-26T23:22:16.5051927Z 2025-08-26T23:22:16.5052001Z --- Parse Warning: 15 / 146 --- 2025-08-26T23:22:16.5052279Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py line=202. 2025-08-26T23:22:16.5052373Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5052435Z Return the sum of each row of the given sparse tensor. 2025-08-26T23:22:16.5052465Z 2025-08-26T23:22:16.5052548Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-08-26T23:22:16.5052624Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-08-26T23:22:16.5052699Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-08-26T23:22:16.5052791Z returns a dense tensor instead of a sparse tensor. 2025-08-26T23:22:16.5052825Z 2025-08-26T23:22:16.5052919Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-08-26T23:22:16.5052990Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-08-26T23:22:16.5053021Z 2025-08-26T23:22:16.5054105Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-08-26T23:22:16.5054223Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-08-26T23:22:16.5054254Z 2025-08-26T23:22:16.5054287Z Args: 2025-08-26T23:22:16.5054336Z input (Tensor): the input sparse tensor 2025-08-26T23:22:16.5054435Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-08-26T23:22:16.5054475Z over all dims. 2025-08-26T23:22:16.5054570Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-08-26T23:22:16.5054623Z Default: dtype of :attr:`input`. 2025-08-26T23:22:16.5054654Z 2025-08-26T23:22:16.5054690Z Example:: 2025-08-26T23:22:16.5054720Z 2025-08-26T23:22:16.5054754Z >>> nnz = 3 2025-08-26T23:22:16.5054794Z >>> dims = [5, 5, 2, 3] 2025-08-26T23:22:16.5054856Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-08-26T23:22:16.5054929Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-08-26T23:22:16.5054978Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-08-26T23:22:16.5055020Z >>> size = torch.Size(dims) 2025-08-26T23:22:16.5055078Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5055130Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-08-26T23:22:16.5055164Z >>> S 2025-08-26T23:22:16.5056206Z tensor(indices=tensor([[2, 0, 3], 2025-08-26T23:22:16.5056250Z [2, 4, 1]]), 2025-08-26T23:22:16.5056352Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-08-26T23:22:16.5056400Z [ 0.3411, 0.0918, -0.2312]], 2025-08-26T23:22:16.5056431Z 2025-08-26T23:22:16.5056476Z [[ 0.5348, 0.0634, -2.0494], 2025-08-26T23:22:16.5056521Z [-0.7125, -1.0646, 2.1844]], 2025-08-26T23:22:16.5056552Z 2025-08-26T23:22:16.5056598Z [[ 0.1276, 0.1874, -0.6334], 2025-08-26T23:22:16.5056646Z [-1.9682, -0.5340, 0.7483]]]), 2025-08-26T23:22:16.5056703Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-08-26T23:22:16.5056734Z 2025-08-26T23:22:16.5056806Z # when sum over only part of sparse_dims, return a sparse tensor 2025-08-26T23:22:16.5056852Z >>> torch.sparse.sum(S, [1, 3]) 2025-08-26T23:22:16.5056897Z tensor(indices=tensor([[0, 2, 3]]), 2025-08-26T23:22:16.5056948Z values=tensor([[-1.4512, 0.4073], 2025-08-26T23:22:16.5056990Z [-0.8901, 0.2017], 2025-08-26T23:22:16.5057035Z [-0.3183, -1.7539]]), 2025-08-26T23:22:16.5057086Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-08-26T23:22:16.5057118Z 2025-08-26T23:22:16.5057178Z # when sum over all sparse dim, return a dense tensor 2025-08-26T23:22:16.5057221Z # with summed dims squeezed 2025-08-26T23:22:16.5058260Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-08-26T23:22:16.5058302Z tensor([-2.6596, -1.1450]) 2025-08-26T23:22:16.5058334Z 2025-08-26T23:22:16.5058425Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5058456Z 2025-08-26T23:22:16.5058493Z warnings.warn(msg) 2025-08-26T23:22:16.5058546Z 2025-08-26T23:22:16.5058620Z --- Parse Warning: 16 / 146 --- 2025-08-26T23:22:16.5058923Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/sparse/__init__.py line=550. 2025-08-26T23:22:16.5059016Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5059102Z Decorate function, to extend gradcheck for sparse tensors. 2025-08-26T23:22:16.5059133Z 2025-08-26T23:22:16.5059213Z Decorator for torch.autograd.gradcheck or its functools.partial 2025-08-26T23:22:16.5059291Z variants that extends the gradcheck function with support to input 2025-08-26T23:22:16.5059356Z functions that operate on or/and return sparse tensors. 2025-08-26T23:22:16.5059387Z 2025-08-26T23:22:16.5059462Z The specified gradcheck function itself is guaranteed to operate 2025-08-26T23:22:16.5059505Z on strided tensors only. 2025-08-26T23:22:16.5059539Z 2025-08-26T23:22:16.5059574Z For example: 2025-08-26T23:22:16.5059605Z 2025-08-26T23:22:16.5059691Z >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck) 2025-08-26T23:22:16.5060787Z >>> x = ( 2025-08-26T23:22:16.5060850Z ... torch.tensor([[0, 1], [2, 3]], dtype=torch.float64) 2025-08-26T23:22:16.5060890Z ... .to_sparse_coo() 2025-08-26T23:22:16.5060936Z ... .requires_grad_(True) 2025-08-26T23:22:16.5060968Z ... ) 2025-08-26T23:22:16.5061019Z >>> gradcheck(lambda x: x.to_sparse_csr(), x) 2025-08-26T23:22:16.5061051Z True 2025-08-26T23:22:16.5061083Z 2025-08-26T23:22:16.5061173Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5061204Z 2025-08-26T23:22:16.5061242Z warnings.warn(msg) 2025-08-26T23:22:16.5061273Z 2025-08-26T23:22:16.5061346Z --- Parse Warning: 17 / 146 --- 2025-08-26T23:22:16.5061679Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/cuda/__init__.py line=434. 2025-08-26T23:22:16.5061768Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5061815Z Retrieves the CUDA runtime API module. 2025-08-26T23:22:16.5061845Z 2025-08-26T23:22:16.5061877Z 2025-08-26T23:22:16.5061966Z This function initializes the CUDA runtime environment if it is not already 2025-08-26T23:22:16.5062049Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-08-26T23:22:16.5062128Z runtime API module provides access to various CUDA runtime functions. 2025-08-26T23:22:16.5063172Z 2025-08-26T23:22:16.5063205Z Args: 2025-08-26T23:22:16.5063238Z ``None`` 2025-08-26T23:22:16.5063269Z 2025-08-26T23:22:16.5063303Z Returns: 2025-08-26T23:22:16.5063361Z module: The CUDA runtime API module (_cudart). 2025-08-26T23:22:16.5063391Z 2025-08-26T23:22:16.5063424Z Raises: 2025-08-26T23:22:16.5063507Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-08-26T23:22:16.5063634Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-08-26T23:22:16.5063665Z 2025-08-26T23:22:16.5063718Z Example of CUDA operations with profiling: 2025-08-26T23:22:16.5063757Z >>> import torch 2025-08-26T23:22:16.5063810Z >>> from torch.cuda import cudart, check_error 2025-08-26T23:22:16.5063848Z >>> import os 2025-08-26T23:22:16.5063880Z >>> 2025-08-26T23:22:16.5063926Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-08-26T23:22:16.5063957Z >>> 2025-08-26T23:22:16.5064011Z >>> def perform_cuda_operations_with_streams(): 2025-08-26T23:22:16.5064093Z >>> stream = torch.cuda.Stream() 2025-08-26T23:22:16.5064140Z >>> with torch.cuda.stream(stream): 2025-08-26T23:22:16.5064192Z >>> x = torch.randn(100, 100, device='cuda') 2025-08-26T23:22:16.5065237Z >>> y = torch.randn(100, 100, device='cuda') 2025-08-26T23:22:16.5065281Z >>> z = torch.mul(x, y) 2025-08-26T23:22:16.5065318Z >>> return z 2025-08-26T23:22:16.5065375Z >>> 2025-08-26T23:22:16.5065420Z >>> torch.cuda.synchronize() 2025-08-26T23:22:16.5065474Z >>> print("====== Start nsys profiling ======") 2025-08-26T23:22:16.5065527Z >>> check_error(cudart().cudaProfilerStart()) 2025-08-26T23:22:16.5065582Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-08-26T23:22:16.5065642Z >>> result = perform_cuda_operations_with_streams() 2025-08-26T23:22:16.5065693Z >>> print("CUDA operations completed.") 2025-08-26T23:22:16.5065759Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-08-26T23:22:16.5065808Z >>> print("====== End nsys profiling ======") 2025-08-26T23:22:16.5065840Z 2025-08-26T23:22:16.5065912Z To run this example and save the profiling information, execute: 2025-08-26T23:22:16.5066045Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T23:22:16.5066076Z 2025-08-26T23:22:16.5066164Z This command profiles the CUDA operations in the provided script and saves 2025-08-26T23:22:16.5066235Z the profiling information to a file named `trace_name.prof`. 2025-08-26T23:22:16.5066320Z The `--profile-from-start off` option ensures that profiling starts only 2025-08-26T23:22:16.5066375Z after the `cudaProfilerStart` call in the script. 2025-08-26T23:22:16.5066456Z The `--csv` and `--print-summary` options format the profiling output as a 2025-08-26T23:22:16.5066538Z CSV file and print a summary, respectively. 2025-08-26T23:22:16.5067632Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-08-26T23:22:16.5067691Z overwrite of the output file if it already exists. 2025-08-26T23:22:16.5067722Z 2025-08-26T23:22:16.5067951Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-08-26T23:22:16.5067983Z 2025-08-26T23:22:16.5068104Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T23:22:16.5068137Z ^ 2025-08-26T23:22:16.5068175Z warnings.warn(msg) 2025-08-26T23:22:16.5068205Z 2025-08-26T23:22:16.5068277Z --- Parse Warning: 18 / 146 --- 2025-08-26T23:22:16.5068573Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py line=101. 2025-08-26T23:22:16.5068667Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5068698Z 2025-08-26T23:22:16.5068780Z Append the given callback function to this ``Future``, which will be run 2025-08-26T23:22:16.5068857Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-08-26T23:22:16.5068932Z the same ``Future``, but the order in which they will be executed cannot 2025-08-26T23:22:16.5069000Z be guaranteed (to enforce a certain order consider chaining: 2025-08-26T23:22:16.5069072Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-08-26T23:22:16.5069149Z is the reference to this ``Future``. The callback function can use the 2025-08-26T23:22:16.5069222Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-08-26T23:22:16.5069327Z already completed, the given callback will be run immediately inline. 2025-08-26T23:22:16.5070411Z 2025-08-26T23:22:16.5070486Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-08-26T23:22:16.5070566Z callback might be invoked while the async kernels that are populating 2025-08-26T23:22:16.5070647Z those tensors haven't yet finished executing on the device. However, the 2025-08-26T23:22:16.5070755Z callback will be invoked with some dedicated streams set as current 2025-08-26T23:22:16.5070830Z (fetched from a global pool) which will be synchronized with those 2025-08-26T23:22:16.5070911Z kernels. Hence any operation performed by the callback on these tensors 2025-08-26T23:22:16.5070986Z will be scheduled on the device after the kernels complete. In other 2025-08-26T23:22:16.5071056Z words, as long as the callback doesn't switch streams, it can safely 2025-08-26T23:22:16.5071138Z manipulate the result without any additional synchronization. This is 2025-08-26T23:22:16.5071203Z similar to the non-blocking behavior of :meth:`wait`. 2025-08-26T23:22:16.5071234Z 2025-08-26T23:22:16.5071308Z Similarly, if the callback returns a value that contains tensors that 2025-08-26T23:22:16.5071378Z reside on a GPU, it can do so even if the kernels that are producing 2025-08-26T23:22:16.5071457Z these tensors are still running on the device, as long as the callback 2025-08-26T23:22:16.5071532Z didn't change streams during its execution. If one wants to change 2025-08-26T23:22:16.5071608Z streams, one must be careful to re-synchronize them with the original 2025-08-26T23:22:16.5071684Z streams, that is, those that were current when the callback was invoked. 2025-08-26T23:22:16.5071716Z 2025-08-26T23:22:16.5071747Z Args: 2025-08-26T23:22:16.5071822Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-08-26T23:22:16.5071868Z the only argument. 2025-08-26T23:22:16.5072937Z 2025-08-26T23:22:16.5072992Z Returns: 2025-08-26T23:22:16.5073059Z A new ``Future`` object that holds the return value of the 2025-08-26T23:22:16.5073126Z ``callback`` and will be marked as completed when the given 2025-08-26T23:22:16.5073167Z ``callback`` finishes. 2025-08-26T23:22:16.5073197Z 2025-08-26T23:22:16.5073265Z .. note:: Note that if the callback function throws, either 2025-08-26T23:22:16.5073343Z through the original future being completed with an exception and 2025-08-26T23:22:16.5073414Z calling ``fut.wait()``, or through other code in the callback, the 2025-08-26T23:22:16.5073487Z future returned by ``then`` will be marked appropriately with the 2025-08-26T23:22:16.5073560Z encountered error. However, if this callback later completes 2025-08-26T23:22:16.5073634Z additional futures, those futures are not marked as completed with 2025-08-26T23:22:16.5073709Z an error and the user is responsible for handling completion/waiting 2025-08-26T23:22:16.5073754Z on those futures independently. 2025-08-26T23:22:16.5073784Z 2025-08-26T23:22:16.5073820Z Example:: 2025-08-26T23:22:16.5073850Z 2025-08-26T23:22:16.5073908Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T23:22:16.5073947Z >>> def callback(fut): 2025-08-26T23:22:16.5074002Z ... print(f"RPC return value is {fut.wait()}.") 2025-08-26T23:22:16.5074049Z >>> fut = torch.futures.Future() 2025-08-26T23:22:16.5075216Z >>> # The inserted callback will print the return value when 2025-08-26T23:22:16.5075266Z >>> # receiving the response from "worker1" 2025-08-26T23:22:16.5075309Z >>> cb_fut = fut.then(callback) 2025-08-26T23:22:16.5075349Z >>> chain_cb_fut = cb_fut.then( 2025-08-26T23:22:16.5075408Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-08-26T23:22:16.5075473Z ... ) 2025-08-26T23:22:16.5075516Z >>> fut.set_result(5) 2025-08-26T23:22:16.5075558Z RPC return value is 5. 2025-08-26T23:22:16.5075598Z Chained cb done. None 2025-08-26T23:22:16.5075628Z 2025-08-26T23:22:16.5075720Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5075750Z 2025-08-26T23:22:16.5075789Z warnings.warn(msg) 2025-08-26T23:22:16.5075819Z 2025-08-26T23:22:16.5075908Z --- Parse Warning: 19 / 146 --- 2025-08-26T23:22:16.5076208Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/futures/__init__.py line=211. 2025-08-26T23:22:16.5076300Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5076331Z 2025-08-26T23:22:16.5076407Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-08-26T23:22:16.5076490Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-08-26T23:22:16.5076534Z cannot be marked completed twice. 2025-08-26T23:22:16.5076566Z 2025-08-26T23:22:16.5077641Z If the result contains tensors that reside on GPUs, this method can be 2025-08-26T23:22:16.5077718Z called even if the asynchronous kernels that are populating those 2025-08-26T23:22:16.5077800Z tensors haven't yet completed running on the device, provided that the 2025-08-26T23:22:16.5077880Z streams on which those kernels were enqueued are set as the current ones 2025-08-26T23:22:16.5077956Z when this method is called. Put simply, it's safe to call this method 2025-08-26T23:22:16.5078033Z immediately after launching those kernels, without any additional 2025-08-26T23:22:16.5078113Z synchronization, as long as one doesn't change streams in between. This 2025-08-26T23:22:16.5078189Z method will record events on all the relevant current streams and will 2025-08-26T23:22:16.5078296Z use them to ensure proper scheduling for all the consumers of this 2025-08-26T23:22:16.5078332Z ``Future``. 2025-08-26T23:22:16.5078363Z 2025-08-26T23:22:16.5078395Z Args: 2025-08-26T23:22:16.5078457Z result (object): the result object of this ``Future``. 2025-08-26T23:22:16.5078488Z 2025-08-26T23:22:16.5078522Z Example:: 2025-08-26T23:22:16.5078553Z 2025-08-26T23:22:16.5078612Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T23:22:16.5078653Z >>> import threading 2025-08-26T23:22:16.5078688Z >>> import time 2025-08-26T23:22:16.5078733Z >>> def slow_set_future(fut, value): 2025-08-26T23:22:16.5078773Z ... time.sleep(0.5) 2025-08-26T23:22:16.5079812Z ... fut.set_result(value) 2025-08-26T23:22:16.5079857Z >>> fut = torch.futures.Future() 2025-08-26T23:22:16.5079898Z >>> t = threading.Thread( 2025-08-26T23:22:16.5079939Z ... target=slow_set_future, 2025-08-26T23:22:16.5079986Z ... args=(fut, torch.ones(2) * 3) 2025-08-26T23:22:16.5080018Z ... ) 2025-08-26T23:22:16.5080052Z >>> t.start() 2025-08-26T23:22:16.5080093Z >>> print(fut.wait()) 2025-08-26T23:22:16.5080129Z tensor([3., 3.]) 2025-08-26T23:22:16.5080163Z >>> t.join() 2025-08-26T23:22:16.5080194Z 2025-08-26T23:22:16.5080291Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5080322Z 2025-08-26T23:22:16.5080715Z warnings.warn(msg) 2025-08-26T23:22:16.5080745Z 2025-08-26T23:22:16.5080820Z --- Parse Warning: 20 / 146 --- 2025-08-26T23:22:16.5081118Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py line=66. 2025-08-26T23:22:16.5081209Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5081338Z Check if the current accelerator is available at runtime: it was build, all the 2025-08-26T23:22:16.5081417Z required drivers are available and at least one device is visible. 2025-08-26T23:22:16.5081476Z See :ref:`accelerator` for details. 2025-08-26T23:22:16.5081506Z 2025-08-26T23:22:16.5082607Z Returns: 2025-08-26T23:22:16.5082739Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-08-26T23:22:16.5082770Z 2025-08-26T23:22:16.5082860Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-08-26T23:22:16.5082953Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-08-26T23:22:16.5083043Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-08-26T23:22:16.5083106Z :ref:`multiprocessing-poison-fork-note`. 2025-08-26T23:22:16.5083140Z 2025-08-26T23:22:16.5083178Z Example:: 2025-08-26T23:22:16.5083208Z 2025-08-26T23:22:16.5083305Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:22:16.5083338Z 2025-08-26T23:22:16.5083535Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-08-26T23:22:16.5083565Z 2025-08-26T23:22:16.5083659Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:22:16.5083700Z ^ 2025-08-26T23:22:16.5083738Z warnings.warn(msg) 2025-08-26T23:22:16.5083768Z 2025-08-26T23:22:16.5083841Z --- Parse Warning: 21 / 146 --- 2025-08-26T23:22:16.5084165Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/accelerator/__init__.py line=212. 2025-08-26T23:22:16.5084273Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5084349Z Wait for all kernels in all streams on the given device to complete. 2025-08-26T23:22:16.5085388Z 2025-08-26T23:22:16.5085420Z Args: 2025-08-26T23:22:16.5085537Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-08-26T23:22:16.5085623Z the current :ref:`accelerator` device type. If not given, 2025-08-26T23:22:16.5085696Z use :func:`torch.accelerator.current_device_index` by default. 2025-08-26T23:22:16.5085726Z 2025-08-26T23:22:16.5085839Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-08-26T23:22:16.5085868Z 2025-08-26T23:22:16.5085903Z Example:: 2025-08-26T23:22:16.5085935Z 2025-08-26T23:22:16.5085996Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5086089Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:22:16.5086146Z >>> start_event = torch.Event(enable_timing=True) 2025-08-26T23:22:16.5086199Z >>> end_event = torch.Event(enable_timing=True) 2025-08-26T23:22:16.5086240Z >>> start_event.record() 2025-08-26T23:22:16.5086330Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-08-26T23:22:16.5086372Z >>> sum = torch.sum(tensor) 2025-08-26T23:22:16.5086414Z >>> end_event.record() 2025-08-26T23:22:16.5086465Z >>> torch.accelerator.synchronize() 2025-08-26T23:22:16.5086528Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-08-26T23:22:16.5086560Z 2025-08-26T23:22:16.5087736Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-08-26T23:22:16.5087789Z 2025-08-26T23:22:16.5087881Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T23:22:16.5087921Z ^ 2025-08-26T23:22:16.5087959Z warnings.warn(msg) 2025-08-26T23:22:16.5087989Z 2025-08-26T23:22:16.5088061Z --- Parse Warning: 22 / 146 --- 2025-08-26T23:22:16.5088369Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/mps/__init__.py line=145. 2025-08-26T23:22:16.5088462Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5088542Z Compiles compute shader from source and allows one to invoke kernels 2025-08-26T23:22:16.5088602Z defined there from the comfort of Python runtime 2025-08-26T23:22:16.5088639Z Example:: 2025-08-26T23:22:16.5088671Z 2025-08-26T23:22:16.5088724Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-08-26T23:22:16.5088772Z >>> lib = torch.mps.compile_shader( 2025-08-26T23:22:16.5088906Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-08-26T23:22:16.5088940Z ... ) 2025-08-26T23:22:16.5088988Z >>> x = torch.zeros(16, device="mps") 2025-08-26T23:22:16.5089029Z >>> lib.full(x, 3.14) 2025-08-26T23:22:16.5089060Z 2025-08-26T23:22:16.5089156Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5089186Z 2025-08-26T23:22:16.5090306Z warnings.warn(msg) 2025-08-26T23:22:16.5090398Z 2025-08-26T23:22:16.5090470Z --- Parse Warning: 23 / 146 --- 2025-08-26T23:22:16.5090770Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/apis.py line=39. 2025-08-26T23:22:16.5090879Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5090909Z 2025-08-26T23:22:16.5090989Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-08-26T23:22:16.5091066Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-08-26T23:22:16.5091145Z pushes the map into PyTorch operations called by ``func``, effectively 2025-08-26T23:22:16.5091189Z vectorizing those operations. 2025-08-26T23:22:16.5091219Z 2025-08-26T23:22:16.5091296Z vmap is useful for handling batch dimensions: one can write a function 2025-08-26T23:22:16.5091369Z ``func`` that runs on examples and then lift it to a function that can 2025-08-26T23:22:16.5091446Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-08-26T23:22:16.5091513Z compute batched gradients when composed with autograd. 2025-08-26T23:22:16.5091545Z 2025-08-26T23:22:16.5091578Z .. note:: 2025-08-26T23:22:16.5091649Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-08-26T23:22:16.5091699Z convenience. Use whichever one you'd like. 2025-08-26T23:22:16.5091730Z 2025-08-26T23:22:16.5091762Z Args: 2025-08-26T23:22:16.5092853Z func (function): A Python function that takes one or more arguments. 2025-08-26T23:22:16.5092900Z Must return one or more Tensors. 2025-08-26T23:22:16.5092974Z in_dims (int or nested structure): Specifies which dimension of the 2025-08-26T23:22:16.5093041Z inputs should be mapped over. ``in_dims`` should have a 2025-08-26T23:22:16.5093112Z structure like the inputs. If the ``in_dim`` for a particular 2025-08-26T23:22:16.5093178Z input is None, then that indicates there is no map dimension. 2025-08-26T23:22:16.5093245Z Default: 0. 2025-08-26T23:22:16.5093318Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-08-26T23:22:16.5093388Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-08-26T23:22:16.5093446Z it should have one element per output. Default: 0. 2025-08-26T23:22:16.5093517Z randomness (str): Specifies whether the randomness in this 2025-08-26T23:22:16.5093610Z vmap should be the same or different across batches. If 'different', 2025-08-26T23:22:16.5093683Z the randomness for each batch will be different. If 'same', the 2025-08-26T23:22:16.5093760Z randomness will be the same across batches. If 'error', any calls to 2025-08-26T23:22:16.5093836Z random functions will error. Default: 'error'. WARNING: this flag 2025-08-26T23:22:16.5093908Z only applies to random PyTorch operations and does not apply to 2025-08-26T23:22:16.5093962Z Python's random module or numpy randomness. 2025-08-26T23:22:16.5094046Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-08-26T23:22:16.5094126Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-08-26T23:22:16.5094219Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-08-26T23:22:16.5094316Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-08-26T23:22:16.5094347Z 2025-08-26T23:22:16.5095373Z Returns: 2025-08-26T23:22:16.5095446Z Returns a new "batched" function. It takes the same inputs as 2025-08-26T23:22:16.5095514Z ``func``, except each input has an extra dimension at the index 2025-08-26T23:22:16.5095585Z specified by ``in_dims``. It takes returns the same outputs as 2025-08-26T23:22:16.5095653Z ``func``, except each output has an extra dimension at the index 2025-08-26T23:22:16.5095698Z specified by ``out_dims``. 2025-08-26T23:22:16.5095765Z 2025-08-26T23:22:16.5095799Z .. warning: 2025-08-26T23:22:16.5095872Z :func:`vmap` works best with functional-style code. Please do not 2025-08-26T23:22:16.5095942Z perform any side-effects in ``func``, with the exception of 2025-08-26T23:22:16.5096026Z in-place PyTorch operations. Examples of side-effects include mutating 2025-08-26T23:22:16.5096109Z Python data structures and assigning values to variables not captured 2025-08-26T23:22:16.5096144Z in ``func``. 2025-08-26T23:22:16.5096174Z 2025-08-26T23:22:16.5096258Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-08-26T23:22:16.5096337Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-08-26T23:22:16.5096415Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-08-26T23:22:16.5096446Z 2025-08-26T23:22:16.5096490Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:22:16.5096567Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-08-26T23:22:16.5096617Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T23:22:16.5097653Z >>> batched_dot(x, y) 2025-08-26T23:22:16.5097684Z 2025-08-26T23:22:16.5097768Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-08-26T23:22:16.5097810Z model authoring experience. 2025-08-26T23:22:16.5097842Z 2025-08-26T23:22:16.5097885Z >>> batch_size, feature_size = 3, 5 2025-08-26T23:22:16.5097950Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T23:22:16.5097982Z >>> 2025-08-26T23:22:16.5098023Z >>> def model(feature_vec): 2025-08-26T23:22:16.5098077Z >>> # Very simple linear model with activation 2025-08-26T23:22:16.5098127Z >>> return feature_vec.dot(weights).relu() 2025-08-26T23:22:16.5098159Z >>> 2025-08-26T23:22:16.5098240Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T23:22:16.5098293Z >>> result = torch.vmap(model)(examples) 2025-08-26T23:22:16.5098323Z 2025-08-26T23:22:16.5098414Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-08-26T23:22:16.5098497Z or impossible to batch. One example is higher-order gradient computation. 2025-08-26T23:22:16.5098579Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-08-26T23:22:16.5098675Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-08-26T23:22:16.5098765Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-08-26T23:22:16.5098849Z we can vectorize the whole computation, computing the Jacobian in a single 2025-08-26T23:22:16.5098891Z call to ``autograd.grad``. 2025-08-26T23:22:16.5099905Z 2025-08-26T23:22:16.5099940Z >>> # Setup 2025-08-26T23:22:16.5099975Z >>> N = 5 2025-08-26T23:22:16.5100016Z >>> f = lambda x: x**2 2025-08-26T23:22:16.5100066Z >>> x = torch.randn(N, requires_grad=True) 2025-08-26T23:22:16.5100101Z >>> y = f(x) 2025-08-26T23:22:16.5100137Z >>> I_N = torch.eye(N) 2025-08-26T23:22:16.5100168Z >>> 2025-08-26T23:22:16.5100211Z >>> # Sequential approach 2025-08-26T23:22:16.5100290Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-08-26T23:22:16.5100394Z >>> for v in I_N.unbind()] 2025-08-26T23:22:16.5100442Z >>> jacobian = torch.stack(jacobian_rows) 2025-08-26T23:22:16.5100474Z >>> 2025-08-26T23:22:16.5100521Z >>> # vectorized gradient computation 2025-08-26T23:22:16.5100559Z >>> def get_vjp(v): 2025-08-26T23:22:16.5100607Z >>> return torch.autograd.grad(y, x, v) 2025-08-26T23:22:16.5100654Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-08-26T23:22:16.5100684Z 2025-08-26T23:22:16.5100812Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-08-26T23:22:16.5100858Z 2025-08-26T23:22:16.5100900Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:22:16.5100941Z >>> batched_dot = torch.vmap( 2025-08-26T23:22:16.5101987Z ... torch.vmap(torch.dot) 2025-08-26T23:22:16.5102038Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-08-26T23:22:16.5102094Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-08-26T23:22:16.5102146Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-08-26T23:22:16.5102177Z 2025-08-26T23:22:16.5102265Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-08-26T23:22:16.5102324Z the dimension that each inputs are batched along as 2025-08-26T23:22:16.5102355Z 2025-08-26T23:22:16.5102396Z >>> torch.dot # [N], [N] -> [] 2025-08-26T23:22:16.5102480Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-08-26T23:22:16.5102533Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T23:22:16.5102571Z >>> batched_dot( 2025-08-26T23:22:16.5102603Z ... x, y 2025-08-26T23:22:16.5102676Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-08-26T23:22:16.5102706Z 2025-08-26T23:22:16.5102798Z If there are multiple inputs each of which is batched along different dimensions, 2025-08-26T23:22:16.5102872Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-08-26T23:22:16.5102903Z 2025-08-26T23:22:16.5102943Z >>> torch.dot # [D], [D] -> [] 2025-08-26T23:22:16.5103027Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-08-26T23:22:16.5103077Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T23:22:16.5104098Z >>> batched_dot( 2025-08-26T23:22:16.5104132Z ... x, y 2025-08-26T23:22:16.5104204Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-08-26T23:22:16.5104268Z 2025-08-26T23:22:16.5104354Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-08-26T23:22:16.5104396Z matching the shape of the input: 2025-08-26T23:22:16.5104427Z 2025-08-26T23:22:16.5104481Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-08-26T23:22:16.5104529Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T23:22:16.5104588Z >>> input = {"x": x, "y": y} 2025-08-26T23:22:16.5104655Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-08-26T23:22:16.5104696Z >>> batched_dot(input) 2025-08-26T23:22:16.5104726Z 2025-08-26T23:22:16.5104827Z By default, the output is batched along the first dimension. However, it can be batched 2025-08-26T23:22:16.5104876Z along any dimension by using ``out_dims`` 2025-08-26T23:22:16.5104906Z 2025-08-26T23:22:16.5104944Z >>> f = lambda x: x**2 2025-08-26T23:22:16.5104985Z >>> x = torch.randn(2, 5) 2025-08-26T23:22:16.5105036Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-08-26T23:22:16.5105076Z >>> batched_pow(x) # [5, 2] 2025-08-26T23:22:16.5105105Z 2025-08-26T23:22:16.5105211Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-08-26T23:22:16.5106245Z accept kwargs 2025-08-26T23:22:16.5106277Z 2025-08-26T23:22:16.5106316Z >>> x = torch.randn([2, 5]) 2025-08-26T23:22:16.5106358Z >>> def fn(x, scale=4.): 2025-08-26T23:22:16.5106396Z >>> return x * scale 2025-08-26T23:22:16.5106427Z >>> 2025-08-26T23:22:16.5106472Z >>> batched_pow = torch.vmap(fn) 2025-08-26T23:22:16.5106528Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-08-26T23:22:16.5106612Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-08-26T23:22:16.5106642Z 2025-08-26T23:22:16.5106678Z .. note:: 2025-08-26T23:22:16.5106796Z vmap does not provide general autobatching or handle variable-length 2025-08-26T23:22:16.5106837Z sequences out of the box. 2025-08-26T23:22:16.5106867Z 2025-08-26T23:22:16.5106958Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5106987Z 2025-08-26T23:22:16.5107025Z warnings.warn(msg) 2025-08-26T23:22:16.5107055Z 2025-08-26T23:22:16.5107130Z --- Parse Warning: 24 / 146 --- 2025-08-26T23:22:16.5107412Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_functorch/apis.py line=306. 2025-08-26T23:22:16.5107507Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5107591Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-08-26T23:22:16.5108657Z input(s) specified by ``argnums``. This operator can be nested to 2025-08-26T23:22:16.5108704Z compute higher-order gradients. 2025-08-26T23:22:16.5108735Z 2025-08-26T23:22:16.5108766Z Args: 2025-08-26T23:22:16.5108843Z func (Callable): A Python function that takes one or more arguments. 2025-08-26T23:22:16.5108938Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-08-26T23:22:16.5109034Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-08-26T23:22:16.5109074Z ``(output, aux)``. 2025-08-26T23:22:16.5109174Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-08-26T23:22:16.5109251Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-08-26T23:22:16.5109330Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-08-26T23:22:16.5109412Z auxiliary objects: ``(output, aux)``. Default: False. 2025-08-26T23:22:16.5109445Z 2025-08-26T23:22:16.5109478Z Returns: 2025-08-26T23:22:16.5109580Z Function to compute gradients with respect to its inputs. By default, the output of 2025-08-26T23:22:16.5109665Z the function is the gradient tensor(s) with respect to the first argument. 2025-08-26T23:22:16.5109761Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-08-26T23:22:16.5109866Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-08-26T23:22:16.5109922Z respect to each ``argnums`` value is returned. 2025-08-26T23:22:16.5109953Z 2025-08-26T23:22:16.5109993Z Example of using ``grad``: 2025-08-26T23:22:16.5111093Z 2025-08-26T23:22:16.5111133Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5111180Z >>> from torch.func import grad 2025-08-26T23:22:16.5111221Z >>> x = torch.randn([]) 2025-08-26T23:22:16.5111278Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-08-26T23:22:16.5111328Z >>> assert torch.allclose(cos_x, x.cos()) 2025-08-26T23:22:16.5111361Z >>> 2025-08-26T23:22:16.5111403Z >>> # Second-order gradients 2025-08-26T23:22:16.5111463Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-08-26T23:22:16.5111516Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-08-26T23:22:16.5111550Z 2025-08-26T23:22:16.5111643Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-08-26T23:22:16.5111674Z 2025-08-26T23:22:16.5111712Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5111760Z >>> from torch.func import grad, vmap 2025-08-26T23:22:16.5111805Z >>> batch_size, feature_size = 3, 5 2025-08-26T23:22:16.5111836Z >>> 2025-08-26T23:22:16.5111883Z >>> def model(weights, feature_vec): 2025-08-26T23:22:16.5111979Z >>> # Very simple linear model with activation 2025-08-26T23:22:16.5112026Z >>> assert feature_vec.dim() == 1 2025-08-26T23:22:16.5112075Z >>> return feature_vec.dot(weights).relu() 2025-08-26T23:22:16.5112107Z >>> 2025-08-26T23:22:16.5113154Z >>> def compute_loss(weights, example, target): 2025-08-26T23:22:16.5113201Z >>> y = model(weights, example) 2025-08-26T23:22:16.5113258Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-08-26T23:22:16.5113291Z >>> 2025-08-26T23:22:16.5113355Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T23:22:16.5113413Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T23:22:16.5113458Z >>> targets = torch.randn(batch_size) 2025-08-26T23:22:16.5113509Z >>> inputs = (weights, examples, targets) 2025-08-26T23:22:16.5113594Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-08-26T23:22:16.5113635Z ... *inputs 2025-08-26T23:22:16.5113667Z ... ) 2025-08-26T23:22:16.5113698Z 2025-08-26T23:22:16.5113764Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-08-26T23:22:16.5113795Z 2025-08-26T23:22:16.5113832Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5113877Z >>> from torch.func import grad 2025-08-26T23:22:16.5113922Z >>> def my_loss_func(y, y_pred): 2025-08-26T23:22:16.5113975Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-08-26T23:22:16.5114021Z >>> loss = loss_per_sample.mean() 2025-08-26T23:22:16.5114073Z >>> return loss, (y_pred, loss_per_sample) 2025-08-26T23:22:16.5114105Z >>> 2025-08-26T23:22:16.5115258Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-08-26T23:22:16.5115303Z >>> y_true = torch.rand(4) 2025-08-26T23:22:16.5115383Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-08-26T23:22:16.5115432Z >>> out = fn(y_true, y_preds) 2025-08-26T23:22:16.5115522Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-08-26T23:22:16.5115553Z 2025-08-26T23:22:16.5115587Z .. note:: 2025-08-26T23:22:16.5115651Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-08-26T23:22:16.5115681Z 2025-08-26T23:22:16.5115762Z Case 1: Using ``torch.no_grad`` inside a function: 2025-08-26T23:22:16.5115792Z 2025-08-26T23:22:16.5115835Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5115873Z >>> def f(x): 2025-08-26T23:22:16.5115917Z >>> with torch.no_grad(): 2025-08-26T23:22:16.5115955Z >>> c = x ** 2 2025-08-26T23:22:16.5115995Z >>> return x - c 2025-08-26T23:22:16.5116025Z 2025-08-26T23:22:16.5116102Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-08-26T23:22:16.5116134Z 2025-08-26T23:22:16.5116203Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-08-26T23:22:16.5116233Z 2025-08-26T23:22:16.5116273Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5117313Z >>> with torch.no_grad(): 2025-08-26T23:22:16.5117353Z >>> grad(f)(x) 2025-08-26T23:22:16.5117384Z 2025-08-26T23:22:16.5117468Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-08-26T23:22:16.5117548Z outer one. This is because ``grad`` is a "function transform": its result 2025-08-26T23:22:16.5117627Z should not depend on the result of a context manager outside of ``f``. 2025-08-26T23:22:16.5117658Z 2025-08-26T23:22:16.5117689Z 2025-08-26T23:22:16.5117780Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5117811Z 2025-08-26T23:22:16.5117887Z warnings.warn(msg) 2025-08-26T23:22:16.5117933Z 2025-08-26T23:22:16.5118008Z --- Parse Warning: 25 / 146 --- 2025-08-26T23:22:16.5118358Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-08-26T23:22:16.5118454Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5118484Z 2025-08-26T23:22:16.5118574Z Config object that specifies the supported data types passed as arguments to 2025-08-26T23:22:16.5118660Z quantize ops in the reference model spec, for input and output activations, 2025-08-26T23:22:16.5118697Z weights, and biases. 2025-08-26T23:22:16.5118726Z 2025-08-26T23:22:16.5118787Z For example, consider the following reference model: 2025-08-26T23:22:16.5118819Z 2025-08-26T23:22:16.5119875Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-08-26T23:22:16.5119906Z 2025-08-26T23:22:16.5119986Z The pattern in the square brackets refers to the reference pattern of 2025-08-26T23:22:16.5120073Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-08-26T23:22:16.5120155Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-08-26T23:22:16.5120238Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-08-26T23:22:16.5120318Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-08-26T23:22:16.5120411Z the second quantize op (quant2). 2025-08-26T23:22:16.5120441Z 2025-08-26T23:22:16.5120521Z Note that the dtype here does not refer to the interface dtypes of the 2025-08-26T23:22:16.5120597Z op. For example, the "input dtype" here is not the dtype of the input 2025-08-26T23:22:16.5120710Z tensor passed to the quantized linear op. Though it can still be the 2025-08-26T23:22:16.5120785Z same as the interface dtype, this is not always the case, e.g. the 2025-08-26T23:22:16.5120863Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-08-26T23:22:16.5120939Z specified in the DTypeConfig would still be quint8. The semantics of 2025-08-26T23:22:16.5121014Z dtypes here are the same as the semantics of the dtypes specified in 2025-08-26T23:22:16.5121049Z the observers. 2025-08-26T23:22:16.5121098Z 2025-08-26T23:22:16.5121173Z These dtypes are matched against the ones specified in the user's 2025-08-26T23:22:16.5121250Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-08-26T23:22:16.5121327Z specified in the DTypeConfig (if any), then we will quantize the given 2025-08-26T23:22:16.5122419Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-08-26T23:22:16.5122463Z the pattern will not be quantized. 2025-08-26T23:22:16.5122497Z 2025-08-26T23:22:16.5122535Z Example usage:: 2025-08-26T23:22:16.5122568Z 2025-08-26T23:22:16.5122609Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:22:16.5122653Z >>> dtype_config1 = DTypeConfig( 2025-08-26T23:22:16.5122696Z ... input_dtype=torch.quint8, 2025-08-26T23:22:16.5122739Z ... output_dtype=torch.quint8, 2025-08-26T23:22:16.5122781Z ... weight_dtype=torch.qint8, 2025-08-26T23:22:16.5122825Z ... bias_dtype=torch.float) 2025-08-26T23:22:16.5122856Z 2025-08-26T23:22:16.5122897Z >>> dtype_config2 = DTypeConfig( 2025-08-26T23:22:16.5122949Z ... input_dtype=DTypeWithConstraints( 2025-08-26T23:22:16.5122988Z ... dtype=torch.quint8, 2025-08-26T23:22:16.5123032Z ... quant_min_lower_bound=0, 2025-08-26T23:22:16.5123076Z ... quant_max_upper_bound=255, 2025-08-26T23:22:16.5123109Z ... ), 2025-08-26T23:22:16.5123160Z ... output_dtype=DTypeWithConstraints( 2025-08-26T23:22:16.5123250Z ... dtype=torch.quint8, 2025-08-26T23:22:16.5123292Z ... quant_min_lower_bound=0, 2025-08-26T23:22:16.5123336Z ... quant_max_upper_bound=255, 2025-08-26T23:22:16.5124360Z ... ), 2025-08-26T23:22:16.5124412Z ... weight_dtype=DTypeWithConstraints( 2025-08-26T23:22:16.5124452Z ... dtype=torch.qint8, 2025-08-26T23:22:16.5124501Z ... quant_min_lower_bound=-128, 2025-08-26T23:22:16.5124544Z ... quant_max_upper_bound=127, 2025-08-26T23:22:16.5124576Z ... ), 2025-08-26T23:22:16.5124615Z ... bias_dtype=torch.float) 2025-08-26T23:22:16.5124645Z 2025-08-26T23:22:16.5124688Z >>> dtype_config1.input_dtype 2025-08-26T23:22:16.5124722Z torch.quint8 2025-08-26T23:22:16.5124753Z 2025-08-26T23:22:16.5124794Z >>> dtype_config2.input_dtype 2025-08-26T23:22:16.5124830Z torch.quint8 2025-08-26T23:22:16.5124861Z 2025-08-26T23:22:16.5124916Z >>> dtype_config2.input_dtype_with_constraints 2025-08-26T23:22:16.5125101Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-08-26T23:22:16.5125133Z 2025-08-26T23:22:16.5125223Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5125254Z 2025-08-26T23:22:16.5125292Z warnings.warn(msg) 2025-08-26T23:22:16.5125322Z 2025-08-26T23:22:16.5125394Z --- Parse Warning: 26 / 146 --- 2025-08-26T23:22:16.5126795Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-08-26T23:22:16.5126910Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5126947Z 2025-08-26T23:22:16.5127043Z Takes in optional filter values and generates two tables with desired information. 2025-08-26T23:22:16.5127074Z 2025-08-26T23:22:16.5127150Z The generated tables are presented in both a list-of-lists format 2025-08-26T23:22:16.5127181Z 2025-08-26T23:22:16.5127256Z The reason for the two tables are that they handle different things: 2025-08-26T23:22:16.5127333Z 1.) the first table handles all tensor level information 2025-08-26T23:22:16.5127410Z 2.) the second table handles and displays all channel based information 2025-08-26T23:22:16.5127441Z 2025-08-26T23:22:16.5127555Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T23:22:16.5127671Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T23:22:16.5127798Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T23:22:16.5127829Z 2025-08-26T23:22:16.5127869Z Tensor table columns: 2025-08-26T23:22:16.5127939Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:22:16.5128003Z ---- --------- --------- --------- --------- --------- 2025-08-26T23:22:16.5128033Z 2025-08-26T23:22:16.5128077Z Per-Channel table columns: 2025-08-26T23:22:16.5128159Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:22:16.5129233Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T23:22:16.5129264Z 2025-08-26T23:22:16.5129297Z Args: 2025-08-26T23:22:16.5129392Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:22:16.5129437Z contain this filter substring 2025-08-26T23:22:16.5129502Z Default = "", results in all the features being printed 2025-08-26T23:22:16.5129631Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:22:16.5129721Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:22:16.5129752Z 2025-08-26T23:22:16.5129794Z Returns a dictionary with two keys: 2025-08-26T23:22:16.5129862Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-08-26T23:22:16.5129913Z "tensor_level_info", "channel_level_info" 2025-08-26T23:22:16.5129958Z Each key maps to a tuple with: 2025-08-26T23:22:16.5130005Z A list of the headers of each table 2025-08-26T23:22:16.5130071Z A list of lists containing the table information row by row 2025-08-26T23:22:16.5130134Z The 0th index row will contain the headers of the columns 2025-08-26T23:22:16.5130184Z The rest of the rows will contain data 2025-08-26T23:22:16.5130216Z 2025-08-26T23:22:16.5130251Z Example Use: 2025-08-26T23:22:16.5130304Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5130419Z >>> mod_report_visualizer.generate_filtered_tables( 2025-08-26T23:22:16.5130492Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:22:16.5131599Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-08-26T23:22:16.5131630Z 2025-08-26T23:22:16.5131721Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5131753Z 2025-08-26T23:22:16.5131791Z warnings.warn(msg) 2025-08-26T23:22:16.5131822Z 2025-08-26T23:22:16.5131894Z --- Parse Warning: 27 / 146 --- 2025-08-26T23:22:16.5132315Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-08-26T23:22:16.5132441Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5132472Z 2025-08-26T23:22:16.5132571Z Takes in optional filter values and prints out formatted tables of the information. 2025-08-26T23:22:16.5132602Z 2025-08-26T23:22:16.5132741Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-08-26T23:22:16.5132805Z 1.) the first table handles all tensor level information 2025-08-26T23:22:16.5132881Z 2.) the second table handles and displays all channel based information 2025-08-26T23:22:16.5132912Z 2025-08-26T23:22:16.5133023Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T23:22:16.5133138Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T23:22:16.5133263Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T23:22:16.5133294Z 2025-08-26T23:22:16.5133333Z Tensor table columns: 2025-08-26T23:22:16.5134389Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:22:16.5134449Z ---- --------- --------- --------- --------- --------- 2025-08-26T23:22:16.5134480Z 2025-08-26T23:22:16.5134524Z Per-Channel table columns: 2025-08-26T23:22:16.5134555Z 2025-08-26T23:22:16.5134635Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T23:22:16.5134698Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T23:22:16.5134727Z 2025-08-26T23:22:16.5134760Z Args: 2025-08-26T23:22:16.5134855Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:22:16.5134926Z contain this filter substring 2025-08-26T23:22:16.5135006Z Default = "", results in all the features being printed 2025-08-26T23:22:16.5135098Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:22:16.5135188Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:22:16.5135218Z 2025-08-26T23:22:16.5135252Z Example Use: 2025-08-26T23:22:16.5135306Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5135369Z >>> mod_report_visualizer.generate_table_visualization( 2025-08-26T23:22:16.5135440Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:22:16.5135472Z ... ) 2025-08-26T23:22:16.5135541Z >>> # prints out neatly formatted table with per_channel_min info 2025-08-26T23:22:16.5135592Z >>> # for all modules in block 1 of the model 2025-08-26T23:22:16.5136609Z 2025-08-26T23:22:16.5136702Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5136732Z 2025-08-26T23:22:16.5136770Z warnings.warn(msg) 2025-08-26T23:22:16.5136800Z 2025-08-26T23:22:16.5136873Z --- Parse Warning: 28 / 146 --- 2025-08-26T23:22:16.5137286Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-08-26T23:22:16.5137379Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5137408Z 2025-08-26T23:22:16.5137493Z Takes in a feature and optional module_filter and plots of the desired data. 2025-08-26T23:22:16.5137523Z 2025-08-26T23:22:16.5137619Z For per channel features, it averages the value across the channels and plots a point 2025-08-26T23:22:16.5137733Z per module. The reason for this is that for models with hundreds of channels, it can 2025-08-26T23:22:16.5137830Z be hard to differentiate one channel line from another, and so the point of generating 2025-08-26T23:22:16.5137923Z a single average point per module is to give a sense of general trends that encourage 2025-08-26T23:22:16.5137961Z further deep dives. 2025-08-26T23:22:16.5137991Z 2025-08-26T23:22:16.5138046Z Note: 2025-08-26T23:22:16.5138142Z Only features in the report that have tensor value data are plottable by this class 2025-08-26T23:22:16.5138206Z When the tensor information is plotted, it will plot: 2025-08-26T23:22:16.5138262Z idx as the x val, feature value as the y_val 2025-08-26T23:22:16.5139319Z When the channel information is plotted, it will plot: 2025-08-26T23:22:16.5139415Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-08-26T23:22:16.5139504Z The reason for this is that we want to be able to compare values across the 2025-08-26T23:22:16.5139587Z channels for same layer, and it will be hard if values are staggered by idx 2025-08-26T23:22:16.5139651Z This means each module is represented by only 1 x value 2025-08-26T23:22:16.5139683Z Args: 2025-08-26T23:22:16.5139764Z feature_filter (str): Filters the features presented to only those that 2025-08-26T23:22:16.5139810Z contain this filter substring 2025-08-26T23:22:16.5139901Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:22:16.5139991Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:22:16.5140021Z 2025-08-26T23:22:16.5140055Z Example Use: 2025-08-26T23:22:16.5140106Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5140170Z >>> mod_report_visualizer.generate_plot_visualization( 2025-08-26T23:22:16.5140276Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:22:16.5140309Z ... ) 2025-08-26T23:22:16.5140436Z >>> # outputs line plot of per_channel_min information for all 2025-08-26T23:22:16.5140505Z >>> # modules in block1 of model each channel gets it's own line, 2025-08-26T23:22:16.5140571Z >>> # and it's plotted across the in-order modules on the x-axis 2025-08-26T23:22:16.5140603Z 2025-08-26T23:22:16.5140692Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5140722Z 2025-08-26T23:22:16.5141752Z warnings.warn(msg) 2025-08-26T23:22:16.5141784Z 2025-08-26T23:22:16.5141856Z --- Parse Warning: 29 / 146 --- 2025-08-26T23:22:16.5142278Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-08-26T23:22:16.5142372Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5142402Z 2025-08-26T23:22:16.5142500Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-08-26T23:22:16.5142530Z 2025-08-26T23:22:16.5142561Z Note: 2025-08-26T23:22:16.5142658Z Only features in the report that have tensor value data can be viewed as a histogram 2025-08-26T23:22:16.5142752Z If you want to plot a histogram from all the channel values of a specific feature for 2025-08-26T23:22:16.5142840Z a specific model, make sure to specify both the model and the feature properly 2025-08-26T23:22:16.5142928Z in the filters and you should be able to see a distribution of the channel data 2025-08-26T23:22:16.5142997Z 2025-08-26T23:22:16.5143028Z Args: 2025-08-26T23:22:16.5143122Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T23:22:16.5143166Z contain this filter substring 2025-08-26T23:22:16.5143227Z Default = "", results in all the features being printed 2025-08-26T23:22:16.5143318Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T23:22:16.5143424Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T23:22:16.5143507Z num_bins (int, optional): The number of bins to create the histogram with 2025-08-26T23:22:16.5144565Z Default = 10, the values will be split into 10 equal sized bins 2025-08-26T23:22:16.5144597Z 2025-08-26T23:22:16.5144630Z Example Use: 2025-08-26T23:22:16.5144672Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5144779Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-08-26T23:22:16.5144855Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T23:22:16.5144886Z ... ) 2025-08-26T23:22:16.5144984Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-08-26T23:22:16.5145073Z information is gathered across all channels for all modules in block 1 for the 2025-08-26T23:22:16.5145152Z per_channel_min and is displayed in a histogram of equally sized bins 2025-08-26T23:22:16.5145185Z 2025-08-26T23:22:16.5145274Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5145304Z 2025-08-26T23:22:16.5145341Z warnings.warn(msg) 2025-08-26T23:22:16.5145371Z 2025-08-26T23:22:16.5145443Z --- Parse Warning: 30 / 146 --- 2025-08-26T23:22:16.5145806Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-08-26T23:22:16.5145916Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5145946Z 2025-08-26T23:22:16.5146053Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-08-26T23:22:16.5146158Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-08-26T23:22:16.5146266Z though the requirements on the type of model more-so depends on the specific report the user 2025-08-26T23:22:16.5147368Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-08-26T23:22:16.5147468Z a set of Detector classes, each of which generate reports on quantization configuration 2025-08-26T23:22:16.5147508Z issues a use might have. 2025-08-26T23:22:16.5147540Z 2025-08-26T23:22:16.5147592Z Currently supports generating reports on: 2025-08-26T23:22:16.5147680Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-08-26T23:22:16.5147775Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-08-26T23:22:16.5147877Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-08-26T23:22:16.5147953Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-08-26T23:22:16.5147985Z 2025-08-26T23:22:16.5148121Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-08-26T23:22:16.5148249Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-08-26T23:22:16.5148376Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-08-26T23:22:16.5148454Z has the capability to remove all the observers it inserted as well. 2025-08-26T23:22:16.5148505Z 2025-08-26T23:22:16.5148609Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-08-26T23:22:16.5148638Z 2025-08-26T23:22:16.5148767Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-08-26T23:22:16.5148878Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-08-26T23:22:16.5148924Z 2025-08-26T23:22:16.5149025Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-08-26T23:22:16.5150094Z This set is generated by calling the get_detector_name() of each detector 2025-08-26T23:22:16.5150125Z 2025-08-26T23:22:16.5150241Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-08-26T23:22:16.5150399Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-08-26T23:22:16.5150450Z can be removed at the end if desired 2025-08-26T23:22:16.5150481Z 2025-08-26T23:22:16.5150591Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-08-26T23:22:16.5150677Z This is to ensure we only insert observers once with the ModelReport instance 2025-08-26T23:22:16.5150707Z 2025-08-26T23:22:16.5150801Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-08-26T23:22:16.5150903Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-08-26T23:22:16.5151017Z instance. This also allows the functionality where we can generate the report multiple times 2025-08-26T23:22:16.5151074Z as long as we haven't removed the observers yet. 2025-08-26T23:22:16.5151105Z 2025-08-26T23:22:16.5151136Z Note: 2025-08-26T23:22:16.5151272Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-08-26T23:22:16.5151395Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-08-26T23:22:16.5151499Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-08-26T23:22:16.5151544Z the QuantizationTracer class. 2025-08-26T23:22:16.5151575Z 2025-08-26T23:22:16.5151616Z General Flow for Fx workflow: 2025-08-26T23:22:16.5151753Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-08-26T23:22:16.5152806Z 2.) Prepare your model with prepare_fx 2025-08-26T23:22:16.5152895Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-08-26T23:22:16.5152939Z 4.) Calibrate your model with data 2025-08-26T23:22:16.5153060Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-08-26T23:22:16.5153096Z Optional 2025-08-26T23:22:16.5153193Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-08-26T23:22:16.5153280Z 7.) To help in parsing report information and debugging, view report info as a: 2025-08-26T23:22:16.5153316Z - Table 2025-08-26T23:22:16.5153352Z - Histogram 2025-08-26T23:22:16.5153388Z - Line plot 2025-08-26T23:22:16.5153499Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-08-26T23:22:16.5153530Z 2025-08-26T23:22:16.5153575Z Example (with QuantizationTracer): 2025-08-26T23:22:16.5153615Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5153658Z >>> # get the necessary qconfig 2025-08-26T23:22:16.5153704Z >>> config = PrepareCustomConfig() 2025-08-26T23:22:16.5153765Z >>> skipped_module_names, skipped_module_classes = ( 2025-08-26T23:22:16.5153853Z ... get_skipped_module_name_and_classes(config, False) 2025-08-26T23:22:16.5153889Z ... ) 2025-08-26T23:22:16.5153919Z 2025-08-26T23:22:16.5153971Z >>> # initialize our model and get GraphModule 2025-08-26T23:22:16.5154010Z >>> model = SomeModel() 2025-08-26T23:22:16.5155187Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-08-26T23:22:16.5155252Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-08-26T23:22:16.5155308Z 2025-08-26T23:22:16.5155367Z >>> # get our set of detectors and ModelReport instance 2025-08-26T23:22:16.5155407Z >>> detector_set = set( 2025-08-26T23:22:16.5155439Z ... [ 2025-08-26T23:22:16.5155494Z ... DynamicStaticDetector(tolerance=0.5), 2025-08-26T23:22:16.5155566Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-08-26T23:22:16.5155598Z ... ] 2025-08-26T23:22:16.5155629Z ... ) 2025-08-26T23:22:16.5155708Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-08-26T23:22:16.5155739Z 2025-08-26T23:22:16.5155798Z >>> # now we insert the observers and calibrate the model 2025-08-26T23:22:16.5155889Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-08-26T23:22:16.5155942Z >>> for i in range(num_callibration_batches): 2025-08-26T23:22:16.5155995Z >>> example_input = get_callibration_input() 2025-08-26T23:22:16.5156049Z >>> tracer_model_with_observers(example_input) 2025-08-26T23:22:16.5156081Z 2025-08-26T23:22:16.5156174Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-08-26T23:22:16.5156234Z >>> reports = tracer_reporter.generate_model_report( 2025-08-26T23:22:16.5156280Z ... remove_inserted_observers=True 2025-08-26T23:22:16.5157303Z ... ) 2025-08-26T23:22:16.5157334Z 2025-08-26T23:22:16.5157419Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-08-26T23:22:16.5157512Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-08-26T23:22:16.5157543Z 2025-08-26T23:22:16.5157628Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-08-26T23:22:16.5157695Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-08-26T23:22:16.5157725Z 2025-08-26T23:22:16.5157826Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-08-26T23:22:16.5157901Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-08-26T23:22:16.5157931Z 2025-08-26T23:22:16.5157961Z 2025-08-26T23:22:16.5158052Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5158082Z 2025-08-26T23:22:16.5158120Z warnings.warn(msg) 2025-08-26T23:22:16.5158149Z 2025-08-26T23:22:16.5158224Z --- Parse Warning: 31 / 146 --- 2025-08-26T23:22:16.5158620Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-08-26T23:22:16.5158714Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5158743Z 2025-08-26T23:22:16.5158836Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-08-26T23:22:16.5158918Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-08-26T23:22:16.5159988Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-08-26T23:22:16.5160025Z input by the user. 2025-08-26T23:22:16.5160107Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-08-26T23:22:16.5160190Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-08-26T23:22:16.5160224Z 2025-08-26T23:22:16.5160259Z Note:: 2025-08-26T23:22:16.5160470Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-08-26T23:22:16.5160502Z 2025-08-26T23:22:16.5160533Z Args: 2025-08-26T23:22:16.5160573Z model (nn.Module): 2025-08-26T23:22:16.5160652Z The model whose layers will be sparsified. The layers that needs to be 2025-08-26T23:22:16.5160773Z sparsified should be added separately using the register_layer() function 2025-08-26T23:22:16.5160819Z aggregate_fn (Optional, Callable): 2025-08-26T23:22:16.5160912Z default aggregate_fn that is used if not specified while registering the layer. 2025-08-26T23:22:16.5160973Z specifies how inputs should be aggregated over time. 2025-08-26T23:22:16.5161075Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-08-26T23:22:16.5161111Z Example 2025-08-26T23:22:16.5161178Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-08-26T23:22:16.5161224Z reduce_fn (Optional, Callable): 2025-08-26T23:22:16.5161311Z default reduce_fn that is used if not specified while registering the layer. 2025-08-26T23:22:16.5161401Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-08-26T23:22:16.5162448Z calling agg_fn() on all inputs. 2025-08-26T23:22:16.5162487Z Example 2025-08-26T23:22:16.5162559Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-08-26T23:22:16.5162604Z mask_fn (Optional, Callable): 2025-08-26T23:22:16.5162711Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-08-26T23:22:16.5162800Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-08-26T23:22:16.5162884Z register_layer(). 2025-08-26T23:22:16.5163005Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-08-26T23:22:16.5163045Z arguments. 2025-08-26T23:22:16.5163088Z features (Optional, list): 2025-08-26T23:22:16.5163140Z default selected features to sparsify. 2025-08-26T23:22:16.5163234Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-08-26T23:22:16.5163275Z For example, 2025-08-26T23:22:16.5163366Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-08-26T23:22:16.5163412Z feature_dim (Optional, int): 2025-08-26T23:22:16.5163509Z default dimension of input features. Again, features along this dim will be chosen 2025-08-26T23:22:16.5163555Z for sparsification. 2025-08-26T23:22:16.5163596Z sparse_config (Dict): 2025-08-26T23:22:16.5163674Z Default configuration for the mask_fn. This config will be passed 2025-08-26T23:22:16.5163715Z with the mask_fn() 2025-08-26T23:22:16.5163745Z 2025-08-26T23:22:16.5163779Z Example: 2025-08-26T23:22:16.5164795Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5164838Z >>> model = SomeModel() 2025-08-26T23:22:16.5164926Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-08-26T23:22:16.5164968Z >>> # Initialize aggregate_fn 2025-08-26T23:22:16.5165005Z >>> def agg_fn(x, y): 2025-08-26T23:22:16.5165044Z >>> return x + y 2025-08-26T23:22:16.5165075Z >>> 2025-08-26T23:22:16.5165116Z >>> # Initialize reduce_fn 2025-08-26T23:22:16.5165153Z >>> def reduce_fn(x): 2025-08-26T23:22:16.5165223Z >>> return torch.mean(x, dim=0) 2025-08-26T23:22:16.5165258Z >>> 2025-08-26T23:22:16.5165298Z >>> # Initialize mask_fn 2025-08-26T23:22:16.5165336Z >>> def mask_fn(data): 2025-08-26T23:22:16.5165394Z >>> return torch.eye(data.shape).to(data.device) 2025-08-26T23:22:16.5165425Z >>> 2025-08-26T23:22:16.5165455Z >>> 2025-08-26T23:22:16.5165502Z >>> act_sparsifier.register_layer( 2025-08-26T23:22:16.5165540Z ... model.some_layer, 2025-08-26T23:22:16.5165596Z ... aggregate_fn=agg_fn, 2025-08-26T23:22:16.5165635Z ... reduce_fn=reduce_fn, 2025-08-26T23:22:16.5165674Z ... mask_fn=mask_fn, 2025-08-26T23:22:16.5165704Z ... ) 2025-08-26T23:22:16.5166716Z >>> 2025-08-26T23:22:16.5166756Z >>> # start training process 2025-08-26T23:22:16.5166793Z >>> for _ in [...]: 2025-08-26T23:22:16.5166830Z >>> # epoch starts 2025-08-26T23:22:16.5166898Z >>> # model.forward(), compute_loss() and model.backwards() 2025-08-26T23:22:16.5166941Z >>> # epoch ends 2025-08-26T23:22:16.5166985Z >>> act_sparsifier.step() 2025-08-26T23:22:16.5167025Z >>> # end training process 2025-08-26T23:22:16.5167065Z >>> sparsifier.squash_mask() 2025-08-26T23:22:16.5167095Z 2025-08-26T23:22:16.5167186Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5167216Z 2025-08-26T23:22:16.5167253Z warnings.warn(msg) 2025-08-26T23:22:16.5167284Z 2025-08-26T23:22:16.5167357Z --- Parse Warning: 32 / 146 --- 2025-08-26T23:22:16.5167754Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-08-26T23:22:16.5167847Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5167898Z 2025-08-26T23:22:16.5167988Z Abstract method that needs to be implemented by the child class. 2025-08-26T23:22:16.5168080Z The expected return type should is a dictionary of name to schedule_param value 2025-08-26T23:22:16.5168174Z The returned values will be updated in sparsifier when the scheduler step() function 2025-08-26T23:22:16.5169192Z is called. 2025-08-26T23:22:16.5169222Z 2025-08-26T23:22:16.5169259Z Example: 2025-08-26T23:22:16.5169303Z >>> def get_schedule_param(self): 2025-08-26T23:22:16.5169343Z ... new_param = {} 2025-08-26T23:22:16.5169405Z ... for name in self.sparsifier.data_groups.keys(): 2025-08-26T23:22:16.5169445Z ... new_param[name] = ( 2025-08-26T23:22:16.5169522Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-08-26T23:22:16.5169557Z ... ) 2025-08-26T23:22:16.5169596Z ... return new_param 2025-08-26T23:22:16.5169628Z 2025-08-26T23:22:16.5169747Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-08-26T23:22:16.5169782Z would be halved 2025-08-26T23:22:16.5169812Z 2025-08-26T23:22:16.5169901Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5169931Z 2025-08-26T23:22:16.5169968Z warnings.warn(msg) 2025-08-26T23:22:16.5169999Z 2025-08-26T23:22:16.5170071Z --- Parse Warning: 33 / 146 --- 2025-08-26T23:22:16.5170484Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-08-26T23:22:16.5170577Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5170674Z Squashes the sparse masks into the appropriate tensors. 2025-08-26T23:22:16.5171681Z 2025-08-26T23:22:16.5171759Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-08-26T23:22:16.5171828Z the module will have a `sparse_params` dict attached to it. 2025-08-26T23:22:16.5171858Z 2025-08-26T23:22:16.5171891Z Args: 2025-08-26T23:22:16.5171961Z params_to_keep: List of keys to save in the module or a dict 2025-08-26T23:22:16.5172047Z representing the modules and keys that will have 2025-08-26T23:22:16.5172099Z sparsity parameters saved 2025-08-26T23:22:16.5172176Z params_to_keep_per_layer: Dict to specify the params that should be 2025-08-26T23:22:16.5172234Z saved for specific layers. The keys in the dict 2025-08-26T23:22:16.5172292Z should be the module fqn, while the values should 2025-08-26T23:22:16.5172356Z be a list of strings with the names of the variables 2025-08-26T23:22:16.5172407Z to save in the `sparse_params` 2025-08-26T23:22:16.5172438Z 2025-08-26T23:22:16.5172473Z Examples: 2025-08-26T23:22:16.5172525Z >>> # xdoctest: +SKIP("locals are undefined") 2025-08-26T23:22:16.5172572Z >>> # Don't save any sparse params 2025-08-26T23:22:16.5172621Z >>> sparsifier.squash_mask() 2025-08-26T23:22:16.5172674Z >>> hasattr(model.submodule1, "sparse_params") 2025-08-26T23:22:16.5172709Z False 2025-08-26T23:22:16.5172739Z 2025-08-26T23:22:16.5173754Z >>> # Keep sparse params per layer 2025-08-26T23:22:16.5173799Z >>> sparsifier.squash_mask( 2025-08-26T23:22:16.5173845Z ... params_to_keep_per_layer={ 2025-08-26T23:22:16.5173898Z ... "submodule1.linear1": ("foo", "bar"), 2025-08-26T23:22:16.5173990Z ... "submodule2.linear42": ("baz",), 2025-08-26T23:22:16.5174026Z ... } 2025-08-26T23:22:16.5174059Z ... ) 2025-08-26T23:22:16.5174121Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:22:16.5174161Z {'foo': 42, 'bar': 24} 2025-08-26T23:22:16.5174225Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:22:16.5174265Z {'baz': 0.1} 2025-08-26T23:22:16.5174296Z 2025-08-26T23:22:16.5174346Z >>> # Keep sparse params for all layers 2025-08-26T23:22:16.5174413Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-08-26T23:22:16.5174473Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:22:16.5174513Z {'foo': 42, 'bar': 24} 2025-08-26T23:22:16.5174573Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:22:16.5174614Z {'foo': 42, 'bar': 24} 2025-08-26T23:22:16.5174646Z 2025-08-26T23:22:16.5174720Z >>> # Keep some sparse params for all layers, and specific ones for 2025-08-26T23:22:16.5174759Z >>> # some other layers 2025-08-26T23:22:16.5174804Z >>> sparsifier.squash_mask( 2025-08-26T23:22:16.5175814Z ... params_to_keep=("foo", "bar"), 2025-08-26T23:22:16.5175890Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-08-26T23:22:16.5175923Z ... ) 2025-08-26T23:22:16.5175983Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T23:22:16.5176020Z {'foo': 42, 'bar': 24} 2025-08-26T23:22:16.5176080Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T23:22:16.5176123Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-08-26T23:22:16.5176155Z 2025-08-26T23:22:16.5176244Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5176303Z 2025-08-26T23:22:16.5176341Z warnings.warn(msg) 2025-08-26T23:22:16.5176371Z 2025-08-26T23:22:16.5176443Z --- Parse Warning: 34 / 146 --- 2025-08-26T23:22:16.5176740Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-08-26T23:22:16.5176848Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5176898Z A quantized long short-term memory (LSTM). 2025-08-26T23:22:16.5176929Z 2025-08-26T23:22:16.5177029Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-08-26T23:22:16.5177061Z 2025-08-26T23:22:16.5177095Z Attributes: 2025-08-26T23:22:16.5177143Z layers : instances of the `_LSTMLayer` 2025-08-26T23:22:16.5177174Z 2025-08-26T23:22:16.5178171Z .. note:: 2025-08-26T23:22:16.5178252Z To access the weights and biases, you need to access them per layer. 2025-08-26T23:22:16.5178319Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-08-26T23:22:16.5178348Z 2025-08-26T23:22:16.5178386Z Examples:: 2025-08-26T23:22:16.5178426Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5178470Z >>> custom_module_config = { 2025-08-26T23:22:16.5178525Z ... 'float_to_observed_custom_module_class': { 2025-08-26T23:22:16.5178578Z ... nn.LSTM: nn.quantizable.LSTM, 2025-08-26T23:22:16.5178611Z ... }, 2025-08-26T23:22:16.5178666Z ... 'observed_to_quantized_custom_module_class': { 2025-08-26T23:22:16.5178723Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-08-26T23:22:16.5178755Z ... } 2025-08-26T23:22:16.5178788Z ... } 2025-08-26T23:22:16.5178888Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-08-26T23:22:16.5178997Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-08-26T23:22:16.5179028Z 2025-08-26T23:22:16.5179117Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5179147Z 2025-08-26T23:22:16.5179184Z warnings.warn(msg) 2025-08-26T23:22:16.5179213Z 2025-08-26T23:22:16.5180264Z --- Parse Warning: 35 / 146 --- 2025-08-26T23:22:16.5180634Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-08-26T23:22:16.5180727Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5180803Z Applies a 1D convolution over a quantized input signal composed of 2025-08-26T23:22:16.5180852Z several quantized input planes. 2025-08-26T23:22:16.5180883Z 2025-08-26T23:22:16.5180960Z For details on input arguments, parameters, and implementation see 2025-08-26T23:22:16.5181003Z :class:`~torch.nn.Conv1d`. 2025-08-26T23:22:16.5181034Z 2025-08-26T23:22:16.5181067Z .. note:: 2025-08-26T23:22:16.5181140Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-08-26T23:22:16.5181170Z 2025-08-26T23:22:16.5181204Z .. note:: 2025-08-26T23:22:16.5181272Z Only `torch.quint8` is supported for the input data type. 2025-08-26T23:22:16.5181302Z 2025-08-26T23:22:16.5181332Z 2025-08-26T23:22:16.5181365Z Attributes: 2025-08-26T23:22:16.5181442Z weight (Tensor): packed tensor derived from the learnable weight 2025-08-26T23:22:16.5181483Z parameter. 2025-08-26T23:22:16.5181542Z scale (Tensor): scalar for the output scale 2025-08-26T23:22:16.5181644Z zero_point (Tensor): scalar for the output zero point 2025-08-26T23:22:16.5181675Z 2025-08-26T23:22:16.5182709Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-08-26T23:22:16.5182741Z 2025-08-26T23:22:16.5182776Z Examples:: 2025-08-26T23:22:16.5182806Z 2025-08-26T23:22:16.5182864Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-08-26T23:22:16.5182971Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-08-26T23:22:16.5183017Z >>> input = torch.randn(20, 16, 100) 2025-08-26T23:22:16.5183062Z >>> # quantize input to quint8 2025-08-26T23:22:16.5183102Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5183179Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-08-26T23:22:16.5183230Z ... dtype=torch.quint8) 2025-08-26T23:22:16.5183272Z >>> output = m(q_input) 2025-08-26T23:22:16.5183307Z 2025-08-26T23:22:16.5183337Z 2025-08-26T23:22:16.5183426Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5183456Z 2025-08-26T23:22:16.5183494Z warnings.warn(msg) 2025-08-26T23:22:16.5183524Z 2025-08-26T23:22:16.5183596Z --- Parse Warning: 36 / 146 --- 2025-08-26T23:22:16.5183888Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py line=120. 2025-08-26T23:22:16.5183981Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5185084Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-08-26T23:22:16.5185116Z 2025-08-26T23:22:16.5185202Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-08-26T23:22:16.5185329Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-08-26T23:22:16.5185409Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-08-26T23:22:16.5185444Z (UAI 2018). 2025-08-26T23:22:16.5185474Z 2025-08-26T23:22:16.5185552Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-08-26T23:22:16.5185637Z but using exponential weights instead of equal weights across iterations. 2025-08-26T23:22:16.5185670Z 2025-08-26T23:22:16.5185752Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-08-26T23:22:16.5185833Z on the device :attr:`device` and allows to compute running averages of the 2025-08-26T23:22:16.5185877Z parameters of the :attr:`model`. 2025-08-26T23:22:16.5185908Z 2025-08-26T23:22:16.5185939Z Args: 2025-08-26T23:22:16.5185999Z model (torch.nn.Module): model to use with SWA/EMA 2025-08-26T23:22:16.5186085Z device (torch.device, optional): if provided, the averaged model will be 2025-08-26T23:22:16.5186131Z stored on the :attr:`device` 2025-08-26T23:22:16.5186206Z avg_fn (function, optional): the averaging function used to update 2025-08-26T23:22:16.5186279Z parameters; the function must take in the current value of the 2025-08-26T23:22:16.5186357Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-08-26T23:22:16.5186429Z parameter, and the number of models already averaged; if None, 2025-08-26T23:22:16.5187455Z an equally weighted average is used (default: None) 2025-08-26T23:22:16.5187537Z multi_avg_fn (function, optional): the averaging function used to update 2025-08-26T23:22:16.5187621Z parameters inplace; the function must take in the current values of the 2025-08-26T23:22:16.5187717Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-08-26T23:22:16.5187824Z parameters as a list, and the number of models already averaged; if None, 2025-08-26T23:22:16.5187885Z an equally weighted average is used (default: None) 2025-08-26T23:22:16.5187959Z use_buffers (bool): if ``True``, it will compute running averages for 2025-08-26T23:22:16.5188042Z both the parameters and the buffers of the model. (default: ``False``) 2025-08-26T23:22:16.5188073Z 2025-08-26T23:22:16.5188131Z Example: 2025-08-26T23:22:16.5188184Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5188235Z >>> loader, optimizer, model, loss_fn = ... 2025-08-26T23:22:16.5188300Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-08-26T23:22:16.5188379Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-08-26T23:22:16.5188425Z >>> T_max=300) 2025-08-26T23:22:16.5188467Z >>> swa_start = 160 2025-08-26T23:22:16.5188525Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-08-26T23:22:16.5188564Z >>> for i in range(300): 2025-08-26T23:22:16.5188611Z >>> for input, target in loader: 2025-08-26T23:22:16.5188655Z >>> optimizer.zero_grad() 2025-08-26T23:22:16.5188709Z >>> loss_fn(model(input), target).backward() 2025-08-26T23:22:16.5188752Z >>> optimizer.step() 2025-08-26T23:22:16.5189761Z >>> if i > swa_start: 2025-08-26T23:22:16.5189812Z >>> swa_model.update_parameters(model) 2025-08-26T23:22:16.5189858Z >>> swa_scheduler.step() 2025-08-26T23:22:16.5189895Z >>> else: 2025-08-26T23:22:16.5189936Z >>> scheduler.step() 2025-08-26T23:22:16.5189968Z >>> 2025-08-26T23:22:16.5190027Z >>> # Update bn statistics for the swa_model at the end 2025-08-26T23:22:16.5190128Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-08-26T23:22:16.5190159Z 2025-08-26T23:22:16.5190266Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-08-26T23:22:16.5190389Z If no averaging function is provided, the default is to compute 2025-08-26T23:22:16.5190448Z equally-weighted average of the weights (SWA). 2025-08-26T23:22:16.5190479Z 2025-08-26T23:22:16.5190515Z Example: 2025-08-26T23:22:16.5190566Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5190642Z >>> # Compute exponential moving averages of the weights and buffers 2025-08-26T23:22:16.5190706Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-08-26T23:22:16.5190787Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-08-26T23:22:16.5190818Z 2025-08-26T23:22:16.5190852Z .. note:: 2025-08-26T23:22:16.5190934Z When using SWA/EMA with models containing Batch Normalization you may 2025-08-26T23:22:16.5191993Z need to update the activation statistics for Batch Normalization. 2025-08-26T23:22:16.5192078Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-08-26T23:22:16.5192160Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-08-26T23:22:16.5192249Z statistics in a post-training step by passing data through the model. The 2025-08-26T23:22:16.5192334Z second does it during the parameter update phase by averaging all buffers. 2025-08-26T23:22:16.5192419Z Empirical evidence has shown that updating the statistics in normalization 2025-08-26T23:22:16.5192499Z layers increases accuracy, but you may wish to empirically test which 2025-08-26T23:22:16.5192559Z approach yields the best results in your problem. 2025-08-26T23:22:16.5192630Z 2025-08-26T23:22:16.5192665Z .. note:: 2025-08-26T23:22:16.5192759Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-08-26T23:22:16.5192789Z 2025-08-26T23:22:16.5192821Z .. note:: 2025-08-26T23:22:16.5192894Z When :meth:`update_parameters` is called for the first time (i.e. 2025-08-26T23:22:16.5192962Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-08-26T23:22:16.5193053Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-08-26T23:22:16.5193122Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-08-26T23:22:16.5193165Z to update the parameters. 2025-08-26T23:22:16.5193196Z 2025-08-26T23:22:16.5193275Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T23:22:16.5193324Z https://arxiv.org/abs/1803.05407 2025-08-26T23:22:16.5193412Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-08-26T23:22:16.5194414Z Average: 2025-08-26T23:22:16.5194518Z https://arxiv.org/abs/1806.05594 2025-08-26T23:22:16.5194593Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-08-26T23:22:16.5194637Z https://arxiv.org/abs/1904.11943 2025-08-26T23:22:16.5194716Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-08-26T23:22:16.5194759Z Generalizes Well: 2025-08-26T23:22:16.5194805Z https://arxiv.org/abs/2001.02312 2025-08-26T23:22:16.5194844Z .. _Polyak averaging: 2025-08-26T23:22:16.5194910Z https://paperswithcode.com/method/polyak-averaging 2025-08-26T23:22:16.5194943Z 2025-08-26T23:22:16.5195031Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5195062Z 2025-08-26T23:22:16.5195099Z warnings.warn(msg) 2025-08-26T23:22:16.5195157Z 2025-08-26T23:22:16.5195248Z --- Parse Warning: 37 / 146 --- 2025-08-26T23:22:16.5195532Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/swa_utils.py line=375. 2025-08-26T23:22:16.5195623Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5195705Z Anneals the learning rate in each parameter group to a fixed value. 2025-08-26T23:22:16.5195735Z 2025-08-26T23:22:16.5195819Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-08-26T23:22:16.5195894Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-08-26T23:22:16.5196901Z 2025-08-26T23:22:16.5196934Z Args: 2025-08-26T23:22:16.5197000Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-08-26T23:22:16.5197075Z swa_lrs (float or list): the learning rate value for all param groups 2025-08-26T23:22:16.5197131Z together or separately for each group. 2025-08-26T23:22:16.5197203Z annealing_epochs (int): number of epochs in the annealing phase 2025-08-26T23:22:16.5197242Z (default: 10) 2025-08-26T23:22:16.5197318Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-08-26T23:22:16.5197397Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-08-26T23:22:16.5197437Z (default: "cos") 2025-08-26T23:22:16.5197504Z last_epoch (int): the index of the last epoch (default: -1) 2025-08-26T23:22:16.5197533Z 2025-08-26T23:22:16.5197602Z The :class:`SWALR` scheduler can be used together with other 2025-08-26T23:22:16.5197682Z schedulers to switch to a constant learning rate late in the training 2025-08-26T23:22:16.5197723Z as in the example below. 2025-08-26T23:22:16.5197777Z 2025-08-26T23:22:16.5197812Z Example: 2025-08-26T23:22:16.5197865Z >>> # xdoctest: +SKIP("Undefined variables") 2025-08-26T23:22:16.5197911Z >>> loader, optimizer, model = ... 2025-08-26T23:22:16.5197957Z >>> lr_lambda = lambda epoch: 0.9 2025-08-26T23:22:16.5198038Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-08-26T23:22:16.5198080Z >>> lr_lambda=lr_lambda) 2025-08-26T23:22:16.5199124Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-08-26T23:22:16.5199192Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-08-26T23:22:16.5199230Z >>> swa_start = 160 2025-08-26T23:22:16.5199271Z >>> for i in range(300): 2025-08-26T23:22:16.5199317Z >>> for input, target in loader: 2025-08-26T23:22:16.5199361Z >>> optimizer.zero_grad() 2025-08-26T23:22:16.5199417Z >>> loss_fn(model(input), target).backward() 2025-08-26T23:22:16.5199465Z >>> optimizer.step() 2025-08-26T23:22:16.5199505Z >>> if i > swa_start: 2025-08-26T23:22:16.5199549Z >>> swa_scheduler.step() 2025-08-26T23:22:16.5199585Z >>> else: 2025-08-26T23:22:16.5199627Z >>> scheduler.step() 2025-08-26T23:22:16.5199657Z 2025-08-26T23:22:16.5199737Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T23:22:16.5199782Z https://arxiv.org/abs/1803.05407 2025-08-26T23:22:16.5199813Z 2025-08-26T23:22:16.5199901Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5199931Z 2025-08-26T23:22:16.5199969Z warnings.warn(msg) 2025-08-26T23:22:16.5199999Z 2025-08-26T23:22:16.5200070Z --- Parse Warning: 38 / 146 --- 2025-08-26T23:22:16.5200473Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/optimizer.py line=867. 2025-08-26T23:22:16.5201571Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5201612Z Load the optimizer state. 2025-08-26T23:22:16.5201643Z 2025-08-26T23:22:16.5201674Z Args: 2025-08-26T23:22:16.5201749Z state_dict (dict): optimizer state. Should be an object returned 2025-08-26T23:22:16.5201799Z from a call to :meth:`state_dict`. 2025-08-26T23:22:16.5201830Z 2025-08-26T23:22:16.5201868Z .. warning:: 2025-08-26T23:22:16.5201988Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-08-26T23:22:16.5202063Z as calling it beforehand will overwrite the loaded learning rates. 2025-08-26T23:22:16.5202095Z 2025-08-26T23:22:16.5202130Z .. note:: 2025-08-26T23:22:16.5202234Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-08-26T23:22:16.5202298Z in :meth:`state_dict`) will not affect the loading process. 2025-08-26T23:22:16.5202413Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-08-26T23:22:16.5202473Z differ from those initialized in the optimizer), 2025-08-26T23:22:16.5202580Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-08-26T23:22:16.5202619Z accordingly. 2025-08-26T23:22:16.5202722Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-08-26T23:22:16.5202831Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-08-26T23:22:16.5202916Z the optimizer ``param_names`` will remain unchanged. 2025-08-26T23:22:16.5203908Z 2025-08-26T23:22:16.5203945Z Example: 2025-08-26T23:22:16.5203986Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5204035Z >>> model = torch.nn.Linear(10, 10) 2025-08-26T23:22:16.5204101Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-08-26T23:22:16.5204162Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-08-26T23:22:16.5204226Z ... optim, 2025-08-26T23:22:16.5204269Z ... start_factor=0.1, 2025-08-26T23:22:16.5204306Z ... end_factor=1, 2025-08-26T23:22:16.5204345Z ... total_iters=20, 2025-08-26T23:22:16.5204378Z ... ) 2025-08-26T23:22:16.5204449Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-08-26T23:22:16.5204486Z ... optim, 2025-08-26T23:22:16.5204525Z ... T_max=80, 2025-08-26T23:22:16.5204568Z ... eta_min=3e-5, 2025-08-26T23:22:16.5204600Z ... ) 2025-08-26T23:22:16.5204657Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-08-26T23:22:16.5204693Z ... optim, 2025-08-26T23:22:16.5204746Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T23:22:16.5204786Z ... milestones=[20], 2025-08-26T23:22:16.5204819Z ... ) 2025-08-26T23:22:16.5204877Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-08-26T23:22:16.5205921Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-08-26T23:22:16.5205985Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-08-26T23:22:16.5206016Z 2025-08-26T23:22:16.5206047Z 2025-08-26T23:22:16.5206136Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5206167Z 2025-08-26T23:22:16.5206242Z warnings.warn(msg) 2025-08-26T23:22:16.5206272Z 2025-08-26T23:22:16.5206343Z --- Parse Warning: 39 / 146 --- 2025-08-26T23:22:16.5206638Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=808. 2025-08-26T23:22:16.5206733Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5206846Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-08-26T23:22:16.5206877Z 2025-08-26T23:22:16.5207003Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-08-26T23:22:16.5207081Z intervals by which each scheduler should be called at a given epoch. 2025-08-26T23:22:16.5207113Z 2025-08-26T23:22:16.5207145Z Args: 2025-08-26T23:22:16.5207202Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:22:16.5207258Z schedulers (list): List of chained schedulers. 2025-08-26T23:22:16.5207336Z milestones (list): List of integers that reflects milestone points. 2025-08-26T23:22:16.5207398Z last_epoch (int): The index of last epoch. Default: -1. 2025-08-26T23:22:16.5208391Z 2025-08-26T23:22:16.5208425Z Example: 2025-08-26T23:22:16.5208468Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5208528Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-08-26T23:22:16.5208572Z >>> # lr = 0.005 if epoch == 0 2025-08-26T23:22:16.5208613Z >>> # lr = 0.005 if epoch == 1 2025-08-26T23:22:16.5208654Z >>> # lr = 0.005 if epoch == 2 2025-08-26T23:22:16.5208686Z >>> # ... 2025-08-26T23:22:16.5208729Z >>> # lr = 0.05 if epoch == 20 2025-08-26T23:22:16.5208790Z >>> # lr = 0.045 if epoch == 21 2025-08-26T23:22:16.5208836Z >>> # lr = 0.0405 if epoch == 22 2025-08-26T23:22:16.5208910Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-08-26T23:22:16.5208969Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-08-26T23:22:16.5209013Z >>> scheduler = SequentialLR( 2025-08-26T23:22:16.5209052Z ... optimizer, 2025-08-26T23:22:16.5209120Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T23:22:16.5209160Z ... milestones=[20], 2025-08-26T23:22:16.5209193Z ... ) 2025-08-26T23:22:16.5209236Z >>> for epoch in range(100): 2025-08-26T23:22:16.5209274Z >>> train(...) 2025-08-26T23:22:16.5209313Z >>> validate(...) 2025-08-26T23:22:16.5209353Z >>> scheduler.step() 2025-08-26T23:22:16.5210407Z 2025-08-26T23:22:16.5210478Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-08-26T23:22:16.5210514Z 2025-08-26T23:22:16.5210606Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5210636Z 2025-08-26T23:22:16.5210673Z warnings.warn(msg) 2025-08-26T23:22:16.5210703Z 2025-08-26T23:22:16.5210775Z --- Parse Warning: 40 / 146 --- 2025-08-26T23:22:16.5211082Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-08-26T23:22:16.5211172Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5211242Z Reduce learning rate when a metric has stopped improving. 2025-08-26T23:22:16.5211273Z 2025-08-26T23:22:16.5211345Z Models often benefit from reducing the learning rate by a factor 2025-08-26T23:22:16.5211417Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-08-26T23:22:16.5211545Z quantity and if no improvement is seen for a 'patience' number 2025-08-26T23:22:16.5211594Z of epochs, the learning rate is reduced. 2025-08-26T23:22:16.5211624Z 2025-08-26T23:22:16.5211655Z Args: 2025-08-26T23:22:16.5211710Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:22:16.5211770Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-08-26T23:22:16.5211833Z be reduced when the quantity monitored has stopped 2025-08-26T23:22:16.5212880Z decreasing; in `max` mode it will be reduced when the 2025-08-26T23:22:16.5212951Z quantity monitored has stopped increasing. Default: 'min'. 2025-08-26T23:22:16.5213017Z factor (float): Factor by which the learning rate will be 2025-08-26T23:22:16.5213071Z reduced. new_lr = lr * factor. Default: 0.1. 2025-08-26T23:22:16.5213151Z patience (int): The number of allowed epochs with no improvement after 2025-08-26T23:22:16.5213205Z which the learning rate will be reduced. 2025-08-26T23:22:16.5213288Z For example, consider the case of having no patience (`patience = 0`). 2025-08-26T23:22:16.5213414Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-08-26T23:22:16.5213489Z In the second epoch, if the performance is worse than the baseline, 2025-08-26T23:22:16.5213546Z we have what is considered an intolerable epoch. 2025-08-26T23:22:16.5213640Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-08-26T23:22:16.5213703Z the learning rate is reduced at the end of this epoch. 2025-08-26T23:22:16.5213813Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-08-26T23:22:16.5213948Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-08-26T23:22:16.5213998Z the learning rate is not adjusted. 2025-08-26T23:22:16.5214038Z Default: 10. 2025-08-26T23:22:16.5214107Z threshold (float): Threshold for measuring the new optimum, 2025-08-26T23:22:16.5214168Z to only focus on significant changes. Default: 1e-4. 2025-08-26T23:22:16.5214251Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-08-26T23:22:16.5214312Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-08-26T23:22:16.5214367Z mode or best * ( 1 - threshold ) in `min` mode. 2025-08-26T23:22:16.5214426Z In `abs` mode, dynamic_threshold = best + threshold in 2025-08-26T23:22:16.5215479Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-08-26T23:22:16.5215545Z cooldown (int): Number of epochs to wait before resuming 2025-08-26T23:22:16.5215612Z normal operation after lr has been reduced. Default: 0. 2025-08-26T23:22:16.5215673Z min_lr (float or list): A scalar or a list of scalars. A 2025-08-26T23:22:16.5215732Z lower bound on the learning rate of all param groups 2025-08-26T23:22:16.5215785Z or each group respectively. Default: 0. 2025-08-26T23:22:16.5215850Z eps (float): Minimal decay applied to lr. If the difference 2025-08-26T23:22:16.5215919Z between new and old lr is smaller than eps, the update is 2025-08-26T23:22:16.5215961Z ignored. Default: 1e-8. 2025-08-26T23:22:16.5215992Z 2025-08-26T23:22:16.5216026Z Example: 2025-08-26T23:22:16.5216067Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5216150Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T23:22:16.5216210Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-08-26T23:22:16.5216270Z >>> for epoch in range(10): 2025-08-26T23:22:16.5216325Z >>> train(...) 2025-08-26T23:22:16.5216369Z >>> val_loss = validate(...) 2025-08-26T23:22:16.5216428Z >>> # Note that step should be called after validate() 2025-08-26T23:22:16.5216472Z >>> scheduler.step(val_loss) 2025-08-26T23:22:16.5216503Z 2025-08-26T23:22:16.5216574Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-08-26T23:22:16.5217589Z 2025-08-26T23:22:16.5217736Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-08-26T23:22:16.5217766Z 2025-08-26T23:22:16.5217809Z scheduler.step(val_loss) 2025-08-26T23:22:16.5217839Z ^ 2025-08-26T23:22:16.5217878Z warnings.warn(msg) 2025-08-26T23:22:16.5217907Z 2025-08-26T23:22:16.5217980Z --- Parse Warning: 41 / 146 --- 2025-08-26T23:22:16.5218274Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-08-26T23:22:16.5218367Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5218481Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-08-26T23:22:16.5218512Z 2025-08-26T23:22:16.5218613Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-08-26T23:22:16.5218707Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-08-26T23:22:16.5218791Z The distance between the two boundaries can be scaled on a per-iteration 2025-08-26T23:22:16.5218832Z or per-cycle basis. 2025-08-26T23:22:16.5218862Z 2025-08-26T23:22:16.5218949Z Cyclical learning rate policy changes the learning rate after every batch. 2025-08-26T23:22:16.5219050Z `step` should be called after a batch has been used for training. 2025-08-26T23:22:16.5219080Z 2025-08-26T23:22:16.5219156Z This class has three built-in policies, as put forth in the paper: 2025-08-26T23:22:16.5219186Z 2025-08-26T23:22:16.5220235Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-08-26T23:22:16.5220442Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-08-26T23:22:16.5220555Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-08-26T23:22:16.5220597Z at each cycle iteration. 2025-08-26T23:22:16.5220627Z 2025-08-26T23:22:16.5220712Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-08-26T23:22:16.5220742Z 2025-08-26T23:22:16.5220774Z Args: 2025-08-26T23:22:16.5220830Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:22:16.5220899Z base_lr (float or list): Initial learning rate which is the 2025-08-26T23:22:16.5220963Z lower boundary in the cycle for each parameter group. 2025-08-26T23:22:16.5221035Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T23:22:16.5221088Z for each parameter group. Functionally, 2025-08-26T23:22:16.5221148Z it defines the cycle amplitude (max_lr - base_lr). 2025-08-26T23:22:16.5221201Z The lr at any cycle is the sum of base_lr 2025-08-26T23:22:16.5221255Z and some scaling of the amplitude; therefore 2025-08-26T23:22:16.5221311Z max_lr may not actually be reached depending on 2025-08-26T23:22:16.5221351Z scaling function. 2025-08-26T23:22:16.5221416Z step_size_up (int): Number of training iterations in the 2025-08-26T23:22:16.5221467Z increasing half of a cycle. Default: 2000 2025-08-26T23:22:16.5221583Z step_size_down (int): Number of training iterations in the 2025-08-26T23:22:16.5221646Z decreasing half of a cycle. If step_size_down is None, 2025-08-26T23:22:16.5222679Z it is set to step_size_up. Default: None 2025-08-26T23:22:16.5222742Z mode (str): One of {triangular, triangular2, exp_range}. 2025-08-26T23:22:16.5222801Z Values correspond to policies detailed above. 2025-08-26T23:22:16.5222860Z If scale_fn is not None, this argument is ignored. 2025-08-26T23:22:16.5222903Z Default: 'triangular' 2025-08-26T23:22:16.5222965Z gamma (float): Constant in 'exp_range' scaling function: 2025-08-26T23:22:16.5223009Z gamma**(cycle iterations) 2025-08-26T23:22:16.5223048Z Default: 1.0 2025-08-26T23:22:16.5223118Z scale_fn (function): Custom scaling policy defined by a single 2025-08-26T23:22:16.5223165Z argument lambda function, where 2025-08-26T23:22:16.5223215Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-08-26T23:22:16.5223264Z If specified, then 'mode' is ignored. 2025-08-26T23:22:16.5223303Z Default: None 2025-08-26T23:22:16.5223354Z scale_mode (str): {'cycle', 'iterations'}. 2025-08-26T23:22:16.5223406Z Defines whether scale_fn is evaluated on 2025-08-26T23:22:16.5223458Z cycle number or cycle iterations (training 2025-08-26T23:22:16.5223504Z iterations since start of cycle). 2025-08-26T23:22:16.5223545Z Default: 'cycle' 2025-08-26T23:22:16.5223619Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T23:22:16.5223687Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T23:22:16.5223725Z Default: True 2025-08-26T23:22:16.5224772Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T23:22:16.5224880Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T23:22:16.5224941Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T23:22:16.5224996Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T23:22:16.5225034Z Default: 0.8 2025-08-26T23:22:16.5225113Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T23:22:16.5225182Z for each parameter group. Functionally, 2025-08-26T23:22:16.5225253Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T23:22:16.5225319Z The momentum at any cycle is the difference of max_momentum 2025-08-26T23:22:16.5225373Z and some scaling of the amplitude; therefore 2025-08-26T23:22:16.5225437Z base_momentum may not actually be reached depending on 2025-08-26T23:22:16.5225504Z scaling function. Note that momentum is cycled inversely 2025-08-26T23:22:16.5225584Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T23:22:16.5225628Z and learning rate is 'base_lr' 2025-08-26T23:22:16.5225666Z Default: 0.9 2025-08-26T23:22:16.5225747Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T23:22:16.5225828Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T23:22:16.5225905Z batch instead of after each epoch, this number represents the total 2025-08-26T23:22:16.5225986Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T23:22:16.5226057Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T23:22:16.5226096Z Default: -1 2025-08-26T23:22:16.5226127Z 2025-08-26T23:22:16.5227146Z Example: 2025-08-26T23:22:16.5227189Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5227307Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T23:22:16.5227367Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-08-26T23:22:16.5227407Z ... optimizer, 2025-08-26T23:22:16.5227444Z ... base_lr=0.01, 2025-08-26T23:22:16.5227482Z ... max_lr=0.1, 2025-08-26T23:22:16.5227522Z ... step_size_up=10, 2025-08-26T23:22:16.5227557Z ... ) 2025-08-26T23:22:16.5227616Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T23:22:16.5227658Z >>> for epoch in range(10): 2025-08-26T23:22:16.5227703Z >>> for batch in data_loader: 2025-08-26T23:22:16.5227743Z >>> train_batch(...) 2025-08-26T23:22:16.5227785Z >>> scheduler.step() 2025-08-26T23:22:16.5227815Z 2025-08-26T23:22:16.5227875Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-08-26T23:22:16.5227907Z 2025-08-26T23:22:16.5228017Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-08-26T23:22:16.5228080Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-08-26T23:22:16.5228111Z 2025-08-26T23:22:16.5228201Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5229202Z 2025-08-26T23:22:16.5229241Z warnings.warn(msg) 2025-08-26T23:22:16.5229272Z 2025-08-26T23:22:16.5229345Z --- Parse Warning: 42 / 146 --- 2025-08-26T23:22:16.5229678Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1722. 2025-08-26T23:22:16.5229772Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5229885Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-08-26T23:22:16.5229918Z 2025-08-26T23:22:16.5229987Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-08-26T23:22:16.5230074Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-08-26T23:22:16.5230129Z of epochs between two warm restarts in SGDR: 2025-08-26T23:22:16.5230159Z 2025-08-26T23:22:16.5230208Z .. math:: 2025-08-26T23:22:16.5230278Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-08-26T23:22:16.5230333Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-08-26T23:22:16.5230421Z 2025-08-26T23:22:16.5230486Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-08-26T23:22:16.5230555Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-08-26T23:22:16.5230585Z 2025-08-26T23:22:16.5230629Z It has been proposed in 2025-08-26T23:22:16.5230697Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-08-26T23:22:16.5230729Z 2025-08-26T23:22:16.5231778Z Args: 2025-08-26T23:22:16.5231833Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:22:16.5231896Z T_0 (int): Number of iterations until the first restart. 2025-08-26T23:22:16.5232000Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-08-26T23:22:16.5232073Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-08-26T23:22:16.5232151Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-08-26T23:22:16.5232182Z 2025-08-26T23:22:16.5232246Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-08-26T23:22:16.5232293Z https://arxiv.org/abs/1608.03983 2025-08-26T23:22:16.5232324Z 2025-08-26T23:22:16.5232359Z Example: 2025-08-26T23:22:16.5232399Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5232531Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-08-26T23:22:16.5232616Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-08-26T23:22:16.5232657Z ... optimizer, T_0=20 2025-08-26T23:22:16.5232689Z ... ) 2025-08-26T23:22:16.5232730Z >>> for epoch in range(100): 2025-08-26T23:22:16.5232767Z >>> train(...) 2025-08-26T23:22:16.5232808Z >>> validate(...) 2025-08-26T23:22:16.5232848Z >>> scheduler.step() 2025-08-26T23:22:16.5232878Z 2025-08-26T23:22:16.5233937Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-08-26T23:22:16.5233970Z 2025-08-26T23:22:16.5234060Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5234091Z 2025-08-26T23:22:16.5234129Z warnings.warn(msg) 2025-08-26T23:22:16.5234163Z 2025-08-26T23:22:16.5234236Z --- Parse Warning: 43 / 146 --- 2025-08-26T23:22:16.5234617Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1872. 2025-08-26T23:22:16.5234709Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5234817Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-08-26T23:22:16.5234847Z 2025-08-26T23:22:16.5234953Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-08-26T23:22:16.5235053Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-08-26T23:22:16.5235102Z lower than the initial learning rate. 2025-08-26T23:22:16.5235209Z This policy was initially described in the paper `Super-Convergence: 2025-08-26T23:22:16.5235290Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-08-26T23:22:16.5235320Z 2025-08-26T23:22:16.5235408Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-08-26T23:22:16.5235479Z `step` should be called after a batch has been used for training. 2025-08-26T23:22:16.5235510Z 2025-08-26T23:22:16.5235552Z This scheduler is not chainable. 2025-08-26T23:22:16.5235601Z 2025-08-26T23:22:16.5236666Z Note also that the total number of steps in the cycle can be determined in one 2025-08-26T23:22:16.5236722Z of two ways (listed in order of precedence): 2025-08-26T23:22:16.5236752Z 2025-08-26T23:22:16.5236810Z #. A value for total_steps is explicitly provided. 2025-08-26T23:22:16.5236878Z #. A number of epochs (epochs) and a number of steps per epoch 2025-08-26T23:22:16.5236924Z (steps_per_epoch) are provided. 2025-08-26T23:22:16.5236995Z In this case, the number of total steps is inferred by 2025-08-26T23:22:16.5237044Z total_steps = epochs * steps_per_epoch 2025-08-26T23:22:16.5237075Z 2025-08-26T23:22:16.5237161Z You must either provide a value for total_steps or provide a value for both 2025-08-26T23:22:16.5237205Z epochs and steps_per_epoch. 2025-08-26T23:22:16.5237235Z 2025-08-26T23:22:16.5237346Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-08-26T23:22:16.5237448Z claims that "unpublished work has shown even better results by using only two phases". To 2025-08-26T23:22:16.5237536Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-08-26T23:22:16.5237566Z 2025-08-26T23:22:16.5237599Z Args: 2025-08-26T23:22:16.5237652Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T23:22:16.5237725Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T23:22:16.5237832Z for each parameter group. 2025-08-26T23:22:16.5237908Z total_steps (int): The total number of steps in the cycle. Note that 2025-08-26T23:22:16.5237985Z if a value is not provided here, then it must be inferred by providing 2025-08-26T23:22:16.5239011Z a value for epochs and steps_per_epoch. 2025-08-26T23:22:16.5239050Z Default: None 2025-08-26T23:22:16.5239127Z epochs (int): The number of epochs to train for. This is used along 2025-08-26T23:22:16.5239216Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-08-26T23:22:16.5239270Z if a value for total_steps is not provided. 2025-08-26T23:22:16.5239308Z Default: None 2025-08-26T23:22:16.5239391Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-08-26T23:22:16.5239475Z used along with epochs in order to infer the total number of steps in the 2025-08-26T23:22:16.5239537Z cycle if a value for total_steps is not provided. 2025-08-26T23:22:16.5239574Z Default: None 2025-08-26T23:22:16.5239657Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-08-26T23:22:16.5239703Z increasing the learning rate. 2025-08-26T23:22:16.5239741Z Default: 0.3 2025-08-26T23:22:16.5239791Z anneal_strategy (str): {'cos', 'linear'} 2025-08-26T23:22:16.5239881Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-08-26T23:22:16.5239920Z linear annealing. 2025-08-26T23:22:16.5239958Z Default: 'cos' 2025-08-26T23:22:16.5240031Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T23:22:16.5240099Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T23:22:16.5240164Z Default: True 2025-08-26T23:22:16.5240245Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T23:22:16.5241391Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T23:22:16.5241455Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T23:22:16.5241512Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T23:22:16.5241585Z Default: 0.85 2025-08-26T23:22:16.5241662Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T23:22:16.5241713Z for each parameter group. Functionally, 2025-08-26T23:22:16.5241784Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T23:22:16.5241833Z Note that momentum is cycled inversely 2025-08-26T23:22:16.5241908Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T23:22:16.5241959Z and learning rate is 'base_lr' 2025-08-26T23:22:16.5241997Z Default: 0.95 2025-08-26T23:22:16.5242064Z div_factor (float): Determines the initial learning rate via 2025-08-26T23:22:16.5242108Z initial_lr = max_lr/div_factor 2025-08-26T23:22:16.5242145Z Default: 25 2025-08-26T23:22:16.5242219Z final_div_factor (float): Determines the minimum learning rate via 2025-08-26T23:22:16.5242270Z min_lr = initial_lr/final_div_factor 2025-08-26T23:22:16.5242308Z Default: 1e4 2025-08-26T23:22:16.5242397Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-08-26T23:22:16.5242490Z learning rate according to 'final_div_factor' instead of modifying the second 2025-08-26T23:22:16.5242577Z phase (the first two phases will be symmetrical about the step indicated by 2025-08-26T23:22:16.5242616Z 'pct_start'). 2025-08-26T23:22:16.5242735Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T23:22:16.5243788Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T23:22:16.5243867Z batch instead of after each epoch, this number represents the total 2025-08-26T23:22:16.5243948Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T23:22:16.5244022Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T23:22:16.5244061Z Default: -1 2025-08-26T23:22:16.5244091Z 2025-08-26T23:22:16.5244125Z Example: 2025-08-26T23:22:16.5244164Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5244224Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T23:22:16.5244308Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-08-26T23:22:16.5244371Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-08-26T23:22:16.5244451Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-08-26T23:22:16.5244484Z ... ) 2025-08-26T23:22:16.5244526Z >>> for epoch in range(10): 2025-08-26T23:22:16.5244569Z >>> for batch in data_loader: 2025-08-26T23:22:16.5244610Z >>> train_batch(...) 2025-08-26T23:22:16.5244651Z >>> optimizer.step() 2025-08-26T23:22:16.5244694Z >>> scheduler.step() 2025-08-26T23:22:16.5244724Z 2025-08-26T23:22:16.5244788Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-08-26T23:22:16.5244818Z 2025-08-26T23:22:16.5245897Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-08-26T23:22:16.5245944Z https://arxiv.org/abs/1708.07120 2025-08-26T23:22:16.5245976Z 2025-08-26T23:22:16.5246097Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5246132Z 2025-08-26T23:22:16.5246170Z warnings.warn(msg) 2025-08-26T23:22:16.5246201Z 2025-08-26T23:22:16.5246273Z --- Parse Warning: 44 / 146 --- 2025-08-26T23:22:16.5246613Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/fake_profile.py line=94. 2025-08-26T23:22:16.5246705Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5246736Z 2025-08-26T23:22:16.5246819Z Registers a fake kernel based on the given operator profiles. This fake 2025-08-26T23:22:16.5246906Z kernel registration will override any existing fake kernel registrations. 2025-08-26T23:22:16.5246936Z 2025-08-26T23:22:16.5247014Z The input is a dictionary mapping operator names to a set of operator 2025-08-26T23:22:16.5247100Z profiles, which we will use to generate fake kernels. The operator profiles 2025-08-26T23:22:16.5247174Z are a record of the input and output tensor metadata. Based on this 2025-08-26T23:22:16.5247257Z information we will match a given input to the recorded profile, and return 2025-08-26T23:22:16.5247336Z an output with the same metadata as in the recorded profile. If a profile 2025-08-26T23:22:16.5247391Z doesn't exist then an exception will be thrown. 2025-08-26T23:22:16.5247422Z 2025-08-26T23:22:16.5247502Z The fake kernel generation is considered unsafe because it relies on the 2025-08-26T23:22:16.5248562Z rigid, pre-defined operator profiles that do not account for potential 2025-08-26T23:22:16.5248651Z variations in output behavior. Specifically, the generated kernels assume a 2025-08-26T23:22:16.5248739Z fixed relationship between input and output ranks. However, in reality, it's 2025-08-26T23:22:16.5248824Z possible that data-dependent operations may produce outputs of different 2025-08-26T23:22:16.5248932Z ranks even when given inputs of the same rank. The generated fake kernels 2025-08-26T23:22:16.5249011Z are inflexible and unable to accommodate these nuances, making them 2025-08-26T23:22:16.5249049Z potentially unsafe. 2025-08-26T23:22:16.5249080Z 2025-08-26T23:22:16.5249112Z Args: 2025-08-26T23:22:16.5249192Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-08-26T23:22:16.5249265Z name to a set of operator profiles from which we will generate fake 2025-08-26T23:22:16.5249299Z kernels. 2025-08-26T23:22:16.5249329Z 2025-08-26T23:22:16.5249362Z Examples: 2025-08-26T23:22:16.5249392Z 2025-08-26T23:22:16.5249458Z >>> # Example: Registering an op-profile from draft-export 2025-08-26T23:22:16.5249494Z >>> import torch 2025-08-26T23:22:16.5249556Z >>> from torch.export._draft_export import draft_export 2025-08-26T23:22:16.5249589Z >>> 2025-08-26T23:22:16.5249660Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-08-26T23:22:16.5249711Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T23:22:16.5250800Z >>> return x + y 2025-08-26T23:22:16.5250833Z >>> 2025-08-26T23:22:16.5250877Z >>> class M(torch.nn.Module): 2025-08-26T23:22:16.5250919Z >>> def forward(self, a, b): 2025-08-26T23:22:16.5250979Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-08-26T23:22:16.5251017Z >>> return res 2025-08-26T23:22:16.5251047Z >>> 2025-08-26T23:22:16.5251112Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-08-26T23:22:16.5251142Z >>> 2025-08-26T23:22:16.5251248Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-08-26T23:22:16.5251296Z >>> decomp = ep.run_decompositions() 2025-08-26T23:22:16.5251361Z 2025-08-26T23:22:16.5251393Z 2025-08-26T23:22:16.5251484Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5251514Z 2025-08-26T23:22:16.5251552Z warnings.warn(msg) 2025-08-26T23:22:16.5251581Z 2025-08-26T23:22:16.5251654Z --- Parse Warning: 45 / 146 --- 2025-08-26T23:22:16.5252001Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/custom_ops.py line=397. 2025-08-26T23:22:16.5252090Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5252157Z Register a FakeTensor implementation for this custom op. 2025-08-26T23:22:16.5252187Z 2025-08-26T23:22:16.5253268Z This is necessary to get the operator to work efficiently with torch.compile. 2025-08-26T23:22:16.5253302Z 2025-08-26T23:22:16.5253387Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-08-26T23:22:16.5253469Z specifies the behavior of this operator on Tensors that carry no data. 2025-08-26T23:22:16.5253526Z Given some input Tensors with certain properties 2025-08-26T23:22:16.5253619Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-08-26T23:22:16.5253661Z the output Tensors are. 2025-08-26T23:22:16.5253694Z 2025-08-26T23:22:16.5253769Z Please see :func:`torch.library.register_fake` for more details. 2025-08-26T23:22:16.5253799Z 2025-08-26T23:22:16.5253833Z Args: 2025-08-26T23:22:16.5253898Z fn (Callable): The function to register as the FakeTensor 2025-08-26T23:22:16.5253939Z implementation. 2025-08-26T23:22:16.5253969Z 2025-08-26T23:22:16.5254004Z Examples: 2025-08-26T23:22:16.5254043Z >>> import torch 2025-08-26T23:22:16.5254113Z >>> import numpy as np 2025-08-26T23:22:16.5254174Z >>> from torch import Tensor 2025-08-26T23:22:16.5254207Z >>> 2025-08-26T23:22:16.5254278Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T23:22:16.5254349Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-08-26T23:22:16.5254422Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T23:22:16.5255447Z >>> return (x @ weight.t()) + bias 2025-08-26T23:22:16.5255480Z >>> 2025-08-26T23:22:16.5255525Z >>> @linear.register_fake 2025-08-26T23:22:16.5255569Z >>> def _(x, weight, bias): 2025-08-26T23:22:16.5255610Z >>> assert x.dim() == 2 2025-08-26T23:22:16.5255655Z >>> assert weight.dim() == 2 2025-08-26T23:22:16.5255698Z >>> assert bias.dim() == 1 2025-08-26T23:22:16.5255752Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T23:22:16.5255806Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T23:22:16.5255855Z >>> assert x.device == weight.device 2025-08-26T23:22:16.5255913Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-08-26T23:22:16.5255945Z >>> 2025-08-26T23:22:16.5255986Z >>> x = torch.randn(2, 2) 2025-08-26T23:22:16.5256032Z >>> weight = torch.randn(2, 2) 2025-08-26T23:22:16.5256072Z >>> bias = torch.randn(2) 2025-08-26T23:22:16.5256127Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:22:16.5256196Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-08-26T23:22:16.5256249Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:22:16.5256340Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-08-26T23:22:16.5256398Z >>> 2025-08-26T23:22:16.5256463Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T23:22:16.5257505Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-08-26T23:22:16.5257555Z >>> def nonzero(x: Tensor) -> Tensor: 2025-08-26T23:22:16.5257600Z >>> x_np = x.cpu().numpy() 2025-08-26T23:22:16.5257671Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T23:22:16.5257727Z >>> return torch.tensor(res, device=x.device) 2025-08-26T23:22:16.5257758Z >>> 2025-08-26T23:22:16.5257802Z >>> @nonzero.register_fake 2025-08-26T23:22:16.5257840Z >>> def _(x): 2025-08-26T23:22:16.5257899Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T23:22:16.5257960Z >>> # Since we cannot peek at the data in an abstract impl, 2025-08-26T23:22:16.5258023Z >>> # we use the ctx object to construct a new symint that 2025-08-26T23:22:16.5258074Z >>> # represents the data-dependent size. 2025-08-26T23:22:16.5258123Z >>> ctx = torch.library.get_ctx() 2025-08-26T23:22:16.5258170Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T23:22:16.5258213Z >>> shape = [nnz, x.dim()] 2025-08-26T23:22:16.5258273Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T23:22:16.5258313Z >>> return result 2025-08-26T23:22:16.5258345Z >>> 2025-08-26T23:22:16.5258392Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-08-26T23:22:16.5258445Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:22:16.5258502Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-08-26T23:22:16.5258554Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T23:22:16.5259620Z >>> assert torch.allclose(out, x.nonzero()) 2025-08-26T23:22:16.5259652Z 2025-08-26T23:22:16.5259684Z 2025-08-26T23:22:16.5259866Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-08-26T23:22:16.5259897Z 2025-08-26T23:22:16.5259930Z _._ = None 2025-08-26T23:22:16.5259961Z ^ 2025-08-26T23:22:16.5260000Z warnings.warn(msg) 2025-08-26T23:22:16.5260032Z 2025-08-26T23:22:16.5260104Z --- Parse Warning: 46 / 146 --- 2025-08-26T23:22:16.5260457Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/triton.py line=96. 2025-08-26T23:22:16.5260551Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5260643Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-08-26T23:22:16.5260676Z 2025-08-26T23:22:16.5260751Z This is a more structured way of using triton kernels with PyTorch. 2025-08-26T23:22:16.5260843Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-08-26T23:22:16.5260935Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-08-26T23:22:16.5260973Z that is simpler; 2025-08-26T23:22:16.5261062Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-08-26T23:22:16.5261145Z want to create an operator that behaves like PyTorch built-in operators. 2025-08-26T23:22:16.5261220Z For example, you may use a ``torch.library`` wrapper API to define the 2025-08-26T23:22:16.5262289Z behavior of the triton kernel when passed a tensor subclass or under 2025-08-26T23:22:16.5262330Z a TorchDispatchMode. 2025-08-26T23:22:16.5262395Z 2025-08-26T23:22:16.5262489Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-08-26T23:22:16.5262530Z when the implementation 2025-08-26T23:22:16.5262607Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-08-26T23:22:16.5262673Z custom operators as opaque (:func:`torch.compile` and 2025-08-26T23:22:16.5262757Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-08-26T23:22:16.5262854Z makes the implementation visible to these subsystems, allowing them 2025-08-26T23:22:16.5262899Z to optimize the triton kernel(s). 2025-08-26T23:22:16.5262931Z 2025-08-26T23:22:16.5263002Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-08-26T23:22:16.5263081Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-08-26T23:22:16.5263154Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-08-26T23:22:16.5263187Z 2025-08-26T23:22:16.5263220Z Args: 2025-08-26T23:22:16.5263303Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-08-26T23:22:16.5263381Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-08-26T23:22:16.5263444Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-08-26T23:22:16.5263530Z To avoid name collisions, please use your project name as the namespace; 2025-08-26T23:22:16.5263605Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-08-26T23:22:16.5263705Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-08-26T23:22:16.5264761Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-08-26T23:22:16.5264857Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-08-26T23:22:16.5264946Z schema (None | str): A schema string for the operator. If None 2025-08-26T23:22:16.5265044Z (recommended) we'll infer a schema for the operator from its type 2025-08-26T23:22:16.5265116Z annotations. We recommend letting us infer a schema unless you 2025-08-26T23:22:16.5265163Z have a specific reason not to. 2025-08-26T23:22:16.5265222Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-08-26T23:22:16.5265253Z 2025-08-26T23:22:16.5265291Z Example:: 2025-08-26T23:22:16.5265322Z 2025-08-26T23:22:16.5265378Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5265419Z >>> import torch 2025-08-26T23:22:16.5265476Z >>> from torch.library import triton_op, wrap_triton 2025-08-26T23:22:16.5265508Z >>> 2025-08-26T23:22:16.5265547Z >>> import triton 2025-08-26T23:22:16.5265594Z >>> from triton import language as tl 2025-08-26T23:22:16.5265628Z >>> 2025-08-26T23:22:16.5265667Z >>> @triton.jit 2025-08-26T23:22:16.5265705Z >>> def add_kernel( 2025-08-26T23:22:16.5265741Z >>> in_ptr0, 2025-08-26T23:22:16.5265777Z >>> in_ptr1, 2025-08-26T23:22:16.5266782Z >>> out_ptr, 2025-08-26T23:22:16.5266820Z >>> n_elements, 2025-08-26T23:22:16.5266866Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T23:22:16.5266899Z >>> ): 2025-08-26T23:22:16.5266947Z >>> pid = tl.program_id(axis=0) 2025-08-26T23:22:16.5266994Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T23:22:16.5267053Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T23:22:16.5267098Z >>> mask = offsets < n_elements 2025-08-26T23:22:16.5267149Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T23:22:16.5267201Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T23:22:16.5267265Z >>> output = x + y 2025-08-26T23:22:16.5267324Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T23:22:16.5267356Z >>> 2025-08-26T23:22:16.5267409Z >>> @triton_op("mylib::add", mutates_args={}) 2025-08-26T23:22:16.5267477Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-08-26T23:22:16.5267524Z >>> output = torch.empty_like(x) 2025-08-26T23:22:16.5267585Z >>> n_elements = output.numel() 2025-08-26T23:22:16.5267618Z >>> 2025-08-26T23:22:16.5267658Z >>> def grid(meta): 2025-08-26T23:22:16.5267721Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T23:22:16.5267753Z >>> 2025-08-26T23:22:16.5267820Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-08-26T23:22:16.5268858Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-08-26T23:22:16.5268905Z >>> return output 2025-08-26T23:22:16.5268937Z >>> 2025-08-26T23:22:16.5268977Z >>> @torch.compile 2025-08-26T23:22:16.5269013Z >>> def f(x, y): 2025-08-26T23:22:16.5269053Z >>> return add(x, y) 2025-08-26T23:22:16.5269086Z >>> 2025-08-26T23:22:16.5269132Z >>> x = torch.randn(3, device="cuda") 2025-08-26T23:22:16.5269178Z >>> y = torch.randn(3, device="cuda") 2025-08-26T23:22:16.5269211Z >>> 2025-08-26T23:22:16.5269248Z >>> z = f(x, y) 2025-08-26T23:22:16.5269293Z >>> assert torch.allclose(z, x + y) 2025-08-26T23:22:16.5269324Z 2025-08-26T23:22:16.5269355Z 2025-08-26T23:22:16.5269445Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5269475Z 2025-08-26T23:22:16.5269512Z warnings.warn(msg) 2025-08-26T23:22:16.5269542Z 2025-08-26T23:22:16.5269614Z --- Parse Warning: 47 / 146 --- 2025-08-26T23:22:16.5269942Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_library/triton.py line=296. 2025-08-26T23:22:16.5270035Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5270107Z Allows capture of a triton kernel into a graph via make_fx or 2025-08-26T23:22:16.5271185Z non-strict ``torch.export``. 2025-08-26T23:22:16.5271217Z 2025-08-26T23:22:16.5271288Z These technologies perform Dispatcher-based tracing (via 2025-08-26T23:22:16.5271359Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-08-26T23:22:16.5271432Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-08-26T23:22:16.5271478Z can actually be traced into a graph. 2025-08-26T23:22:16.5271510Z 2025-08-26T23:22:16.5271593Z Please use this API together with :func:`torch.library.triton_op`. 2025-08-26T23:22:16.5271623Z 2025-08-26T23:22:16.5271658Z Examples: 2025-08-26T23:22:16.5271688Z 2025-08-26T23:22:16.5271729Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5271766Z >>> import torch 2025-08-26T23:22:16.5271805Z >>> import triton 2025-08-26T23:22:16.5271850Z >>> from triton import language as tl 2025-08-26T23:22:16.5271922Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T23:22:16.5271972Z >>> from torch.library import wrap_triton 2025-08-26T23:22:16.5272005Z >>> 2025-08-26T23:22:16.5272042Z >>> @triton.jit 2025-08-26T23:22:16.5272079Z >>> def add_kernel( 2025-08-26T23:22:16.5272114Z >>> in_ptr0, 2025-08-26T23:22:16.5273122Z >>> in_ptr1, 2025-08-26T23:22:16.5273158Z >>> out_ptr, 2025-08-26T23:22:16.5273236Z >>> n_elements, 2025-08-26T23:22:16.5273286Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T23:22:16.5273318Z >>> ): 2025-08-26T23:22:16.5273363Z >>> pid = tl.program_id(axis=0) 2025-08-26T23:22:16.5273409Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T23:22:16.5273469Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T23:22:16.5273511Z >>> mask = offsets < n_elements 2025-08-26T23:22:16.5273581Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T23:22:16.5273632Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T23:22:16.5273675Z >>> output = x + y 2025-08-26T23:22:16.5273732Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T23:22:16.5273764Z >>> 2025-08-26T23:22:16.5273802Z >>> def add(x, y): 2025-08-26T23:22:16.5273848Z >>> output = torch.empty_like(x) 2025-08-26T23:22:16.5273894Z >>> n_elements = output.numel() 2025-08-26T23:22:16.5273928Z >>> 2025-08-26T23:22:16.5273969Z >>> def grid_fn(meta): 2025-08-26T23:22:16.5274032Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T23:22:16.5274064Z >>> 2025-08-26T23:22:16.5274136Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-08-26T23:22:16.5275261Z >>> return output 2025-08-26T23:22:16.5275297Z >>> 2025-08-26T23:22:16.5275343Z >>> x = torch.randn(3, device="cuda") 2025-08-26T23:22:16.5275388Z >>> y = torch.randn(3, device="cuda") 2025-08-26T23:22:16.5275430Z >>> gm = make_fx(add)(x, y) 2025-08-26T23:22:16.5275469Z >>> print(gm.code) 2025-08-26T23:22:16.5275514Z >>> # def forward(self, x_1, y_1): 2025-08-26T23:22:16.5275601Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-08-26T23:22:16.5275734Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-08-26T23:22:16.5275786Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-08-26T23:22:16.5275835Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-08-26T23:22:16.5275896Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-08-26T23:22:16.5275949Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-08-26T23:22:16.5275985Z >>> # }) 2025-08-26T23:22:16.5276026Z >>> # return empty_like 2025-08-26T23:22:16.5276057Z 2025-08-26T23:22:16.5276088Z 2025-08-26T23:22:16.5276178Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5276209Z 2025-08-26T23:22:16.5276247Z warnings.warn(msg) 2025-08-26T23:22:16.5276277Z 2025-08-26T23:22:16.5276348Z --- Parse Warning: 48 / 146 --- 2025-08-26T23:22:16.5277676Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-08-26T23:22:16.5277774Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5277847Z Return a new dict with new, potentially nested, key value pair 2025-08-26T23:22:16.5277879Z 2025-08-26T23:22:16.5277917Z >>> purchase = { 2025-08-26T23:22:16.5277956Z ... "name": "Alice", 2025-08-26T23:22:16.5278022Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:22:16.5278072Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:22:16.5278104Z ... } 2025-08-26T23:22:16.5278180Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-08-26T23:22:16.5278245Z {'credit card': '5555-1234-1234-1234', 2025-08-26T23:22:16.5278286Z 'name': 'Alice', 2025-08-26T23:22:16.5278350Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-08-26T23:22:16.5278382Z 2025-08-26T23:22:16.5278471Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5278502Z 2025-08-26T23:22:16.5278539Z warnings.warn(msg) 2025-08-26T23:22:16.5278570Z 2025-08-26T23:22:16.5278656Z --- Parse Warning: 49 / 146 --- 2025-08-26T23:22:16.5278993Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-08-26T23:22:16.5279083Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5280129Z Update value in a (potentially) nested dictionary 2025-08-26T23:22:16.5280166Z 2025-08-26T23:22:16.5280202Z inputs: 2025-08-26T23:22:16.5280248Z d - dictionary on which to operate 2025-08-26T23:22:16.5280329Z keys - list or tuple giving the location of the value to be changed in d 2025-08-26T23:22:16.5280452Z func - function to operate on that value 2025-08-26T23:22:16.5280483Z 2025-08-26T23:22:16.5280556Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-08-26T23:22:16.5280641Z original dictionary with v replaced by func(v), but does not mutate the 2025-08-26T23:22:16.5280680Z original dictionary. 2025-08-26T23:22:16.5280711Z 2025-08-26T23:22:16.5280787Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-08-26T23:22:16.5280866Z specified by the keys, with the innermost value set to func(default). 2025-08-26T23:22:16.5280896Z 2025-08-26T23:22:16.5280937Z >>> inc = lambda x: x + 1 2025-08-26T23:22:16.5280983Z >>> update_in({"a": 0}, ["a"], inc) 2025-08-26T23:22:16.5281071Z {'a': 1} 2025-08-26T23:22:16.5281103Z 2025-08-26T23:22:16.5281141Z >>> transaction = { 2025-08-26T23:22:16.5281180Z ... "name": "Alice", 2025-08-26T23:22:16.5281251Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:22:16.5281298Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:22:16.5282308Z ... } 2025-08-26T23:22:16.5282393Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-08-26T23:22:16.5282436Z {'credit card': '5555-1234-1234-1234', 2025-08-26T23:22:16.5282474Z 'name': 'Alice', 2025-08-26T23:22:16.5282537Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-08-26T23:22:16.5282568Z 2025-08-26T23:22:16.5282616Z >>> # updating a value when k0 is not in d 2025-08-26T23:22:16.5282670Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-08-26T23:22:16.5282709Z {1: {2: {3: 'bar'}}} 2025-08-26T23:22:16.5282760Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-08-26T23:22:16.5282798Z {1: 'foo', 2: {3: {4: 1}}} 2025-08-26T23:22:16.5282830Z 2025-08-26T23:22:16.5282919Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5282951Z 2025-08-26T23:22:16.5282987Z warnings.warn(msg) 2025-08-26T23:22:16.5283017Z 2025-08-26T23:22:16.5283090Z --- Parse Warning: 50 / 146 --- 2025-08-26T23:22:16.5283420Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-08-26T23:22:16.5283511Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5283576Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-08-26T23:22:16.5283639Z 2025-08-26T23:22:16.5284683Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-08-26T23:22:16.5284760Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-08-26T23:22:16.5284790Z 2025-08-26T23:22:16.5284865Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-08-26T23:22:16.5284915Z structures such as dictionaries and lists. 2025-08-26T23:22:16.5284972Z 2025-08-26T23:22:16.5285011Z >>> transaction = { 2025-08-26T23:22:16.5285050Z ... "name": "Alice", 2025-08-26T23:22:16.5285119Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T23:22:16.5285166Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T23:22:16.5285198Z ... } 2025-08-26T23:22:16.5285254Z >>> get_in(["purchase", "items", 0], transaction) 2025-08-26T23:22:16.5285289Z 'Apple' 2025-08-26T23:22:16.5285333Z >>> get_in(["name"], transaction) 2025-08-26T23:22:16.5285369Z 'Alice' 2025-08-26T23:22:16.5285421Z >>> get_in(["purchase", "total"], transaction) 2025-08-26T23:22:16.5285479Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-08-26T23:22:16.5285532Z >>> get_in(["purchase", "items", 10], transaction) 2025-08-26T23:22:16.5285584Z >>> get_in(["purchase", "total"], transaction, 0) 2025-08-26T23:22:16.5285616Z 0 2025-08-26T23:22:16.5285662Z >>> get_in(["y"], {}, no_default=True) 2025-08-26T23:22:16.5285707Z Traceback (most recent call last): 2025-08-26T23:22:16.5286702Z ... 2025-08-26T23:22:16.5286738Z KeyError: 'y' 2025-08-26T23:22:16.5286769Z 2025-08-26T23:22:16.5286802Z See Also: 2025-08-26T23:22:16.5286840Z itertoolz.get 2025-08-26T23:22:16.5286879Z operator.getitem 2025-08-26T23:22:16.5286910Z 2025-08-26T23:22:16.5287003Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5287071Z 2025-08-26T23:22:16.5287109Z warnings.warn(msg) 2025-08-26T23:22:16.5287139Z 2025-08-26T23:22:16.5287211Z --- Parse Warning: 51 / 146 --- 2025-08-26T23:22:16.5287551Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-08-26T23:22:16.5287643Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5287688Z Group a collection by a key function 2025-08-26T23:22:16.5287718Z 2025-08-26T23:22:16.5287783Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-08-26T23:22:16.5287831Z >>> groupby(len, names) # doctest: +SKIP 2025-08-26T23:22:16.5287894Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-08-26T23:22:16.5287926Z 2025-08-26T23:22:16.5287969Z >>> iseven = lambda x: x % 2 == 0 2025-08-26T23:22:16.5288035Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-08-26T23:22:16.5289047Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-08-26T23:22:16.5289079Z 2025-08-26T23:22:16.5289136Z Non-callable keys imply grouping on a member. 2025-08-26T23:22:16.5289167Z 2025-08-26T23:22:16.5289201Z >>> groupby( 2025-08-26T23:22:16.5289239Z ... "gender", 2025-08-26T23:22:16.5289270Z ... [ 2025-08-26T23:22:16.5289319Z ... {"name": "Alice", "gender": "F"}, 2025-08-26T23:22:16.5289365Z ... {"name": "Bob", "gender": "M"}, 2025-08-26T23:22:16.5289415Z ... {"name": "Charlie", "gender": "M"}, 2025-08-26T23:22:16.5289448Z ... ], 2025-08-26T23:22:16.5289487Z ... ) # doctest:+SKIP 2025-08-26T23:22:16.5289532Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-08-26T23:22:16.5289599Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-08-26T23:22:16.5289643Z {'gender': 'M', 'name': 'Charlie'}]} 2025-08-26T23:22:16.5289674Z 2025-08-26T23:22:16.5289728Z Not to be confused with ``itertools.groupby`` 2025-08-26T23:22:16.5289759Z 2025-08-26T23:22:16.5289793Z See Also: 2025-08-26T23:22:16.5289825Z countby 2025-08-26T23:22:16.5289857Z 2025-08-26T23:22:16.5289964Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5291046Z 2025-08-26T23:22:16.5291083Z warnings.warn(msg) 2025-08-26T23:22:16.5291114Z 2025-08-26T23:22:16.5291186Z --- Parse Warning: 52 / 146 --- 2025-08-26T23:22:16.5291486Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/profiler.py line=734. 2025-08-26T23:22:16.5291586Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5291721Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-08-26T23:22:16.5291791Z Label will only appear if CPU activity tracing is enabled. 2025-08-26T23:22:16.5291823Z 2025-08-26T23:22:16.5291872Z It is useful when tracing the code profile. 2025-08-26T23:22:16.5291903Z 2025-08-26T23:22:16.5291937Z Args: 2025-08-26T23:22:16.5291995Z name (str): Label assigned to the block of code. 2025-08-26T23:22:16.5292063Z node_id (int): ID of node, for distributed profiling. Unset in 2025-08-26T23:22:16.5292107Z non-distributed cases. 2025-08-26T23:22:16.5292136Z 2025-08-26T23:22:16.5292170Z Example: 2025-08-26T23:22:16.5292237Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-08-26T23:22:16.5292291Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-08-26T23:22:16.5292404Z >>> with torch.autograd.profiler.profile() as prof: 2025-08-26T23:22:16.5292441Z ... y = x**2 2025-08-26T23:22:16.5293490Z ... with torch.autograd.profiler.record_function( 2025-08-26T23:22:16.5293531Z ... "label-z" 2025-08-26T23:22:16.5293573Z ... ): # label the block 2025-08-26T23:22:16.5293610Z ... z = y**3 2025-08-26T23:22:16.5293651Z ... y.backward() 2025-08-26T23:22:16.5293693Z >>> # xdoctest: +IGNORE_WANT 2025-08-26T23:22:16.5293748Z >>> # NOTE: some columns were removed for brevity 2025-08-26T23:22:16.5293822Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-08-26T23:22:16.5293899Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5293968Z Name Self CPU total % CPU time avg Number of Calls 2025-08-26T23:22:16.5294046Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5294099Z pow 60.77% 47.470us 3 2025-08-26T23:22:16.5294151Z mul 21.73% 25.465us 2 2025-08-26T23:22:16.5294216Z PowBackward0 12.03% 121.891us 1 2025-08-26T23:22:16.5294297Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-08-26T23:22:16.5294352Z label-z 2.13% 12.421us 1 2025-08-26T23:22:16.5294425Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-08-26T23:22:16.5294496Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5294568Z Self CPU time total: 234.344us 2025-08-26T23:22:16.5294612Z CUDA time total: 0.000us 2025-08-26T23:22:16.5294644Z 2025-08-26T23:22:16.5294675Z 2025-08-26T23:22:16.5295731Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5295762Z 2025-08-26T23:22:16.5295800Z warnings.warn(msg) 2025-08-26T23:22:16.5295830Z 2025-08-26T23:22:16.5295904Z --- Parse Warning: 53 / 146 --- 2025-08-26T23:22:16.5296227Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-08-26T23:22:16.5296320Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5296375Z Register a container-like type as pytree node. 2025-08-26T23:22:16.5296407Z 2025-08-26T23:22:16.5296441Z Args: 2025-08-26T23:22:16.5296513Z cls (type): A Python type to treat as an internal pytree node. 2025-08-26T23:22:16.5296610Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-08-26T23:22:16.5296702Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-08-26T23:22:16.5296806Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-08-26T23:22:16.5296854Z passed to the ``unflatten_fn``. 2025-08-26T23:22:16.5296952Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-08-26T23:22:16.5297046Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-08-26T23:22:16.5297107Z The function should return an instance of ``cls``. 2025-08-26T23:22:16.5297203Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-08-26T23:22:16.5297297Z qualified name used when serializing the tree spec. 2025-08-26T23:22:16.5297406Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-08-26T23:22:16.5298495Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-08-26T23:22:16.5298597Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-08-26T23:22:16.5298703Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-08-26T23:22:16.5298797Z how to convert the custom json dumpable representation of the context back to the 2025-08-26T23:22:16.5298889Z original context. This is used for json deserialization, which is being used in 2025-08-26T23:22:16.5298936Z :mod:`torch.export` right now. 2025-08-26T23:22:16.5298968Z 2025-08-26T23:22:16.5299004Z Example:: 2025-08-26T23:22:16.5299036Z 2025-08-26T23:22:16.5299078Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5299136Z >>> # Registry a Python type with lambda functions 2025-08-26T23:22:16.5299179Z >>> register_pytree_node( 2025-08-26T23:22:16.5299215Z ... set, 2025-08-26T23:22:16.5299266Z ... lambda s: (sorted(s), None, None), 2025-08-26T23:22:16.5299317Z ... lambda children, _: set(children), 2025-08-26T23:22:16.5299350Z ... ) 2025-08-26T23:22:16.5299383Z 2025-08-26T23:22:16.5299471Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5299502Z 2025-08-26T23:22:16.5299539Z warnings.warn(msg) 2025-08-26T23:22:16.5299569Z 2025-08-26T23:22:16.5299640Z --- Parse Warning: 54 / 146 --- 2025-08-26T23:22:16.5301000Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1218. 2025-08-26T23:22:16.5301135Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5301167Z 2025-08-26T23:22:16.5301245Z Context passed to policy function during selective checkpointing. 2025-08-26T23:22:16.5301276Z 2025-08-26T23:22:16.5301386Z This class is used to pass relevant metadata to the policy function during 2025-08-26T23:22:16.5301482Z selective checkpointing. The metadata includes whether the current invocation 2025-08-26T23:22:16.5301543Z of the policy function is during recomputation or not. 2025-08-26T23:22:16.5301574Z 2025-08-26T23:22:16.5301607Z Example: 2025-08-26T23:22:16.5301651Z >>> # xdoctest: +SKIP(stub) 2025-08-26T23:22:16.5301683Z >>> 2025-08-26T23:22:16.5301735Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T23:22:16.5301781Z >>> print(ctx.is_recompute) 2025-08-26T23:22:16.5301814Z >>> 2025-08-26T23:22:16.5301913Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T23:22:16.5301945Z >>> 2025-08-26T23:22:16.5302003Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T23:22:16.5302040Z >>> fn, x, y, 2025-08-26T23:22:16.5302081Z >>> use_reentrant=False, 2025-08-26T23:22:16.5302123Z >>> context_fn=context_fn, 2025-08-26T23:22:16.5303136Z >>> ) 2025-08-26T23:22:16.5303167Z 2025-08-26T23:22:16.5303257Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5303287Z 2025-08-26T23:22:16.5303325Z warnings.warn(msg) 2025-08-26T23:22:16.5303355Z 2025-08-26T23:22:16.5303427Z --- Parse Warning: 55 / 146 --- 2025-08-26T23:22:16.5303780Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1358. 2025-08-26T23:22:16.5303893Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5303923Z 2025-08-26T23:22:16.5304009Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-08-26T23:22:16.5304039Z 2025-08-26T23:22:16.5304121Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-08-26T23:22:16.5304184Z operations are recomputed during the backward pass. 2025-08-26T23:22:16.5304214Z 2025-08-26T23:22:16.5304246Z Args: 2025-08-26T23:22:16.5304295Z policy_fn_or_list (Callable or List): 2025-08-26T23:22:16.5304359Z - If a policy function is provided, it should accept a 2025-08-26T23:22:16.5304446Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-08-26T23:22:16.5304525Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-08-26T23:22:16.5304611Z indicating whether the execution of the op should be recomputed or not. 2025-08-26T23:22:16.5304685Z - If a list of operations is provided, it is equivalent to a policy 2025-08-26T23:22:16.5305730Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-08-26T23:22:16.5305810Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-08-26T23:22:16.5305849Z operations. 2025-08-26T23:22:16.5305925Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-08-26T23:22:16.5306000Z raised if any tensors cached by selective activation checkpoint are 2025-08-26T23:22:16.5306075Z mutated in order to ensure correctness. If set to `True`, this check 2025-08-26T23:22:16.5306110Z is disabled. 2025-08-26T23:22:16.5306144Z Returns: 2025-08-26T23:22:16.5306206Z A tuple of two context managers. 2025-08-26T23:22:16.5306240Z 2025-08-26T23:22:16.5306275Z Example: 2025-08-26T23:22:16.5306318Z >>> # xdoctest: +REQUIRES(LINUX) 2025-08-26T23:22:16.5306357Z >>> import functools 2025-08-26T23:22:16.5306389Z >>> 2025-08-26T23:22:16.5306439Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-08-26T23:22:16.5306487Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-08-26T23:22:16.5306519Z >>> 2025-08-26T23:22:16.5306571Z >>> ops_to_save = [ 2025-08-26T23:22:16.5306619Z >>> torch.ops.aten.mm.default, 2025-08-26T23:22:16.5306651Z >>> ] 2025-08-26T23:22:16.5306683Z >>> 2025-08-26T23:22:16.5306733Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T23:22:16.5307745Z >>> if op in ops_to_save: 2025-08-26T23:22:16.5307796Z >>> return CheckpointPolicy.MUST_SAVE 2025-08-26T23:22:16.5307831Z >>> else: 2025-08-26T23:22:16.5307891Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-08-26T23:22:16.5307926Z >>> 2025-08-26T23:22:16.5308025Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T23:22:16.5308057Z >>> 2025-08-26T23:22:16.5308096Z >>> # or equivalently 2025-08-26T23:22:16.5308194Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-08-26T23:22:16.5308225Z >>> 2025-08-26T23:22:16.5308262Z >>> def fn(x, y): 2025-08-26T23:22:16.5308338Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-08-26T23:22:16.5308370Z >>> 2025-08-26T23:22:16.5308425Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T23:22:16.5308461Z >>> fn, x, y, 2025-08-26T23:22:16.5308503Z >>> use_reentrant=False, 2025-08-26T23:22:16.5308544Z >>> context_fn=context_fn, 2025-08-26T23:22:16.5308576Z >>> ) 2025-08-26T23:22:16.5308607Z 2025-08-26T23:22:16.5308719Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5308763Z 2025-08-26T23:22:16.5309775Z warnings.warn(msg) 2025-08-26T23:22:16.5309806Z 2025-08-26T23:22:16.5309879Z --- Parse Warning: 56 / 146 --- 2025-08-26T23:22:16.5310203Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-08-26T23:22:16.5310295Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5310326Z 2025-08-26T23:22:16.5310487Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-08-26T23:22:16.5310517Z 2025-08-26T23:22:16.5310623Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-08-26T23:22:16.5310715Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-08-26T23:22:16.5310799Z server like load. It can emulate multiple calling threads to a single module 2025-08-26T23:22:16.5310885Z provided. In the future we plan to enhance this component to support inter and 2025-08-26T23:22:16.5310971Z intra-op parallelism as well as multiple models running in a single process. 2025-08-26T23:22:16.5311002Z 2025-08-26T23:22:16.5311093Z Please note that even though nn.Module is supported, it might incur an overhead 2025-08-26T23:22:16.5311172Z from the need to hold GIL every time we execute Python code or pass around 2025-08-26T23:22:16.5311256Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-08-26T23:22:16.5311339Z model for inference deployment it is better to switch to using it in this 2025-08-26T23:22:16.5311374Z benchmark. 2025-08-26T23:22:16.5311404Z 2025-08-26T23:22:16.5311439Z Example:: 2025-08-26T23:22:16.5311507Z 2025-08-26T23:22:16.5312547Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5312604Z >>> from torch.utils import ThroughputBenchmark 2025-08-26T23:22:16.5312655Z >>> bench = ThroughputBenchmark(my_module) 2025-08-26T23:22:16.5312718Z >>> # Pre-populate benchmark's data set with the inputs 2025-08-26T23:22:16.5312759Z >>> for input in inputs: 2025-08-26T23:22:16.5312865Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-08-26T23:22:16.5312917Z ... bench.add_input(input[0], x2=input[1]) 2025-08-26T23:22:16.5312991Z >>> # Inputs supplied above are randomly used during the execution 2025-08-26T23:22:16.5313033Z >>> stats = bench.benchmark( 2025-08-26T23:22:16.5313074Z ... num_calling_threads=4, 2025-08-26T23:22:16.5313115Z ... num_warmup_iters = 100, 2025-08-26T23:22:16.5313155Z ... num_iters = 1000, 2025-08-26T23:22:16.5313189Z ... ) 2025-08-26T23:22:16.5313259Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-08-26T23:22:16.5313325Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-08-26T23:22:16.5313356Z 2025-08-26T23:22:16.5313445Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5313476Z 2025-08-26T23:22:16.5313513Z warnings.warn(msg) 2025-08-26T23:22:16.5313544Z 2025-08-26T23:22:16.5313616Z --- Parse Warning: 57 / 146 --- 2025-08-26T23:22:16.5314970Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1159. 2025-08-26T23:22:16.5315063Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5315095Z 2025-08-26T23:22:16.5315151Z Create a :class:`setuptools.Extension` for C++. 2025-08-26T23:22:16.5315209Z 2025-08-26T23:22:16.5315314Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:22:16.5315395Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-08-26T23:22:16.5315425Z 2025-08-26T23:22:16.5315503Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:22:16.5315559Z constructor. Full list arguments can be found at 2025-08-26T23:22:16.5315679Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T23:22:16.5315711Z 2025-08-26T23:22:16.5315745Z .. warning:: 2025-08-26T23:22:16.5315828Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:22:16.5315904Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:22:16.5315977Z the user's responsibility in their library to not use APIs from 2025-08-26T23:22:16.5316060Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:22:16.5316140Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:22:16.5316216Z example, to give access to custom ops from python, the library should 2025-08-26T23:22:16.5316266Z register the ops through the dispatcher. 2025-08-26T23:22:16.5316297Z 2025-08-26T23:22:16.5316375Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:22:16.5317426Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:22:16.5317503Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:22:16.5317580Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:22:16.5317656Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:22:16.5317734Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:22:16.5317801Z CPython version of choice. 2025-08-26T23:22:16.5317833Z 2025-08-26T23:22:16.5317868Z Example: 2025-08-26T23:22:16.5317909Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5317969Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:22:16.5318014Z >>> from setuptools import setup 2025-08-26T23:22:16.5318092Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-08-26T23:22:16.5318141Z >>> setup( 2025-08-26T23:22:16.5318182Z ... name='extension', 2025-08-26T23:22:16.5318220Z ... ext_modules=[ 2025-08-26T23:22:16.5318258Z ... CppExtension( 2025-08-26T23:22:16.5318300Z ... name='extension', 2025-08-26T23:22:16.5318348Z ... sources=['extension.cpp'], 2025-08-26T23:22:16.5318397Z ... extra_compile_args=['-g'], 2025-08-26T23:22:16.5318458Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-08-26T23:22:16.5318493Z ... ], 2025-08-26T23:22:16.5318532Z ... cmdclass={ 2025-08-26T23:22:16.5319545Z ... 'build_ext': BuildExtension 2025-08-26T23:22:16.5319577Z ... }) 2025-08-26T23:22:16.5319608Z 2025-08-26T23:22:16.5319697Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5319728Z 2025-08-26T23:22:16.5319765Z warnings.warn(msg) 2025-08-26T23:22:16.5319795Z 2025-08-26T23:22:16.5319869Z --- Parse Warning: 58 / 146 --- 2025-08-26T23:22:16.5320171Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1229. 2025-08-26T23:22:16.5320262Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5320293Z 2025-08-26T23:22:16.5320414Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-08-26T23:22:16.5320496Z 2025-08-26T23:22:16.5320581Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:22:16.5320656Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-08-26T23:22:16.5320738Z extension. This includes the CUDA include path, library path and runtime 2025-08-26T23:22:16.5320770Z library. 2025-08-26T23:22:16.5320802Z 2025-08-26T23:22:16.5320878Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:22:16.5320935Z constructor. Full list arguments can be found at 2025-08-26T23:22:16.5321051Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T23:22:16.5322067Z 2025-08-26T23:22:16.5322103Z .. warning:: 2025-08-26T23:22:16.5322185Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:22:16.5322261Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:22:16.5322338Z the user's responsibility in their library to not use APIs from 2025-08-26T23:22:16.5322418Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:22:16.5322496Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:22:16.5322570Z example, to give access to custom ops from python, the library should 2025-08-26T23:22:16.5322621Z register the ops through the dispatcher. 2025-08-26T23:22:16.5322652Z 2025-08-26T23:22:16.5322731Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:22:16.5322804Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:22:16.5322878Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:22:16.5322952Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:22:16.5323067Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:22:16.5323145Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:22:16.5323189Z CPython version of choice. 2025-08-26T23:22:16.5323220Z 2025-08-26T23:22:16.5323254Z Example: 2025-08-26T23:22:16.5323293Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5323352Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:22:16.5323419Z >>> from setuptools import setup 2025-08-26T23:22:16.5324475Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-08-26T23:22:16.5324510Z >>> setup( 2025-08-26T23:22:16.5324552Z ... name='cuda_extension', 2025-08-26T23:22:16.5324589Z ... ext_modules=[ 2025-08-26T23:22:16.5324629Z ... CUDAExtension( 2025-08-26T23:22:16.5324676Z ... name='cuda_extension', 2025-08-26T23:22:16.5324740Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:22:16.5324797Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T23:22:16.5324846Z ... 'nvcc': ['-O2']}, 2025-08-26T23:22:16.5324905Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-08-26T23:22:16.5324937Z ... ], 2025-08-26T23:22:16.5324974Z ... cmdclass={ 2025-08-26T23:22:16.5325021Z ... 'build_ext': BuildExtension 2025-08-26T23:22:16.5325053Z ... }) 2025-08-26T23:22:16.5325083Z 2025-08-26T23:22:16.5325122Z Compute capabilities: 2025-08-26T23:22:16.5325152Z 2025-08-26T23:22:16.5325261Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T23:22:16.5325366Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-08-26T23:22:16.5325470Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-08-26T23:22:16.5325612Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-08-26T23:22:16.5326682Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-08-26T23:22:16.5326732Z support (see below for details on PTX). 2025-08-26T23:22:16.5326763Z 2025-08-26T23:22:16.5326875Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-08-26T23:22:16.5326923Z CCs you want the extension to support: 2025-08-26T23:22:16.5326953Z 2025-08-26T23:22:16.5327025Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-08-26T23:22:16.5327109Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-08-26T23:22:16.5327140Z 2025-08-26T23:22:16.5327252Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-08-26T23:22:16.5327365Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-08-26T23:22:16.5327471Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-08-26T23:22:16.5327576Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-08-26T23:22:16.5327690Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-08-26T23:22:16.5327789Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-08-26T23:22:16.5327902Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-08-26T23:22:16.5328013Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-08-26T23:22:16.5328052Z "8.0 8.6" would be better. 2025-08-26T23:22:16.5328082Z 2025-08-26T23:22:16.5328210Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T23:22:16.5328314Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T23:22:16.5328345Z 2025-08-26T23:22:16.5329440Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-08-26T23:22:16.5329521Z To workaround the issue, move python binding logic to pure C++ file. 2025-08-26T23:22:16.5329571Z 2025-08-26T23:22:16.5329605Z Example use: 2025-08-26T23:22:16.5329645Z #include 2025-08-26T23:22:16.5329707Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-08-26T23:22:16.5329737Z 2025-08-26T23:22:16.5329771Z Instead of: 2025-08-26T23:22:16.5329813Z #include 2025-08-26T23:22:16.5329876Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-08-26T23:22:16.5329906Z 2025-08-26T23:22:16.5330008Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-08-26T23:22:16.5330191Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-08-26T23:22:16.5330222Z 2025-08-26T23:22:16.5330263Z Relocatable device code linking: 2025-08-26T23:22:16.5330294Z 2025-08-26T23:22:16.5330446Z If you want to reference device symbols across compilation units (across object files), 2025-08-26T23:22:16.5330541Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-08-26T23:22:16.5330667Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-08-26T23:22:16.5330782Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-08-26T23:22:16.5330895Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-08-26T23:22:16.5331993Z helps reduce the protentional perf degradation of `-rdc`. 2025-08-26T23:22:16.5332060Z Note that it needs to be used at both steps to be useful. 2025-08-26T23:22:16.5332091Z 2025-08-26T23:22:16.5332221Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-08-26T23:22:16.5332289Z There is also a case where `-dlink` is used without `-rdc`: 2025-08-26T23:22:16.5332382Z when an extension is linked against a static lib containing rdc-compiled objects 2025-08-26T23:22:16.5332463Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-08-26T23:22:16.5332493Z 2025-08-26T23:22:16.5332567Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-08-26T23:22:16.5332597Z 2025-08-26T23:22:16.5332630Z Example: 2025-08-26T23:22:16.5332670Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5332728Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:22:16.5332770Z >>> CUDAExtension( 2025-08-26T23:22:16.5332813Z ... name='cuda_extension', 2025-08-26T23:22:16.5332876Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:22:16.5332913Z ... dlink=True, 2025-08-26T23:22:16.5332961Z ... dlink_libraries=["dlink_lib"], 2025-08-26T23:22:16.5333011Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T23:22:16.5333063Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-08-26T23:22:16.5333093Z 2025-08-26T23:22:16.5333185Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5334178Z 2025-08-26T23:22:16.5334217Z warnings.warn(msg) 2025-08-26T23:22:16.5334247Z 2025-08-26T23:22:16.5334322Z --- Parse Warning: 59 / 146 --- 2025-08-26T23:22:16.5334628Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1420. 2025-08-26T23:22:16.5334750Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5334780Z 2025-08-26T23:22:16.5334844Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-08-26T23:22:16.5334874Z 2025-08-26T23:22:16.5334962Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T23:22:16.5335054Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-08-26T23:22:16.5335089Z extension. 2025-08-26T23:22:16.5335119Z 2025-08-26T23:22:16.5335194Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T23:22:16.5335229Z constructor. 2025-08-26T23:22:16.5335259Z 2025-08-26T23:22:16.5335294Z .. warning:: 2025-08-26T23:22:16.5335376Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T23:22:16.5335457Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T23:22:16.5335530Z the user's responsibility in their library to not use APIs from 2025-08-26T23:22:16.5335612Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T23:22:16.5335689Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T23:22:16.5336732Z example, to give access to custom ops from python, the library should 2025-08-26T23:22:16.5336783Z register the ops through the dispatcher. 2025-08-26T23:22:16.5336815Z 2025-08-26T23:22:16.5336894Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T23:22:16.5336970Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T23:22:16.5337044Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T23:22:16.5337121Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T23:22:16.5337236Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T23:22:16.5337314Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T23:22:16.5337357Z CPython version of choice. 2025-08-26T23:22:16.5337388Z 2025-08-26T23:22:16.5337421Z Example: 2025-08-26T23:22:16.5337461Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5337519Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:22:16.5337598Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-08-26T23:22:16.5337631Z >>> setup( 2025-08-26T23:22:16.5337674Z ... name='xpu_extension', 2025-08-26T23:22:16.5337711Z ... ext_modules=[ 2025-08-26T23:22:16.5337749Z ... SyclExtension( 2025-08-26T23:22:16.5337796Z ... name='xpu_extension', 2025-08-26T23:22:16.5337858Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-08-26T23:22:16.5338897Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-08-26T23:22:16.5338931Z ... ], 2025-08-26T23:22:16.5338968Z ... cmdclass={ 2025-08-26T23:22:16.5339013Z ... 'build_ext': BuildExtension 2025-08-26T23:22:16.5339045Z ... }) 2025-08-26T23:22:16.5339075Z 2025-08-26T23:22:16.5339183Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T23:22:16.5339274Z building process of the extension. If down the road a new card is installed the 2025-08-26T23:22:16.5339364Z extension may need to be recompiled. You can override the default behavior using 2025-08-26T23:22:16.5339469Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-08-26T23:22:16.5339504Z to support: 2025-08-26T23:22:16.5339534Z 2025-08-26T23:22:16.5339629Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-08-26T23:22:16.5339663Z 2025-08-26T23:22:16.5339768Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T23:22:16.5339873Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T23:22:16.5339903Z 2025-08-26T23:22:16.5339958Z Note: Ninja is required to build SyclExtension. 2025-08-26T23:22:16.5339989Z 2025-08-26T23:22:16.5340093Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5340124Z 2025-08-26T23:22:16.5340161Z warnings.warn(msg) 2025-08-26T23:22:16.5341239Z 2025-08-26T23:22:16.5341312Z --- Parse Warning: 60 / 146 --- 2025-08-26T23:22:16.5341600Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1597. 2025-08-26T23:22:16.5341697Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5341728Z 2025-08-26T23:22:16.5341786Z Load a PyTorch C++ extension just-in-time (JIT). 2025-08-26T23:22:16.5341816Z 2025-08-26T23:22:16.5341892Z To load an extension, a Ninja build file is emitted, which is used to 2025-08-26T23:22:16.5341967Z compile the given sources into a dynamic library. This library is 2025-08-26T23:22:16.5342051Z subsequently loaded into the current Python process as a module and 2025-08-26T23:22:16.5342100Z returned from this function, ready for use. 2025-08-26T23:22:16.5342131Z 2025-08-26T23:22:16.5342206Z By default, the directory to which the build file is emitted and the 2025-08-26T23:22:16.5342290Z resulting library compiled to is ``/torch_extensions/``, where 2025-08-26T23:22:16.5342363Z ```` is the temporary folder on the current platform and ```` 2025-08-26T23:22:16.5342497Z the name of the extension. This location can be overridden in two ways. 2025-08-26T23:22:16.5342571Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-08-26T23:22:16.5342649Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-08-26T23:22:16.5342727Z into subfolders of this directory. Second, if the ``build_directory`` 2025-08-26T23:22:16.5342809Z argument to this function is supplied, it overrides the entire path, i.e. 2025-08-26T23:22:16.5342872Z the library will be compiled into that folder directly. 2025-08-26T23:22:16.5343878Z 2025-08-26T23:22:16.5343955Z To compile the sources, the default system compiler (``c++``) is used, 2025-08-26T23:22:16.5344042Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-08-26T23:22:16.5344121Z additional arguments to the compilation process, ``extra_cflags`` or 2025-08-26T23:22:16.5344201Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-08-26T23:22:16.5344281Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-08-26T23:22:16.5344341Z ``extra_cflags`` to pass further include directories. 2025-08-26T23:22:16.5344372Z 2025-08-26T23:22:16.5344455Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-08-26T23:22:16.5344524Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-08-26T23:22:16.5344612Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-08-26T23:22:16.5344687Z passing the CUDA lib64 directory as a library directory, and linking 2025-08-26T23:22:16.5344747Z ``cudart``. You can pass additional flags to nvcc via 2025-08-26T23:22:16.5344820Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-08-26T23:22:16.5344902Z heuristics for finding the CUDA install directory are used, which usually 2025-08-26T23:22:16.5345005Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-08-26T23:22:16.5345043Z safest option. 2025-08-26T23:22:16.5345073Z 2025-08-26T23:22:16.5345155Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-08-26T23:22:16.5345228Z files (``.sycl``) along with other sources. Such files will be detected 2025-08-26T23:22:16.5345305Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-08-26T23:22:16.5345403Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-08-26T23:22:16.5346445Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-08-26T23:22:16.5346521Z SYCL compiler is expected to be found via system PATH environment 2025-08-26T23:22:16.5346554Z variable. 2025-08-26T23:22:16.5346586Z 2025-08-26T23:22:16.5346618Z Args: 2025-08-26T23:22:16.5346696Z name: The name of the extension to build. This MUST be the same as the 2025-08-26T23:22:16.5346741Z name of the pybind11 module! 2025-08-26T23:22:16.5346818Z sources: A list of relative or absolute paths to C++ source files. 2025-08-26T23:22:16.5346898Z extra_cflags: optional list of compiler flags to forward to the build. 2025-08-26T23:22:16.5346976Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-08-26T23:22:16.5347018Z when building CUDA sources. 2025-08-26T23:22:16.5347097Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-08-26T23:22:16.5347144Z compiler when building SYCL sources. 2025-08-26T23:22:16.5347221Z extra_ldflags: optional list of linker flags to forward to the build. 2025-08-26T23:22:16.5347297Z extra_include_paths: optional list of include directories to forward 2025-08-26T23:22:16.5347335Z to the build. 2025-08-26T23:22:16.5347403Z build_directory: optional path to use as build workspace. 2025-08-26T23:22:16.5347472Z verbose: If ``True``, turns on verbose logging of load steps. 2025-08-26T23:22:16.5347589Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T23:22:16.5347652Z the build. If set to ``None`` (default), this value is 2025-08-26T23:22:16.5347726Z automatically determined based on the existence of ``.cu`` or 2025-08-26T23:22:16.5348757Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-08-26T23:22:16.5348803Z and libraries to be included. 2025-08-26T23:22:16.5348881Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T23:22:16.5348942Z the build. If set to ``None`` (default), this value is 2025-08-26T23:22:16.5349016Z automatically determined based on the existence of ``.sycl`` in 2025-08-26T23:22:16.5349077Z ``sources``. Set it to `True`` to force SYCL headers and 2025-08-26T23:22:16.5349120Z libraries to be included. 2025-08-26T23:22:16.5349197Z is_python_module: If ``True`` (default), imports the produced shared 2025-08-26T23:22:16.5349267Z library as a Python module. If ``False``, behavior depends on 2025-08-26T23:22:16.5349306Z ``is_standalone``. 2025-08-26T23:22:16.5349379Z is_standalone: If ``False`` (default) loads the constructed extension 2025-08-26T23:22:16.5349450Z into the process as a plain dynamic library. If ``True``, build a 2025-08-26T23:22:16.5349493Z standalone executable. 2025-08-26T23:22:16.5349523Z 2025-08-26T23:22:16.5349555Z Returns: 2025-08-26T23:22:16.5349602Z If ``is_python_module`` is ``True``: 2025-08-26T23:22:16.5349669Z Returns the loaded PyTorch extension as a Python module. 2025-08-26T23:22:16.5349700Z 2025-08-26T23:22:16.5349775Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-08-26T23:22:16.5349851Z Returns nothing. (The shared library is loaded into the process as 2025-08-26T23:22:16.5349911Z a side effect.) 2025-08-26T23:22:16.5349944Z 2025-08-26T23:22:16.5351018Z If ``is_standalone`` is ``True``. 2025-08-26T23:22:16.5351092Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-08-26T23:22:16.5351157Z added to the PATH environment variable as a side effect.) 2025-08-26T23:22:16.5351188Z 2025-08-26T23:22:16.5351221Z Example: 2025-08-26T23:22:16.5351262Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5351344Z >>> from torch.utils.cpp_extension import load 2025-08-26T23:22:16.5351383Z >>> module = load( 2025-08-26T23:22:16.5351424Z ... name='extension', 2025-08-26T23:22:16.5351487Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T23:22:16.5351528Z ... extra_cflags=['-O2'], 2025-08-26T23:22:16.5351566Z ... verbose=True) 2025-08-26T23:22:16.5351596Z 2025-08-26T23:22:16.5351685Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5351720Z 2025-08-26T23:22:16.5351757Z warnings.warn(msg) 2025-08-26T23:22:16.5351789Z 2025-08-26T23:22:16.5351861Z --- Parse Warning: 61 / 146 --- 2025-08-26T23:22:16.5352158Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1882. 2025-08-26T23:22:16.5352252Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5352283Z 2025-08-26T23:22:16.5352360Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-08-26T23:22:16.5353362Z 2025-08-26T23:22:16.5353444Z This function behaves exactly like :func:`load`, but takes its sources as 2025-08-26T23:22:16.5353527Z strings rather than filenames. These strings are stored to files in the 2025-08-26T23:22:16.5353630Z build directory, after which the behavior of :func:`load_inline` is 2025-08-26T23:22:16.5353689Z identical to :func:`load`. 2025-08-26T23:22:16.5353718Z 2025-08-26T23:22:16.5353751Z See `the 2025-08-26T23:22:16.5353866Z tests `_ 2025-08-26T23:22:16.5353916Z for good examples of using this function. 2025-08-26T23:22:16.5353946Z 2025-08-26T23:22:16.5354032Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-08-26T23:22:16.5354118Z the necessary header includes, as well as the (pybind11) binding code. More 2025-08-26T23:22:16.5354204Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-08-26T23:22:16.5354275Z single ``.cpp`` file. This file is then prepended with ``#include 2025-08-26T23:22:16.5354314Z `` 2025-08-26T23:22:16.5354345Z 2025-08-26T23:22:16.5354526Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-08-26T23:22:16.5354613Z automatically generated for each function specified. ``functions`` can 2025-08-26T23:22:16.5354692Z either be a list of function names, or a dictionary mapping from function 2025-08-26T23:22:16.5354770Z names to docstrings. If a list is given, the name of each function is used 2025-08-26T23:22:16.5354806Z as its docstring. 2025-08-26T23:22:16.5355822Z 2025-08-26T23:22:16.5355900Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-08-26T23:22:16.5355970Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-08-26T23:22:16.5356045Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-08-26T23:22:16.5356124Z separately, but ultimately linked into a single library. Note that no 2025-08-26T23:22:16.5356204Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-08-26T23:22:16.5356281Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-08-26T23:22:16.5356385Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-08-26T23:22:16.5356430Z include its name in ``functions``). 2025-08-26T23:22:16.5356461Z 2025-08-26T23:22:16.5356539Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-08-26T23:22:16.5356616Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-08-26T23:22:16.5356706Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-08-26T23:22:16.5356782Z linked into a single library. Note that no bindings are generated for 2025-08-26T23:22:16.5356859Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-08-26T23:22:16.5356934Z create a C++ function that calls it, and either declare or define this 2025-08-26T23:22:16.5357004Z C++ function in one of the ``cpp_sources`` (and include its name 2025-08-26T23:22:16.5357042Z in ``functions``). 2025-08-26T23:22:16.5357074Z 2025-08-26T23:22:16.5357104Z 2025-08-26T23:22:16.5357135Z 2025-08-26T23:22:16.5357205Z See :func:`load` for a description of arguments omitted below. 2025-08-26T23:22:16.5358199Z 2025-08-26T23:22:16.5358232Z Args: 2025-08-26T23:22:16.5358312Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-08-26T23:22:16.5358392Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-08-26T23:22:16.5358473Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-08-26T23:22:16.5358546Z functions: A list of function names for which to generate function 2025-08-26T23:22:16.5358623Z bindings. If a dictionary is given, it should map function names to 2025-08-26T23:22:16.5358690Z docstrings (which are otherwise just the function names). 2025-08-26T23:22:16.5358768Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T23:22:16.5358863Z the build. If set to ``None`` (default), this value is 2025-08-26T23:22:16.5358936Z automatically determined based on whether ``cuda_sources`` is 2025-08-26T23:22:16.5358996Z provided. Set it to ``True`` to force CUDA headers 2025-08-26T23:22:16.5359040Z and libraries to be included. 2025-08-26T23:22:16.5359117Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T23:22:16.5359177Z the build. If set to ``None`` (default), this value is 2025-08-26T23:22:16.5359250Z automatically determined based on whether ``sycl_sources`` is 2025-08-26T23:22:16.5359307Z provided. Set it to ``True`` to force SYCL headers 2025-08-26T23:22:16.5359350Z and libraries to be included. 2025-08-26T23:22:16.5359424Z with_pytorch_error_handling: Determines whether pytorch error and 2025-08-26T23:22:16.5359497Z warning macros are handled by pytorch instead of pybind. To do 2025-08-26T23:22:16.5359579Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-08-26T23:22:16.5360680Z function. This redirection might cause issues in obscure cases 2025-08-26T23:22:16.5360749Z of cpp. This flag should be set to ``False`` when this redirect 2025-08-26T23:22:16.5360790Z causes issues. 2025-08-26T23:22:16.5360881Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-08-26T23:22:16.5360966Z ``#include `` and ``#include `` lines. 2025-08-26T23:22:16.5361028Z Use this option to improve cold start times when you 2025-08-26T23:22:16.5361121Z already include the necessary headers in your source code. Default: ``False``. 2025-08-26T23:22:16.5361152Z 2025-08-26T23:22:16.5361185Z Example: 2025-08-26T23:22:16.5361242Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T23:22:16.5361340Z >>> from torch.utils.cpp_extension import load_inline 2025-08-26T23:22:16.5361380Z >>> source = """ 2025-08-26T23:22:16.5361439Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-08-26T23:22:16.5361480Z return x.sin() + y.sin(); 2025-08-26T23:22:16.5361513Z } 2025-08-26T23:22:16.5361544Z """ 2025-08-26T23:22:16.5361601Z >>> module = load_inline(name='inline_extension', 2025-08-26T23:22:16.5361670Z ... cpp_sources=[source], 2025-08-26T23:22:16.5361720Z ... functions=['sin_add']) 2025-08-26T23:22:16.5361751Z 2025-08-26T23:22:16.5361784Z .. note:: 2025-08-26T23:22:16.5361871Z Since load_inline will just-in-time compile the source code, please ensure 2025-08-26T23:22:16.5362924Z that you have the right toolchains installed in the runtime. For example, 2025-08-26T23:22:16.5363004Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-08-26T23:22:16.5363097Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-08-26T23:22:16.5363186Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-08-26T23:22:16.5363270Z are not included when you install torch and must be additionally installed. 2025-08-26T23:22:16.5363302Z 2025-08-26T23:22:16.5363393Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-08-26T23:22:16.5363475Z the extension. This may use up too many resources on some systems. One 2025-08-26T23:22:16.5363554Z can control the number of workers by setting the `MAX_JOBS` environment 2025-08-26T23:22:16.5363601Z variable to a non-negative number. 2025-08-26T23:22:16.5363632Z 2025-08-26T23:22:16.5363722Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5363752Z 2025-08-26T23:22:16.5363792Z warnings.warn(msg) 2025-08-26T23:22:16.5363850Z 2025-08-26T23:22:16.5363942Z --- Parse Warning: 62 / 146 --- 2025-08-26T23:22:16.5364258Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py line=227. 2025-08-26T23:22:16.5364351Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5364444Z Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights). 2025-08-26T23:22:16.5364475Z 2025-08-26T23:22:16.5364507Z Args: 2025-08-26T23:22:16.5365564Z weights (sequence) : a sequence of weights, not necessary summing up to one 2025-08-26T23:22:16.5365621Z num_samples (int): number of samples to draw 2025-08-26T23:22:16.5365698Z replacement (bool): if ``True``, samples are drawn with replacement. 2025-08-26T23:22:16.5365775Z If not, they are drawn without replacement, which means that when a 2025-08-26T23:22:16.5365857Z sample index is drawn for a row, it cannot be drawn again for that row. 2025-08-26T23:22:16.5365917Z generator (Generator): Generator used in sampling. 2025-08-26T23:22:16.5365949Z 2025-08-26T23:22:16.5365982Z Example: 2025-08-26T23:22:16.5366040Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5366073Z >>> list( 2025-08-26T23:22:16.5366122Z ... WeightedRandomSampler( 2025-08-26T23:22:16.5366176Z ... [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True 2025-08-26T23:22:16.5366209Z ... ) 2025-08-26T23:22:16.5366242Z ... ) 2025-08-26T23:22:16.5366277Z [4, 4, 1, 4, 5] 2025-08-26T23:22:16.5366311Z >>> list( 2025-08-26T23:22:16.5366356Z ... WeightedRandomSampler( 2025-08-26T23:22:16.5366433Z ... [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False 2025-08-26T23:22:16.5366468Z ... ) 2025-08-26T23:22:16.5366500Z ... ) 2025-08-26T23:22:16.5366535Z [0, 1, 4, 3, 2] 2025-08-26T23:22:16.5366566Z 2025-08-26T23:22:16.5367612Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5367644Z 2025-08-26T23:22:16.5367681Z warnings.warn(msg) 2025-08-26T23:22:16.5367712Z 2025-08-26T23:22:16.5367800Z --- Parse Warning: 63 / 146 --- 2025-08-26T23:22:16.5368096Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/sampler.py line=300. 2025-08-26T23:22:16.5368187Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5368253Z Wraps another sampler to yield a mini-batch of indices. 2025-08-26T23:22:16.5368285Z 2025-08-26T23:22:16.5368318Z Args: 2025-08-26T23:22:16.5368401Z sampler (Sampler or Iterable): Base sampler. Can be any iterable object 2025-08-26T23:22:16.5368450Z batch_size (int): Size of mini-batch. 2025-08-26T23:22:16.5368524Z drop_last (bool): If ``True``, the sampler will drop the last batch if 2025-08-26T23:22:16.5368576Z its size would be less than ``batch_size`` 2025-08-26T23:22:16.5368608Z 2025-08-26T23:22:16.5368642Z Example: 2025-08-26T23:22:16.5368676Z >>> list( 2025-08-26T23:22:16.5368717Z ... BatchSampler( 2025-08-26T23:22:16.5368790Z ... SequentialSampler(range(10)), batch_size=3, drop_last=False 2025-08-26T23:22:16.5368823Z ... ) 2025-08-26T23:22:16.5368854Z ... ) 2025-08-26T23:22:16.5368896Z [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] 2025-08-26T23:22:16.5369901Z >>> list( 2025-08-26T23:22:16.5370016Z ... BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True) 2025-08-26T23:22:16.5370067Z ... ) 2025-08-26T23:22:16.5370107Z [[0, 1, 2], [3, 4, 5], [6, 7, 8]] 2025-08-26T23:22:16.5370139Z 2025-08-26T23:22:16.5370228Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5370259Z 2025-08-26T23:22:16.5370296Z warnings.warn(msg) 2025-08-26T23:22:16.5370327Z 2025-08-26T23:22:16.5370466Z --- Parse Warning: 64 / 146 --- 2025-08-26T23:22:16.5370776Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/distributed.py line=18. 2025-08-26T23:22:16.5370867Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5370943Z Sampler that restricts data loading to a subset of the dataset. 2025-08-26T23:22:16.5370975Z 2025-08-26T23:22:16.5371029Z It is especially useful in conjunction with 2025-08-26T23:22:16.5371119Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-08-26T23:22:16.5371213Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-08-26T23:22:16.5371298Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-08-26T23:22:16.5371347Z original dataset that is exclusive to it. 2025-08-26T23:22:16.5371379Z 2025-08-26T23:22:16.5371412Z .. note:: 2025-08-26T23:22:16.5372472Z Dataset is assumed to be of constant size and that any instance of it always 2025-08-26T23:22:16.5372528Z returns the same elements in the same order. 2025-08-26T23:22:16.5372560Z 2025-08-26T23:22:16.5372591Z Args: 2025-08-26T23:22:16.5372639Z dataset: Dataset used for sampling. 2025-08-26T23:22:16.5372752Z num_replicas (int, optional): Number of processes participating in 2025-08-26T23:22:16.5372845Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-08-26T23:22:16.5372890Z current distributed group. 2025-08-26T23:22:16.5372977Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-08-26T23:22:16.5373050Z By default, :attr:`rank` is retrieved from the current distributed 2025-08-26T23:22:16.5373104Z group. 2025-08-26T23:22:16.5373187Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-08-26T23:22:16.5373222Z indices. 2025-08-26T23:22:16.5373291Z seed (int, optional): random seed used to shuffle the sampler if 2025-08-26T23:22:16.5373364Z :attr:`shuffle=True`. This number should be identical across all 2025-08-26T23:22:16.5373425Z processes in the distributed group. Default: ``0``. 2025-08-26T23:22:16.5373507Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-08-26T23:22:16.5373578Z tail of the data to make it evenly divisible across the number of 2025-08-26T23:22:16.5373649Z replicas. If ``False``, the sampler will add extra indices to make 2025-08-26T23:22:16.5373723Z the data evenly divisible across the replicas. Default: ``False``. 2025-08-26T23:22:16.5373755Z 2025-08-26T23:22:16.5373791Z .. warning:: 2025-08-26T23:22:16.5374832Z In distributed mode, calling the :meth:`set_epoch` method at 2025-08-26T23:22:16.5374925Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-08-26T23:22:16.5375018Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-08-26T23:22:16.5375066Z the same ordering will be always used. 2025-08-26T23:22:16.5375097Z 2025-08-26T23:22:16.5375133Z Example:: 2025-08-26T23:22:16.5375191Z 2025-08-26T23:22:16.5375251Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5375330Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-08-26T23:22:16.5375396Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-08-26T23:22:16.5375446Z ... sampler=sampler) 2025-08-26T23:22:16.5375500Z >>> for epoch in range(start_epoch, n_epochs): 2025-08-26T23:22:16.5375544Z ... if is_distributed: 2025-08-26T23:22:16.5375591Z ... sampler.set_epoch(epoch) 2025-08-26T23:22:16.5375629Z ... train(loader) 2025-08-26T23:22:16.5375661Z 2025-08-26T23:22:16.5375750Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5375781Z 2025-08-26T23:22:16.5375818Z warnings.warn(msg) 2025-08-26T23:22:16.5375849Z 2025-08-26T23:22:16.5375921Z --- Parse Warning: 65 / 146 --- 2025-08-26T23:22:16.5377205Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py line=56. 2025-08-26T23:22:16.5377297Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5377329Z 2025-08-26T23:22:16.5377371Z Iterable-style DataPipe. 2025-08-26T23:22:16.5377403Z 2025-08-26T23:22:16.5377492Z All DataPipes that represent an iterable of data samples should subclass this. 2025-08-26T23:22:16.5377582Z This style of DataPipes is particularly useful when data come from a stream, or 2025-08-26T23:22:16.5377707Z when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its 2025-08-26T23:22:16.5377813Z elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``. 2025-08-26T23:22:16.5377867Z 2025-08-26T23:22:16.5377951Z All subclasses should overwrite :meth:`__iter__`, which would return an 2025-08-26T23:22:16.5378071Z iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its 2025-08-26T23:22:16.5378201Z method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should 2025-08-26T23:22:16.5378313Z override ``reset()`` if necessary. The common usages include resetting buffers, pointers, 2025-08-26T23:22:16.5378389Z and various state variables within the custom ``IterDataPipe``. 2025-08-26T23:22:16.5378419Z 2025-08-26T23:22:16.5378451Z Note: 2025-08-26T23:22:16.5378528Z Only `one` iterator can be valid for each ``IterDataPipe`` at a time, 2025-08-26T23:22:16.5378649Z and the creation a second iterator will invalidate the first one. This constraint is necessary because 2025-08-26T23:22:16.5378781Z some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators. 2025-08-26T23:22:16.5378878Z The code example below presents details on how this constraint looks in practice. 2025-08-26T23:22:16.5379005Z If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_. 2025-08-26T23:22:16.5380015Z 2025-08-26T23:22:16.5380120Z These DataPipes can be invoked in two ways, using the class constructor or applying their 2025-08-26T23:22:16.5380246Z functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes). 2025-08-26T23:22:16.5380436Z You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple 2025-08-26T23:22:16.5380479Z operations in succession. 2025-08-26T23:22:16.5380510Z 2025-08-26T23:22:16.5380561Z .. _GitHub IterDataPipe Single Iterator Issue: 2025-08-26T23:22:16.5380616Z https://github.com/pytorch/data/issues/45 2025-08-26T23:22:16.5380680Z 2025-08-26T23:22:16.5380732Z Note: 2025-08-26T23:22:16.5380815Z When a subclass is used with :class:`~torch.utils.data.DataLoader`, each 2025-08-26T23:22:16.5380915Z item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader` 2025-08-26T23:22:16.5380996Z iterator. When :attr:`num_workers > 0`, each worker process will have a 2025-08-26T23:22:16.5381081Z different copy of the DataPipe object, so it is often desired to configure 2025-08-26T23:22:16.5381166Z each copy independently to avoid having duplicate data returned from the 2025-08-26T23:22:16.5381254Z workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker 2025-08-26T23:22:16.5381341Z process, returns information about the worker. It can be used in either the 2025-08-26T23:22:16.5381430Z dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's 2025-08-26T23:22:16.5381500Z :attr:`worker_init_fn` option to modify each copy's behavior. 2025-08-26T23:22:16.5381534Z 2025-08-26T23:22:16.5381568Z Examples: 2025-08-26T23:22:16.5382598Z General Usage: 2025-08-26T23:22:16.5382639Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5382717Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T23:22:16.5382764Z >>> dp = IterableWrapper(range(10)) 2025-08-26T23:22:16.5382836Z >>> map_dp_1 = Mapper(dp, lambda x: x + 1) # Using class constructor 2025-08-26T23:22:16.5382878Z >>> map_dp_2 = dp.map( 2025-08-26T23:22:16.5382920Z ... lambda x: x + 1 2025-08-26T23:22:16.5382973Z ... ) # Using functional form (recommended) 2025-08-26T23:22:16.5383014Z >>> list(map_dp_1) 2025-08-26T23:22:16.5383054Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T23:22:16.5383093Z >>> list(map_dp_2) 2025-08-26T23:22:16.5383131Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T23:22:16.5383224Z >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0) 2025-08-26T23:22:16.5383264Z >>> list(filter_dp) 2025-08-26T23:22:16.5383300Z [2, 4, 6, 8, 10] 2025-08-26T23:22:16.5383346Z Single Iterator Constraint Example: 2025-08-26T23:22:16.5383420Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T23:22:16.5383473Z >>> source_dp = IterableWrapper(range(10)) 2025-08-26T23:22:16.5383542Z >>> it1 = iter(source_dp) 2025-08-26T23:22:16.5383580Z >>> list(it1) 2025-08-26T23:22:16.5383620Z [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 2025-08-26T23:22:16.5383661Z >>> it1 = iter(source_dp) 2025-08-26T23:22:16.5384676Z >>> it2 = iter( 2025-08-26T23:22:16.5384717Z ... source_dp 2025-08-26T23:22:16.5384781Z ... ) # The creation of a new iterator invalidates `it1` 2025-08-26T23:22:16.5384817Z >>> next(it2) 2025-08-26T23:22:16.5384854Z 0 2025-08-26T23:22:16.5384925Z >>> next(it1) # Further usage of `it1` will raise a `RunTimeError` 2025-08-26T23:22:16.5384956Z 2025-08-26T23:22:16.5385045Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5385076Z 2025-08-26T23:22:16.5385114Z warnings.warn(msg) 2025-08-26T23:22:16.5385144Z 2025-08-26T23:22:16.5385217Z --- Parse Warning: 66 / 146 --- 2025-08-26T23:22:16.5385564Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155. 2025-08-26T23:22:16.5385657Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5385687Z 2025-08-26T23:22:16.5385831Z Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``. 2025-08-26T23:22:16.5385927Z 2025-08-26T23:22:16.5385971Z (functional name: ``groupby``). 2025-08-26T23:22:16.5386002Z 2025-08-26T23:22:16.5386136Z The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group 2025-08-26T23:22:16.5386242Z will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full, 2025-08-26T23:22:16.5387332Z the DataPipe will yield the largest batch with the same key, provided that its size is larger 2025-08-26T23:22:16.5387446Z than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``. 2025-08-26T23:22:16.5387477Z 2025-08-26T23:22:16.5387610Z After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity 2025-08-26T23:22:16.5387720Z will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``. 2025-08-26T23:22:16.5387753Z 2025-08-26T23:22:16.5387785Z Args: 2025-08-26T23:22:16.5387837Z datapipe: Iterable datapipe to be grouped 2025-08-26T23:22:16.5387937Z group_key_fn: Function used to generate group key from the data of the source datapipe 2025-08-26T23:22:16.5388023Z keep_key: Option to yield the matching key along with the items in a tuple, 2025-08-26T23:22:16.5388090Z resulting in `(key, [items])` otherwise returning [items] 2025-08-26T23:22:16.5388151Z buffer_size: The size of buffer for ungrouped data 2025-08-26T23:22:16.5388250Z group_size: The max size of each group, a batch is yielded as soon as it reaches this size 2025-08-26T23:22:16.5388366Z guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full 2025-08-26T23:22:16.5388488Z drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer 2025-08-26T23:22:16.5388549Z when the buffer is full 2025-08-26T23:22:16.5388581Z 2025-08-26T23:22:16.5388616Z Example: 2025-08-26T23:22:16.5388651Z >>> import os 2025-08-26T23:22:16.5388691Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5388758Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:22:16.5388798Z >>> def group_fn(file): 2025-08-26T23:22:16.5389822Z ... return os.path.basename(file).split(".")[0] 2025-08-26T23:22:16.5389887Z >>> source_dp = IterableWrapper( 2025-08-26T23:22:16.5389952Z ... ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"] 2025-08-26T23:22:16.5389984Z ... ) 2025-08-26T23:22:16.5390040Z >>> dp0 = source_dp.groupby(group_key_fn=group_fn) 2025-08-26T23:22:16.5390075Z >>> list(dp0) 2025-08-26T23:22:16.5390138Z [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']] 2025-08-26T23:22:16.5390208Z >>> # A group is yielded as soon as its size equals to `group_size` 2025-08-26T23:22:16.5390279Z >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2) 2025-08-26T23:22:16.5390315Z >>> list(dp1) 2025-08-26T23:22:16.5390434Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T23:22:16.5390557Z >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size` 2025-08-26T23:22:16.5390601Z >>> dp2 = source_dp.groupby( 2025-08-26T23:22:16.5390643Z ... group_key_fn=group_fn, 2025-08-26T23:22:16.5390682Z ... buffer_size=3, 2025-08-26T23:22:16.5390721Z ... group_size=3, 2025-08-26T23:22:16.5390764Z ... guaranteed_group_size=2, 2025-08-26T23:22:16.5390795Z ... ) 2025-08-26T23:22:16.5390829Z >>> list(dp2) 2025-08-26T23:22:16.5390889Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T23:22:16.5390922Z 2025-08-26T23:22:16.5391016Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5392088Z 2025-08-26T23:22:16.5392126Z warnings.warn(msg) 2025-08-26T23:22:16.5392157Z 2025-08-26T23:22:16.5392230Z --- Parse Warning: 67 / 146 --- 2025-08-26T23:22:16.5392579Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18. 2025-08-26T23:22:16.5392671Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5392702Z 2025-08-26T23:22:16.5392830Z Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``). 2025-08-26T23:22:16.5392861Z 2025-08-26T23:22:16.5392893Z Args: 2025-08-26T23:22:16.5392957Z datapipe: Iterable datapipe that provides pathnames 2025-08-26T23:22:16.5393026Z mode: An optional string that specifies the mode in which 2025-08-26T23:22:16.5393106Z the file is opened by ``open()``. It defaults to ``r``, other options are 2025-08-26T23:22:16.5393168Z ``b`` for reading in binary mode and ``t`` for text mode. 2025-08-26T23:22:16.5393242Z encoding: An optional string that specifies the encoding of the 2025-08-26T23:22:16.5393337Z underlying file. It defaults to ``None`` to match the default encoding of ``open``. 2025-08-26T23:22:16.5393386Z length: Nominal length of the datapipe 2025-08-26T23:22:16.5393417Z 2025-08-26T23:22:16.5393449Z Note: 2025-08-26T23:22:16.5393545Z The opened file handles will be closed by Python's GC periodically. Users can choose 2025-08-26T23:22:16.5393586Z to close them explicitly. 2025-08-26T23:22:16.5394652Z 2025-08-26T23:22:16.5394686Z Example: 2025-08-26T23:22:16.5394726Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5394804Z >>> from torchdata.datapipes.iter import ( 2025-08-26T23:22:16.5394848Z ... FileLister, 2025-08-26T23:22:16.5394885Z ... FileOpener, 2025-08-26T23:22:16.5394923Z ... StreamReader, 2025-08-26T23:22:16.5394954Z ... ) 2025-08-26T23:22:16.5395034Z >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt")) 2025-08-26T23:22:16.5395073Z >>> dp = FileOpener(dp) 2025-08-26T23:22:16.5395114Z >>> dp = StreamReader(dp) 2025-08-26T23:22:16.5395168Z >>> list(dp) 2025-08-26T23:22:16.5395208Z [('./abc.txt', 'abc')] 2025-08-26T23:22:16.5395238Z 2025-08-26T23:22:16.5395328Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5395359Z 2025-08-26T23:22:16.5395396Z warnings.warn(msg) 2025-08-26T23:22:16.5395427Z 2025-08-26T23:22:16.5395499Z --- Parse Warning: 68 / 146 --- 2025-08-26T23:22:16.5395852Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=375. 2025-08-26T23:22:16.5395947Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5395978Z 2025-08-26T23:22:16.5397111Z Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``). 2025-08-26T23:22:16.5397146Z 2025-08-26T23:22:16.5397218Z A list of the child DataPipes is returned from this operation. 2025-08-26T23:22:16.5397249Z 2025-08-26T23:22:16.5397281Z Args: 2025-08-26T23:22:16.5397333Z datapipe: Iterable DataPipe being filtered 2025-08-26T23:22:16.5397404Z num_instances: number of instances of the DataPipe to create 2025-08-26T23:22:16.5397536Z classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None`` 2025-08-26T23:22:16.5397687Z drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None`` 2025-08-26T23:22:16.5397799Z buffer_size: this defines the maximum number of inputs that the buffer can hold across all child 2025-08-26T23:22:16.5397867Z DataPipes while waiting for their values to be yielded. 2025-08-26T23:22:16.5397933Z Defaults to ``1000``. Use ``-1`` for the unlimited buffer. 2025-08-26T23:22:16.5397964Z 2025-08-26T23:22:16.5397999Z Examples: 2025-08-26T23:22:16.5398048Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:22:16.5398116Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:22:16.5398154Z >>> def odd_or_even(n): 2025-08-26T23:22:16.5398193Z ... return n % 2 2025-08-26T23:22:16.5398241Z >>> source_dp = IterableWrapper(range(5)) 2025-08-26T23:22:16.5398318Z >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even) 2025-08-26T23:22:16.5398354Z >>> list(dp1) 2025-08-26T23:22:16.5399352Z [0, 2, 4] 2025-08-26T23:22:16.5399387Z >>> list(dp2) 2025-08-26T23:22:16.5399420Z [1, 3] 2025-08-26T23:22:16.5399505Z >>> # It can also filter out any element that gets `None` from the `classifier_fn` 2025-08-26T23:22:16.5399548Z >>> def odd_or_even_no_zero(n): 2025-08-26T23:22:16.5399594Z ... return n % 2 if n != 0 else None 2025-08-26T23:22:16.5399638Z >>> dp1, dp2 = source_dp.demux( 2025-08-26T23:22:16.5399717Z ... num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True 2025-08-26T23:22:16.5399748Z ... ) 2025-08-26T23:22:16.5399782Z >>> list(dp1) 2025-08-26T23:22:16.5399814Z [2, 4] 2025-08-26T23:22:16.5399848Z >>> list(dp2) 2025-08-26T23:22:16.5399879Z [1, 3] 2025-08-26T23:22:16.5399909Z 2025-08-26T23:22:16.5400000Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5400057Z 2025-08-26T23:22:16.5400094Z warnings.warn(msg) 2025-08-26T23:22:16.5400125Z 2025-08-26T23:22:16.5400197Z --- Parse Warning: 69 / 146 --- 2025-08-26T23:22:16.5400603Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=594. 2025-08-26T23:22:16.5400735Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5400766Z 2025-08-26T23:22:16.5401854Z Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``). 2025-08-26T23:22:16.5401886Z 2025-08-26T23:22:16.5402006Z As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration, 2025-08-26T23:22:16.5402077Z and so on. It ends when the shortest input DataPipe is exhausted. 2025-08-26T23:22:16.5402110Z 2025-08-26T23:22:16.5402145Z Args: 2025-08-26T23:22:16.5402285Z datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted 2025-08-26T23:22:16.5402316Z 2025-08-26T23:22:16.5402349Z Example: 2025-08-26T23:22:16.5402398Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:22:16.5402467Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:22:16.5402507Z >>> dp1, dp2, dp3 = ( 2025-08-26T23:22:16.5402554Z ... IterableWrapper(range(3)), 2025-08-26T23:22:16.5402600Z ... IterableWrapper(range(10, 15)), 2025-08-26T23:22:16.5402646Z ... IterableWrapper(range(20, 25)), 2025-08-26T23:22:16.5402678Z ... ) 2025-08-26T23:22:16.5402720Z >>> list(dp1.mux(dp2, dp3)) 2025-08-26T23:22:16.5402761Z [0, 10, 20, 1, 11, 21, 2, 12, 22] 2025-08-26T23:22:16.5402793Z 2025-08-26T23:22:16.5402915Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5402964Z 2025-08-26T23:22:16.5403000Z warnings.warn(msg) 2025-08-26T23:22:16.5404001Z 2025-08-26T23:22:16.5404072Z --- Parse Warning: 70 / 146 --- 2025-08-26T23:22:16.5404408Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py line=665. 2025-08-26T23:22:16.5404499Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5404530Z 2025-08-26T23:22:16.5404638Z Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``). 2025-08-26T23:22:16.5404669Z 2025-08-26T23:22:16.5404752Z The output is stopped as soon as the shortest input DataPipe is exhausted. 2025-08-26T23:22:16.5404783Z 2025-08-26T23:22:16.5404818Z Args: 2025-08-26T23:22:16.5404878Z *datapipes: Iterable DataPipes being aggregated 2025-08-26T23:22:16.5404909Z 2025-08-26T23:22:16.5404941Z Example: 2025-08-26T23:22:16.5404990Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T23:22:16.5405054Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T23:22:16.5405095Z >>> dp1, dp2, dp3 = ( 2025-08-26T23:22:16.5405139Z ... IterableWrapper(range(5)), 2025-08-26T23:22:16.5405186Z ... IterableWrapper(range(10, 15)), 2025-08-26T23:22:16.5405231Z ... IterableWrapper(range(20, 25)), 2025-08-26T23:22:16.5405263Z ... ) 2025-08-26T23:22:16.5405303Z >>> list(dp1.zip(dp2, dp3)) 2025-08-26T23:22:16.5406319Z [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)] 2025-08-26T23:22:16.5406350Z 2025-08-26T23:22:16.5406441Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5406511Z 2025-08-26T23:22:16.5406550Z warnings.warn(msg) 2025-08-26T23:22:16.5406581Z 2025-08-26T23:22:16.5406651Z --- Parse Warning: 71 / 146 --- 2025-08-26T23:22:16.5406946Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/testing/_comparison.py line=1331. 2025-08-26T23:22:16.5407055Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5407114Z Asserts that ``actual`` and ``expected`` are close. 2025-08-26T23:22:16.5407145Z 2025-08-26T23:22:16.5407276Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-08-26T23:22:16.5407306Z 2025-08-26T23:22:16.5407342Z .. math:: 2025-08-26T23:22:16.5407372Z 2025-08-26T23:22:16.5407503Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-08-26T23:22:16.5407535Z 2025-08-26T23:22:16.5407659Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-08-26T23:22:16.5407734Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-08-26T23:22:16.5407764Z 2025-08-26T23:22:16.5407837Z In addition, they are only considered close if they have the same 2025-08-26T23:22:16.5407869Z 2025-08-26T23:22:16.5408914Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-08-26T23:22:16.5408969Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-08-26T23:22:16.5409027Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-08-26T23:22:16.5409076Z - stride (if ``check_stride`` is ``True``). 2025-08-26T23:22:16.5409106Z 2025-08-26T23:22:16.5409213Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-08-26T23:22:16.5409265Z 2025-08-26T23:22:16.5409407Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-08-26T23:22:16.5409538Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-08-26T23:22:16.5409622Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-08-26T23:22:16.5409757Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-08-26T23:22:16.5409788Z 2025-08-26T23:22:16.5409888Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-08-26T23:22:16.5410012Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-08-26T23:22:16.5410050Z definition above. 2025-08-26T23:22:16.5410082Z 2025-08-26T23:22:16.5410192Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-08-26T23:22:16.5410323Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-08-26T23:22:16.5410518Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-08-26T23:22:16.5410652Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-08-26T23:22:16.5410735Z their elements are considered close according to the above definition. 2025-08-26T23:22:16.5411745Z 2025-08-26T23:22:16.5411780Z .. note:: 2025-08-26T23:22:16.5411810Z 2025-08-26T23:22:16.5411926Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-08-26T23:22:16.5412080Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-08-26T23:22:16.5412181Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-08-26T23:22:16.5412212Z 2025-08-26T23:22:16.5412243Z Args: 2025-08-26T23:22:16.5412287Z actual (Any): Actual input. 2025-08-26T23:22:16.5412332Z expected (Any): Expected input. 2025-08-26T23:22:16.5412478Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-08-26T23:22:16.5412543Z are allowed. Otherwise type equality is required. 2025-08-26T23:22:16.5412668Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-08-26T23:22:16.5412765Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T23:22:16.5412890Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-08-26T23:22:16.5412985Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T23:22:16.5413073Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-08-26T23:22:16.5413174Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-08-26T23:22:16.5413266Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-08-26T23:22:16.5413350Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-08-26T23:22:16.5413471Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-08-26T23:22:16.5413590Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-08-26T23:22:16.5414664Z :func:`torch.promote_types`) before being compared. 2025-08-26T23:22:16.5414787Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-08-26T23:22:16.5414902Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-08-26T23:22:16.5414939Z compared. 2025-08-26T23:22:16.5415068Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-08-26T23:22:16.5415192Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-08-26T23:22:16.5415314Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-08-26T23:22:16.5415360Z should return the new message. 2025-08-26T23:22:16.5415393Z 2025-08-26T23:22:16.5415426Z Raises: 2025-08-26T23:22:16.5415514Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-08-26T23:22:16.5415578Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-08-26T23:22:16.5415692Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-08-26T23:22:16.5415816Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-08-26T23:22:16.5415857Z different types. 2025-08-26T23:22:16.5415984Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-08-26T23:22:16.5416107Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-08-26T23:22:16.5416218Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-08-26T23:22:16.5416341Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-08-26T23:22:16.5416389Z :attr:`~torch.Tensor.layout`. 2025-08-26T23:22:16.5416468Z AssertionError: If only one of corresponding tensors is quantized. 2025-08-26T23:22:16.5417566Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-08-26T23:22:16.5417689Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-08-26T23:22:16.5417736Z :attr:`~torch.Tensor.device`. 2025-08-26T23:22:16.5417849Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-08-26T23:22:16.5417969Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-08-26T23:22:16.5418096Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-08-26T23:22:16.5418127Z 2025-08-26T23:22:16.5418252Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-08-26T23:22:16.5418313Z ``dtype``'s, the maximum of both tolerances is used. 2025-08-26T23:22:16.5418344Z 2025-08-26T23:22:16.5418399Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5418452Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-08-26T23:22:16.5418496Z +===========================+============+==========+ 2025-08-26T23:22:16.5418549Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-08-26T23:22:16.5418598Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5418649Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-08-26T23:22:16.5418698Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5418780Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5418829Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5418879Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-08-26T23:22:16.5418927Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5418978Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-08-26T23:22:16.5419996Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420049Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420097Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420148Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-08-26T23:22:16.5420196Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420246Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420297Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420406Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420454Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420504Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420552Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420602Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420650Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420699Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T23:22:16.5420747Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420794Z | other | ``0.0`` | ``0.0`` | 2025-08-26T23:22:16.5420842Z +---------------------------+------------+----------+ 2025-08-26T23:22:16.5420907Z 2025-08-26T23:22:16.5420942Z .. note:: 2025-08-26T23:22:16.5420973Z 2025-08-26T23:22:16.5421107Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-08-26T23:22:16.5422195Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-08-26T23:22:16.5422319Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-08-26T23:22:16.5422350Z 2025-08-26T23:22:16.5422391Z >>> import functools 2025-08-26T23:22:16.5422484Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-08-26T23:22:16.5422528Z >>> assert_equal(1e-9, 1e-10) 2025-08-26T23:22:16.5422576Z Traceback (most recent call last): 2025-08-26T23:22:16.5422608Z ... 2025-08-26T23:22:16.5422658Z AssertionError: Scalars are not equal! 2025-08-26T23:22:16.5422697Z 2025-08-26T23:22:16.5422743Z Expected 1e-10 but got 1e-09. 2025-08-26T23:22:16.5422794Z Absolute difference: 9.000000000000001e-10 2025-08-26T23:22:16.5422837Z Relative difference: 9.0 2025-08-26T23:22:16.5422868Z 2025-08-26T23:22:16.5422902Z Examples: 2025-08-26T23:22:16.5422947Z >>> # tensor to tensor comparison 2025-08-26T23:22:16.5423001Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-08-26T23:22:16.5423057Z >>> actual = torch.acos(torch.cos(expected)) 2025-08-26T23:22:16.5423116Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5423146Z 2025-08-26T23:22:16.5423191Z >>> # scalar to scalar comparison 2025-08-26T23:22:16.5423229Z >>> import math 2025-08-26T23:22:16.5424233Z >>> expected = math.sqrt(2.0) 2025-08-26T23:22:16.5424278Z >>> actual = 2.0 / math.sqrt(2.0) 2025-08-26T23:22:16.5424336Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5424413Z 2025-08-26T23:22:16.5424465Z >>> # numpy array to numpy array comparison 2025-08-26T23:22:16.5424507Z >>> import numpy as np 2025-08-26T23:22:16.5424557Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-08-26T23:22:16.5424608Z >>> actual = np.arccos(np.cos(expected)) 2025-08-26T23:22:16.5424662Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5424696Z 2025-08-26T23:22:16.5424742Z >>> # sequence to sequence comparison 2025-08-26T23:22:16.5424784Z >>> import numpy as np 2025-08-26T23:22:16.5424875Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-08-26T23:22:16.5424927Z >>> # length and their elements have to match. 2025-08-26T23:22:16.5424988Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-08-26T23:22:16.5425032Z >>> actual = tuple(expected) 2025-08-26T23:22:16.5425088Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5425119Z 2025-08-26T23:22:16.5425166Z >>> # mapping to mapping comparison 2025-08-26T23:22:16.5425214Z >>> from collections import OrderedDict 2025-08-26T23:22:16.5425254Z >>> import numpy as np 2025-08-26T23:22:16.5426263Z >>> foo = torch.tensor(1.0) 2025-08-26T23:22:16.5426300Z >>> bar = 2.0 2025-08-26T23:22:16.5426342Z >>> baz = np.array(3.0) 2025-08-26T23:22:16.5426434Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-08-26T23:22:16.5426510Z >>> # have to have the same set of keys and their elements have to match. 2025-08-26T23:22:16.5426584Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-08-26T23:22:16.5426637Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-08-26T23:22:16.5426714Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5426746Z 2025-08-26T23:22:16.5426795Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T23:22:16.5426840Z >>> actual = expected.clone() 2025-08-26T23:22:16.5426903Z >>> # By default, directly related instances can be compared 2025-08-26T23:22:16.5426983Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-08-26T23:22:16.5427070Z >>> # This check can be made more strict with allow_subclasses=False 2025-08-26T23:22:16.5427115Z >>> torch.testing.assert_close( 2025-08-26T23:22:16.5427190Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-08-26T23:22:16.5427222Z ... ) 2025-08-26T23:22:16.5427268Z Traceback (most recent call last): 2025-08-26T23:22:16.5427301Z ... 2025-08-26T23:22:16.5427377Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T23:22:16.5427460Z and . 2025-08-26T23:22:16.5427543Z >>> # If the inputs are not directly related, they are never considered close 2025-08-26T23:22:16.5428571Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-08-26T23:22:16.5428619Z Traceback (most recent call last): 2025-08-26T23:22:16.5428651Z ... 2025-08-26T23:22:16.5428757Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T23:22:16.5428799Z and . 2025-08-26T23:22:16.5428893Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-08-26T23:22:16.5428940Z >>> # their type if check_dtype=False. 2025-08-26T23:22:16.5429005Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-08-26T23:22:16.5429037Z 2025-08-26T23:22:16.5429079Z >>> # NaN != NaN by default. 2025-08-26T23:22:16.5429166Z >>> expected = torch.tensor(float("Nan")) 2025-08-26T23:22:16.5429209Z >>> actual = expected.clone() 2025-08-26T23:22:16.5429264Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T23:22:16.5429310Z Traceback (most recent call last): 2025-08-26T23:22:16.5429342Z ... 2025-08-26T23:22:16.5429390Z AssertionError: Scalars are not close! 2025-08-26T23:22:16.5429427Z 2025-08-26T23:22:16.5429471Z Expected nan but got nan. 2025-08-26T23:22:16.5429528Z Absolute difference: nan (up to 1e-05 allowed) 2025-08-26T23:22:16.5429584Z Relative difference: nan (up to 1.3e-06 allowed) 2025-08-26T23:22:16.5429658Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-08-26T23:22:16.5430723Z 2025-08-26T23:22:16.5430777Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T23:22:16.5430828Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-08-26T23:22:16.5430887Z >>> # The default error message can be overwritten. 2025-08-26T23:22:16.5430932Z >>> torch.testing.assert_close( 2025-08-26T23:22:16.5431002Z ... actual, expected, msg="Argh, the tensors are not close!" 2025-08-26T23:22:16.5431033Z ... ) 2025-08-26T23:22:16.5431080Z Traceback (most recent call last): 2025-08-26T23:22:16.5431112Z ... 2025-08-26T23:22:16.5431170Z AssertionError: Argh, the tensors are not close! 2025-08-26T23:22:16.5431250Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-08-26T23:22:16.5431292Z >>> # extra information 2025-08-26T23:22:16.5431336Z >>> torch.testing.assert_close( 2025-08-26T23:22:16.5431410Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-08-26T23:22:16.5431474Z ... ) 2025-08-26T23:22:16.5431522Z Traceback (most recent call last): 2025-08-26T23:22:16.5431554Z ... 2025-08-26T23:22:16.5431595Z AssertionError: Header 2025-08-26T23:22:16.5431630Z 2025-08-26T23:22:16.5431672Z Tensor-likes are not close! 2025-08-26T23:22:16.5431707Z 2025-08-26T23:22:16.5431751Z Mismatched elements: 2 / 3 (66.7%) 2025-08-26T23:22:16.5432827Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-08-26T23:22:16.5432913Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-08-26T23:22:16.5432949Z 2025-08-26T23:22:16.5432982Z Footer 2025-08-26T23:22:16.5433015Z 2025-08-26T23:22:16.5433104Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5433136Z 2025-08-26T23:22:16.5433173Z warnings.warn(msg) 2025-08-26T23:22:16.5433206Z 2025-08-26T23:22:16.5433287Z --- Parse Warning: 72 / 146 --- 2025-08-26T23:22:16.5433637Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-08-26T23:22:16.5433729Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5433763Z 2025-08-26T23:22:16.5433841Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-08-26T23:22:16.5433915Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-08-26T23:22:16.5433999Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-08-26T23:22:16.5434062Z its samples are on simplex, and are reparametrizable. 2025-08-26T23:22:16.5434092Z 2025-08-26T23:22:16.5434128Z Example:: 2025-08-26T23:22:16.5434159Z 2025-08-26T23:22:16.5434253Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5434314Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-08-26T23:22:16.5435406Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-08-26T23:22:16.5435443Z >>> m.sample() 2025-08-26T23:22:16.5435493Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-08-26T23:22:16.5435524Z 2025-08-26T23:22:16.5435555Z Args: 2025-08-26T23:22:16.5435614Z temperature (Tensor): relaxation temperature 2025-08-26T23:22:16.5435661Z probs (Tensor): event probabilities 2025-08-26T23:22:16.5435731Z logits (Tensor): unnormalized log probability for each event 2025-08-26T23:22:16.5435761Z 2025-08-26T23:22:16.5435851Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5435882Z 2025-08-26T23:22:16.5435920Z warnings.warn(msg) 2025-08-26T23:22:16.5435951Z 2025-08-26T23:22:16.5436025Z --- Parse Warning: 73 / 146 --- 2025-08-26T23:22:16.5436351Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-08-26T23:22:16.5436444Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5436475Z 2025-08-26T23:22:16.5436557Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-08-26T23:22:16.5436644Z distribution where all component are from different parameterizations of 2025-08-26T23:22:16.5436721Z the same distribution type. It is parameterized by a `Categorical` 2025-08-26T23:22:16.5436794Z "selecting distribution" (over `k` component) and a component 2025-08-26T23:22:16.5437834Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-08-26T23:22:16.5437922Z (equal to `[k]`) which indexes each (batch of) component. 2025-08-26T23:22:16.5437957Z 2025-08-26T23:22:16.5437993Z Examples:: 2025-08-26T23:22:16.5438024Z 2025-08-26T23:22:16.5438070Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5438143Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-08-26T23:22:16.5438187Z >>> # weighted normal distributions 2025-08-26T23:22:16.5438234Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T23:22:16.5438306Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-08-26T23:22:16.5438353Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:22:16.5438384Z 2025-08-26T23:22:16.5438456Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-08-26T23:22:16.5438509Z >>> # weighted bivariate normal distributions 2025-08-26T23:22:16.5438554Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T23:22:16.5438601Z >>> comp = D.Independent(D.Normal( 2025-08-26T23:22:16.5438656Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-08-26T23:22:16.5438702Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:22:16.5438733Z 2025-08-26T23:22:16.5438800Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-08-26T23:22:16.5438870Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-08-26T23:22:16.5438917Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-08-26T23:22:16.5439927Z >>> comp = D.Independent(D.Normal( 2025-08-26T23:22:16.5439983Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-08-26T23:22:16.5440029Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T23:22:16.5440061Z 2025-08-26T23:22:16.5440093Z Args: 2025-08-26T23:22:16.5440171Z mixture_distribution: `torch.distributions.Categorical`-like 2025-08-26T23:22:16.5440240Z instance. Manages the probability of selecting component. 2025-08-26T23:22:16.5440338Z The number of categories must match the rightmost batch 2025-08-26T23:22:16.5440464Z dimension of the `component_distribution`. Must have either 2025-08-26T23:22:16.5440521Z scalar `batch_shape` or `batch_shape` matching 2025-08-26T23:22:16.5440574Z `component_distribution.batch_shape[:-1]` 2025-08-26T23:22:16.5440654Z component_distribution: `torch.distributions.Distribution`-like 2025-08-26T23:22:16.5440720Z instance. Right-most batch dimension indexes component. 2025-08-26T23:22:16.5440751Z 2025-08-26T23:22:16.5440841Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5440871Z 2025-08-26T23:22:16.5440909Z warnings.warn(msg) 2025-08-26T23:22:16.5440939Z 2025-08-26T23:22:16.5441011Z --- Parse Warning: 74 / 146 --- 2025-08-26T23:22:16.5441334Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-08-26T23:22:16.5441429Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5441460Z 2025-08-26T23:22:16.5442513Z Creates a RelaxedBernoulli distribution, parametrized by 2025-08-26T23:22:16.5442584Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-08-26T23:22:16.5442664Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-08-26T23:22:16.5442733Z so the values are in (0, 1), and has reparametrizable samples. 2025-08-26T23:22:16.5442765Z 2025-08-26T23:22:16.5442799Z Example:: 2025-08-26T23:22:16.5442830Z 2025-08-26T23:22:16.5442885Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5442937Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-08-26T23:22:16.5443022Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-08-26T23:22:16.5443062Z >>> m.sample() 2025-08-26T23:22:16.5443109Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-08-26T23:22:16.5443141Z 2025-08-26T23:22:16.5443173Z Args: 2025-08-26T23:22:16.5443227Z temperature (Tensor): relaxation temperature 2025-08-26T23:22:16.5443293Z probs (Number, Tensor): the probability of sampling `1` 2025-08-26T23:22:16.5443380Z logits (Number, Tensor): the log-odds of sampling `1` 2025-08-26T23:22:16.5443412Z 2025-08-26T23:22:16.5443502Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5443533Z 2025-08-26T23:22:16.5443570Z warnings.warn(msg) 2025-08-26T23:22:16.5444574Z 2025-08-26T23:22:16.5444645Z --- Parse Warning: 75 / 146 --- 2025-08-26T23:22:16.5445000Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-08-26T23:22:16.5445094Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5445125Z 2025-08-26T23:22:16.5445233Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-08-26T23:22:16.5445305Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-08-26T23:22:16.5445337Z 2025-08-26T23:22:16.5445404Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-08-26T23:22:16.5445434Z 2025-08-26T23:22:16.5445468Z Example: 2025-08-26T23:22:16.5445523Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T23:22:16.5445578Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5445626Z >>> m = LowRankMultivariateNormal( 2025-08-26T23:22:16.5445695Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-08-26T23:22:16.5445757Z ... ) 2025-08-26T23:22:16.5445880Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-08-26T23:22:16.5445921Z tensor([-0.2102, -0.5429]) 2025-08-26T23:22:16.5445952Z 2025-08-26T23:22:16.5445984Z Args: 2025-08-26T23:22:16.5446071Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-08-26T23:22:16.5446166Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-08-26T23:22:16.5447188Z `batch_shape + event_shape + (rank,)` 2025-08-26T23:22:16.5447281Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-08-26T23:22:16.5447325Z `batch_shape + event_shape` 2025-08-26T23:22:16.5447355Z 2025-08-26T23:22:16.5447387Z Note: 2025-08-26T23:22:16.5447481Z The computation for determinant and inverse of covariance matrix is avoided when 2025-08-26T23:22:16.5447572Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-08-26T23:22:16.5447651Z `_ and 2025-08-26T23:22:16.5447756Z `matrix determinant lemma `_. 2025-08-26T23:22:16.5447845Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-08-26T23:22:16.5447895Z the small size "capacitance" matrix:: 2025-08-26T23:22:16.5447927Z 2025-08-26T23:22:16.5447995Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-08-26T23:22:16.5448026Z 2025-08-26T23:22:16.5448114Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5448145Z 2025-08-26T23:22:16.5448182Z warnings.warn(msg) 2025-08-26T23:22:16.5448214Z 2025-08-26T23:22:16.5448285Z --- Parse Warning: 76 / 146 --- 2025-08-26T23:22:16.5448610Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=286. 2025-08-26T23:22:16.5448703Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5449706Z 2025-08-26T23:22:16.5449808Z Test if two objects are equal, and print an error message if test fails. 2025-08-26T23:22:16.5449839Z 2025-08-26T23:22:16.5449896Z The test is performed with ``actual == desired``. 2025-08-26T23:22:16.5449927Z 2025-08-26T23:22:16.5449960Z Parameters 2025-08-26T23:22:16.5449995Z ---------- 2025-08-26T23:22:16.5450031Z test_string : str 2025-08-26T23:22:16.5450080Z The message supplied to AssertionError. 2025-08-26T23:22:16.5450115Z actual : object 2025-08-26T23:22:16.5450174Z The object to test for equality against `desired`. 2025-08-26T23:22:16.5450214Z desired : object 2025-08-26T23:22:16.5450254Z The expected result. 2025-08-26T23:22:16.5450286Z 2025-08-26T23:22:16.5450318Z Examples 2025-08-26T23:22:16.5450411Z -------- 2025-08-26T23:22:16.5450457Z >>> np.testing.print_assert_equal( 2025-08-26T23:22:16.5450505Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-08-26T23:22:16.5450544Z ... ) # doctest: +SKIP 2025-08-26T23:22:16.5450589Z >>> np.testing.print_assert_equal( 2025-08-26T23:22:16.5450636Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-08-26T23:22:16.5450675Z ... ) # doctest: +SKIP 2025-08-26T23:22:16.5451702Z Traceback (most recent call last): 2025-08-26T23:22:16.5451736Z ... 2025-08-26T23:22:16.5451785Z AssertionError: Test XYZ of func xyz failed 2025-08-26T23:22:16.5451819Z ACTUAL: 2025-08-26T23:22:16.5451850Z [0, 1] 2025-08-26T23:22:16.5451883Z DESIRED: 2025-08-26T23:22:16.5451915Z [0, 2] 2025-08-26T23:22:16.5451946Z 2025-08-26T23:22:16.5451977Z 2025-08-26T23:22:16.5452118Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5452150Z 2025-08-26T23:22:16.5452187Z warnings.warn(msg) 2025-08-26T23:22:16.5452217Z 2025-08-26T23:22:16.5452288Z --- Parse Warning: 77 / 146 --- 2025-08-26T23:22:16.5452593Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=331. 2025-08-26T23:22:16.5452684Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5452715Z 2025-08-26T23:22:16.5452791Z Raises an AssertionError if two items are not equal up to desired 2025-08-26T23:22:16.5452826Z precision. 2025-08-26T23:22:16.5452856Z 2025-08-26T23:22:16.5452923Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:22:16.5452995Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:22:16.5454042Z instead of this function for more consistent floating point 2025-08-26T23:22:16.5454081Z comparisons. 2025-08-26T23:22:16.5454112Z 2025-08-26T23:22:16.5454192Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-08-26T23:22:16.5454223Z 2025-08-26T23:22:16.5454285Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-08-26T23:22:16.5454315Z 2025-08-26T23:22:16.5454397Z That is a looser test than originally documented, but agrees with what the 2025-08-26T23:22:16.5454480Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-08-26T23:22:16.5454564Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-08-26T23:22:16.5454611Z delegates to assert_array_almost_equal 2025-08-26T23:22:16.5454642Z 2025-08-26T23:22:16.5454702Z Parameters 2025-08-26T23:22:16.5454737Z ---------- 2025-08-26T23:22:16.5454776Z actual : array_like 2025-08-26T23:22:16.5454816Z The object to check. 2025-08-26T23:22:16.5454853Z desired : array_like 2025-08-26T23:22:16.5454892Z The expected object. 2025-08-26T23:22:16.5454931Z decimal : int, optional 2025-08-26T23:22:16.5454977Z Desired precision, default is 7. 2025-08-26T23:22:16.5455015Z err_msg : str, optional 2025-08-26T23:22:16.5456064Z The error message to be printed in case of failure. 2025-08-26T23:22:16.5456104Z verbose : bool, optional 2025-08-26T23:22:16.5456180Z If True, the conflicting values are appended to the error message. 2025-08-26T23:22:16.5456210Z 2025-08-26T23:22:16.5456242Z Raises 2025-08-26T23:22:16.5456275Z ------ 2025-08-26T23:22:16.5456310Z AssertionError 2025-08-26T23:22:16.5456382Z If actual and desired are not equal up to specified precision. 2025-08-26T23:22:16.5456413Z 2025-08-26T23:22:16.5456448Z See Also 2025-08-26T23:22:16.5456481Z -------- 2025-08-26T23:22:16.5456567Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:22:16.5456620Z relative and/or absolute precision. 2025-08-26T23:22:16.5456696Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:22:16.5456727Z 2025-08-26T23:22:16.5456759Z Examples 2025-08-26T23:22:16.5456791Z -------- 2025-08-26T23:22:16.5456857Z >>> from torch._numpy.testing import assert_almost_equal 2025-08-26T23:22:16.5456910Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-08-26T23:22:16.5456975Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-08-26T23:22:16.5457019Z Traceback (most recent call last): 2025-08-26T23:22:16.5457050Z ... 2025-08-26T23:22:16.5458052Z AssertionError: 2025-08-26T23:22:16.5458101Z Arrays are not almost equal to 10 decimals 2025-08-26T23:22:16.5458140Z ACTUAL: 2.3333333333333 2025-08-26T23:22:16.5458199Z DESIRED: 2.33333334 2025-08-26T23:22:16.5458246Z 2025-08-26T23:22:16.5458285Z >>> assert_almost_equal( 2025-08-26T23:22:16.5458362Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-08-26T23:22:16.5458394Z ... ) 2025-08-26T23:22:16.5458437Z Traceback (most recent call last): 2025-08-26T23:22:16.5458468Z ... 2025-08-26T23:22:16.5458504Z AssertionError: 2025-08-26T23:22:16.5458553Z Arrays are not almost equal to 9 decimals 2025-08-26T23:22:16.5458587Z 2025-08-26T23:22:16.5458628Z Mismatched elements: 1 / 2 (50%) 2025-08-26T23:22:16.5458680Z Max absolute difference: 6.666699636781459e-09 2025-08-26T23:22:16.5458730Z Max relative difference: 2.8571569790287484e-09 2025-08-26T23:22:16.5458787Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T23:22:16.5458841Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T23:22:16.5458872Z 2025-08-26T23:22:16.5458903Z 2025-08-26T23:22:16.5458995Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5459026Z 2025-08-26T23:22:16.5460030Z warnings.warn(msg) 2025-08-26T23:22:16.5460062Z 2025-08-26T23:22:16.5460135Z --- Parse Warning: 78 / 146 --- 2025-08-26T23:22:16.5460507Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=457. 2025-08-26T23:22:16.5460600Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5460631Z 2025-08-26T23:22:16.5460711Z Raises an AssertionError if two items are not equal up to significant 2025-08-26T23:22:16.5460744Z digits. 2025-08-26T23:22:16.5460773Z 2025-08-26T23:22:16.5460838Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:22:16.5460947Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:22:16.5461016Z instead of this function for more consistent floating point 2025-08-26T23:22:16.5461054Z comparisons. 2025-08-26T23:22:16.5461085Z 2025-08-26T23:22:16.5461153Z Given two numbers, check that they are approximately equal. 2025-08-26T23:22:16.5461233Z Approximately equal is defined as the number of significant digits 2025-08-26T23:22:16.5461290Z that agree. 2025-08-26T23:22:16.5461321Z 2025-08-26T23:22:16.5461355Z Parameters 2025-08-26T23:22:16.5461387Z ---------- 2025-08-26T23:22:16.5461422Z actual : scalar 2025-08-26T23:22:16.5462436Z The object to check. 2025-08-26T23:22:16.5462471Z desired : scalar 2025-08-26T23:22:16.5462509Z The expected object. 2025-08-26T23:22:16.5462551Z significant : int, optional 2025-08-26T23:22:16.5462596Z Desired precision, default is 7. 2025-08-26T23:22:16.5462637Z err_msg : str, optional 2025-08-26T23:22:16.5462699Z The error message to be printed in case of failure. 2025-08-26T23:22:16.5462739Z verbose : bool, optional 2025-08-26T23:22:16.5462812Z If True, the conflicting values are appended to the error message. 2025-08-26T23:22:16.5462843Z 2025-08-26T23:22:16.5462874Z Raises 2025-08-26T23:22:16.5462907Z ------ 2025-08-26T23:22:16.5462942Z AssertionError 2025-08-26T23:22:16.5463017Z If actual and desired are not equal up to specified precision. 2025-08-26T23:22:16.5463047Z 2025-08-26T23:22:16.5463079Z See Also 2025-08-26T23:22:16.5463112Z -------- 2025-08-26T23:22:16.5463195Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:22:16.5463247Z relative and/or absolute precision. 2025-08-26T23:22:16.5463323Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:22:16.5463353Z 2025-08-26T23:22:16.5463387Z Examples 2025-08-26T23:22:16.5464418Z -------- 2025-08-26T23:22:16.5464486Z >>> np.testing.assert_approx_equal( 2025-08-26T23:22:16.5464532Z ... 0.12345677777777e-20, 0.1234567e-20 2025-08-26T23:22:16.5464569Z ... ) # doctest: +SKIP 2025-08-26T23:22:16.5464614Z >>> np.testing.assert_approx_equal( 2025-08-26T23:22:16.5464650Z ... 0.12345670e-20, 2025-08-26T23:22:16.5464697Z ... 0.12345671e-20, # doctest: +SKIP 2025-08-26T23:22:16.5464734Z ... significant=8, 2025-08-26T23:22:16.5464767Z ... ) 2025-08-26T23:22:16.5464810Z >>> np.testing.assert_approx_equal( 2025-08-26T23:22:16.5464846Z ... 0.12345670e-20, 2025-08-26T23:22:16.5464888Z ... 0.12345672e-20, # doctest: +SKIP 2025-08-26T23:22:16.5464926Z ... significant=8, 2025-08-26T23:22:16.5464956Z ... ) 2025-08-26T23:22:16.5465000Z Traceback (most recent call last): 2025-08-26T23:22:16.5465032Z ... 2025-08-26T23:22:16.5465067Z AssertionError: 2025-08-26T23:22:16.5465120Z Items are not equal to 8 significant digits: 2025-08-26T23:22:16.5465159Z ACTUAL: 1.234567e-21 2025-08-26T23:22:16.5465197Z DESIRED: 1.2345672e-21 2025-08-26T23:22:16.5465227Z 2025-08-26T23:22:16.5465290Z the evaluated condition that raises the exception is 2025-08-26T23:22:16.5466280Z 2025-08-26T23:22:16.5466356Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-08-26T23:22:16.5466388Z True 2025-08-26T23:22:16.5466418Z 2025-08-26T23:22:16.5466449Z 2025-08-26T23:22:16.5466542Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5466572Z 2025-08-26T23:22:16.5466610Z warnings.warn(msg) 2025-08-26T23:22:16.5466640Z 2025-08-26T23:22:16.5466712Z --- Parse Warning: 79 / 146 --- 2025-08-26T23:22:16.5467021Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=744. 2025-08-26T23:22:16.5467135Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5467166Z 2025-08-26T23:22:16.5467242Z Raises an AssertionError if two array_like objects are not equal. 2025-08-26T23:22:16.5467273Z 2025-08-26T23:22:16.5467348Z Given two array_like objects, check that the shape is equal and all 2025-08-26T23:22:16.5467452Z elements of these objects are equal (but see the Notes for the special 2025-08-26T23:22:16.5467527Z handling of a scalar). An exception is raised at shape mismatch or 2025-08-26T23:22:16.5467608Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-08-26T23:22:16.5467687Z are compared like numbers, no assertion is raised if both objects have 2025-08-26T23:22:16.5467729Z NaNs in the same positions. 2025-08-26T23:22:16.5467759Z 2025-08-26T23:22:16.5468811Z The usual caution for verifying equality with floating point numbers is 2025-08-26T23:22:16.5468846Z advised. 2025-08-26T23:22:16.5468877Z 2025-08-26T23:22:16.5468910Z Parameters 2025-08-26T23:22:16.5468944Z ---------- 2025-08-26T23:22:16.5468977Z x : array_like 2025-08-26T23:22:16.5469020Z The actual object to check. 2025-08-26T23:22:16.5469053Z y : array_like 2025-08-26T23:22:16.5469098Z The desired, expected object. 2025-08-26T23:22:16.5469136Z err_msg : str, optional 2025-08-26T23:22:16.5469196Z The error message to be printed in case of failure. 2025-08-26T23:22:16.5469237Z verbose : bool, optional 2025-08-26T23:22:16.5469308Z If True, the conflicting values are appended to the error message. 2025-08-26T23:22:16.5469348Z strict : bool, optional 2025-08-26T23:22:16.5469418Z If True, raise an AssertionError when either the shape or the data 2025-08-26T23:22:16.5469488Z type of the array_like objects does not match. The special 2025-08-26T23:22:16.5469585Z handling for scalars mentioned in the Notes section is disabled. 2025-08-26T23:22:16.5469631Z 2025-08-26T23:22:16.5469662Z Raises 2025-08-26T23:22:16.5469695Z ------ 2025-08-26T23:22:16.5469729Z AssertionError 2025-08-26T23:22:16.5470804Z If actual and desired objects are not equal. 2025-08-26T23:22:16.5470835Z 2025-08-26T23:22:16.5470868Z See Also 2025-08-26T23:22:16.5470900Z -------- 2025-08-26T23:22:16.5470987Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:22:16.5471038Z relative and/or absolute precision. 2025-08-26T23:22:16.5471113Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:22:16.5471143Z 2025-08-26T23:22:16.5471176Z Notes 2025-08-26T23:22:16.5471208Z ----- 2025-08-26T23:22:16.5471277Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-08-26T23:22:16.5471359Z function checks that each element of the array_like object is equal to 2025-08-26T23:22:16.5471444Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-08-26T23:22:16.5471475Z 2025-08-26T23:22:16.5471507Z Examples 2025-08-26T23:22:16.5471540Z -------- 2025-08-26T23:22:16.5471593Z The first assert does not raise an exception: 2025-08-26T23:22:16.5471624Z 2025-08-26T23:22:16.5471667Z >>> np.testing.assert_array_equal( 2025-08-26T23:22:16.5471727Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-08-26T23:22:16.5471758Z ... ) 2025-08-26T23:22:16.5471789Z 2025-08-26T23:22:16.5472846Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-08-26T23:22:16.5472892Z functions for these cases instead: 2025-08-26T23:22:16.5472923Z 2025-08-26T23:22:16.5472966Z >>> np.testing.assert_allclose( 2025-08-26T23:22:16.5473042Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-08-26T23:22:16.5473114Z ... ) 2025-08-26T23:22:16.5473145Z 2025-08-26T23:22:16.5473221Z As mentioned in the Notes section, `assert_array_equal` has special 2025-08-26T23:22:16.5473302Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-08-26T23:22:16.5473332Z 2025-08-26T23:22:16.5473375Z >>> x = np.full((2, 5), fill_value=3) 2025-08-26T23:22:16.5473421Z >>> np.testing.assert_array_equal(x, 3) 2025-08-26T23:22:16.5473452Z 2025-08-26T23:22:16.5473546Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-08-26T23:22:16.5473579Z array: 2025-08-26T23:22:16.5473609Z 2025-08-26T23:22:16.5473667Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-08-26T23:22:16.5473709Z Traceback (most recent call last): 2025-08-26T23:22:16.5473740Z ... 2025-08-26T23:22:16.5473777Z AssertionError: 2025-08-26T23:22:16.5473816Z Arrays are not equal 2025-08-26T23:22:16.5473848Z 2025-08-26T23:22:16.5474931Z (shapes (2, 5), () mismatch) 2025-08-26T23:22:16.5474975Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-08-26T23:22:16.5475014Z [3, 3, 3, 3, 3]]) 2025-08-26T23:22:16.5475051Z y: torch.ndarray(3) 2025-08-26T23:22:16.5475081Z 2025-08-26T23:22:16.5475158Z The `strict` parameter also ensures that the array data types match: 2025-08-26T23:22:16.5475188Z 2025-08-26T23:22:16.5475227Z >>> x = np.array([2, 2, 2]) 2025-08-26T23:22:16.5475284Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-08-26T23:22:16.5475342Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-08-26T23:22:16.5475384Z Traceback (most recent call last): 2025-08-26T23:22:16.5475416Z ... 2025-08-26T23:22:16.5475451Z AssertionError: 2025-08-26T23:22:16.5475490Z Arrays are not equal 2025-08-26T23:22:16.5475523Z 2025-08-26T23:22:16.5475580Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-08-26T23:22:16.5475620Z x: torch.ndarray([2, 2, 2]) 2025-08-26T23:22:16.5475663Z y: torch.ndarray([2., 2., 2.]) 2025-08-26T23:22:16.5476141Z 2025-08-26T23:22:16.5476232Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5476264Z 2025-08-26T23:22:16.5477294Z warnings.warn(msg) 2025-08-26T23:22:16.5477325Z 2025-08-26T23:22:16.5477401Z --- Parse Warning: 80 / 146 --- 2025-08-26T23:22:16.5477718Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=851. 2025-08-26T23:22:16.5477810Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5477842Z 2025-08-26T23:22:16.5477918Z Raises an AssertionError if two objects are not equal up to desired 2025-08-26T23:22:16.5477953Z precision. 2025-08-26T23:22:16.5477983Z 2025-08-26T23:22:16.5478050Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T23:22:16.5478118Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T23:22:16.5478188Z instead of this function for more consistent floating point 2025-08-26T23:22:16.5478226Z comparisons. 2025-08-26T23:22:16.5478257Z 2025-08-26T23:22:16.5478343Z The test verifies identical shapes and that the elements of ``actual`` and 2025-08-26T23:22:16.5478381Z ``desired`` satisfy. 2025-08-26T23:22:16.5478411Z 2025-08-26T23:22:16.5478464Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-08-26T23:22:16.5478494Z 2025-08-26T23:22:16.5478576Z That is a looser test than originally documented, but agrees with what the 2025-08-26T23:22:16.5478661Z actual implementation did up to rounding vagaries. An exception is raised 2025-08-26T23:22:16.5478743Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-08-26T23:22:16.5479812Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-08-26T23:22:16.5479863Z objects have NaNs in the same positions. 2025-08-26T23:22:16.5479894Z 2025-08-26T23:22:16.5479928Z Parameters 2025-08-26T23:22:16.5479960Z ---------- 2025-08-26T23:22:16.5479994Z x : array_like 2025-08-26T23:22:16.5480036Z The actual object to check. 2025-08-26T23:22:16.5480069Z y : array_like 2025-08-26T23:22:16.5480114Z The desired, expected object. 2025-08-26T23:22:16.5480172Z decimal : int, optional 2025-08-26T23:22:16.5480218Z Desired precision, default is 6. 2025-08-26T23:22:16.5480256Z err_msg : str, optional 2025-08-26T23:22:16.5480318Z The error message to be printed in case of failure. 2025-08-26T23:22:16.5480414Z verbose : bool, optional 2025-08-26T23:22:16.5480489Z If True, the conflicting values are appended to the error message. 2025-08-26T23:22:16.5480519Z 2025-08-26T23:22:16.5480554Z Raises 2025-08-26T23:22:16.5480586Z ------ 2025-08-26T23:22:16.5480622Z AssertionError 2025-08-26T23:22:16.5480696Z If actual and desired are not equal up to specified precision. 2025-08-26T23:22:16.5480726Z 2025-08-26T23:22:16.5480758Z See Also 2025-08-26T23:22:16.5481760Z -------- 2025-08-26T23:22:16.5481846Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T23:22:16.5481896Z relative and/or absolute precision. 2025-08-26T23:22:16.5481975Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T23:22:16.5482006Z 2025-08-26T23:22:16.5482039Z Examples 2025-08-26T23:22:16.5482071Z -------- 2025-08-26T23:22:16.5482123Z the first assert does not raise an exception 2025-08-26T23:22:16.5482153Z 2025-08-26T23:22:16.5482245Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-08-26T23:22:16.5482275Z 2025-08-26T23:22:16.5482324Z >>> np.testing.assert_array_almost_equal( 2025-08-26T23:22:16.5482433Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-08-26T23:22:16.5482465Z ... ) 2025-08-26T23:22:16.5482509Z Traceback (most recent call last): 2025-08-26T23:22:16.5482541Z ... 2025-08-26T23:22:16.5482575Z AssertionError: 2025-08-26T23:22:16.5482622Z Arrays are not almost equal to 5 decimals 2025-08-26T23:22:16.5482656Z 2025-08-26T23:22:16.5482698Z Mismatched elements: 1 / 3 (33.3%) 2025-08-26T23:22:16.5482750Z Max absolute difference: 5.999999999994898e-05 2025-08-26T23:22:16.5483771Z Max relative difference: 2.5713661239633743e-05 2025-08-26T23:22:16.5483839Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T23:22:16.5483900Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-08-26T23:22:16.5483931Z 2025-08-26T23:22:16.5483978Z >>> np.testing.assert_array_almost_equal( 2025-08-26T23:22:16.5484032Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-08-26T23:22:16.5484066Z ... ) 2025-08-26T23:22:16.5484111Z Traceback (most recent call last): 2025-08-26T23:22:16.5484141Z ... 2025-08-26T23:22:16.5484177Z AssertionError: 2025-08-26T23:22:16.5484223Z Arrays are not almost equal to 5 decimals 2025-08-26T23:22:16.5484257Z 2025-08-26T23:22:16.5484299Z x and y nan location mismatch: 2025-08-26T23:22:16.5484360Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T23:22:16.5484420Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-08-26T23:22:16.5484451Z 2025-08-26T23:22:16.5484481Z 2025-08-26T23:22:16.5484571Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5484602Z 2025-08-26T23:22:16.5484640Z warnings.warn(msg) 2025-08-26T23:22:16.5484670Z 2025-08-26T23:22:16.5484743Z --- Parse Warning: 81 / 146 --- 2025-08-26T23:22:16.5486046Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-08-26T23:22:16.5486140Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5486219Z Context manager that resets warning registry for catching warnings 2025-08-26T23:22:16.5486249Z 2025-08-26T23:22:16.5486360Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-08-26T23:22:16.5486441Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-08-26T23:22:16.5486525Z it impossible to retrigger the warning in this module, whatever you put in 2025-08-26T23:22:16.5486613Z the warnings filters. This context manager accepts a sequence of `modules` 2025-08-26T23:22:16.5486669Z as a keyword argument to its constructor and: 2025-08-26T23:22:16.5486703Z 2025-08-26T23:22:16.5486787Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-08-26T23:22:16.5486821Z on entry; 2025-08-26T23:22:16.5486891Z * resets ``__warningregistry__`` to its previous state on exit. 2025-08-26T23:22:16.5486921Z 2025-08-26T23:22:16.5487002Z This makes it possible to trigger any warning afresh inside the context 2025-08-26T23:22:16.5487070Z manager without disturbing the state of warnings outside. 2025-08-26T23:22:16.5487103Z 2025-08-26T23:22:16.5487186Z For compatibility with Python 3.0, please consider all arguments to be 2025-08-26T23:22:16.5487223Z keyword-only. 2025-08-26T23:22:16.5487254Z 2025-08-26T23:22:16.5487288Z Parameters 2025-08-26T23:22:16.5487322Z ---------- 2025-08-26T23:22:16.5488331Z record : bool, optional 2025-08-26T23:22:16.5488402Z Specifies whether warnings should be captured by a custom 2025-08-26T23:22:16.5488506Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-08-26T23:22:16.5488596Z returned by the context manager. Otherwise None is returned by the 2025-08-26T23:22:16.5488677Z context manager. The objects appended to the list are arguments whose 2025-08-26T23:22:16.5488741Z attributes mirror the arguments to ``showwarning()``. 2025-08-26T23:22:16.5488785Z modules : sequence, optional 2025-08-26T23:22:16.5488867Z Sequence of modules for which to reset warnings registry on entry and 2025-08-26T23:22:16.5488936Z restore on exit. To work correctly, all 'ignore' filters should 2025-08-26T23:22:16.5488982Z filter by one of these modules. 2025-08-26T23:22:16.5489012Z 2025-08-26T23:22:16.5489048Z Examples 2025-08-26T23:22:16.5489082Z -------- 2025-08-26T23:22:16.5489121Z >>> import warnings 2025-08-26T23:22:16.5489189Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-08-26T23:22:16.5489240Z ... modules=[np.core.fromnumeric] 2025-08-26T23:22:16.5489272Z ... ): 2025-08-26T23:22:16.5489322Z ... warnings.simplefilter("always") 2025-08-26T23:22:16.5489404Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-08-26T23:22:16.5489470Z ... # do something that raises a warning but ignore those in 2025-08-26T23:22:16.5489512Z ... # np.core.fromnumeric 2025-08-26T23:22:16.5490576Z 2025-08-26T23:22:16.5490667Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5490698Z 2025-08-26T23:22:16.5490736Z warnings.warn(msg) 2025-08-26T23:22:16.5490766Z 2025-08-26T23:22:16.5490838Z --- Parse Warning: 82 / 146 --- 2025-08-26T23:22:16.5491155Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/device_mesh.py line=721. 2025-08-26T23:22:16.5491279Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T23:22:16.5491310Z 2025-08-26T23:22:16.5491406Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-08-26T23:22:16.5491500Z The submesh created consists of the dimensions and the communicators indicated by 2025-08-26T23:22:16.5491536Z ``mesh_dim_names`` 2025-08-26T23:22:16.5491592Z 2025-08-26T23:22:16.5491626Z Args: 2025-08-26T23:22:16.5491712Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-08-26T23:22:16.5491783Z mesh dimension of the DeviceMesh to create the submesh for. 2025-08-26T23:22:16.5491815Z Returns: 2025-08-26T23:22:16.5491858Z A :class:`DeviceMesh` object 2025-08-26T23:22:16.5491888Z 2025-08-26T23:22:16.5491991Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-08-26T23:22:16.5492033Z In the first example: 2025-08-26T23:22:16.5492129Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-08-26T23:22:16.5493200Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-08-26T23:22:16.5493284Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-08-26T23:22:16.5493365Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-08-26T23:22:16.5493441Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-08-26T23:22:16.5493516Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-08-26T23:22:16.5493547Z 2025-08-26T23:22:16.5493587Z In the second example: 2025-08-26T23:22:16.5493682Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-08-26T23:22:16.5493813Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-08-26T23:22:16.5493904Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-08-26T23:22:16.5493991Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-08-26T23:22:16.5494022Z 2025-08-26T23:22:16.5494057Z Example:: 2025-08-26T23:22:16.5494089Z 2025-08-26T23:22:16.5494133Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:22:16.5494199Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-08-26T23:22:16.5494230Z >>> 2025-08-26T23:22:16.5494305Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-08-26T23:22:16.5494362Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-08-26T23:22:16.5494456Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T23:22:16.5494500Z >>> tp_mesh = mesh_2d["tp"] 2025-08-26T23:22:16.5495519Z >>> dp_mesh = mesh_2d["dp"] 2025-08-26T23:22:16.5495551Z >>> 2025-08-26T23:22:16.5495590Z >>> # Initialize a 3D mesh. 2025-08-26T23:22:16.5495690Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-08-26T23:22:16.5495796Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-08-26T23:22:16.5495844Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-08-26T23:22:16.5495888Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-08-26T23:22:16.5495920Z 2025-08-26T23:22:16.5496150Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-08-26T23:22:16.5496205Z 2025-08-26T23:22:16.5496298Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T23:22:16.5496349Z ^ 2025-08-26T23:22:16.5496387Z warnings.warn(msg) 2025-08-26T23:22:16.5496418Z 2025-08-26T23:22:16.5496490Z --- Parse Warning: 83 / 146 --- 2025-08-26T23:22:16.5496828Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2710. 2025-08-26T23:22:16.5496921Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5496952Z 2025-08-26T23:22:16.5497041Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-08-26T23:22:16.5497072Z 2025-08-26T23:22:16.5497161Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-08-26T23:22:16.5497240Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-08-26T23:22:16.5498246Z 2025-08-26T23:22:16.5498279Z Args: 2025-08-26T23:22:16.5498363Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-08-26T23:22:16.5498446Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-08-26T23:22:16.5498525Z matters and it needs to match with corresponding isend/irecv on the 2025-08-26T23:22:16.5498561Z remote end. 2025-08-26T23:22:16.5498591Z 2025-08-26T23:22:16.5498624Z Returns: 2025-08-26T23:22:16.5498711Z A list of distributed request objects returned by calling the corresponding 2025-08-26T23:22:16.5498750Z op in the op_list. 2025-08-26T23:22:16.5498781Z 2025-08-26T23:22:16.5498814Z Examples: 2025-08-26T23:22:16.5498859Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:22:16.5498931Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-08-26T23:22:16.5499025Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-08-26T23:22:16.5499101Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-08-26T23:22:16.5499145Z >>> recv_op = dist.P2POp( 2025-08-26T23:22:16.5499216Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-08-26T23:22:16.5499248Z ... ) 2025-08-26T23:22:16.5499303Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-08-26T23:22:16.5499342Z >>> for req in reqs: 2025-08-26T23:22:16.5499378Z >>> req.wait() 2025-08-26T23:22:16.5500440Z >>> recv_tensor 2025-08-26T23:22:16.5500480Z tensor([2, 3]) # Rank 0 2025-08-26T23:22:16.5500518Z tensor([0, 1]) # Rank 1 2025-08-26T23:22:16.5500548Z 2025-08-26T23:22:16.5500637Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-08-26T23:22:16.5500718Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-08-26T23:22:16.5500764Z lead to unexpected hang issues. 2025-08-26T23:22:16.5500794Z 2025-08-26T23:22:16.5500870Z In addition, if this API is the first collective call in the ``group`` 2025-08-26T23:22:16.5500951Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-08-26T23:22:16.5501033Z this API call; otherwise, the behavior is undefined. If this API call is 2025-08-26T23:22:16.5501111Z not the first collective call in the ``group``, batched P2P operations 2025-08-26T23:22:16.5501184Z involving only a subset of ranks of the ``group`` are allowed. 2025-08-26T23:22:16.5501214Z 2025-08-26T23:22:16.5501302Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5501333Z 2025-08-26T23:22:16.5501371Z warnings.warn(msg) 2025-08-26T23:22:16.5501402Z 2025-08-26T23:22:16.5501510Z --- Parse Warning: 84 / 146 --- 2025-08-26T23:22:16.5501820Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2842. 2025-08-26T23:22:16.5501911Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5502928Z 2025-08-26T23:22:16.5503049Z Reduces the tensor data across all machines in a way that all get the final result. 2025-08-26T23:22:16.5503081Z 2025-08-26T23:22:16.5503161Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-08-26T23:22:16.5503193Z 2025-08-26T23:22:16.5503236Z Complex tensors are supported. 2025-08-26T23:22:16.5503267Z 2025-08-26T23:22:16.5503298Z Args: 2025-08-26T23:22:16.5503374Z tensor (Tensor): Input and output of the collective. The function 2025-08-26T23:22:16.5503418Z operates in-place. 2025-08-26T23:22:16.5503469Z op (optional): One of the values from 2025-08-26T23:22:16.5503518Z ``torch.distributed.ReduceOp`` 2025-08-26T23:22:16.5503592Z enum. Specifies an operation used for element-wise reductions. 2025-08-26T23:22:16.5503674Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5503724Z the default process group will be used. 2025-08-26T23:22:16.5503798Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T23:22:16.5503829Z 2025-08-26T23:22:16.5503860Z Returns: 2025-08-26T23:22:16.5503915Z Async work handle, if async_op is set to True. 2025-08-26T23:22:16.5503974Z None, if not async_op or if not part of the group 2025-08-26T23:22:16.5504004Z 2025-08-26T23:22:16.5504037Z Examples: 2025-08-26T23:22:16.5505051Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T23:22:16.5505107Z >>> # All tensors below are of torch.int64 type. 2025-08-26T23:22:16.5505198Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5505247Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T23:22:16.5505329Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T23:22:16.5505363Z >>> tensor 2025-08-26T23:22:16.5505409Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5505453Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5505507Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T23:22:16.5505541Z >>> tensor 2025-08-26T23:22:16.5505584Z tensor([4, 6], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5505627Z tensor([4, 6], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5505657Z 2025-08-26T23:22:16.5505711Z >>> # All tensors below are of torch.cfloat type. 2025-08-26T23:22:16.5505755Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5505799Z >>> tensor = torch.tensor( 2025-08-26T23:22:16.5505860Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T23:22:16.5505898Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T23:22:16.5505932Z >>> tensor 2025-08-26T23:22:16.5505987Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5506040Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5507057Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T23:22:16.5507093Z >>> tensor 2025-08-26T23:22:16.5507145Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5507195Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5507225Z 2025-08-26T23:22:16.5507256Z 2025-08-26T23:22:16.5507346Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5507377Z 2025-08-26T23:22:16.5507415Z warnings.warn(msg) 2025-08-26T23:22:16.5507467Z 2025-08-26T23:22:16.5507543Z --- Parse Warning: 85 / 146 --- 2025-08-26T23:22:16.5507858Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3202. 2025-08-26T23:22:16.5507950Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5507981Z 2025-08-26T23:22:16.5508095Z Gathers picklable objects from the whole group in a single process. 2025-08-26T23:22:16.5508127Z 2025-08-26T23:22:16.5508211Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-08-26T23:22:16.5508270Z object must be picklable in order to be gathered. 2025-08-26T23:22:16.5508300Z 2025-08-26T23:22:16.5508332Z Args: 2025-08-26T23:22:16.5508383Z obj (Any): Input object. Must be picklable. 2025-08-26T23:22:16.5508460Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-08-26T23:22:16.5509504Z should be correctly sized as the size of the group for this 2025-08-26T23:22:16.5509585Z collective and will contain the output. Must be ``None`` on non-dst 2025-08-26T23:22:16.5509629Z ranks. (default is ``None``) 2025-08-26T23:22:16.5509743Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-08-26T23:22:16.5509818Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-08-26T23:22:16.5509901Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5509971Z the default process group will be used. Default is ``None``. 2025-08-26T23:22:16.5510092Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-08-26T23:22:16.5510124Z 2025-08-26T23:22:16.5510157Z Returns: 2025-08-26T23:22:16.5510262Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-08-26T23:22:16.5510305Z output of the collective. 2025-08-26T23:22:16.5510337Z 2025-08-26T23:22:16.5510466Z .. note:: Note that this API differs slightly from the gather collective 2025-08-26T23:22:16.5510545Z since it does not provide an async_op handle and thus will be a blocking 2025-08-26T23:22:16.5510577Z call. 2025-08-26T23:22:16.5510608Z 2025-08-26T23:22:16.5510690Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-08-26T23:22:16.5510766Z of objects must be moved to the GPU device before communication takes 2025-08-26T23:22:16.5510823Z place. In this case, the device used is given by 2025-08-26T23:22:16.5510902Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-08-26T23:22:16.5510975Z ensure that this is set so that each rank has an individual GPU, via 2025-08-26T23:22:16.5512002Z ``torch.cuda.set_device()``. 2025-08-26T23:22:16.5512035Z 2025-08-26T23:22:16.5512070Z .. warning:: 2025-08-26T23:22:16.5512154Z Object collectives have a number of serious performance and scalability 2025-08-26T23:22:16.5512222Z limitations. See :ref:`object_collectives` for details. 2025-08-26T23:22:16.5512252Z 2025-08-26T23:22:16.5512287Z .. warning:: 2025-08-26T23:22:16.5512360Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-08-26T23:22:16.5512439Z known to be insecure. It is possible to construct malicious pickle data 2025-08-26T23:22:16.5512515Z which will execute arbitrary code during unpickling. Only call this 2025-08-26T23:22:16.5512559Z function with data you trust. 2025-08-26T23:22:16.5512590Z 2025-08-26T23:22:16.5512623Z .. warning:: 2025-08-26T23:22:16.5512699Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-08-26T23:22:16.5512815Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-08-26T23:22:16.5512882Z pickled. Please consider using :func:`gather` instead. 2025-08-26T23:22:16.5512913Z 2025-08-26T23:22:16.5512948Z Example:: 2025-08-26T23:22:16.5513001Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T23:22:16.5513069Z >>> # Note: Process group initialization omitted on each rank. 2025-08-26T23:22:16.5513116Z >>> import torch.distributed as dist 2025-08-26T23:22:16.5514146Z >>> # Assumes world_size of 3. 2025-08-26T23:22:16.5514215Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-08-26T23:22:16.5514264Z >>> output = [None for _ in gather_objects] 2025-08-26T23:22:16.5514303Z >>> dist.gather_object( 2025-08-26T23:22:16.5514351Z ... gather_objects[dist.get_rank()], 2025-08-26T23:22:16.5514402Z ... output if dist.get_rank() == 0 else None, 2025-08-26T23:22:16.5514500Z ... dst=0 2025-08-26T23:22:16.5514533Z ... ) 2025-08-26T23:22:16.5514570Z >>> # On rank 0 2025-08-26T23:22:16.5514603Z >>> output 2025-08-26T23:22:16.5514640Z ['foo', 12, {1: 2}] 2025-08-26T23:22:16.5514671Z 2025-08-26T23:22:16.5514762Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5514793Z 2025-08-26T23:22:16.5514830Z warnings.warn(msg) 2025-08-26T23:22:16.5514861Z 2025-08-26T23:22:16.5514936Z --- Parse Warning: 86 / 146 --- 2025-08-26T23:22:16.5515243Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3798. 2025-08-26T23:22:16.5515336Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5515367Z 2025-08-26T23:22:16.5515421Z Gathers tensors from the whole group in a list. 2025-08-26T23:22:16.5515476Z 2025-08-26T23:22:16.5516534Z Complex and uneven sized tensors are supported. 2025-08-26T23:22:16.5516566Z 2025-08-26T23:22:16.5516599Z Args: 2025-08-26T23:22:16.5516669Z tensor_list (list[Tensor]): Output list. It should contain 2025-08-26T23:22:16.5516746Z correctly-sized tensors to be used for output of the collective. 2025-08-26T23:22:16.5516794Z Uneven sized tensors are supported. 2025-08-26T23:22:16.5516866Z tensor (Tensor): Tensor to be broadcast from current process. 2025-08-26T23:22:16.5516948Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5516996Z the default process group will be used. 2025-08-26T23:22:16.5517069Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T23:22:16.5517099Z 2025-08-26T23:22:16.5517132Z Returns: 2025-08-26T23:22:16.5517186Z Async work handle, if async_op is set to True. 2025-08-26T23:22:16.5517245Z None, if not async_op or if not part of the group 2025-08-26T23:22:16.5517275Z 2025-08-26T23:22:16.5517308Z Examples: 2025-08-26T23:22:16.5517360Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T23:22:16.5517412Z >>> # All tensors below are of torch.int64 dtype. 2025-08-26T23:22:16.5517459Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5517505Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T23:22:16.5517545Z >>> tensor_list = [ 2025-08-26T23:22:16.5517621Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-08-26T23:22:16.5518618Z ... ] 2025-08-26T23:22:16.5518654Z >>> tensor_list 2025-08-26T23:22:16.5518732Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-08-26T23:22:16.5518801Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-08-26T23:22:16.5518909Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T23:22:16.5518943Z >>> tensor 2025-08-26T23:22:16.5518989Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5519033Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5519078Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T23:22:16.5519113Z >>> tensor_list 2025-08-26T23:22:16.5519197Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-08-26T23:22:16.5519266Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-08-26T23:22:16.5519297Z 2025-08-26T23:22:16.5519352Z >>> # All tensors below are of torch.cfloat dtype. 2025-08-26T23:22:16.5519398Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5519436Z >>> tensor_list = [ 2025-08-26T23:22:16.5519512Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-08-26T23:22:16.5519545Z ... ] 2025-08-26T23:22:16.5519581Z >>> tensor_list 2025-08-26T23:22:16.5519672Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-08-26T23:22:16.5519756Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-08-26T23:22:16.5520865Z >>> tensor = torch.tensor( 2025-08-26T23:22:16.5520925Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T23:22:16.5520966Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T23:22:16.5520999Z >>> tensor 2025-08-26T23:22:16.5521053Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T23:22:16.5521104Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T23:22:16.5521151Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T23:22:16.5521185Z >>> tensor_list 2025-08-26T23:22:16.5521269Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-08-26T23:22:16.5521401Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-08-26T23:22:16.5521433Z 2025-08-26T23:22:16.5521463Z 2025-08-26T23:22:16.5521554Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5521584Z 2025-08-26T23:22:16.5521623Z warnings.warn(msg) 2025-08-26T23:22:16.5521652Z 2025-08-26T23:22:16.5521726Z --- Parse Warning: 87 / 146 --- 2025-08-26T23:22:16.5522039Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4504. 2025-08-26T23:22:16.5522133Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5522163Z 2025-08-26T23:22:16.5522254Z Split input tensor and then scatter the split list to all processes in a group. 2025-08-26T23:22:16.5522286Z 2025-08-26T23:22:16.5523359Z Later the received tensors are concatenated from all the processes in the group 2025-08-26T23:22:16.5523408Z and returned as a single output tensor. 2025-08-26T23:22:16.5523439Z 2025-08-26T23:22:16.5523482Z Complex tensors are supported. 2025-08-26T23:22:16.5523512Z 2025-08-26T23:22:16.5523544Z Args: 2025-08-26T23:22:16.5523609Z output (Tensor): Gathered concatenated output tensor. 2025-08-26T23:22:16.5523659Z input (Tensor): Input tensor to scatter. 2025-08-26T23:22:16.5523740Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-08-26T23:22:16.5523816Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-08-26T23:22:16.5523858Z equally by ``world_size``. 2025-08-26T23:22:16.5523937Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-08-26T23:22:16.5524033Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-08-26T23:22:16.5524078Z equally by ``world_size``. 2025-08-26T23:22:16.5524158Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5524207Z the default process group will be used. 2025-08-26T23:22:16.5524280Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T23:22:16.5524311Z 2025-08-26T23:22:16.5524362Z Returns: 2025-08-26T23:22:16.5524417Z Async work handle, if async_op is set to True. 2025-08-26T23:22:16.5524474Z None, if not async_op or if not part of the group. 2025-08-26T23:22:16.5525477Z 2025-08-26T23:22:16.5525512Z .. warning:: 2025-08-26T23:22:16.5525579Z `all_to_all_single` is experimental and subject to change. 2025-08-26T23:22:16.5525609Z 2025-08-26T23:22:16.5525643Z Examples: 2025-08-26T23:22:16.5525690Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T23:22:16.5525741Z >>> input = torch.arange(4) + rank * 4 2025-08-26T23:22:16.5525774Z >>> input 2025-08-26T23:22:16.5525816Z tensor([0, 1, 2, 3]) # Rank 0 2025-08-26T23:22:16.5525857Z tensor([4, 5, 6, 7]) # Rank 1 2025-08-26T23:22:16.5525895Z tensor([8, 9, 10, 11]) # Rank 2 2025-08-26T23:22:16.5525933Z tensor([12, 13, 14, 15]) # Rank 3 2025-08-26T23:22:16.5525989Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T23:22:16.5526040Z >>> dist.all_to_all_single(output, input) 2025-08-26T23:22:16.5526073Z >>> output 2025-08-26T23:22:16.5526112Z tensor([0, 4, 8, 12]) # Rank 0 2025-08-26T23:22:16.5526150Z tensor([1, 5, 9, 13]) # Rank 1 2025-08-26T23:22:16.5526188Z tensor([2, 6, 10, 14]) # Rank 2 2025-08-26T23:22:16.5526225Z tensor([3, 7, 11, 15]) # Rank 3 2025-08-26T23:22:16.5526256Z 2025-08-26T23:22:16.5526317Z >>> # Essentially, it is similar to following operation: 2025-08-26T23:22:16.5526409Z >>> scatter_list = list(input.chunk(world_size)) 2025-08-26T23:22:16.5527430Z >>> gather_list = list(output.chunk(world_size)) 2025-08-26T23:22:16.5527475Z >>> for i in range(world_size): 2025-08-26T23:22:16.5527562Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-08-26T23:22:16.5527593Z 2025-08-26T23:22:16.5527639Z >>> # Another example with uneven split 2025-08-26T23:22:16.5527674Z >>> input 2025-08-26T23:22:16.5527806Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T23:22:16.5527868Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T23:22:16.5527924Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T23:22:16.5527980Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T23:22:16.5528019Z >>> input_splits 2025-08-26T23:22:16.5528072Z [2, 2, 1, 1] # Rank 0 2025-08-26T23:22:16.5528119Z [3, 2, 2, 2] # Rank 1 2025-08-26T23:22:16.5528164Z [2, 1, 1, 1] # Rank 2 2025-08-26T23:22:16.5528209Z [2, 2, 2, 1] # Rank 3 2025-08-26T23:22:16.5528247Z >>> output_splits 2025-08-26T23:22:16.5528294Z [2, 3, 2, 2] # Rank 0 2025-08-26T23:22:16.5528340Z [2, 2, 1, 2] # Rank 1 2025-08-26T23:22:16.5528389Z [1, 2, 1, 2] # Rank 2 2025-08-26T23:22:16.5528433Z [1, 2, 1, 1] # Rank 3 2025-08-26T23:22:16.5528471Z >>> output = ... 2025-08-26T23:22:16.5528570Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-08-26T23:22:16.5529713Z >>> output 2025-08-26T23:22:16.5529771Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-08-26T23:22:16.5529830Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-08-26T23:22:16.5529886Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-08-26T23:22:16.5529965Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-08-26T23:22:16.5529996Z 2025-08-26T23:22:16.5530027Z 2025-08-26T23:22:16.5530089Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T23:22:16.5530132Z >>> input = torch.tensor( 2025-08-26T23:22:16.5530188Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T23:22:16.5530227Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T23:22:16.5530262Z >>> input 2025-08-26T23:22:16.5530330Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-08-26T23:22:16.5530454Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-08-26T23:22:16.5530521Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-08-26T23:22:16.5530587Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-08-26T23:22:16.5530642Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T23:22:16.5530693Z >>> dist.all_to_all_single(output, input) 2025-08-26T23:22:16.5530726Z >>> output 2025-08-26T23:22:16.5530789Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-08-26T23:22:16.5530851Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-08-26T23:22:16.5531945Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-08-26T23:22:16.5532009Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-08-26T23:22:16.5532099Z 2025-08-26T23:22:16.5532187Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5532218Z 2025-08-26T23:22:16.5532256Z warnings.warn(msg) 2025-08-26T23:22:16.5532287Z 2025-08-26T23:22:16.5532361Z --- Parse Warning: 88 / 146 --- 2025-08-26T23:22:16.5532667Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4646. 2025-08-26T23:22:16.5532759Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5532791Z 2025-08-26T23:22:16.5532919Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-08-26T23:22:16.5532951Z 2025-08-26T23:22:16.5532994Z Complex tensors are supported. 2025-08-26T23:22:16.5533026Z 2025-08-26T23:22:16.5533059Z Args: 2025-08-26T23:22:16.5533139Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-08-26T23:22:16.5533174Z per rank. 2025-08-26T23:22:16.5533256Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-08-26T23:22:16.5533339Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5533390Z the default process group will be used. 2025-08-26T23:22:16.5533464Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T23:22:16.5534467Z 2025-08-26T23:22:16.5534500Z Returns: 2025-08-26T23:22:16.5534556Z Async work handle, if async_op is set to True. 2025-08-26T23:22:16.5534613Z None, if not async_op or if not part of the group. 2025-08-26T23:22:16.5534644Z 2025-08-26T23:22:16.5534678Z .. warning:: 2025-08-26T23:22:16.5534761Z `all_to_all` is experimental and subject to change. 2025-08-26T23:22:16.5534796Z 2025-08-26T23:22:16.5534829Z Examples: 2025-08-26T23:22:16.5534877Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T23:22:16.5534922Z >>> input = torch.arange(4) + rank * 4 2025-08-26T23:22:16.5534966Z >>> input = list(input.chunk(4)) 2025-08-26T23:22:16.5534998Z >>> input 2025-08-26T23:22:16.5535064Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-08-26T23:22:16.5535141Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-08-26T23:22:16.5535203Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-08-26T23:22:16.5535263Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-08-26T23:22:16.5535333Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T23:22:16.5535378Z >>> dist.all_to_all(output, input) 2025-08-26T23:22:16.5535415Z >>> output 2025-08-26T23:22:16.5535477Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-08-26T23:22:16.5536501Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-08-26T23:22:16.5536560Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-08-26T23:22:16.5536618Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-08-26T23:22:16.5536649Z 2025-08-26T23:22:16.5536713Z >>> # Essentially, it is similar to following operation: 2025-08-26T23:22:16.5536754Z >>> scatter_list = input 2025-08-26T23:22:16.5536794Z >>> gather_list = output 2025-08-26T23:22:16.5536836Z >>> for i in range(world_size): 2025-08-26T23:22:16.5536920Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-08-26T23:22:16.5536950Z 2025-08-26T23:22:16.5536982Z >>> input 2025-08-26T23:22:16.5537040Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T23:22:16.5537132Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T23:22:16.5537190Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T23:22:16.5537246Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T23:22:16.5537283Z >>> input_splits 2025-08-26T23:22:16.5537330Z [2, 2, 1, 1] # Rank 0 2025-08-26T23:22:16.5537375Z [3, 2, 2, 2] # Rank 1 2025-08-26T23:22:16.5537420Z [2, 1, 1, 1] # Rank 2 2025-08-26T23:22:16.5537465Z [2, 2, 2, 1] # Rank 3 2025-08-26T23:22:16.5537502Z >>> output_splits 2025-08-26T23:22:16.5537548Z [2, 3, 2, 2] # Rank 0 2025-08-26T23:22:16.5538560Z [2, 2, 1, 2] # Rank 1 2025-08-26T23:22:16.5538607Z [1, 2, 1, 2] # Rank 2 2025-08-26T23:22:16.5538651Z [1, 2, 1, 1] # Rank 3 2025-08-26T23:22:16.5538703Z >>> input = list(input.split(input_splits)) 2025-08-26T23:22:16.5538735Z >>> input 2025-08-26T23:22:16.5538812Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-08-26T23:22:16.5538885Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-08-26T23:22:16.5538957Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-08-26T23:22:16.5539028Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-08-26T23:22:16.5539065Z >>> output = ... 2025-08-26T23:22:16.5539131Z >>> dist.all_to_all(output, input) 2025-08-26T23:22:16.5539169Z >>> output 2025-08-26T23:22:16.5539239Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-08-26T23:22:16.5539310Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-08-26T23:22:16.5539380Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-08-26T23:22:16.5539464Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-08-26T23:22:16.5539494Z 2025-08-26T23:22:16.5539557Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T23:22:16.5539599Z >>> input = torch.tensor( 2025-08-26T23:22:16.5539655Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T23:22:16.5539694Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T23:22:16.5540773Z >>> input = list(input.chunk(4)) 2025-08-26T23:22:16.5540812Z >>> input 2025-08-26T23:22:16.5540891Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-08-26T23:22:16.5540965Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-08-26T23:22:16.5541041Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-08-26T23:22:16.5541121Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-08-26T23:22:16.5541191Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T23:22:16.5541236Z >>> dist.all_to_all(output, input) 2025-08-26T23:22:16.5541269Z >>> output 2025-08-26T23:22:16.5541342Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-08-26T23:22:16.5541416Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-08-26T23:22:16.5541519Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-08-26T23:22:16.5541637Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-08-26T23:22:16.5541668Z 2025-08-26T23:22:16.5541699Z 2025-08-26T23:22:16.5541790Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5541820Z 2025-08-26T23:22:16.5541859Z warnings.warn(msg) 2025-08-26T23:22:16.5541890Z 2025-08-26T23:22:16.5541964Z --- Parse Warning: 89 / 146 --- 2025-08-26T23:22:16.5542247Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/launch.py line=2. 2025-08-26T23:22:16.5542342Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5543344Z 2025-08-26T23:22:16.5543393Z Module ``torch.distributed.launch``. 2025-08-26T23:22:16.5543426Z 2025-08-26T23:22:16.5543516Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-08-26T23:22:16.5543575Z training processes on each of the training nodes. 2025-08-26T23:22:16.5543606Z 2025-08-26T23:22:16.5543639Z .. warning:: 2025-08-26T23:22:16.5543670Z 2025-08-26T23:22:16.5543762Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-08-26T23:22:16.5543794Z 2025-08-26T23:22:16.5543880Z The utility can be used for single-node distributed training, in which one or 2025-08-26T23:22:16.5543964Z more processes per node will be spawned. The utility can be used for either 2025-08-26T23:22:16.5544044Z CPU training or GPU training. If the utility is used for GPU training, 2025-08-26T23:22:16.5544132Z each distributed process will be operating on a single GPU. This can achieve 2025-08-26T23:22:16.5544243Z well-improved single-node training performance. It can also be used in 2025-08-26T23:22:16.5544342Z multi-node distributed training, by spawning up multiple processes on each node 2025-08-26T23:22:16.5544424Z for well-improved multi-node distributed training performance as well. 2025-08-26T23:22:16.5544507Z This will especially be beneficial for systems with multiple Infiniband 2025-08-26T23:22:16.5544599Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-08-26T23:22:16.5544664Z aggregated communication bandwidth. 2025-08-26T23:22:16.5544696Z 2025-08-26T23:22:16.5545742Z In both cases of single-node distributed training or multi-node distributed 2025-08-26T23:22:16.5545828Z training, this utility will launch the given number of processes per node 2025-08-26T23:22:16.5545912Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-08-26T23:22:16.5545990Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-08-26T23:22:16.5546066Z and each process will be operating on a single GPU from *GPU 0 to 2025-08-26T23:22:16.5546110Z GPU (nproc_per_node - 1)*. 2025-08-26T23:22:16.5546140Z 2025-08-26T23:22:16.5546182Z **How to use this module:** 2025-08-26T23:22:16.5546212Z 2025-08-26T23:22:16.5546273Z 1. Single-Node multi-process distributed training 2025-08-26T23:22:16.5546304Z 2025-08-26T23:22:16.5546338Z :: 2025-08-26T23:22:16.5546368Z 2025-08-26T23:22:16.5546457Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:22:16.5546527Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-08-26T23:22:16.5546578Z arguments of your training script) 2025-08-26T23:22:16.5546608Z 2025-08-26T23:22:16.5546686Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-08-26T23:22:16.5546716Z 2025-08-26T23:22:16.5546746Z 2025-08-26T23:22:16.5546805Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-08-26T23:22:16.5546858Z 2025-08-26T23:22:16.5547869Z :: 2025-08-26T23:22:16.5547900Z 2025-08-26T23:22:16.5547985Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:22:16.5548047Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-08-26T23:22:16.5548126Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T23:22:16.5548185Z and all other arguments of your training script) 2025-08-26T23:22:16.5548216Z 2025-08-26T23:22:16.5548248Z Node 2: 2025-08-26T23:22:16.5548279Z 2025-08-26T23:22:16.5548310Z :: 2025-08-26T23:22:16.5548341Z 2025-08-26T23:22:16.5548422Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T23:22:16.5548482Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-08-26T23:22:16.5548557Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T23:22:16.5548618Z and all other arguments of your training script) 2025-08-26T23:22:16.5548648Z 2025-08-26T23:22:16.5548712Z 3. To look up what optional arguments this module offers: 2025-08-26T23:22:16.5548742Z 2025-08-26T23:22:16.5548773Z :: 2025-08-26T23:22:16.5548804Z 2025-08-26T23:22:16.5548858Z python -m torch.distributed.launch --help 2025-08-26T23:22:16.5548889Z 2025-08-26T23:22:16.5549880Z 2025-08-26T23:22:16.5549923Z **Important Notices:** 2025-08-26T23:22:16.5549954Z 2025-08-26T23:22:16.5550026Z 1. This utility and multi-process distributed (single-node or 2025-08-26T23:22:16.5550115Z multi-node) GPU training currently only achieves the best performance using 2025-08-26T23:22:16.5550204Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-08-26T23:22:16.5550243Z use for GPU training. 2025-08-26T23:22:16.5550302Z 2025-08-26T23:22:16.5550458Z 2. In your training program, you must parse the command-line argument: 2025-08-26T23:22:16.5550543Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-08-26T23:22:16.5550624Z If your training program uses GPUs, you should ensure that your code only 2025-08-26T23:22:16.5550696Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-08-26T23:22:16.5550727Z 2025-08-26T23:22:16.5550770Z Parsing the local_rank argument 2025-08-26T23:22:16.5550831Z 2025-08-26T23:22:16.5550866Z :: 2025-08-26T23:22:16.5550895Z 2025-08-26T23:22:16.5550935Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5550975Z >>> import argparse 2025-08-26T23:22:16.5551027Z >>> parser = argparse.ArgumentParser() 2025-08-26T23:22:16.5551100Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-08-26T23:22:16.5551145Z >>> args = parser.parse_args() 2025-08-26T23:22:16.5552177Z 2025-08-26T23:22:16.5552226Z Set your device to local rank using either 2025-08-26T23:22:16.5552260Z 2025-08-26T23:22:16.5552290Z :: 2025-08-26T23:22:16.5552321Z 2025-08-26T23:22:16.5552394Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-08-26T23:22:16.5552424Z 2025-08-26T23:22:16.5552454Z or 2025-08-26T23:22:16.5552484Z 2025-08-26T23:22:16.5552515Z :: 2025-08-26T23:22:16.5552546Z 2025-08-26T23:22:16.5552601Z >>> with torch.cuda.device(args.local_rank): 2025-08-26T23:22:16.5552642Z >>> # your code to run 2025-08-26T23:22:16.5552675Z >>> ... 2025-08-26T23:22:16.5552705Z 2025-08-26T23:22:16.5552747Z .. versionchanged:: 2.0.0 2025-08-26T23:22:16.5552776Z 2025-08-26T23:22:16.5552868Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-08-26T23:22:16.5552955Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-08-26T23:22:16.5553013Z previously used underscored ``--local_rank``. 2025-08-26T23:22:16.5553091Z 2025-08-26T23:22:16.5554144Z For backward compatibility, it may be necessary for users to handle both 2025-08-26T23:22:16.5554243Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-08-26T23:22:16.5554323Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-08-26T23:22:16.5554413Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-08-26T23:22:16.5554559Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-08-26T23:22:16.5554617Z including ``"--local-rank"`` should be sufficient. 2025-08-26T23:22:16.5554648Z 2025-08-26T23:22:16.5554731Z 3. In your training program, you are supposed to call the following function 2025-08-26T23:22:16.5554816Z at the beginning to start the distributed backend. It is strongly recommended 2025-08-26T23:22:16.5554898Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-08-26T23:22:16.5554971Z but ``env://`` is the one that is officially supported by this module. 2025-08-26T23:22:16.5555002Z 2025-08-26T23:22:16.5555034Z :: 2025-08-26T23:22:16.5555064Z 2025-08-26T23:22:16.5555140Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-08-26T23:22:16.5555192Z >>> init_method='env://') 2025-08-26T23:22:16.5555224Z 2025-08-26T23:22:16.5555309Z 4. In your training program, you can either use regular distributed functions 2025-08-26T23:22:16.5555395Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-08-26T23:22:16.5555471Z training program uses GPUs for training and you would like to use 2025-08-26T23:22:16.5555545Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-08-26T23:22:16.5555588Z here is how to configure it. 2025-08-26T23:22:16.5556644Z 2025-08-26T23:22:16.5556678Z :: 2025-08-26T23:22:16.5556708Z 2025-08-26T23:22:16.5556785Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-08-26T23:22:16.5556840Z >>> device_ids=[args.local_rank], 2025-08-26T23:22:16.5556895Z >>> output_device=args.local_rank) 2025-08-26T23:22:16.5556925Z 2025-08-26T23:22:16.5557030Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-08-26T23:22:16.5557114Z that your code will be operating on. This is generally the local rank of the 2025-08-26T23:22:16.5557199Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-08-26T23:22:16.5557278Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-08-26T23:22:16.5557311Z utility 2025-08-26T23:22:16.5557341Z 2025-08-26T23:22:16.5557429Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-08-26T23:22:16.5557511Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-08-26T23:22:16.5557591Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-08-26T23:22:16.5557663Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-08-26T23:22:16.5557729Z will not pass ``--local-rank`` when you specify this flag. 2025-08-26T23:22:16.5557760Z 2025-08-26T23:22:16.5557796Z .. warning:: 2025-08-26T23:22:16.5557826Z 2025-08-26T23:22:16.5558863Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-08-26T23:22:16.5558933Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-08-26T23:22:16.5558982Z write to a networked filesystem. See 2025-08-26T23:22:16.5559063Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-08-26T23:22:16.5559127Z how things can go wrong if you don't do this correctly. 2025-08-26T23:22:16.5559177Z 2025-08-26T23:22:16.5559222Z 2025-08-26T23:22:16.5559254Z 2025-08-26T23:22:16.5559284Z 2025-08-26T23:22:16.5559375Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5559405Z 2025-08-26T23:22:16.5559443Z warnings.warn(msg) 2025-08-26T23:22:16.5559472Z 2025-08-26T23:22:16.5559549Z --- Parse Warning: 90 / 146 --- 2025-08-26T23:22:16.5559874Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-08-26T23:22:16.5559967Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5559998Z 2025-08-26T23:22:16.5560080Z Custom reducer class that can be used to specify a custom operation that 2025-08-26T23:22:16.5560147Z reduces losses of multiple microbatches into one value. 2025-08-26T23:22:16.5560180Z 2025-08-26T23:22:16.5560214Z Example: 2025-08-26T23:22:16.5560253Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5561344Z >>> sum_reducer = _CustomReducer( 2025-08-26T23:22:16.5561386Z >>> torch.tensor(0.0), 2025-08-26T23:22:16.5561425Z >>> lambda a, b: a + b 2025-08-26T23:22:16.5561458Z >>> ) 2025-08-26T23:22:16.5561488Z 2025-08-26T23:22:16.5561579Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5561610Z 2025-08-26T23:22:16.5561648Z warnings.warn(msg) 2025-08-26T23:22:16.5561678Z 2025-08-26T23:22:16.5561750Z --- Parse Warning: 91 / 146 --- 2025-08-26T23:22:16.5562099Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/options.py line=113. 2025-08-26T23:22:16.5562229Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5562260Z 2025-08-26T23:22:16.5562336Z Set device mapping between each RPC caller and callee pair. This 2025-08-26T23:22:16.5562405Z function can be called multiple times to incrementally add 2025-08-26T23:22:16.5562452Z device placement configurations. 2025-08-26T23:22:16.5562484Z 2025-08-26T23:22:16.5562515Z Args: 2025-08-26T23:22:16.5562574Z to (str): Callee name. 2025-08-26T23:22:16.5562647Z device_map (Dict of int, str, or torch.device): Device placement 2025-08-26T23:22:16.5562717Z mappings from this worker to the callee. This map must be 2025-08-26T23:22:16.5562753Z invertible. 2025-08-26T23:22:16.5563755Z 2025-08-26T23:22:16.5563789Z Example: 2025-08-26T23:22:16.5563838Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5563878Z >>> # both workers 2025-08-26T23:22:16.5563919Z >>> def add(x, y): 2025-08-26T23:22:16.5563976Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-08-26T23:22:16.5564020Z >>> return x + y, (x + y).to(2) 2025-08-26T23:22:16.5564053Z >>> 2025-08-26T23:22:16.5564089Z >>> # on worker 0 2025-08-26T23:22:16.5564146Z >>> options = TensorPipeRpcBackendOptions( 2025-08-26T23:22:16.5564187Z >>> num_worker_threads=8, 2025-08-26T23:22:16.5564235Z >>> device_maps={"worker1": {0: 1}} 2025-08-26T23:22:16.5564288Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-08-26T23:22:16.5564320Z >>> ) 2025-08-26T23:22:16.5564371Z >>> options.set_device_map("worker1", {1: 2}) 2025-08-26T23:22:16.5564422Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-08-26T23:22:16.5564454Z >>> 2025-08-26T23:22:16.5564492Z >>> rpc.init_rpc( 2025-08-26T23:22:16.5564528Z >>> "worker0", 2025-08-26T23:22:16.5564563Z >>> rank=0, 2025-08-26T23:22:16.5564658Z >>> world_size=2, 2025-08-26T23:22:16.5565678Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-08-26T23:22:16.5565723Z >>> rpc_backend_options=options 2025-08-26T23:22:16.5565755Z >>> ) 2025-08-26T23:22:16.5565786Z >>> 2025-08-26T23:22:16.5565824Z >>> x = torch.ones(2) 2025-08-26T23:22:16.5565890Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-08-26T23:22:16.5565961Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-08-26T23:22:16.5566029Z >>> # sending the return value back, it will follow the invert of 2025-08-26T23:22:16.5566095Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-08-26T23:22:16.5566134Z >>> # cuda:1 on worker0 2025-08-26T23:22:16.5566194Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-08-26T23:22:16.5566250Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-08-26T23:22:16.5566284Z 2025-08-26T23:22:16.5566374Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5566405Z 2025-08-26T23:22:16.5566443Z warnings.warn(msg) 2025-08-26T23:22:16.5566473Z 2025-08-26T23:22:16.5566544Z --- Parse Warning: 92 / 146 --- 2025-08-26T23:22:16.5566850Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/functions.py line=6. 2025-08-26T23:22:16.5566943Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5566974Z 2025-08-26T23:22:16.5567060Z A decorator for a function indicating that the return value of the function 2025-08-26T23:22:16.5568097Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-08-26T23:22:16.5568208Z function can run asynchronously on the RPC callee. More specifically, the 2025-08-26T23:22:16.5568295Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-08-26T23:22:16.5568378Z function and installs subsequent processing steps as a callback to that 2025-08-26T23:22:16.5568461Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-08-26T23:22:16.5568537Z from the :class:`~torch.futures.Future` when completed and send the 2025-08-26T23:22:16.5568622Z value back as the RPC response. That also means the returned 2025-08-26T23:22:16.5568704Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-08-26T23:22:16.5568784Z sent through RPC. This decorator is useful when the wrapped function's 2025-08-26T23:22:16.5568855Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-08-26T23:22:16.5568937Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-08-26T23:22:16.5568970Z 2025-08-26T23:22:16.5569049Z .. note:: To enable asynchronous execution, applications must pass the 2025-08-26T23:22:16.5569133Z function object returned by this decorator to RPC APIs. If RPC detected 2025-08-26T23:22:16.5569209Z attributes installed by this decorator, it knows that this function 2025-08-26T23:22:16.5569278Z returns a ``Future`` object and will handle that accordingly. 2025-08-26T23:22:16.5569355Z However, this does not mean this decorator has to be outmost one when 2025-08-26T23:22:16.5569436Z defining a function. For example, when combined with ``@staticmethod`` 2025-08-26T23:22:16.5569511Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-08-26T23:22:16.5569588Z inner decorator to allow the target function be recognized as a static 2025-08-26T23:22:16.5569669Z or class function. This target function can still execute asynchronously 2025-08-26T23:22:16.5570822Z because, when accessed, the static or class method preserves attributes 2025-08-26T23:22:16.5570937Z installed by ``@rpc.functions.async_execution``. 2025-08-26T23:22:16.5570970Z 2025-08-26T23:22:16.5571001Z 2025-08-26T23:22:16.5571035Z Example:: 2025-08-26T23:22:16.5571109Z The returned :class:`~torch.futures.Future` object can come from 2025-08-26T23:22:16.5571160Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-08-26T23:22:16.5571245Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-08-26T23:22:16.5571310Z constructor. The example below shows directly using the 2025-08-26T23:22:16.5571362Z :class:`~torch.futures.Future` returned by 2025-08-26T23:22:16.5571411Z :meth:`~torch.futures.Future.then`. 2025-08-26T23:22:16.5571443Z 2025-08-26T23:22:16.5571490Z >>> from torch.distributed import rpc 2025-08-26T23:22:16.5571523Z >>> 2025-08-26T23:22:16.5571568Z >>> # omitting setup and shutdown RPC 2025-08-26T23:22:16.5571601Z >>> 2025-08-26T23:22:16.5571642Z >>> # On all workers 2025-08-26T23:22:16.5571689Z >>> @rpc.functions.async_execution 2025-08-26T23:22:16.5571735Z >>> def async_add_chained(to, x, y, z): 2025-08-26T23:22:16.5571806Z >>> # This function runs on "worker1" and returns immediately when 2025-08-26T23:22:16.5571873Z >>> # the callback is installed through the `then(cb)` API. In the 2025-08-26T23:22:16.5571941Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-08-26T23:22:16.5572994Z >>> # When the return value of that `rpc_async` arrives at 2025-08-26T23:22:16.5573066Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-08-26T23:22:16.5573132Z >>> # and set the value for the previously returned `Future`, which 2025-08-26T23:22:16.5573199Z >>> # will then trigger RPC to send the result back to "worker0". 2025-08-26T23:22:16.5573296Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:22:16.5573347Z >>> lambda fut: fut.wait() + z 2025-08-26T23:22:16.5573380Z >>> ) 2025-08-26T23:22:16.5573411Z >>> 2025-08-26T23:22:16.5573447Z >>> # On worker0 2025-08-26T23:22:16.5573487Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5573529Z >>> ret = rpc.rpc_sync( 2025-08-26T23:22:16.5573564Z >>> "worker1", 2025-08-26T23:22:16.5573605Z >>> async_add_chained, 2025-08-26T23:22:16.5573678Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-08-26T23:22:16.5573711Z >>> ) 2025-08-26T23:22:16.5573758Z >>> print(ret) # prints tensor([3., 3.]) 2025-08-26T23:22:16.5573789Z 2025-08-26T23:22:16.5573868Z When combined with TorchScript decorators, this decorator must be the 2025-08-26T23:22:16.5573904Z outmost one. 2025-08-26T23:22:16.5573935Z 2025-08-26T23:22:16.5573977Z >>> from torch import Tensor 2025-08-26T23:22:16.5574024Z >>> from torch.futures import Future 2025-08-26T23:22:16.5575718Z >>> from torch.distributed import rpc 2025-08-26T23:22:16.5575752Z >>> 2025-08-26T23:22:16.5575799Z >>> # omitting setup and shutdown RPC 2025-08-26T23:22:16.5575829Z >>> 2025-08-26T23:22:16.5575867Z >>> # On all workers 2025-08-26T23:22:16.5575908Z >>> @torch.jit.script 2025-08-26T23:22:16.5575967Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T23:22:16.5576008Z >>> return x + y 2025-08-26T23:22:16.5576039Z >>> 2025-08-26T23:22:16.5576086Z >>> @rpc.functions.async_execution 2025-08-26T23:22:16.5576124Z >>> @torch.jit.script 2025-08-26T23:22:16.5576195Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-08-26T23:22:16.5576252Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-08-26T23:22:16.5576283Z >>> 2025-08-26T23:22:16.5576318Z >>> # On worker0 2025-08-26T23:22:16.5576382Z >>> ret = rpc.rpc_sync( 2025-08-26T23:22:16.5576440Z >>> "worker1", 2025-08-26T23:22:16.5576477Z >>> async_add, 2025-08-26T23:22:16.5576525Z >>> args=("worker2", torch.ones(2), 1) 2025-08-26T23:22:16.5576556Z >>> ) 2025-08-26T23:22:16.5576603Z >>> print(ret) # prints tensor([2., 2.]) 2025-08-26T23:22:16.5577621Z 2025-08-26T23:22:16.5577700Z When combined with static or class method, this decorator must be the 2025-08-26T23:22:16.5577735Z inner one. 2025-08-26T23:22:16.5577767Z 2025-08-26T23:22:16.5577813Z >>> from torch.distributed import rpc 2025-08-26T23:22:16.5577845Z >>> 2025-08-26T23:22:16.5577889Z >>> # omitting setup and shutdown RPC 2025-08-26T23:22:16.5577920Z >>> 2025-08-26T23:22:16.5577957Z >>> # On all workers 2025-08-26T23:22:16.5578003Z >>> class AsyncExecutionClass: 2025-08-26T23:22:16.5578034Z >>> 2025-08-26T23:22:16.5578074Z >>> @staticmethod 2025-08-26T23:22:16.5578123Z >>> @rpc.functions.async_execution 2025-08-26T23:22:16.5578170Z >>> def static_async_add(to, x, y, z): 2025-08-26T23:22:16.5578234Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:22:16.5578280Z >>> lambda fut: fut.wait() + z 2025-08-26T23:22:16.5578314Z >>> ) 2025-08-26T23:22:16.5578346Z >>> 2025-08-26T23:22:16.5578384Z >>> @classmethod 2025-08-26T23:22:16.5578430Z >>> @rpc.functions.async_execution 2025-08-26T23:22:16.5578480Z >>> def class_async_add(cls, to, x, y, z): 2025-08-26T23:22:16.5578530Z >>> ret_fut = torch.futures.Future() 2025-08-26T23:22:16.5579606Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:22:16.5579666Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-08-26T23:22:16.5579700Z >>> ) 2025-08-26T23:22:16.5579766Z >>> return ret_fut 2025-08-26T23:22:16.5579801Z >>> 2025-08-26T23:22:16.5579846Z >>> @rpc.functions.async_execution 2025-08-26T23:22:16.5579897Z >>> def bound_async_add(self, to, x, y, z): 2025-08-26T23:22:16.5579959Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T23:22:16.5580004Z >>> lambda fut: fut.wait() + z 2025-08-26T23:22:16.5580037Z >>> ) 2025-08-26T23:22:16.5580085Z >>> 2025-08-26T23:22:16.5580121Z >>> # On worker0 2025-08-26T23:22:16.5580161Z >>> ret = rpc.rpc_sync( 2025-08-26T23:22:16.5580196Z >>> "worker1", 2025-08-26T23:22:16.5580250Z >>> AsyncExecutionClass.static_async_add, 2025-08-26T23:22:16.5580297Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T23:22:16.5580329Z >>> ) 2025-08-26T23:22:16.5580444Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:22:16.5580476Z >>> 2025-08-26T23:22:16.5580517Z >>> ret = rpc.rpc_sync( 2025-08-26T23:22:16.5580554Z >>> "worker1", 2025-08-26T23:22:16.5580606Z >>> AsyncExecutionClass.class_async_add, 2025-08-26T23:22:16.5581638Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T23:22:16.5581671Z >>> ) 2025-08-26T23:22:16.5581717Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:22:16.5581749Z 2025-08-26T23:22:16.5581812Z This decorator also works with RRef helpers, i.e., . 2025-08-26T23:22:16.5581870Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-08-26T23:22:16.5581933Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-08-26T23:22:16.5581988Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-08-26T23:22:16.5582019Z 2025-08-26T23:22:16.5582066Z >>> from torch.distributed import rpc 2025-08-26T23:22:16.5582096Z >>> 2025-08-26T23:22:16.5582150Z >>> # reuse the AsyncExecutionClass class above 2025-08-26T23:22:16.5582247Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:22:16.5582342Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-08-26T23:22:16.5582388Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:22:16.5582420Z >>> 2025-08-26T23:22:16.5582479Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:22:16.5582563Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-08-26T23:22:16.5582610Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:22:16.5582641Z >>> 2025-08-26T23:22:16.5582700Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T23:22:16.5583771Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-08-26T23:22:16.5583818Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T23:22:16.5583848Z 2025-08-26T23:22:16.5583942Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5583975Z 2025-08-26T23:22:16.5584014Z warnings.warn(msg) 2025-08-26T23:22:16.5584044Z 2025-08-26T23:22:16.5584121Z --- Parse Warning: 93 / 146 --- 2025-08-26T23:22:16.5584491Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-08-26T23:22:16.5584584Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5584615Z 2025-08-26T23:22:16.5584692Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-08-26T23:22:16.5584790Z except that it enables profiling on all threads running RPC server request callbacks. 2025-08-26T23:22:16.5584821Z 2025-08-26T23:22:16.5584919Z Context manager that manages autograd profiler state and holds a summary of results. 2025-08-26T23:22:16.5585035Z Under the hood it just records events of functions being executed in C++ and 2025-08-26T23:22:16.5585119Z exposes those events to Python. You can wrap any code into it and it will 2025-08-26T23:22:16.5585169Z only report runtime of PyTorch functions. 2025-08-26T23:22:16.5585263Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-08-26T23:22:16.5585294Z 2025-08-26T23:22:16.5585346Z Args: 2025-08-26T23:22:16.5585446Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-08-26T23:22:16.5586470Z Default: ``True``. 2025-08-26T23:22:16.5586502Z 2025-08-26T23:22:16.5586604Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-08-26T23:22:16.5586678Z Adds approximately 4us of overhead to each tensor operation. 2025-08-26T23:22:16.5586718Z Default: ``False`` 2025-08-26T23:22:16.5586749Z 2025-08-26T23:22:16.5586832Z record_shapes (bool, optional): If shapes recording is set, information 2025-08-26T23:22:16.5586915Z about input dimensions will be collected. This allows one to see which 2025-08-26T23:22:16.5586991Z dimensions have been used under the hood and further group by them 2025-08-26T23:22:16.5587069Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-08-26T23:22:16.5587151Z shape recording might skew your profiling data. It is recommended to 2025-08-26T23:22:16.5587235Z use separate runs with and without shape recording to validate the timing. 2025-08-26T23:22:16.5587318Z Most likely the skew will be negligible for bottom most events (in a case 2025-08-26T23:22:16.5587393Z of nested function calls). But for higher level functions the total 2025-08-26T23:22:16.5587466Z self cpu time might be artificially increased because of the shape 2025-08-26T23:22:16.5587526Z collection. 2025-08-26T23:22:16.5587573Z 2025-08-26T23:22:16.5587670Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-08-26T23:22:16.5587701Z 2025-08-26T23:22:16.5587736Z .. warning:: 2025-08-26T23:22:16.5587811Z Enabling memory profiling incurs additional profiler overhead 2025-08-26T23:22:16.5587841Z 2025-08-26T23:22:16.5588873Z .. warning:: 2025-08-26T23:22:16.5588979Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-08-26T23:22:16.5589054Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-08-26T23:22:16.5589140Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-08-26T23:22:16.5589204Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-08-26T23:22:16.5589234Z 2025-08-26T23:22:16.5589268Z Example: 2025-08-26T23:22:16.5589309Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5589349Z >>> # On worker 0: 2025-08-26T23:22:16.5589386Z >>> import torch 2025-08-26T23:22:16.5589436Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5589492Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:22:16.5589542Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-08-26T23:22:16.5589588Z >>> outer_profile_rref = rpc.remote( 2025-08-26T23:22:16.5589652Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T23:22:16.5589684Z ... ) 2025-08-26T23:22:16.5589736Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-08-26T23:22:16.5589795Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-08-26T23:22:16.5589841Z >>> inner_profile_rref = rpc.remote( 2025-08-26T23:22:16.5589904Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T23:22:16.5589935Z ... ) 2025-08-26T23:22:16.5591060Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-08-26T23:22:16.5591120Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-08-26T23:22:16.5591188Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T23:22:16.5591251Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T23:22:16.5591313Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-08-26T23:22:16.5591452Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5591567Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T23:22:16.5591654Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5591729Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-08-26T23:22:16.5591802Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-08-26T23:22:16.5591887Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5591931Z Self CPU time total: 89.667us 2025-08-26T23:22:16.5591993Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-08-26T23:22:16.5592076Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5592183Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T23:22:16.5592266Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5592331Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-08-26T23:22:16.5592421Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-08-26T23:22:16.5592515Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-08-26T23:22:16.5592600Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T23:22:16.5592644Z Self CPU time total: 213.926us 2025-08-26T23:22:16.5592687Z >>> rpc.shutdown() 2025-08-26T23:22:16.5593708Z 2025-08-26T23:22:16.5593745Z >>> # On worker 1: 2025-08-26T23:22:16.5593797Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5593853Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:22:16.5593917Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-08-26T23:22:16.5593954Z >>> rpc.shutdown() 2025-08-26T23:22:16.5593986Z 2025-08-26T23:22:16.5594077Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5594111Z 2025-08-26T23:22:16.5594149Z warnings.warn(msg) 2025-08-26T23:22:16.5594180Z 2025-08-26T23:22:16.5594253Z --- Parse Warning: 94 / 146 --- 2025-08-26T23:22:16.5594753Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-08-26T23:22:16.5594847Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5594878Z 2025-08-26T23:22:16.5595017Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-08-26T23:22:16.5595048Z 2025-08-26T23:22:16.5595138Z The sharing is done as described by `ZeRO `_. 2025-08-26T23:22:16.5595195Z 2025-08-26T23:22:16.5595256Z The local optimizer instance in each rank is only 2025-08-26T23:22:16.5595344Z responsible for updating approximately ``1 / world_size`` parameters and 2025-08-26T23:22:16.5596412Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-08-26T23:22:16.5596501Z parameters are updated locally, each rank will broadcast its parameters to 2025-08-26T23:22:16.5596570Z all other peers to keep all model replicas in the same state. 2025-08-26T23:22:16.5596666Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-08-26T23:22:16.5596761Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-08-26T23:22:16.5596799Z memory consumption. 2025-08-26T23:22:16.5596830Z 2025-08-26T23:22:16.5596921Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-08-26T23:22:16.5597004Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-08-26T23:22:16.5597093Z not divided among ranks. The partition is arbitrary and might not match the 2025-08-26T23:22:16.5597146Z the parameter registration or usage order. 2025-08-26T23:22:16.5597176Z 2025-08-26T23:22:16.5597211Z Arguments: 2025-08-26T23:22:16.5597283Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-08-26T23:22:16.5597353Z or :class:`dict` s giving all parameters, which will be sharded 2025-08-26T23:22:16.5597390Z across ranks. 2025-08-26T23:22:16.5597421Z 2025-08-26T23:22:16.5597456Z Keyword Args: 2025-08-26T23:22:16.5597538Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-08-26T23:22:16.5597573Z optimizer. 2025-08-26T23:22:16.5597651Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-08-26T23:22:16.5597722Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-08-26T23:22:16.5598758Z :meth:`torch.distributed.init_process_group`). 2025-08-26T23:22:16.5598875Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-08-26T23:22:16.5598953Z packed into buckets to speed up communication, and ``param.data`` 2025-08-26T23:22:16.5599025Z fields point to bucket views at different offsets; if ``False``, 2025-08-26T23:22:16.5599099Z each individual parameter is communicated separately, and each 2025-08-26T23:22:16.5599161Z ``params.data`` stays intact (default: ``False``). 2025-08-26T23:22:16.5599234Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-08-26T23:22:16.5599307Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-08-26T23:22:16.5599384Z synchronization; this requires (1) either a functional optimizer 2025-08-26T23:22:16.5599452Z for the ``optimizer_class`` argument or one with a functional 2025-08-26T23:22:16.5599517Z equivalent and (2) registering a DDP communication hook 2025-08-26T23:22:16.5599592Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-08-26T23:22:16.5599655Z parameters are packed into buckets matching those in 2025-08-26T23:22:16.5599717Z :class:`DistributedDataParallel`, meaning that the 2025-08-26T23:22:16.5599775Z ``parameters_as_bucket_view`` argument is ignored. 2025-08-26T23:22:16.5599845Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-08-26T23:22:16.5599884Z (per normal). 2025-08-26T23:22:16.5599927Z (default: ``False``) 2025-08-26T23:22:16.5600002Z **defaults: any trailing arguments, which are forwarded to the local 2025-08-26T23:22:16.5600039Z optimizer. 2025-08-26T23:22:16.5600069Z 2025-08-26T23:22:16.5601290Z Example:: 2025-08-26T23:22:16.5601322Z 2025-08-26T23:22:16.5601363Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5601405Z >>> import torch.nn as nn 2025-08-26T23:22:16.5601519Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-08-26T23:22:16.5601595Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T23:22:16.5601681Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-08-26T23:22:16.5601727Z >>> ddp = DDP(model, device_ids=[rank]) 2025-08-26T23:22:16.5601777Z >>> opt = ZeroRedundancyOptimizer( 2025-08-26T23:22:16.5601818Z >>> ddp.parameters(), 2025-08-26T23:22:16.5601889Z >>> optimizer_class=torch.optim.Adam, 2025-08-26T23:22:16.5601924Z >>> lr=0.01 2025-08-26T23:22:16.5601956Z >>> ) 2025-08-26T23:22:16.5602000Z >>> ddp(inputs).sum().backward() 2025-08-26T23:22:16.5602036Z >>> opt.step() 2025-08-26T23:22:16.5602067Z 2025-08-26T23:22:16.5602101Z .. warning:: 2025-08-26T23:22:16.5602179Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-08-26T23:22:16.5602239Z passed-in parameters are the same dense type. 2025-08-26T23:22:16.5602274Z 2025-08-26T23:22:16.5602308Z .. warning:: 2025-08-26T23:22:16.5602385Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-08-26T23:22:16.5603463Z the way that overlapping :class:`DistributedDataParallel` with 2025-08-26T23:22:16.5603549Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-08-26T23:22:16.5603628Z two or three training iterations do not perform parameter updates in 2025-08-26T23:22:16.5603700Z the optimizer step, depending on if ``static_graph=False`` or 2025-08-26T23:22:16.5603769Z ``static_graph=True``, respectively. This is because it needs 2025-08-26T23:22:16.5603839Z information about the gradient bucketing strategy used by 2025-08-26T23:22:16.5603918Z :class:`DistributedDataParallel`, which is not finalized until the 2025-08-26T23:22:16.5603991Z second forward pass if ``static_graph=False`` or until the third 2025-08-26T23:22:16.5604106Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-08-26T23:22:16.5604152Z is to prepend dummy inputs. 2025-08-26T23:22:16.5604182Z 2025-08-26T23:22:16.5604273Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-08-26T23:22:16.5604303Z 2025-08-26T23:22:16.5604394Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5604427Z 2025-08-26T23:22:16.5604466Z warnings.warn(msg) 2025-08-26T23:22:16.5604496Z 2025-08-26T23:22:16.5604570Z --- Parse Warning: 95 / 146 --- 2025-08-26T23:22:16.5604925Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-08-26T23:22:16.5605021Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5605054Z 2025-08-26T23:22:16.5606170Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-08-26T23:22:16.5606231Z This optimizer runs local optimizer at every step. 2025-08-26T23:22:16.5606350Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-08-26T23:22:16.5606380Z 2025-08-26T23:22:16.5606415Z Args: 2025-08-26T23:22:16.5606457Z optim: The local optimizer. 2025-08-26T23:22:16.5606537Z averager: A model averager instance to run post-localSGD algorithm. 2025-08-26T23:22:16.5606567Z 2025-08-26T23:22:16.5606602Z Example:: 2025-08-26T23:22:16.5606632Z 2025-08-26T23:22:16.5606684Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5606722Z >>> import torch 2025-08-26T23:22:16.5606768Z >>> import torch.distributed as dist 2025-08-26T23:22:16.5606894Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T23:22:16.5606935Z >>> import torch.nn as nn 2025-08-26T23:22:16.5607008Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-08-26T23:22:16.5607105Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T23:22:16.5607147Z >>> PostLocalSGDState, 2025-08-26T23:22:16.5607203Z >>> post_localSGD_hook, 2025-08-26T23:22:16.5607236Z >>> ) 2025-08-26T23:22:16.5607267Z >>> 2025-08-26T23:22:16.5607330Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:22:16.5608362Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:22:16.5608395Z >>> ) 2025-08-26T23:22:16.5608426Z >>> 2025-08-26T23:22:16.5608484Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:22:16.5608590Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T23:22:16.5608656Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:22:16.5608688Z >>> 2025-08-26T23:22:16.5608761Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-08-26T23:22:16.5608853Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-08-26T23:22:16.5608917Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:22:16.5608995Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-08-26T23:22:16.5609042Z >>> opt = PostLocalSGDOptimizer( 2025-08-26T23:22:16.5609085Z >>> optim=local_optim, 2025-08-26T23:22:16.5609175Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T23:22:16.5609207Z >>> ) 2025-08-26T23:22:16.5609237Z >>> 2025-08-26T23:22:16.5609319Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-08-26T23:22:16.5609461Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-08-26T23:22:16.5609592Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-08-26T23:22:16.5609634Z >>> for step in range(0, 200): 2025-08-26T23:22:16.5609675Z >>> opt.zero_grad() 2025-08-26T23:22:16.5609723Z >>> loss = loss_fn(output, labels) 2025-08-26T23:22:16.5610828Z >>> loss.backward() 2025-08-26T23:22:16.5610867Z >>> opt.step() 2025-08-26T23:22:16.5610898Z 2025-08-26T23:22:16.5610989Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5611020Z 2025-08-26T23:22:16.5611057Z warnings.warn(msg) 2025-08-26T23:22:16.5611089Z 2025-08-26T23:22:16.5611162Z --- Parse Warning: 96 / 146 --- 2025-08-26T23:22:16.5611496Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-08-26T23:22:16.5611590Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5611621Z 2025-08-26T23:22:16.5611706Z DistributedOptimizer takes remote references to parameters scattered 2025-08-26T23:22:16.5611793Z across workers and applies the given optimizer locally for each parameter. 2025-08-26T23:22:16.5611824Z 2025-08-26T23:22:16.5611909Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-08-26T23:22:16.5611969Z to retrieve the gradients for specific parameters. 2025-08-26T23:22:16.5612000Z 2025-08-26T23:22:16.5612037Z Concurrent calls to 2025-08-26T23:22:16.5612120Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-08-26T23:22:16.5612212Z either from the same or different clients, will 2025-08-26T23:22:16.5612297Z be serialized on each worker -- as each worker's optimizer can only work 2025-08-26T23:22:16.5613359Z on one set of gradients at a time. However, there is no guarantee that 2025-08-26T23:22:16.5613448Z the full forward-backward-optimizer sequence will execute for one client 2025-08-26T23:22:16.5613527Z at a time. This means that the gradients being applied may not correspond 2025-08-26T23:22:16.5613631Z to the latest forward pass executed on a given worker. Also, there is no 2025-08-26T23:22:16.5613677Z guaranteed ordering across workers. 2025-08-26T23:22:16.5613708Z 2025-08-26T23:22:16.5613812Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-08-26T23:22:16.5613892Z by default, so that optimizer updates are not blocked by the Python Global 2025-08-26T23:22:16.5613979Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-08-26T23:22:16.5614069Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-08-26T23:22:16.5614162Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-08-26T23:22:16.5614205Z for your own custom optimizers. 2025-08-26T23:22:16.5614237Z 2025-08-26T23:22:16.5614268Z Args: 2025-08-26T23:22:16.5614343Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-08-26T23:22:16.5614389Z instantiate on each worker. 2025-08-26T23:22:16.5614465Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-08-26T23:22:16.5614502Z to optimize. 2025-08-26T23:22:16.5614579Z args: arguments to pass to the optimizer constructor on each worker. 2025-08-26T23:22:16.5614658Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-08-26T23:22:16.5614689Z 2025-08-26T23:22:16.5614724Z Example:: 2025-08-26T23:22:16.5615745Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5615858Z >>> import torch.distributed.autograd as dist_autograd 2025-08-26T23:22:16.5615908Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5615949Z >>> from torch import optim 2025-08-26T23:22:16.5616020Z >>> from torch.distributed.optim import DistributedOptimizer 2025-08-26T23:22:16.5616052Z >>> 2025-08-26T23:22:16.5616106Z >>> with dist_autograd.context() as context_id: 2025-08-26T23:22:16.5616149Z >>> # Forward pass. 2025-08-26T23:22:16.5616222Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-08-26T23:22:16.5616292Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-08-26T23:22:16.5616342Z >>> loss = rref1.to_here() + rref2.to_here() 2025-08-26T23:22:16.5616374Z >>> 2025-08-26T23:22:16.5616413Z >>> # Backward pass. 2025-08-26T23:22:16.5616471Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-08-26T23:22:16.5616504Z >>> 2025-08-26T23:22:16.5616543Z >>> # Optimizer. 2025-08-26T23:22:16.5616592Z >>> dist_optim = DistributedOptimizer( 2025-08-26T23:22:16.5616631Z >>> optim.SGD, 2025-08-26T23:22:16.5616670Z >>> [rref1, rref2], 2025-08-26T23:22:16.5616705Z >>> lr=0.05, 2025-08-26T23:22:16.5616737Z >>> ) 2025-08-26T23:22:16.5617750Z >>> dist_optim.step(context_id) 2025-08-26T23:22:16.5617782Z 2025-08-26T23:22:16.5617843Z __ https://github.com/pytorch/tutorials/pull/1465 2025-08-26T23:22:16.5617875Z 2025-08-26T23:22:16.5617966Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5617997Z 2025-08-26T23:22:16.5618034Z warnings.warn(msg) 2025-08-26T23:22:16.5618065Z 2025-08-26T23:22:16.5618136Z --- Parse Warning: 97 / 146 --- 2025-08-26T23:22:16.5618492Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-08-26T23:22:16.5618612Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5618643Z 2025-08-26T23:22:16.5618748Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-08-26T23:22:16.5618850Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-08-26T23:22:16.5618881Z 2025-08-26T23:22:16.5618944Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-08-26T23:22:16.5618974Z 2025-08-26T23:22:16.5619010Z .. warning:: 2025-08-26T23:22:16.5619076Z Current implementation only supports loading Tensors. 2025-08-26T23:22:16.5619107Z 2025-08-26T23:22:16.5619152Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5619192Z >>> sd = {"mode": model} 2025-08-26T23:22:16.5620203Z >>> dcp.load( 2025-08-26T23:22:16.5620239Z >>> sd, 2025-08-26T23:22:16.5620300Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T23:22:16.5620349Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T23:22:16.5620482Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T23:22:16.5620514Z >>> ) 2025-08-26T23:22:16.5620546Z 2025-08-26T23:22:16.5620638Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5620669Z 2025-08-26T23:22:16.5620706Z warnings.warn(msg) 2025-08-26T23:22:16.5620737Z 2025-08-26T23:22:16.5620808Z --- Parse Warning: 98 / 146 --- 2025-08-26T23:22:16.5621150Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-08-26T23:22:16.5621290Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5621322Z 2025-08-26T23:22:16.5621448Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-08-26T23:22:16.5621564Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-08-26T23:22:16.5621608Z metadata file, like Torch Save files. 2025-08-26T23:22:16.5621639Z 2025-08-26T23:22:16.5621708Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-08-26T23:22:16.5621739Z 2025-08-26T23:22:16.5621772Z .. warning:: 2025-08-26T23:22:16.5622831Z Current implementation only supports loading Tensors. 2025-08-26T23:22:16.5622861Z 2025-08-26T23:22:16.5622907Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5622946Z >>> sd = {"mode": model} 2025-08-26T23:22:16.5622980Z >>> dcp.load( 2025-08-26T23:22:16.5623014Z >>> sd, 2025-08-26T23:22:16.5623076Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T23:22:16.5623125Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T23:22:16.5623169Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T23:22:16.5623201Z >>> ) 2025-08-26T23:22:16.5623231Z 2025-08-26T23:22:16.5623321Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5623351Z 2025-08-26T23:22:16.5623389Z warnings.warn(msg) 2025-08-26T23:22:16.5623420Z 2025-08-26T23:22:16.5623491Z --- Parse Warning: 99 / 146 --- 2025-08-26T23:22:16.5623806Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97. 2025-08-26T23:22:16.5623900Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5623955Z 2025-08-26T23:22:16.5624003Z Save a distributed model in SPMD style. 2025-08-26T23:22:16.5624033Z 2025-08-26T23:22:16.5625065Z This function is different from ``torch.save()`` as it handles 2025-08-26T23:22:16.5625160Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-08-26T23:22:16.5625191Z 2025-08-26T23:22:16.5625285Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T23:22:16.5625371Z save will call ``state_dict`` before serialization. 2025-08-26T23:22:16.5625401Z 2025-08-26T23:22:16.5625436Z .. warning:: 2025-08-26T23:22:16.5625519Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-08-26T23:22:16.5625559Z for saved state_dicts. 2025-08-26T23:22:16.5625592Z 2025-08-26T23:22:16.5625625Z .. warning:: 2025-08-26T23:22:16.5625702Z If using the `process_group` argument, make sure that only its ranks 2025-08-26T23:22:16.5625781Z call `save_state_dict` and that all data in state_dict belong to it. 2025-08-26T23:22:16.5625812Z 2025-08-26T23:22:16.5625844Z .. note:: 2025-08-26T23:22:16.5625938Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-08-26T23:22:16.5626030Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-08-26T23:22:16.5626075Z group needs to be passed in. 2025-08-26T23:22:16.5626105Z 2025-08-26T23:22:16.5626139Z .. note:: 2025-08-26T23:22:16.5626234Z If no process group is available, this function assumes the intention is to save the 2025-08-26T23:22:16.5626279Z state_dict in the local process. 2025-08-26T23:22:16.5627266Z 2025-08-26T23:22:16.5627300Z .. note: 2025-08-26T23:22:16.5627356Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T23:22:16.5627388Z 2025-08-26T23:22:16.5627417Z 2025-08-26T23:22:16.5627450Z Args: 2025-08-26T23:22:16.5627532Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T23:22:16.5627602Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:22:16.5627681Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:22:16.5627755Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:22:16.5627821Z It can also be a key if the storage is a key-value store. 2025-08-26T23:22:16.5627863Z (Default: ``None``) 2025-08-26T23:22:16.5627914Z storage_writer (Optional[StorageWriter]): 2025-08-26T23:22:16.5627988Z Instance of StorageWriter used to perform writes. If this is not 2025-08-26T23:22:16.5628062Z specified, DCP will automatically infer the writer based on the 2025-08-26T23:22:16.5628134Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:22:16.5628179Z be raised. (Default: ``None``) 2025-08-26T23:22:16.5628226Z planner (Optional[SavePlanner]): 2025-08-26T23:22:16.5628299Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T23:22:16.5628349Z planner will be used. (Default: ``None``) 2025-08-26T23:22:16.5628399Z process_group (Optional[ProcessGroup]): 2025-08-26T23:22:16.5628467Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:22:16.5629469Z (Default: ``None``) 2025-08-26T23:22:16.5629507Z no_dist (bool): 2025-08-26T23:22:16.5629572Z If ``True``, this function will assume the intent is to load 2025-08-26T23:22:16.5629621Z a checkpoint on a single rank/process. 2025-08-26T23:22:16.5629662Z (Default: ``False``) 2025-08-26T23:22:16.5629755Z use_collectives (bool): If ``False``, this function will assume the intent is to save 2025-08-26T23:22:16.5629822Z a checkpoint without using cross-rank synchronization. 2025-08-26T23:22:16.5629880Z (Default: ``True``) 2025-08-26T23:22:16.5629963Z This configuration is experimental and should be used with caution. 2025-08-26T23:22:16.5630060Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T23:22:16.5630092Z 2025-08-26T23:22:16.5630124Z Returns: 2025-08-26T23:22:16.5630186Z Metadata: Metadata object for the saved checkpoint. 2025-08-26T23:22:16.5630218Z 2025-08-26T23:22:16.5630251Z Example: 2025-08-26T23:22:16.5630309Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5630427Z >>> my_model = MyModule() 2025-08-26T23:22:16.5630459Z 2025-08-26T23:22:16.5630505Z >>> state_dict = {"model": my_model} 2025-08-26T23:22:16.5630536Z 2025-08-26T23:22:16.5630622Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T23:22:16.5631634Z ... "/checkpoint/1" 2025-08-26T23:22:16.5631666Z ... ) 2025-08-26T23:22:16.5631722Z >>> torch.distributed.checkpoint.save( 2025-08-26T23:22:16.5631766Z >>> state_dict=state_dict, 2025-08-26T23:22:16.5631815Z >>> storage_writer=fs_storage_writer, 2025-08-26T23:22:16.5631846Z >>> ) 2025-08-26T23:22:16.5631877Z 2025-08-26T23:22:16.5631909Z .. note:: 2025-08-26T23:22:16.5631988Z save_state_dict uses collectives to coordinate writes across ranks. 2025-08-26T23:22:16.5632066Z For NCCL-based process groups, internal tensor representations of 2025-08-26T23:22:16.5632151Z objects must be moved to the GPU device before communication takes place. 2025-08-26T23:22:16.5632231Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T23:22:16.5632304Z and it is the user's responsibility to ensure that this is set so that 2025-08-26T23:22:16.5632376Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T23:22:16.5632406Z 2025-08-26T23:22:16.5632496Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5632577Z 2025-08-26T23:22:16.5632616Z warnings.warn(msg) 2025-08-26T23:22:16.5632646Z 2025-08-26T23:22:16.5632721Z --- Parse Warning: 100 / 146 --- 2025-08-26T23:22:16.5633050Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230. 2025-08-26T23:22:16.5633143Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5634203Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-08-26T23:22:16.5634309Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-08-26T23:22:16.5634340Z 2025-08-26T23:22:16.5634376Z .. warning:: 2025-08-26T23:22:16.5634671Z This feature is experimental and subject to change. 2025-08-26T23:22:16.5634734Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-08-26T23:22:16.5634764Z 2025-08-26T23:22:16.5634796Z Args: 2025-08-26T23:22:16.5634857Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T23:22:16.5634914Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:22:16.5634990Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:22:16.5635065Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:22:16.5635128Z It can also be a key if the storage is a key-value store. 2025-08-26T23:22:16.5635169Z (Default: ``None``) 2025-08-26T23:22:16.5635221Z storage_writer (Optional[StorageWriter]): 2025-08-26T23:22:16.5635297Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-08-26T23:22:16.5635428Z this is not specified, DCP will automatically infer the writer based on the 2025-08-26T23:22:16.5635504Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:22:16.5635549Z be raised. (Default: ``None``) 2025-08-26T23:22:16.5635596Z planner (Optional[SavePlanner]): 2025-08-26T23:22:16.5635666Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T23:22:16.5636729Z planner will be used. (Default: ``None``) 2025-08-26T23:22:16.5636782Z process_group (Optional[ProcessGroup]): 2025-08-26T23:22:16.5636851Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:22:16.5636891Z (Default: ``None``) 2025-08-26T23:22:16.5636954Z async_checkpointer_type (AsyncCheckpointerType): 2025-08-26T23:22:16.5637020Z whether to do checkpoint in separate thread or process 2025-08-26T23:22:16.5637082Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-08-26T23:22:16.5637126Z async_stager (AsyncStager): 2025-08-26T23:22:16.5637218Z provides staging implementation. If storage_writer implements AsyncStager 2025-08-26T23:22:16.5637296Z and async_stager is provided, async_stager will be used for staging 2025-08-26T23:22:16.5637334Z no_dist (bool): 2025-08-26T23:22:16.5637398Z If ``True``, this function will assume the intent is to save 2025-08-26T23:22:16.5637450Z a checkpoint on a single rank/process. 2025-08-26T23:22:16.5637492Z (Default: ``False``) 2025-08-26T23:22:16.5637600Z use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``) 2025-08-26T23:22:16.5637681Z This configuration is experimental and should be used with caution. 2025-08-26T23:22:16.5637776Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T23:22:16.5637824Z 2025-08-26T23:22:16.5637875Z Returns: 2025-08-26T23:22:16.5637953Z Future: A future holding the resultant Metadata object from `save`. 2025-08-26T23:22:16.5637983Z 2025-08-26T23:22:16.5638017Z Example: 2025-08-26T23:22:16.5639024Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5639067Z >>> my_model = MyModule() 2025-08-26T23:22:16.5639097Z 2025-08-26T23:22:16.5639145Z >>> state_dict = {"model": my_model} 2025-08-26T23:22:16.5639175Z 2025-08-26T23:22:16.5639263Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T23:22:16.5639302Z ... "/checkpoint/1" 2025-08-26T23:22:16.5639335Z ... ) 2025-08-26T23:22:16.5639411Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-08-26T23:22:16.5639454Z >>> state_dict=state_dict, 2025-08-26T23:22:16.5639504Z >>> storage_writer=fs_storage_writer, 2025-08-26T23:22:16.5639538Z >>> ) 2025-08-26T23:22:16.5639572Z >>> 2025-08-26T23:22:16.5639612Z >>> # ... do some work ... 2025-08-26T23:22:16.5639644Z >>> 2025-08-26T23:22:16.5639688Z >>> checkpoint_future.result() 2025-08-26T23:22:16.5639719Z 2025-08-26T23:22:16.5639749Z 2025-08-26T23:22:16.5639840Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5639870Z 2025-08-26T23:22:16.5639909Z warnings.warn(msg) 2025-08-26T23:22:16.5639939Z 2025-08-26T23:22:16.5641041Z --- Parse Warning: 101 / 146 --- 2025-08-26T23:22:16.5641364Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-08-26T23:22:16.5641457Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5641527Z 2025-08-26T23:22:16.5641630Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-08-26T23:22:16.5641660Z 2025-08-26T23:22:16.5641765Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-08-26T23:22:16.5641795Z 2025-08-26T23:22:16.5641893Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T23:22:16.5641983Z will be visible to the whole process. 2025-08-26T23:22:16.5642014Z 2025-08-26T23:22:16.5642111Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-08-26T23:22:16.5642141Z 2025-08-26T23:22:16.5642189Z 1) set_up_planner - called on all ranks. 2025-08-26T23:22:16.5642238Z Signals the start of a checkpoint save. 2025-08-26T23:22:16.5642268Z 2025-08-26T23:22:16.5642316Z 2) create_local_plan - called on all ranks. 2025-08-26T23:22:16.5642423Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-08-26T23:22:16.5642454Z 2025-08-26T23:22:16.5642523Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T23:22:16.5642596Z Takes the SavePlan from all ranks and make any global decision. 2025-08-26T23:22:16.5643599Z 2025-08-26T23:22:16.5643645Z 4) finish_plan - called on all ranks. 2025-08-26T23:22:16.5643727Z This gives each rank a chance to adjust to global planning decisions. 2025-08-26T23:22:16.5643757Z 2025-08-26T23:22:16.5643817Z 5) resolve_data - called multiple times on each rank 2025-08-26T23:22:16.5643891Z Lookups a value on the `state_dict` for the storage layer to write. 2025-08-26T23:22:16.5643921Z 2025-08-26T23:22:16.5644028Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-08-26T23:22:16.5644098Z most changes can be expressed by changes in a single method. 2025-08-26T23:22:16.5644172Z 2025-08-26T23:22:16.5644242Z There are 3 usual patterns of extension: 2025-08-26T23:22:16.5644273Z 2025-08-26T23:22:16.5644364Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-08-26T23:22:16.5644446Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-08-26T23:22:16.5644476Z 2025-08-26T23:22:16.5644522Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5644574Z >>> class RenamePlanner(DefaultSavePlanner): 2025-08-26T23:22:16.5644615Z >>> def set_up_planner( 2025-08-26T23:22:16.5644649Z >>> self, 2025-08-26T23:22:16.5644693Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T23:22:16.5644744Z >>> storage_meta: Optional[StorageMeta], 2025-08-26T23:22:16.5644787Z >>> is_coordinator: bool, 2025-08-26T23:22:16.5645785Z >>> ) -> None: 2025-08-26T23:22:16.5645831Z >>> # prefix all keys with `foo_`` 2025-08-26T23:22:16.5645941Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-08-26T23:22:16.5645974Z 2025-08-26T23:22:16.5646090Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-08-26T23:22:16.5646121Z 2025-08-26T23:22:16.5646165Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5646216Z >>> class FP16Planner(DefaultSavePlanner): 2025-08-26T23:22:16.5646260Z >>> def create_local_plan(self): 2025-08-26T23:22:16.5646309Z >>> plan = super().create_local_plan() 2025-08-26T23:22:16.5646348Z >>> for p in plan: 2025-08-26T23:22:16.5646395Z >>> if p.tensor_data is not None: 2025-08-26T23:22:16.5646457Z >>> p.tensor_data.properties.dtype = torch.float16 2025-08-26T23:22:16.5646494Z >>> return plan 2025-08-26T23:22:16.5646527Z >>> 2025-08-26T23:22:16.5646572Z >>> def resolve_data(self, write_item): 2025-08-26T23:22:16.5646648Z >>> item = super().resolve_data(write_item) 2025-08-26T23:22:16.5646747Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-08-26T23:22:16.5646778Z 2025-08-26T23:22:16.5646896Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-08-26T23:22:16.5646927Z 2025-08-26T23:22:16.5646972Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5647995Z >>> from itertools import zip_longest 2025-08-26T23:22:16.5648039Z >>> from dataclasses import replace 2025-08-26T23:22:16.5648106Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-08-26T23:22:16.5648205Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-08-26T23:22:16.5648257Z >>> # This sample doesn't handle ShardedTensors 2025-08-26T23:22:16.5648308Z >>> def create_global_plan(self, all_plans): 2025-08-26T23:22:16.5648373Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-08-26T23:22:16.5648413Z >>> items_per_rank = [ 2025-08-26T23:22:16.5648467Z >>> [item for item in items if item is not None] 2025-08-26T23:22:16.5648526Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-08-26T23:22:16.5648559Z >>> ] 2025-08-26T23:22:16.5648598Z >>> all_plans = [ 2025-08-26T23:22:16.5648646Z >>> replace(plan, items=items) 2025-08-26T23:22:16.5648716Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-08-26T23:22:16.5648748Z >>> ] 2025-08-26T23:22:16.5648803Z >>> return super().create_global_plan(all_plans) 2025-08-26T23:22:16.5648833Z 2025-08-26T23:22:16.5648928Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-08-26T23:22:16.5649024Z accomplished by having each rank contribute their data items in the local plan and 2025-08-26T23:22:16.5649098Z the global planner aggregate them: 2025-08-26T23:22:16.5649129Z 2025-08-26T23:22:16.5650139Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5650201Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-08-26T23:22:16.5650254Z >>> def create_local_plan(self) -> SavePlan: 2025-08-26T23:22:16.5650301Z >>> plan = super().create_local_plan() 2025-08-26T23:22:16.5650434Z >>> return replace(plan, planner_data="per-rank-data") 2025-08-26T23:22:16.5650466Z >>> 2025-08-26T23:22:16.5650575Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-08-26T23:22:16.5650647Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-08-26T23:22:16.5650709Z >>> merged_data = [p.planner_data for p in global_plan] 2025-08-26T23:22:16.5650773Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-08-26T23:22:16.5650820Z >>> return global_plan, metadata 2025-08-26T23:22:16.5650851Z 2025-08-26T23:22:16.5650941Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5650972Z 2025-08-26T23:22:16.5651010Z warnings.warn(msg) 2025-08-26T23:22:16.5651040Z 2025-08-26T23:22:16.5651115Z --- Parse Warning: 102 / 146 --- 2025-08-26T23:22:16.5651438Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-08-26T23:22:16.5651532Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5651563Z 2025-08-26T23:22:16.5651664Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-08-26T23:22:16.5651694Z 2025-08-26T23:22:16.5652806Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-08-26T23:22:16.5652839Z 2025-08-26T23:22:16.5652939Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T23:22:16.5652985Z will be visible to the whole process. 2025-08-26T23:22:16.5653015Z 2025-08-26T23:22:16.5653112Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-08-26T23:22:16.5653142Z 2025-08-26T23:22:16.5653213Z 1) set_up_planner - called on all ranks. 2025-08-26T23:22:16.5653264Z Signals the start of loading a checkpoint. 2025-08-26T23:22:16.5653295Z 2025-08-26T23:22:16.5653344Z 2) create_local_plan - called on all ranks. 2025-08-26T23:22:16.5653446Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-08-26T23:22:16.5653476Z 2025-08-26T23:22:16.5653544Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T23:22:16.5653620Z Takes the LoadPlan from all ranks and make any global decision. 2025-08-26T23:22:16.5653652Z 2025-08-26T23:22:16.5653709Z 4) load_bytes - called multiple times on each rank 2025-08-26T23:22:16.5653774Z This is called once per non-tensor value in state_dict. 2025-08-26T23:22:16.5653804Z 2025-08-26T23:22:16.5653885Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-08-26T23:22:16.5653955Z They are called in pair for each Tensor value in state_dict. 2025-08-26T23:22:16.5654949Z 2025-08-26T23:22:16.5655055Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-08-26T23:22:16.5655124Z most changes can be expressed by changes in a single method. 2025-08-26T23:22:16.5655154Z 2025-08-26T23:22:16.5655204Z There are two usual patterns of extension: 2025-08-26T23:22:16.5655234Z 2025-08-26T23:22:16.5655327Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-08-26T23:22:16.5655460Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-08-26T23:22:16.5655543Z to keep a reference to the original state_dict as load happens in place so 2025-08-26T23:22:16.5655594Z we need to be able to perform it in place 2025-08-26T23:22:16.5655625Z 2025-08-26T23:22:16.5655670Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5655720Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-08-26T23:22:16.5655763Z >>> def set_up_planner( 2025-08-26T23:22:16.5655797Z >>> self, 2025-08-26T23:22:16.5655841Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T23:22:16.5655881Z >>> metadata: Metadata, 2025-08-26T23:22:16.5655924Z >>> is_coordinator: bool, 2025-08-26T23:22:16.5655959Z >>> ) -> None: 2025-08-26T23:22:16.5656011Z >>> self.original_state_dict = state_dict 2025-08-26T23:22:16.5656076Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-08-26T23:22:16.5656111Z >>> 2025-08-26T23:22:16.5657117Z >>> if self.flatten_sharded_tensors: 2025-08-26T23:22:16.5657179Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-08-26T23:22:16.5657210Z >>> 2025-08-26T23:22:16.5657254Z >>> if self.flatten_state_dict: 2025-08-26T23:22:16.5657321Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-08-26T23:22:16.5657353Z >>> 2025-08-26T23:22:16.5657396Z >>> self.state_dict = state_dict 2025-08-26T23:22:16.5657438Z >>> self.metadata = metadata 2025-08-26T23:22:16.5657487Z >>> self.is_coordinator = is_coordinator 2025-08-26T23:22:16.5657518Z >>> 2025-08-26T23:22:16.5657566Z >>> def load_bytes(self, read_item, value): 2025-08-26T23:22:16.5657608Z >>> # Remove the "foo_" prefix 2025-08-26T23:22:16.5657722Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-08-26T23:22:16.5657785Z 2025-08-26T23:22:16.5657817Z 2025-08-26T23:22:16.5657909Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-08-26T23:22:16.5657940Z 2025-08-26T23:22:16.5657984Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T23:22:16.5658044Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-08-26T23:22:16.5658090Z >>> def resolve_tensor(self, read_item): 2025-08-26T23:22:16.5658160Z >>> tensor = super().resolve_tensor(read_item) 2025-08-26T23:22:16.5658218Z >>> return torch.empty_like(tensor, device="cpu") 2025-08-26T23:22:16.5659207Z >>> 2025-08-26T23:22:16.5659259Z >>> def commit_tensor(self, read_item, tensor): 2025-08-26T23:22:16.5659322Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-08-26T23:22:16.5659352Z 2025-08-26T23:22:16.5659443Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5659476Z 2025-08-26T23:22:16.5659517Z warnings.warn(msg) 2025-08-26T23:22:16.5659547Z 2025-08-26T23:22:16.5659621Z --- Parse Warning: 103 / 146 --- 2025-08-26T23:22:16.5659944Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-08-26T23:22:16.5660038Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5660069Z 2025-08-26T23:22:16.5660131Z Return the model state_dict and optimizers state_dict. 2025-08-26T23:22:16.5660162Z 2025-08-26T23:22:16.5660241Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-08-26T23:22:16.5660334Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-08-26T23:22:16.5660476Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-08-26T23:22:16.5660599Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-08-26T23:22:16.5660676Z with a different number of trainers and/or different parallelisms. 2025-08-26T23:22:16.5660766Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-08-26T23:22:16.5660800Z these APIs. 2025-08-26T23:22:16.5661824Z 3.) sanity checking the result state_dict. 2025-08-26T23:22:16.5661855Z 2025-08-26T23:22:16.5661934Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-08-26T23:22:16.5662017Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-08-26T23:22:16.5662102Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-08-26T23:22:16.5662176Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-08-26T23:22:16.5662254Z ``module.named_buffers()`` when the module is not distributed by any 2025-08-26T23:22:16.5662347Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-08-26T23:22:16.5662424Z a parameter, there will be a conversion from the parameter IDs to the 2025-08-26T23:22:16.5662470Z canonical FQNs when calling this API. 2025-08-26T23:22:16.5662502Z 2025-08-26T23:22:16.5662579Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-08-26T23:22:16.5662660Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-08-26T23:22:16.5662715Z optimizer parameter IDs to the canonical FQNs. 2025-08-26T23:22:16.5662746Z 2025-08-26T23:22:16.5662779Z Example: 2025-08-26T23:22:16.5662820Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5662856Z >>> import torch 2025-08-26T23:22:16.5662942Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:22:16.5663018Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T23:22:16.5663135Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-08-26T23:22:16.5663166Z 2025-08-26T23:22:16.5664177Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-08-26T23:22:16.5664249Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T23:22:16.5664298Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-08-26T23:22:16.5664365Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T23:22:16.5664420Z 2025-08-26T23:22:16.5664452Z 2025-08-26T23:22:16.5664537Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-08-26T23:22:16.5664602Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-08-26T23:22:16.5664644Z ... fsdp_model, fsdp_optim 2025-08-26T23:22:16.5664677Z ... ) 2025-08-26T23:22:16.5664707Z 2025-08-26T23:22:16.5664785Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-08-26T23:22:16.5664830Z >>> # the asserts will fail. 2025-08-26T23:22:16.5664882Z >>> assert ddp_state_dict == fsdp_state_dict 2025-08-26T23:22:16.5664940Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-08-26T23:22:16.5664971Z 2025-08-26T23:22:16.5665001Z 2025-08-26T23:22:16.5665034Z Args: 2025-08-26T23:22:16.5665090Z model (nn.Module): the nn.Module to the model. 2025-08-26T23:22:16.5665162Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-08-26T23:22:16.5665224Z The optimizers that are used to optimize ``model``. 2025-08-26T23:22:16.5666285Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-08-26T23:22:16.5666331Z that belong to the submodules. 2025-08-26T23:22:16.5666398Z options (StateDictOptions): the options to control how 2025-08-26T23:22:16.5666472Z model state_dict and optimizer state_dict should be returned. See 2025-08-26T23:22:16.5666557Z `StateDictOptions` for the details. 2025-08-26T23:22:16.5666589Z 2025-08-26T23:22:16.5666622Z Returns: 2025-08-26T23:22:16.5666695Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-08-26T23:22:16.5666725Z 2025-08-26T23:22:16.5666808Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-08-26T23:22:16.5666839Z 2025-08-26T23:22:16.5666930Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5666960Z 2025-08-26T23:22:16.5666998Z warnings.warn(msg) 2025-08-26T23:22:16.5667028Z 2025-08-26T23:22:16.5667101Z --- Parse Warning: 104 / 146 --- 2025-08-26T23:22:16.5667423Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69. 2025-08-26T23:22:16.5667517Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5667548Z 2025-08-26T23:22:16.5667622Z Load a checkpoint into a distributed state dict in SPMD style. 2025-08-26T23:22:16.5667652Z 2025-08-26T23:22:16.5667732Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-08-26T23:22:16.5668776Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-08-26T23:22:16.5668857Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-08-26T23:22:16.5668890Z costs). 2025-08-26T23:22:16.5668921Z 2025-08-26T23:22:16.5668989Z Each rank will try to read the least amount of data necessary 2025-08-26T23:22:16.5669072Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-08-26T23:22:16.5669160Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-08-26T23:22:16.5669213Z 2025-08-26T23:22:16.5669309Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T23:22:16.5669401Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-08-26T23:22:16.5669468Z ``load_state_dict`` once the deserialization is complete. 2025-08-26T23:22:16.5669560Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-08-26T23:22:16.5669635Z it in the ``state_dict`` with the deserialized object. 2025-08-26T23:22:16.5669666Z 2025-08-26T23:22:16.5669702Z .. warning:: 2025-08-26T23:22:16.5669765Z All tensors in ``state_dict`` must be allocated on their 2025-08-26T23:22:16.5669829Z destination device *prior to* calling this function. 2025-08-26T23:22:16.5669859Z 2025-08-26T23:22:16.5669942Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-08-26T23:22:16.5669978Z on state_dict. 2025-08-26T23:22:16.5670010Z 2025-08-26T23:22:16.5670043Z .. warning:: 2025-08-26T23:22:16.5671150Z Users must call `load_state_dict` on the root module to ensure load 2025-08-26T23:22:16.5671221Z pos-processing and non-tensor data properly propagates. 2025-08-26T23:22:16.5671252Z 2025-08-26T23:22:16.5671284Z .. note: 2025-08-26T23:22:16.5671365Z If no process group is initialized, this function will assume the intent 2025-08-26T23:22:16.5671448Z is to load a checkpoint into the local process. This can be useful in the 2025-08-26T23:22:16.5671537Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-08-26T23:22:16.5671576Z or ShardedTensor) 2025-08-26T23:22:16.5671607Z 2025-08-26T23:22:16.5671640Z .. note: 2025-08-26T23:22:16.5671694Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T23:22:16.5671726Z 2025-08-26T23:22:16.5671758Z Args: 2025-08-26T23:22:16.5671835Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-08-26T23:22:16.5671949Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T23:22:16.5672025Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T23:22:16.5672098Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T23:22:16.5672162Z It can also be a key if the storage is a key-value store. 2025-08-26T23:22:16.5672202Z (Default: ``None``) 2025-08-26T23:22:16.5672253Z storage_reader (Optional[StorageReader]): 2025-08-26T23:22:16.5672326Z Instance of StorageWriter used to perform reads. If this is not 2025-08-26T23:22:16.5673365Z specified, DCP will automatically infer the reader based on the 2025-08-26T23:22:16.5673437Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T23:22:16.5673482Z be raised. (Default: ``None``) 2025-08-26T23:22:16.5673528Z planner (Optional[LoadPlanner]): 2025-08-26T23:22:16.5673604Z Instance of LoadPlanner. If this is not specified, the default 2025-08-26T23:22:16.5673655Z planner will be used. (Default: ``None``) 2025-08-26T23:22:16.5673705Z process_group (Optional[ProcessGroup]): 2025-08-26T23:22:16.5673773Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T23:22:16.5673812Z (Default: ``None``) 2025-08-26T23:22:16.5673891Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-08-26T23:22:16.5673982Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-08-26T23:22:16.5674015Z Returns: 2025-08-26T23:22:16.5674047Z None. 2025-08-26T23:22:16.5674078Z 2025-08-26T23:22:16.5674111Z Examples 2025-08-26T23:22:16.5674152Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5674192Z >>> my_model = MyModule() 2025-08-26T23:22:16.5674246Z >>> optimizer = Adagrad(my_model.parameters()) 2025-08-26T23:22:16.5674323Z >>> model_state_dict = my_model.state_dict() 2025-08-26T23:22:16.5674412Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-08-26T23:22:16.5674523Z ... "/checkpoint/1" 2025-08-26T23:22:16.5674556Z ... ) 2025-08-26T23:22:16.5675551Z 2025-08-26T23:22:16.5675616Z >>> torch.distributed.checkpoint.load_state_dict( 2025-08-26T23:22:16.5675661Z >>> state_dict=model_state_dict, 2025-08-26T23:22:16.5675732Z >>> storage_reader=fs_storage_reader, 2025-08-26T23:22:16.5675764Z >>> ) 2025-08-26T23:22:16.5675795Z 2025-08-26T23:22:16.5675866Z >>> # module.load_state_dict() function might have customized steps 2025-08-26T23:22:16.5675916Z >>> # to flush the state_dict, must call it to 2025-08-26T23:22:16.5675959Z >>> # ensure correct behavior. 2025-08-26T23:22:16.5676010Z >>> my_model.load_state_dict(model_state_dict) 2025-08-26T23:22:16.5676043Z 2025-08-26T23:22:16.5676077Z .. note:: 2025-08-26T23:22:16.5676155Z load_state_dict uses collectives to coordinate reads across ranks. 2025-08-26T23:22:16.5676231Z For NCCL-based process groups, internal tensor representations of 2025-08-26T23:22:16.5676314Z objects must be moved to the GPU device before communication takes place. 2025-08-26T23:22:16.5676394Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T23:22:16.5676478Z and it is the user's responsibility to ensure that this is set so that each 2025-08-26T23:22:16.5676545Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T23:22:16.5676578Z 2025-08-26T23:22:16.5676666Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5676698Z 2025-08-26T23:22:16.5676735Z warnings.warn(msg) 2025-08-26T23:22:16.5677729Z 2025-08-26T23:22:16.5677806Z --- Parse Warning: 105 / 146 --- 2025-08-26T23:22:16.5678176Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-08-26T23:22:16.5678289Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5678320Z 2025-08-26T23:22:16.5678398Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-08-26T23:22:16.5678429Z 2025-08-26T23:22:16.5678491Z This is the current recommended way to checkpoint FSDP. 2025-08-26T23:22:16.5678531Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5678589Z >>> import torch.distributed.checkpoint as dist_cp 2025-08-26T23:22:16.5678623Z >>> # Save 2025-08-26T23:22:16.5678664Z >>> model: torch.nn.Model 2025-08-26T23:22:16.5678711Z >>> optim_params = model.parameters() 2025-08-26T23:22:16.5678766Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-08-26T23:22:16.5678801Z >>> # Save 2025-08-26T23:22:16.5678880Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-08-26T23:22:16.5678918Z >>> state_dict = { 2025-08-26T23:22:16.5678980Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-08-26T23:22:16.5679025Z >>> "model": model.state_dict() 2025-08-26T23:22:16.5679056Z >>> } 2025-08-26T23:22:16.5679098Z >>> dist_cp.save_state_dict( 2025-08-26T23:22:16.5680104Z >>> state_dict=optim_state, 2025-08-26T23:22:16.5680173Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-08-26T23:22:16.5680226Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-08-26T23:22:16.5680257Z >>> ) 2025-08-26T23:22:16.5680289Z >>> 2025-08-26T23:22:16.5680321Z >>> # Load 2025-08-26T23:22:16.5680476Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-08-26T23:22:16.5680561Z >>> model_state_dict = model_tp.state_dict() 2025-08-26T23:22:16.5680605Z >>> checkpoint = { 2025-08-26T23:22:16.5680648Z >>> "model": model_state_dict 2025-08-26T23:22:16.5680680Z >>> } 2025-08-26T23:22:16.5680721Z >>> dist_cp.load_state_dict( 2025-08-26T23:22:16.5680763Z >>> state_dict=checkpoint, 2025-08-26T23:22:16.5680832Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-08-26T23:22:16.5680908Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-08-26T23:22:16.5680939Z >>> ) 2025-08-26T23:22:16.5680999Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-08-26T23:22:16.5681031Z >>> 2025-08-26T23:22:16.5681096Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-08-26T23:22:16.5681136Z >>> model_state_dict, 2025-08-26T23:22:16.5681180Z >>> optimizer_key="optimizer", 2025-08-26T23:22:16.5681246Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-08-26T23:22:16.5682251Z >>> ) 2025-08-26T23:22:16.5682286Z >>> 2025-08-26T23:22:16.5682344Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-08-26T23:22:16.5682395Z >>> model, optim, optim_state["optimizer"] 2025-08-26T23:22:16.5682425Z >>> ) 2025-08-26T23:22:16.5682457Z >>> 2025-08-26T23:22:16.5682505Z >>> optim.load_state_dict(flattened_osd) 2025-08-26T23:22:16.5682536Z 2025-08-26T23:22:16.5682628Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5682660Z 2025-08-26T23:22:16.5682697Z warnings.warn(msg) 2025-08-26T23:22:16.5682728Z 2025-08-26T23:22:16.5682800Z --- Parse Warning: 106 / 146 --- 2025-08-26T23:22:16.5683106Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=114. 2025-08-26T23:22:16.5683241Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5683273Z 2025-08-26T23:22:16.5683336Z This configures FSDP-native mixed precision training. 2025-08-26T23:22:16.5683367Z 2025-08-26T23:22:16.5683401Z Attributes: 2025-08-26T23:22:16.5683486Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-08-26T23:22:16.5683560Z parameters during forward and backward and thus the dtype for 2025-08-26T23:22:16.5684609Z forward and backward computation. Outside forward and backward, the 2025-08-26T23:22:16.5684681Z *sharded* parameters are kept in full precision (e.g. for the 2025-08-26T23:22:16.5684756Z optimizer step), and for model checkpointing, the parameters are 2025-08-26T23:22:16.5684817Z always saved in full precision. (Default: ``None``) 2025-08-26T23:22:16.5684894Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T23:22:16.5684975Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-08-26T23:22:16.5685042Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-08-26T23:22:16.5685114Z the ``param_dtype`` value, still running gradient reduction in low 2025-08-26T23:22:16.5685190Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-08-26T23:22:16.5685262Z to force gradient reduction to run in full precision. (Default: 2025-08-26T23:22:16.5685298Z ``None``) 2025-08-26T23:22:16.5685375Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T23:22:16.5685447Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-08-26T23:22:16.5685519Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-08-26T23:22:16.5685592Z dtype thereafter. For model checkpointing, the buffers are saved 2025-08-26T23:22:16.5685685Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-08-26T23:22:16.5685719Z ``None``) 2025-08-26T23:22:16.5685792Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-08-26T23:22:16.5685869Z gradients to full precision after the backward pass in preparation 2025-08-26T23:22:16.5685942Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-08-26T23:22:16.5686026Z in the dtype used for gradient reduction, which can save memory if 2025-08-26T23:22:16.5686100Z using a custom optimizer that supports running in low precision. 2025-08-26T23:22:16.5687101Z (Default: ``False``) 2025-08-26T23:22:16.5687178Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-08-26T23:22:16.5687251Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-08-26T23:22:16.5687328Z that parameter and input dtypes match for forward computation, as 2025-08-26T23:22:16.5687403Z required by many ops. This may need to be set to ``True`` when only 2025-08-26T23:22:16.5687482Z applying mixed precision to some but not all FSDP modules, in which 2025-08-26T23:22:16.5687555Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-08-26T23:22:16.5687596Z (Default: ``False``) 2025-08-26T23:22:16.5687675Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-08-26T23:22:16.5687747Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-08-26T23:22:16.5687814Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-08-26T23:22:16.5687870Z this does not do anything. (Default: ``True``) 2025-08-26T23:22:16.5687946Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-08-26T23:22:16.5688015Z module classes to ignore for mixed precision when using an 2025-08-26T23:22:16.5688114Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-08-26T23:22:16.5688190Z applied to them separately with mixed precision disabled (meaning 2025-08-26T23:22:16.5688261Z that the final FSDP construction would deviate from the specified 2025-08-26T23:22:16.5688331Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-08-26T23:22:16.5688402Z not do anything. This API is experimental and subject to change. 2025-08-26T23:22:16.5688447Z (Default: ``(_BatchNorm,)``) 2025-08-26T23:22:16.5688477Z 2025-08-26T23:22:16.5689506Z .. note:: This API is experimental and subject to change. 2025-08-26T23:22:16.5689538Z 2025-08-26T23:22:16.5689619Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-08-26T23:22:16.5689649Z 2025-08-26T23:22:16.5689718Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-08-26T23:22:16.5689766Z precision, but buffers are not. 2025-08-26T23:22:16.5689798Z 2025-08-26T23:22:16.5689872Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-08-26T23:22:16.5689946Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-08-26T23:22:16.5690029Z Disabling FSDP's mixed precision for those norm modules only means that 2025-08-26T23:22:16.5690107Z the affine parameters are kept in ``float32``. However, this incurs 2025-08-26T23:22:16.5690191Z separate all-gathers and reduce-scatters for those norm modules, which 2025-08-26T23:22:16.5690266Z may be inefficient, so if the workload permits, the user should prefer 2025-08-26T23:22:16.5690325Z to still apply mixed precision to those modules. 2025-08-26T23:22:16.5690414Z 2025-08-26T23:22:16.5690489Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-08-26T23:22:16.5690591Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-08-26T23:22:16.5690674Z modules will have FSDP applied to them separately with mixed precision 2025-08-26T23:22:16.5690741Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-08-26T23:22:16.5690772Z 2025-08-26T23:22:16.5690846Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-08-26T23:22:16.5690923Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-08-26T23:22:16.5691986Z its ``cast_root_forward_inputs`` takes precedence over its 2025-08-26T23:22:16.5692054Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-08-26T23:22:16.5692129Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-08-26T23:22:16.5692208Z sufficient for the typical case where each FSDP instance has the same 2025-08-26T23:22:16.5692286Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-08-26T23:22:16.5692359Z ``param_dtype`` at the beginning of the model's forward pass. 2025-08-26T23:22:16.5692391Z 2025-08-26T23:22:16.5692466Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-08-26T23:22:16.5692547Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-08-26T23:22:16.5692622Z values to configure casting inputs or not before each instance's 2025-08-26T23:22:16.5692695Z forward. In such a case, since the casts happen before each FSDP 2025-08-26T23:22:16.5692773Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-08-26T23:22:16.5692854Z submodules run before its FSDP submodules to avoid the activation dtype 2025-08-26T23:22:16.5692928Z being changed due to a different ``MixedPrecision`` configuration. 2025-08-26T23:22:16.5692959Z 2025-08-26T23:22:16.5692994Z Example:: 2025-08-26T23:22:16.5693024Z 2025-08-26T23:22:16.5693080Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5693179Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-08-26T23:22:16.5693219Z >>> model[1] = FSDP( 2025-08-26T23:22:16.5693258Z >>> model[1], 2025-08-26T23:22:16.5694326Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-08-26T23:22:16.5694360Z >>> ) 2025-08-26T23:22:16.5694399Z >>> model = FSDP( 2025-08-26T23:22:16.5694437Z >>> model, 2025-08-26T23:22:16.5694545Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-08-26T23:22:16.5694577Z >>> ) 2025-08-26T23:22:16.5694607Z 2025-08-26T23:22:16.5694682Z The above shows a working example. On the other hand, if ``model[1]`` 2025-08-26T23:22:16.5694755Z were replaced with ``model[0]``, meaning that the submodule using 2025-08-26T23:22:16.5694836Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-08-26T23:22:16.5694916Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-08-26T23:22:16.5694948Z ones. 2025-08-26T23:22:16.5694978Z 2025-08-26T23:22:16.5695009Z 2025-08-26T23:22:16.5695099Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5695130Z 2025-08-26T23:22:16.5695167Z warnings.warn(msg) 2025-08-26T23:22:16.5695198Z 2025-08-26T23:22:16.5695272Z --- Parse Warning: 107 / 146 --- 2025-08-26T23:22:16.5695588Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=295. 2025-08-26T23:22:16.5695681Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5695731Z 2025-08-26T23:22:16.5696771Z ``FullStateDictConfig`` is a config class meant to be used with 2025-08-26T23:22:16.5696847Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-08-26T23:22:16.5696921Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-08-26T23:22:16.5697001Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-08-26T23:22:16.5697072Z is meant to be used via the :func:`state_dict_type` context manager as 2025-08-26T23:22:16.5697127Z follows: 2025-08-26T23:22:16.5697158Z 2025-08-26T23:22:16.5697212Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5697297Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:22:16.5697349Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-08-26T23:22:16.5697422Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-08-26T23:22:16.5697500Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-08-26T23:22:16.5697549Z >>> state = fsdp.state_dict() 2025-08-26T23:22:16.5697627Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-08-26T23:22:16.5697714Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-08-26T23:22:16.5697799Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-08-26T23:22:16.5697842Z >>> if dist.get_rank() == 0: 2025-08-26T23:22:16.5697912Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-08-26T23:22:16.5697968Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-08-26T23:22:16.5698015Z >>> model.load_state_dict(state_dict) 2025-08-26T23:22:16.5698099Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-08-26T23:22:16.5698185Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-08-26T23:22:16.5699218Z >>> fsdp = FSDP( 2025-08-26T23:22:16.5699265Z ... model, 2025-08-26T23:22:16.5699320Z ... device_id=torch.cuda.current_device(), 2025-08-26T23:22:16.5699362Z ... auto_wrap_policy=..., 2025-08-26T23:22:16.5699405Z ... sync_module_states=True, 2025-08-26T23:22:16.5699437Z ... ) 2025-08-26T23:22:16.5699514Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-08-26T23:22:16.5699544Z 2025-08-26T23:22:16.5699582Z Attributes: 2025-08-26T23:22:16.5699655Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-08-26T23:22:16.5699729Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-08-26T23:22:16.5699789Z ranks save the full state dict. (Default: ``False``) 2025-08-26T23:22:16.5699820Z 2025-08-26T23:22:16.5699909Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5699940Z 2025-08-26T23:22:16.5699979Z warnings.warn(msg) 2025-08-26T23:22:16.5700009Z 2025-08-26T23:22:16.5700083Z --- Parse Warning: 108 / 146 --- 2025-08-26T23:22:16.5700547Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634. 2025-08-26T23:22:16.5700644Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5700733Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T23:22:16.5701740Z 2025-08-26T23:22:16.5701837Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-08-26T23:22:16.5701911Z The target module does not have to be a FSDP module. If the target 2025-08-26T23:22:16.5702025Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-08-26T23:22:16.5702058Z 2025-08-26T23:22:16.5702130Z .. note:: This API should be called for only the top-level (root) 2025-08-26T23:22:16.5702166Z module. 2025-08-26T23:22:16.5702196Z 2025-08-26T23:22:16.5702271Z .. note:: This API enables users to transparently use the conventional 2025-08-26T23:22:16.5702358Z ``state_dict`` API to take model checkpoints in cases where the 2025-08-26T23:22:16.5702434Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-08-26T23:22:16.5702509Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-08-26T23:22:16.5702594Z instances, while dispatching into `sharded_state_dict` implementation 2025-08-26T23:22:16.5702631Z for FSDP: 2025-08-26T23:22:16.5702663Z 2025-08-26T23:22:16.5702698Z Example:: 2025-08-26T23:22:16.5702733Z 2025-08-26T23:22:16.5702789Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5702834Z >>> model = DDP(FSDP(...)) 2025-08-26T23:22:16.5702881Z >>> FSDP.set_state_dict_type( 2025-08-26T23:22:16.5702919Z >>> model, 2025-08-26T23:22:16.5702971Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T23:22:16.5704017Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-08-26T23:22:16.5704099Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-08-26T23:22:16.5704133Z >>> ) 2025-08-26T23:22:16.5704182Z >>> param_state_dict = model.state_dict() 2025-08-26T23:22:16.5704247Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T23:22:16.5704277Z 2025-08-26T23:22:16.5704310Z Args: 2025-08-26T23:22:16.5704361Z module (torch.nn.Module): Root module. 2025-08-26T23:22:16.5704484Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T23:22:16.5704568Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-08-26T23:22:16.5704614Z target ``state_dict_type``. 2025-08-26T23:22:16.5704706Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-08-26T23:22:16.5704753Z for the optimizer state dict. 2025-08-26T23:22:16.5704784Z 2025-08-26T23:22:16.5704817Z Returns: 2025-08-26T23:22:16.5704898Z A StateDictSettings that include the previous state_dict type and 2025-08-26T23:22:16.5704943Z configuration for the module. 2025-08-26T23:22:16.5704976Z 2025-08-26T23:22:16.5705066Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5705097Z 2025-08-26T23:22:16.5705134Z warnings.warn(msg) 2025-08-26T23:22:16.5706136Z 2025-08-26T23:22:16.5706210Z --- Parse Warning: 109 / 146 --- 2025-08-26T23:22:16.5706594Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792. 2025-08-26T23:22:16.5706687Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5706775Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T23:22:16.5706805Z 2025-08-26T23:22:16.5706918Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-08-26T23:22:16.5706971Z :meth:`set_state_dict_type` for the detail. 2025-08-26T23:22:16.5707002Z 2025-08-26T23:22:16.5707059Z Example:: 2025-08-26T23:22:16.5707093Z 2025-08-26T23:22:16.5707147Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5707191Z >>> model = DDP(FSDP(...)) 2025-08-26T23:22:16.5707236Z >>> with FSDP.state_dict_type( 2025-08-26T23:22:16.5707274Z >>> model, 2025-08-26T23:22:16.5707325Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T23:22:16.5707358Z >>> ): 2025-08-26T23:22:16.5707424Z >>> checkpoint = model.state_dict() 2025-08-26T23:22:16.5707455Z 2025-08-26T23:22:16.5707488Z Args: 2025-08-26T23:22:16.5707538Z module (torch.nn.Module): Root module. 2025-08-26T23:22:16.5707622Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T23:22:16.5708669Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-08-26T23:22:16.5708731Z configuration for the target ``state_dict_type``. 2025-08-26T23:22:16.5708819Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-08-26T23:22:16.5708893Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-08-26T23:22:16.5708925Z 2025-08-26T23:22:16.5709015Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5709046Z 2025-08-26T23:22:16.5709083Z warnings.warn(msg) 2025-08-26T23:22:16.5709115Z 2025-08-26T23:22:16.5709188Z --- Parse Warning: 110 / 146 --- 2025-08-26T23:22:16.5709572Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805. 2025-08-26T23:22:16.5709665Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5709713Z 2025-08-26T23:22:16.5709810Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-08-26T23:22:16.5709841Z 2025-08-26T23:22:16.5709916Z The given state-dict can be transformed to one of three types: 2025-08-26T23:22:16.5710023Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-08-26T23:22:16.5710055Z 2025-08-26T23:22:16.5710137Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-08-26T23:22:16.5710214Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-08-26T23:22:16.5710248Z avoid OOM. 2025-08-26T23:22:16.5711309Z 2025-08-26T23:22:16.5711393Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-08-26T23:22:16.5711469Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-08-26T23:22:16.5711501Z memory. 2025-08-26T23:22:16.5711534Z 2025-08-26T23:22:16.5711613Z For local state_dict, no transformation will be performed. But a state 2025-08-26T23:22:16.5711699Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-08-26T23:22:16.5711743Z nature (this is not supported yet). 2025-08-26T23:22:16.5711774Z 2025-08-26T23:22:16.5711809Z Example:: 2025-08-26T23:22:16.5711839Z 2025-08-26T23:22:16.5711892Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5711978Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:22:16.5712039Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T23:22:16.5712106Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T23:22:16.5712180Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T23:22:16.5712220Z >>> # Save a checkpoint 2025-08-26T23:22:16.5712261Z >>> model, optim = ... 2025-08-26T23:22:16.5712335Z >>> FSDP.set_state_dict_type( 2025-08-26T23:22:16.5712372Z >>> model, 2025-08-26T23:22:16.5712421Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:22:16.5712473Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5713495Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5713529Z >>> ) 2025-08-26T23:22:16.5713574Z >>> state_dict = model.state_dict() 2025-08-26T23:22:16.5713661Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T23:22:16.5713717Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T23:22:16.5713757Z >>> # Load a checkpoint 2025-08-26T23:22:16.5713796Z >>> model, optim = ... 2025-08-26T23:22:16.5713855Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T23:22:16.5713898Z >>> FSDP.set_state_dict_type( 2025-08-26T23:22:16.5713931Z >>> model, 2025-08-26T23:22:16.5713981Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:22:16.5714034Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5714090Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5714121Z >>> ) 2025-08-26T23:22:16.5714168Z >>> model.load_state_dict(state_dict) 2025-08-26T23:22:16.5714227Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T23:22:16.5714272Z >>> model, optim, optim_state_dict 2025-08-26T23:22:16.5714304Z >>> ) 2025-08-26T23:22:16.5714353Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T23:22:16.5714383Z 2025-08-26T23:22:16.5714416Z Args: 2025-08-26T23:22:16.5714548Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T23:22:16.5715589Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T23:22:16.5715644Z were passed into the optimizer ``optim``. 2025-08-26T23:22:16.5715715Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T23:22:16.5715811Z parameters. 2025-08-26T23:22:16.5715888Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-08-26T23:22:16.5715963Z transform. If the value is None, optim.state_dict() will be used. ( 2025-08-26T23:22:16.5716003Z Default: ``None``) 2025-08-26T23:22:16.5716087Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T23:22:16.5716161Z are sharded or ``None`` if using the default process group. ( 2025-08-26T23:22:16.5716198Z Default: ``None``) 2025-08-26T23:22:16.5716228Z 2025-08-26T23:22:16.5716261Z Returns: 2025-08-26T23:22:16.5716331Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-08-26T23:22:16.5716396Z ``model``. The sharding of the optimizer state is based on 2025-08-26T23:22:16.5716435Z ``state_dict_type``. 2025-08-26T23:22:16.5716468Z 2025-08-26T23:22:16.5716557Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5716590Z 2025-08-26T23:22:16.5716628Z warnings.warn(msg) 2025-08-26T23:22:16.5716659Z 2025-08-26T23:22:16.5716732Z --- Parse Warning: 111 / 146 --- 2025-08-26T23:22:16.5718089Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903. 2025-08-26T23:22:16.5718183Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5718214Z 2025-08-26T23:22:16.5718337Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-08-26T23:22:16.5718368Z 2025-08-26T23:22:16.5718431Z Given a ``optim_state_dict`` that is transformed through 2025-08-26T23:22:16.5718531Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-08-26T23:22:16.5718608Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-08-26T23:22:16.5718680Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-08-26T23:22:16.5718710Z 2025-08-26T23:22:16.5718762Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5718895Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T23:22:16.5718956Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T23:22:16.5719022Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T23:22:16.5719095Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T23:22:16.5719135Z >>> # Save a checkpoint 2025-08-26T23:22:16.5719174Z >>> model, optim = ... 2025-08-26T23:22:16.5719217Z >>> FSDP.set_state_dict_type( 2025-08-26T23:22:16.5719251Z >>> model, 2025-08-26T23:22:16.5719301Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:22:16.5719354Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5719410Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5720471Z >>> ) 2025-08-26T23:22:16.5720519Z >>> state_dict = model.state_dict() 2025-08-26T23:22:16.5720566Z >>> original_osd = optim.state_dict() 2025-08-26T23:22:16.5720622Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-08-26T23:22:16.5720656Z >>> model, 2025-08-26T23:22:16.5720690Z >>> optim, 2025-08-26T23:22:16.5720735Z >>> optim_state_dict=original_osd 2025-08-26T23:22:16.5720766Z >>> ) 2025-08-26T23:22:16.5720821Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T23:22:16.5720860Z >>> # Load a checkpoint 2025-08-26T23:22:16.5720899Z >>> model, optim = ... 2025-08-26T23:22:16.5720960Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T23:22:16.5721055Z >>> FSDP.set_state_dict_type( 2025-08-26T23:22:16.5721090Z >>> model, 2025-08-26T23:22:16.5721137Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T23:22:16.5721188Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5721242Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T23:22:16.5721273Z >>> ) 2025-08-26T23:22:16.5721319Z >>> model.load_state_dict(state_dict) 2025-08-26T23:22:16.5721377Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T23:22:16.5721422Z >>> model, optim, optim_state_dict 2025-08-26T23:22:16.5722424Z >>> ) 2025-08-26T23:22:16.5722475Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T23:22:16.5722506Z 2025-08-26T23:22:16.5722539Z Args: 2025-08-26T23:22:16.5722612Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T23:22:16.5722689Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T23:22:16.5722742Z were passed into the optimizer ``optim``. 2025-08-26T23:22:16.5722812Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T23:22:16.5722849Z parameters. 2025-08-26T23:22:16.5722926Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-08-26T23:22:16.5723000Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-08-26T23:22:16.5723071Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-08-26T23:22:16.5723136Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-08-26T23:22:16.5723207Z load_directly (bool): If this is set to True, this API will also 2025-08-26T23:22:16.5723279Z call optim.load_state_dict(result) before returning the result. 2025-08-26T23:22:16.5723359Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-08-26T23:22:16.5723428Z (Default: ``False``) 2025-08-26T23:22:16.5723514Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T23:22:16.5723583Z are sharded or ``None`` if using the default process group. ( 2025-08-26T23:22:16.5723622Z Default: ``None``) 2025-08-26T23:22:16.5723652Z 2025-08-26T23:22:16.5723742Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5724761Z 2025-08-26T23:22:16.5724800Z warnings.warn(msg) 2025-08-26T23:22:16.5724831Z 2025-08-26T23:22:16.5724903Z --- Parse Warning: 112 / 146 --- 2025-08-26T23:22:16.5725304Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-08-26T23:22:16.5725401Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5725433Z 2025-08-26T23:22:16.5725551Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-08-26T23:22:16.5725582Z 2025-08-26T23:22:16.5725691Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-08-26T23:22:16.5725769Z by using different periods concurrently after the warm-up stage. 2025-08-26T23:22:16.5725914Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-08-26T23:22:16.5726034Z that supports `post-local SGD `_, which essentially only supports 2025-08-26T23:22:16.5726143Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-08-26T23:22:16.5726268Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-08-26T23:22:16.5726404Z Similarly, the process groups within this class do not have such an intra-machine process 2025-08-26T23:22:16.5726502Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-08-26T23:22:16.5726533Z 2025-08-26T23:22:16.5726566Z Args: 2025-08-26T23:22:16.5726660Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-08-26T23:22:16.5726737Z process group size, used for initializing process groups of 2025-08-26T23:22:16.5726819Z different sizes in a hierarchy to average parameters concurrently. 2025-08-26T23:22:16.5727880Z Particularly, at each iteration, there will be at most a single 2025-08-26T23:22:16.5727962Z process group that runs averaging -- the period of such group should 2025-08-26T23:22:16.5728042Z have the largest period which the current step can be divided by. 2025-08-26T23:22:16.5728105Z For example, if the dict has three keys: 2, 4, and 8, 2025-08-26T23:22:16.5728181Z then this means totally three process groups will be created to 2025-08-26T23:22:16.5728257Z average parameters every 2, 4, and 8 iterations, respectively. 2025-08-26T23:22:16.5728328Z At the 4th iteration, only the second process group will run 2025-08-26T23:22:16.5728394Z averaging, because the first process group should be a 2025-08-26T23:22:16.5728474Z subset of the second process group, and no need to execute the first 2025-08-26T23:22:16.5728525Z process group redundantly. 2025-08-26T23:22:16.5728598Z On the other hand, the third process group can only be triggered 2025-08-26T23:22:16.5728697Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-08-26T23:22:16.5728805Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-08-26T23:22:16.5728960Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-08-26T23:22:16.5729041Z If ``None``, the default process group, which is created 2025-08-26T23:22:16.5729116Z by :func:`torch.distributed.init_process_group`, will be used. 2025-08-26T23:22:16.5729167Z (default: ``None``) 2025-08-26T23:22:16.5729198Z 2025-08-26T23:22:16.5729234Z Example:: 2025-08-26T23:22:16.5729281Z >>> # xdoctest: +SKIP('undefined rank') 2025-08-26T23:22:16.5729328Z >>> from collections import OrderedDict 2025-08-26T23:22:16.5730433Z >>> import torch 2025-08-26T23:22:16.5730485Z >>> import torch.distributed as dist 2025-08-26T23:22:16.5730584Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T23:22:16.5730628Z >>> PostLocalSGDState, 2025-08-26T23:22:16.5730669Z >>> post_localSGD_hook, 2025-08-26T23:22:16.5730701Z >>> ) 2025-08-26T23:22:16.5730834Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-08-26T23:22:16.5730876Z >>> import torch.nn as nn 2025-08-26T23:22:16.5730907Z >>> 2025-08-26T23:22:16.5730976Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T23:22:16.5731020Z >>> torch.cuda.set_device(rank) 2025-08-26T23:22:16.5731074Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T23:22:16.5731137Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:22:16.5731195Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:22:16.5731282Z >>> ) 2025-08-26T23:22:16.5731338Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:22:16.5731440Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-08-26T23:22:16.5731487Z >>> subgroup, _ = dist.new_subgroups() 2025-08-26T23:22:16.5731599Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-08-26T23:22:16.5731661Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:22:16.5731694Z >>> 2025-08-26T23:22:16.5732771Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-08-26T23:22:16.5732821Z >>> # the 16 processes every 16 iterations. 2025-08-26T23:22:16.5732894Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-08-26T23:22:16.5732980Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-08-26T23:22:16.5733093Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:22:16.5733190Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T23:22:16.5733249Z >>> # After 100 steps, run model averaging at two levels. 2025-08-26T23:22:16.5733295Z >>> for step in range(0, 200): 2025-08-26T23:22:16.5733339Z >>> optimizer.zero_grad() 2025-08-26T23:22:16.5733388Z >>> loss = loss_fn(output, labels) 2025-08-26T23:22:16.5733428Z >>> loss.backward() 2025-08-26T23:22:16.5733470Z >>> optimizer.step() 2025-08-26T23:22:16.5733531Z >>> # Average parameters after ``optimizer.step()``. 2025-08-26T23:22:16.5733635Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-08-26T23:22:16.5733720Z >>> averager.average_parameters(model.parameters()) 2025-08-26T23:22:16.5733755Z 2025-08-26T23:22:16.5733790Z .. warning :: 2025-08-26T23:22:16.5733882Z The last group size in the dict must be the size of the provided ``process_group``, 2025-08-26T23:22:16.5733967Z which indicates model averaging at the highest level of the hierarchy. 2025-08-26T23:22:16.5734075Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-08-26T23:22:16.5734123Z 2025-08-26T23:22:16.5734159Z .. warning :: 2025-08-26T23:22:16.5735205Z `HierarchicalModelAverager` is experimental and subject to change. 2025-08-26T23:22:16.5735238Z 2025-08-26T23:22:16.5735329Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5735360Z 2025-08-26T23:22:16.5735397Z warnings.warn(msg) 2025-08-26T23:22:16.5735428Z 2025-08-26T23:22:16.5735502Z --- Parse Warning: 113 / 146 --- 2025-08-26T23:22:16.5735879Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-08-26T23:22:16.5735973Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5736004Z 2025-08-26T23:22:16.5736077Z Averages parameters periodically after the warm-up stage. 2025-08-26T23:22:16.5736108Z 2025-08-26T23:22:16.5736201Z This can be used for running `post-local SGD `_, 2025-08-26T23:22:16.5736274Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-08-26T23:22:16.5736361Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-08-26T23:22:16.5736391Z 2025-08-26T23:22:16.5736424Z Args: 2025-08-26T23:22:16.5736488Z period (int): The number of steps per model averaging. 2025-08-26T23:22:16.5736616Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-08-26T23:22:16.5736668Z Otherwise, only DDP needs to be used. 2025-08-26T23:22:16.5736746Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-08-26T23:22:16.5736795Z model averaging is skipped. 2025-08-26T23:22:16.5737843Z process_group: The process group to be used for all-reduce. 2025-08-26T23:22:16.5737900Z If ``None``, the default process group, which 2025-08-26T23:22:16.5737972Z is created by :func:`torch.distributed.init_process_group`, 2025-08-26T23:22:16.5738023Z will be used. (default: ``None``) 2025-08-26T23:22:16.5738055Z 2025-08-26T23:22:16.5738089Z Example:: 2025-08-26T23:22:16.5738120Z 2025-08-26T23:22:16.5738172Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T23:22:16.5738211Z >>> import torch 2025-08-26T23:22:16.5738260Z >>> import torch.distributed as dist 2025-08-26T23:22:16.5738372Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-08-26T23:22:16.5738469Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T23:22:16.5738511Z >>> import torch.nn as nn 2025-08-26T23:22:16.5738543Z >>> 2025-08-26T23:22:16.5738612Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T23:22:16.5738655Z >>> torch.cuda.set_device(rank) 2025-08-26T23:22:16.5738708Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-08-26T23:22:16.5738770Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T23:22:16.5738825Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T23:22:16.5738858Z >>> ) 2025-08-26T23:22:16.5738913Z >>> # Register a post-localSGD communication hook. 2025-08-26T23:22:16.5740005Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T23:22:16.5740067Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:22:16.5740100Z >>> 2025-08-26T23:22:16.5740195Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T23:22:16.5740256Z >>> # After 100 steps, run model averaging every 4 steps. 2025-08-26T23:22:16.5740464Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T23:22:16.5740556Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T23:22:16.5740597Z >>> for step in range(0, 200): 2025-08-26T23:22:16.5740639Z >>> optimizer.zero_grad() 2025-08-26T23:22:16.5740685Z >>> loss = loss_fn(output, labels) 2025-08-26T23:22:16.5740728Z >>> loss.backward() 2025-08-26T23:22:16.5740769Z >>> optimizer.step() 2025-08-26T23:22:16.5740841Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-08-26T23:22:16.5740914Z >>> # inter-node communication only occurs every 4 iterations after 2025-08-26T23:22:16.5740966Z >>> # the initial ``warmup_steps`` period. 2025-08-26T23:22:16.5741026Z >>> averager.average_parameters(model.parameters()) 2025-08-26T23:22:16.5741058Z 2025-08-26T23:22:16.5741149Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5741181Z 2025-08-26T23:22:16.5741218Z warnings.warn(msg) 2025-08-26T23:22:16.5741250Z 2025-08-26T23:22:16.5741322Z --- Parse Warning: 114 / 146 --- 2025-08-26T23:22:16.5742701Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-08-26T23:22:16.5742812Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5742843Z 2025-08-26T23:22:16.5742887Z Run post-localSGD algorithm. 2025-08-26T23:22:16.5742918Z 2025-08-26T23:22:16.5743003Z This DDP communication hook is used for running post-localSGD algorithm, 2025-08-26T23:22:16.5743064Z by combining with a model averaging component (e.g., 2025-08-26T23:22:16.5743189Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-08-26T23:22:16.5743234Z that runs after the optimizer step. 2025-08-26T23:22:16.5743264Z 2025-08-26T23:22:16.5743296Z Args: 2025-08-26T23:22:16.5743379Z state (PostLocalSGDState): State information to run post-localSGD. 2025-08-26T23:22:16.5743476Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-08-26T23:22:16.5743628Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T23:22:16.5743718Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T23:22:16.5743779Z only exactly one tensor is stored in this bucket. 2025-08-26T23:22:16.5743809Z 2025-08-26T23:22:16.5743843Z Returns: 2025-08-26T23:22:16.5743930Z Future handler of the communication, which updates the gradients in place. 2025-08-26T23:22:16.5743961Z 2025-08-26T23:22:16.5743995Z Example:: 2025-08-26T23:22:16.5744997Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5745089Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-08-26T23:22:16.5745138Z start_localSGD_iter=10) 2025-08-26T23:22:16.5745203Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T23:22:16.5745344Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-08-26T23:22:16.5745467Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-08-26T23:22:16.5745498Z 2025-08-26T23:22:16.5745589Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5745620Z 2025-08-26T23:22:16.5745657Z warnings.warn(msg) 2025-08-26T23:22:16.5745688Z 2025-08-26T23:22:16.5745776Z --- Parse Warning: 115 / 146 --- 2025-08-26T23:22:16.5746127Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-08-26T23:22:16.5746220Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5746252Z 2025-08-26T23:22:16.5746297Z Implement PowerSGD algorithm. 2025-08-26T23:22:16.5746330Z 2025-08-26T23:22:16.5746412Z This DDP communication hook implements PowerSGD gradient compression 2025-08-26T23:22:16.5746497Z algorithm described in the `paper `_. 2025-08-26T23:22:16.5746582Z Once gradient tensors are aggregated across all workers, this hook applies 2025-08-26T23:22:16.5746622Z compression as follows: 2025-08-26T23:22:16.5746654Z 2025-08-26T23:22:16.5747767Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-08-26T23:22:16.5747799Z 2025-08-26T23:22:16.5747944Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-08-26T23:22:16.5747975Z 2025-08-26T23:22:16.5748116Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-08-26T23:22:16.5748167Z 2025-08-26T23:22:16.5748223Z 2. Handles uncompressed tensors: 2025-08-26T23:22:16.5748254Z 2025-08-26T23:22:16.5748430Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-08-26T23:22:16.5748461Z 2025-08-26T23:22:16.5748581Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-08-26T23:22:16.5748612Z 2025-08-26T23:22:16.5748696Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-08-26T23:22:16.5748726Z 2025-08-26T23:22:16.5748813Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-08-26T23:22:16.5748922Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-08-26T23:22:16.5748953Z 2025-08-26T23:22:16.5749010Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-08-26T23:22:16.5749043Z 2025-08-26T23:22:16.5749087Z 3.3. Allreduces Ps as a batch; 2025-08-26T23:22:16.5749117Z 2025-08-26T23:22:16.5750122Z 3.4. Orthogonalizes each P in Ps; 2025-08-26T23:22:16.5750153Z 2025-08-26T23:22:16.5750227Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-08-26T23:22:16.5750256Z 2025-08-26T23:22:16.5750298Z 3.6. Allreduces Qs as a batch; 2025-08-26T23:22:16.5750329Z 2025-08-26T23:22:16.5750497Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-08-26T23:22:16.5750528Z 2025-08-26T23:22:16.5750669Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-08-26T23:22:16.5750770Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-08-26T23:22:16.5750916Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-08-26T23:22:16.5750979Z 2025-08-26T23:22:16.5751011Z Args: 2025-08-26T23:22:16.5751160Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-08-26T23:22:16.5751284Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-08-26T23:22:16.5751353Z and ``min_compression_rate``. 2025-08-26T23:22:16.5751497Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T23:22:16.5751587Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T23:22:16.5751647Z only exactly one tensor is stored in this bucket. 2025-08-26T23:22:16.5751678Z 2025-08-26T23:22:16.5751710Z Returns: 2025-08-26T23:22:16.5751798Z Future handler of the communication, which updates the gradients in place. 2025-08-26T23:22:16.5752812Z 2025-08-26T23:22:16.5752848Z Example:: 2025-08-26T23:22:16.5752888Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5752988Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-08-26T23:22:16.5753050Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-08-26T23:22:16.5753115Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-08-26T23:22:16.5753145Z 2025-08-26T23:22:16.5753236Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5753266Z 2025-08-26T23:22:16.5753304Z warnings.warn(msg) 2025-08-26T23:22:16.5753334Z 2025-08-26T23:22:16.5753406Z --- Parse Warning: 116 / 146 --- 2025-08-26T23:22:16.5753774Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-08-26T23:22:16.5753886Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5753915Z 2025-08-26T23:22:16.5754001Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-08-26T23:22:16.5754060Z Needs to be called on all ranks in an SPMD fashion. 2025-08-26T23:22:16.5754090Z 2025-08-26T23:22:16.5754124Z Args: 2025-08-26T23:22:16.5754223Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-08-26T23:22:16.5754288Z of shards that represent the local shards on this rank. 2025-08-26T23:22:16.5754370Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-08-26T23:22:16.5755460Z shape of the overall sharded tensor. 2025-08-26T23:22:16.5755490Z 2025-08-26T23:22:16.5755526Z Keyword args: 2025-08-26T23:22:16.5755623Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T23:22:16.5755674Z the default process group will be used. 2025-08-26T23:22:16.5755741Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T23:22:16.5755818Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T23:22:16.5755887Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T23:22:16.5755928Z Default: ``False``. 2025-08-26T23:22:16.5755958Z 2025-08-26T23:22:16.5755992Z Returns: 2025-08-26T23:22:16.5756049Z A :class:`ShardedTensor` object handle on this rank 2025-08-26T23:22:16.5756081Z 2025-08-26T23:22:16.5756111Z 2025-08-26T23:22:16.5756145Z Examples: 2025-08-26T23:22:16.5756236Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-08-26T23:22:16.5756329Z each shard have a (5, 5) local tensor, we can do it like below: 2025-08-26T23:22:16.5756362Z 2025-08-26T23:22:16.5756396Z on rank 0: 2025-08-26T23:22:16.5756444Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T23:22:16.5756492Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T23:22:16.5757495Z >>> shard_offsets=[0, 0], 2025-08-26T23:22:16.5757537Z >>> shard_lengths=[5, 5], 2025-08-26T23:22:16.5757583Z >>> placement="rank:0/cuda:0" 2025-08-26T23:22:16.5757638Z >>> ) 2025-08-26T23:22:16.5757710Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T23:22:16.5757781Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T23:22:16.5757812Z 2025-08-26T23:22:16.5757844Z on rank 1: 2025-08-26T23:22:16.5757891Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T23:22:16.5757938Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T23:22:16.5757981Z >>> shard_offsets=[5, 0], 2025-08-26T23:22:16.5758023Z >>> shard_lengths=[5, 5], 2025-08-26T23:22:16.5758066Z >>> placement="rank:1/cuda:1" 2025-08-26T23:22:16.5758098Z >>> ) 2025-08-26T23:22:16.5758167Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T23:22:16.5758236Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T23:22:16.5758266Z 2025-08-26T23:22:16.5758359Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5758390Z 2025-08-26T23:22:16.5758428Z warnings.warn(msg) 2025-08-26T23:22:16.5758458Z 2025-08-26T23:22:16.5758529Z --- Parse Warning: 117 / 146 --- 2025-08-26T23:22:16.5759822Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-08-26T23:22:16.5759959Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5759990Z 2025-08-26T23:22:16.5760071Z Representation of a sharding plan, describes how to shard a module 2025-08-26T23:22:16.5760167Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-08-26T23:22:16.5760271Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-08-26T23:22:16.5760452Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-08-26T23:22:16.5760485Z 2025-08-26T23:22:16.5760517Z Args: 2025-08-26T23:22:16.5760615Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-08-26T23:22:16.5760681Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-08-26T23:22:16.5760780Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-08-26T23:22:16.5760874Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-08-26T23:22:16.5760924Z a parameter to a `ShardingSpec`. 2025-08-26T23:22:16.5761017Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-08-26T23:22:16.5761059Z to a `Sharder` object. 2025-08-26T23:22:16.5761176Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-08-26T23:22:16.5761269Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-08-26T23:22:16.5761353Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-08-26T23:22:16.5761393Z Default: `None` 2025-08-26T23:22:16.5761484Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-08-26T23:22:16.5762585Z a module's sharded output to be returned as a Tensor from its local shards to 2025-08-26T23:22:16.5762679Z ensure further processing in a data parallel fashion. ("" in list means the 2025-08-26T23:22:16.5762717Z root module). 2025-08-26T23:22:16.5762754Z Default: None 2025-08-26T23:22:16.5762787Z Example: 2025-08-26T23:22:16.5762889Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-08-26T23:22:16.5763013Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-08-26T23:22:16.5763044Z 2025-08-26T23:22:16.5763109Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-08-26T23:22:16.5763152Z >>> class MyModule(nn.Module): 2025-08-26T23:22:16.5763199Z >>> def __init__(self) -> None: 2025-08-26T23:22:16.5763239Z >>> super().__init__() 2025-08-26T23:22:16.5763282Z >>> self.fc1 = nn.Linear() 2025-08-26T23:22:16.5763325Z >>> self.gelu = nn.GELU() 2025-08-26T23:22:16.5763368Z >>> self.fc2 = nn.Linear() 2025-08-26T23:22:16.5763411Z >>> self.relu = nn.Linear() 2025-08-26T23:22:16.5763442Z >>> 2025-08-26T23:22:16.5763484Z >>> def forward(self, input): 2025-08-26T23:22:16.5763550Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-08-26T23:22:16.5763582Z 2025-08-26T23:22:16.5763611Z 2025-08-26T23:22:16.5763665Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-08-26T23:22:16.5764670Z >>> sharding_plan = ShardingPlan( 2025-08-26T23:22:16.5764707Z >>> plan={ 2025-08-26T23:22:16.5764749Z >>> "fc1.weight": spec1, 2025-08-26T23:22:16.5764790Z >>> "fc2.weight": spec2 2025-08-26T23:22:16.5764822Z >>> }, 2025-08-26T23:22:16.5764863Z >>> output_plan={ 2025-08-26T23:22:16.5764903Z >>> "fc2": output_spec 2025-08-26T23:22:16.5764937Z >>> }, 2025-08-26T23:22:16.5765033Z >>> return_local_tensor=["fc2"] 2025-08-26T23:22:16.5765066Z >>> ) 2025-08-26T23:22:16.5765096Z 2025-08-26T23:22:16.5765187Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5765219Z 2025-08-26T23:22:16.5765256Z warnings.warn(msg) 2025-08-26T23:22:16.5765287Z 2025-08-26T23:22:16.5765361Z --- Parse Warning: 118 / 146 --- 2025-08-26T23:22:16.5765724Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-08-26T23:22:16.5765818Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5765849Z 2025-08-26T23:22:16.5765941Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-08-26T23:22:16.5765988Z size and sharding spec on each rank. 2025-08-26T23:22:16.5766019Z 2025-08-26T23:22:16.5767015Z Args: 2025-08-26T23:22:16.5767098Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-08-26T23:22:16.5767193Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-08-26T23:22:16.5767259Z The specification describing how to shard the Tensor. 2025-08-26T23:22:16.5767325Z global_size (Sequence[int]): Size of the sharded tensor. 2025-08-26T23:22:16.5767415Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-08-26T23:22:16.5767453Z Default: None 2025-08-26T23:22:16.5767518Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T23:22:16.5767595Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T23:22:16.5767667Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T23:22:16.5767730Z Default: ``False``. 2025-08-26T23:22:16.5767762Z 2025-08-26T23:22:16.5767794Z Returns: 2025-08-26T23:22:16.5767881Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-08-26T23:22:16.5767929Z tensor stored in the current rank. 2025-08-26T23:22:16.5767959Z 2025-08-26T23:22:16.5767992Z Examples: 2025-08-26T23:22:16.5768033Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5768107Z >>> # All tensors below are of torch.int64 type. 2025-08-26T23:22:16.5768155Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5768222Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T23:22:16.5769250Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-08-26T23:22:16.5769288Z >>> local_tensor 2025-08-26T23:22:16.5769329Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-08-26T23:22:16.5769368Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-08-26T23:22:16.5769410Z >>> sharding_dim = 0 2025-08-26T23:22:16.5769460Z >>> sharding_spec = ChunkShardingSpec( 2025-08-26T23:22:16.5769501Z dim=sharding_dim, 2025-08-26T23:22:16.5769540Z placements=[ 2025-08-26T23:22:16.5769580Z "rank:0/cuda:0", 2025-08-26T23:22:16.5769618Z "rank:1/cuda:1", 2025-08-26T23:22:16.5769651Z ], 2025-08-26T23:22:16.5769681Z ) 2025-08-26T23:22:16.5769739Z >>> st = ShardedTensor._init_from_local_tensor( 2025-08-26T23:22:16.5769788Z ... local_tensor, sharding_spec, [2, 4] 2025-08-26T23:22:16.5769820Z ... ) 2025-08-26T23:22:16.5769852Z >>> st 2025-08-26T23:22:16.5769888Z ShardedTensor( 2025-08-26T23:22:16.5769933Z ShardedTensorMetadata( 2025-08-26T23:22:16.5769971Z shards_metadata=[ 2025-08-26T23:22:16.5770069Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-08-26T23:22:16.5770199Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-08-26T23:22:16.5770233Z ], 2025-08-26T23:22:16.5771340Z size=torch.Size([2, 4]) 2025-08-26T23:22:16.5771374Z ) 2025-08-26T23:22:16.5771413Z >>> st.local_tensor() 2025-08-26T23:22:16.5771454Z tensor([1, 2, 3, 4]) # Rank 0 2025-08-26T23:22:16.5771492Z tensor([3, 4, 5, 6]) # Rank 1 2025-08-26T23:22:16.5771525Z 2025-08-26T23:22:16.5771624Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-08-26T23:22:16.5771710Z rank validations, and we only validate the local shard on the current rank. 2025-08-26T23:22:16.5771787Z We fully rely on the user to ensure local tensor is sharded based on the 2025-08-26T23:22:16.5771826Z sharding spec. 2025-08-26T23:22:16.5771857Z 2025-08-26T23:22:16.5771949Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5771982Z 2025-08-26T23:22:16.5772020Z warnings.warn(msg) 2025-08-26T23:22:16.5772050Z 2025-08-26T23:22:16.5772122Z --- Parse Warning: 119 / 146 --- 2025-08-26T23:22:16.5772466Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-08-26T23:22:16.5772561Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5772591Z 2025-08-26T23:22:16.5772682Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-08-26T23:22:16.5772720Z single local shard. 2025-08-26T23:22:16.5773713Z 2025-08-26T23:22:16.5773796Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-08-26T23:22:16.5773915Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-08-26T23:22:16.5773959Z we swap local shards directly. 2025-08-26T23:22:16.5774052Z For more generic cases, we merge different shards across different ranks and split 2025-08-26T23:22:16.5774141Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-08-26T23:22:16.5774172Z 2025-08-26T23:22:16.5774204Z Args: 2025-08-26T23:22:16.5774325Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-08-26T23:22:16.5774389Z specification describing how the tensor is sharded. 2025-08-26T23:22:16.5774419Z 2025-08-26T23:22:16.5774452Z Returns: 2025-08-26T23:22:16.5774526Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-08-26T23:22:16.5774556Z 2025-08-26T23:22:16.5774589Z Examples: 2025-08-26T23:22:16.5774629Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5774678Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T23:22:16.5774748Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T23:22:16.5774796Z >>> tensor = torch.stack([tensor, tensor]) 2025-08-26T23:22:16.5774830Z >>> tensor 2025-08-26T23:22:16.5774879Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-08-26T23:22:16.5774927Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-08-26T23:22:16.5775935Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-08-26T23:22:16.5775986Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-08-26T23:22:16.5776026Z >>> sharding_dim = 0 2025-08-26T23:22:16.5776069Z >>> spec = ChunkShardingSpec( 2025-08-26T23:22:16.5776110Z dim=sharding_dim, 2025-08-26T23:22:16.5776148Z placements=[ 2025-08-26T23:22:16.5776186Z "rank:0/cuda:0", 2025-08-26T23:22:16.5776223Z "rank:1/cuda:1", 2025-08-26T23:22:16.5776261Z "rank:2/cuda:2", 2025-08-26T23:22:16.5776340Z "rank:3/cuda:3", 2025-08-26T23:22:16.5776374Z ], 2025-08-26T23:22:16.5776405Z ) 2025-08-26T23:22:16.5776446Z >>> current_offsets = [0] * 2 2025-08-26T23:22:16.5776488Z >>> current_offsets[0] = rank * 2 2025-08-26T23:22:16.5776535Z >>> shard_metadata = ShardMetadata( 2025-08-26T23:22:16.5776594Z shard_offsets=copy.deepcopy(current_offsets), 2025-08-26T23:22:16.5776639Z shard_sizes=tensor.size(), 2025-08-26T23:22:16.5776688Z placement=spec.placements[rank], 2025-08-26T23:22:16.5776719Z ) 2025-08-26T23:22:16.5776756Z >>> local_shards = [ 2025-08-26T23:22:16.5776790Z Shard( 2025-08-26T23:22:16.5776831Z tensor=tensor, 2025-08-26T23:22:16.5777832Z metadata=shard_metadata, 2025-08-26T23:22:16.5777865Z ) 2025-08-26T23:22:16.5777897Z ] 2025-08-26T23:22:16.5777983Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-08-26T23:22:16.5778021Z >>> sharding_dim = 1 2025-08-26T23:22:16.5778070Z >>> resharding_spec = ChunkShardingSpec( 2025-08-26T23:22:16.5778109Z dim=sharding_dim, 2025-08-26T23:22:16.5778147Z placements=[ 2025-08-26T23:22:16.5778184Z "rank:0/cuda:0", 2025-08-26T23:22:16.5778221Z "rank:1/cuda:1", 2025-08-26T23:22:16.5778258Z "rank:2/cuda:2", 2025-08-26T23:22:16.5778295Z "rank:3/cuda:3", 2025-08-26T23:22:16.5778327Z ], 2025-08-26T23:22:16.5778358Z ) 2025-08-26T23:22:16.5778399Z >>> st.reshard(resharding_spec) 2025-08-26T23:22:16.5778444Z >>> tensor = st.local_shards()[0].tensor 2025-08-26T23:22:16.5778476Z >>> tensor 2025-08-26T23:22:16.5778534Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-08-26T23:22:16.5778610Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-08-26T23:22:16.5778664Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-08-26T23:22:16.5778720Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-08-26T23:22:16.5779706Z 2025-08-26T23:22:16.5779798Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5779829Z 2025-08-26T23:22:16.5779868Z warnings.warn(msg) 2025-08-26T23:22:16.5779917Z 2025-08-26T23:22:16.5779990Z --- Parse Warning: 120 / 146 --- 2025-08-26T23:22:16.5780405Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-08-26T23:22:16.5780499Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5780533Z 2025-08-26T23:22:16.5780635Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-08-26T23:22:16.5780719Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-08-26T23:22:16.5780811Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-08-26T23:22:16.5780899Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-08-26T23:22:16.5780997Z when users would like to overwrite default sharding strategies of existing operators. 2025-08-26T23:22:16.5781028Z 2025-08-26T23:22:16.5781060Z Args: 2025-08-26T23:22:16.5781111Z op (Union[OpOverload, List[OpOverload]]): 2025-08-26T23:22:16.5781183Z An op or a list of ops to register the customized sharding function. 2025-08-26T23:22:16.5781213Z 2025-08-26T23:22:16.5781246Z Returns: 2025-08-26T23:22:16.5781340Z A function decorator which can be used to wrap a function that defines the sharding 2025-08-26T23:22:16.5781505Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-08-26T23:22:16.5782587Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-08-26T23:22:16.5782695Z already implemented the operator. The customized sharding function takes the same inputs 2025-08-26T23:22:16.5782784Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-08-26T23:22:16.5782880Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-08-26T23:22:16.5782976Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-08-26T23:22:16.5783022Z corresponding input placements. 2025-08-26T23:22:16.5783052Z 2025-08-26T23:22:16.5783085Z Example: 2025-08-26T23:22:16.5783131Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5783187Z >>> @register_sharding(aten._softmax.default) 2025-08-26T23:22:16.5783248Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-08-26T23:22:16.5783303Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-08-26T23:22:16.5783348Z >>> acceptable_shardings = [] 2025-08-26T23:22:16.5783379Z >>> 2025-08-26T23:22:16.5783446Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-08-26T23:22:16.5783505Z >>> acceptable_shardings.append(all_replicate) 2025-08-26T23:22:16.5783538Z >>> 2025-08-26T23:22:16.5783584Z >>> for sharding_dim in range(x.ndim): 2025-08-26T23:22:16.5783630Z >>> if sharding_dim != softmax_dim: 2025-08-26T23:22:16.5783669Z >>> all_sharded = ( 2025-08-26T23:22:16.5783714Z >>> [Shard(sharding_dim)], 2025-08-26T23:22:16.5783764Z >>> [Shard(sharding_dim), None, None], 2025-08-26T23:22:16.5784795Z >>> ) 2025-08-26T23:22:16.5784854Z >>> acceptable_shardings.append(all_sharded) 2025-08-26T23:22:16.5784886Z >>> 2025-08-26T23:22:16.5784930Z >>> return acceptable_shardings 2025-08-26T23:22:16.5784962Z 2025-08-26T23:22:16.5785036Z .. note:: This API is currently experimental and subject to change 2025-08-26T23:22:16.5785067Z 2025-08-26T23:22:16.5785156Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5785222Z 2025-08-26T23:22:16.5785260Z warnings.warn(msg) 2025-08-26T23:22:16.5785291Z 2025-08-26T23:22:16.5785363Z --- Parse Warning: 121 / 146 --- 2025-08-26T23:22:16.5785695Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-08-26T23:22:16.5785791Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5785823Z 2025-08-26T23:22:16.5785918Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-08-26T23:22:16.5786018Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-08-26T23:22:16.5786114Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-08-26T23:22:16.5786178Z :class:`DTensor` according to the ``out_placements``. 2025-08-26T23:22:16.5786210Z 2025-08-26T23:22:16.5786241Z Args: 2025-08-26T23:22:16.5787280Z func (Callable): the function to be applied on each local shard of 2025-08-26T23:22:16.5787321Z :class:`DTensor` s. 2025-08-26T23:22:16.5787402Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-08-26T23:22:16.5787496Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-08-26T23:22:16.5787618Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-08-26T23:22:16.5787705Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-08-26T23:22:16.5787794Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-08-26T23:22:16.5787842Z mapping to the flattened ``output``. 2025-08-26T23:22:16.5787919Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-08-26T23:22:16.5788017Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-08-26T23:22:16.5788057Z should be `None`. 2025-08-26T23:22:16.5788141Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-08-26T23:22:16.5788220Z in. In this case, even if `out_placements` is not `None`, the result function 2025-08-26T23:22:16.5790083Z should ignore the desired placements because the function is not running with 2025-08-26T23:22:16.5790129Z :class:`DTensor` s. 2025-08-26T23:22:16.5790195Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T23:22:16.5790295Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-08-26T23:22:16.5790456Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-08-26T23:22:16.5790543Z placements of each :class:`DTensor` argument is the same as the required 2025-08-26T23:22:16.5790611Z placements or not. If the placements are not the same and 2025-08-26T23:22:16.5792104Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-08-26T23:22:16.5792194Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-08-26T23:22:16.5792291Z the required sharding placements before passing its local tensor to ``func``. 2025-08-26T23:22:16.5792467Z The only exception is when required placements are not ``None`` and the 2025-08-26T23:22:16.5792554Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-08-26T23:22:16.5792634Z will be skipped and the argument will be directly passed to ``func``. 2025-08-26T23:22:16.5792713Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-08-26T23:22:16.5792773Z Default: None 2025-08-26T23:22:16.5792844Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T23:22:16.5792921Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-08-26T23:22:16.5792996Z to the flattened input DTensor. This argument is the hint that user 2025-08-26T23:22:16.5793065Z can give to :meth:`to_local` in case the gradient layout of the 2025-08-26T23:22:16.5793142Z local tensor input does not match its :class:`DTensor` input layout. 2025-08-26T23:22:16.5793218Z If not specified, we will assume the gradient layout of the local 2025-08-26T23:22:16.5793296Z tensor input remains the same as the original :class:`DTensor` input 2025-08-26T23:22:16.5793361Z and use that for gradient computation. Default: None. 2025-08-26T23:22:16.5793416Z device_mesh (:class:`DeviceMesh`, optional): 2025-08-26T23:22:16.5793500Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-08-26T23:22:16.5793593Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-08-26T23:22:16.5793636Z mesh. Default: None. 2025-08-26T23:22:16.5793667Z 2025-08-26T23:22:16.5794893Z Keyword Args: 2025-08-26T23:22:16.5794945Z redistribute_inputs (bool, optional): 2025-08-26T23:22:16.5795036Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-08-26T23:22:16.5795128Z their placements are different from the required input placements. If this 2025-08-26T23:22:16.5795237Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-08-26T23:22:16.5795291Z an exception will be raised. Default: False. 2025-08-26T23:22:16.5795323Z 2025-08-26T23:22:16.5795356Z Returns: 2025-08-26T23:22:16.5795452Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-08-26T23:22:16.5795541Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-08-26T23:22:16.5795573Z 2025-08-26T23:22:16.5795605Z Raises: 2025-08-26T23:22:16.5795692Z AssertionError: For any non-DTensor output, we require its corresponding 2025-08-26T23:22:16.5795785Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-08-26T23:22:16.5795826Z if this is not the case. 2025-08-26T23:22:16.5795859Z 2025-08-26T23:22:16.5796025Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-08-26T23:22:16.5796085Z a redistribution according to ``in_placements``. 2025-08-26T23:22:16.5796116Z 2025-08-26T23:22:16.5796149Z Example: 2025-08-26T23:22:16.5796194Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5796250Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-08-26T23:22:16.5797436Z >>> partial_sum_tensor = torch.mm(W, X) 2025-08-26T23:22:16.5797526Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-08-26T23:22:16.5797573Z >>> return reduced_tensor 2025-08-26T23:22:16.5797604Z >>> 2025-08-26T23:22:16.5797655Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-08-26T23:22:16.5797706Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-08-26T23:22:16.5797746Z >>> Y = torch.mm(W, X) 2025-08-26T23:22:16.5797843Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-08-26T23:22:16.5797912Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-08-26T23:22:16.5797945Z >>> 2025-08-26T23:22:16.5798043Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion 2025-08-26T23:22:16.5798093Z >>> local_mm_allreduce_forward = local_map( 2025-08-26T23:22:16.5798133Z >>> mm_allreduce_forward, 2025-08-26T23:22:16.5798198Z >>> out_placements=[Replicate()], 2025-08-26T23:22:16.5798245Z >>> in_placements=[col_wise, row_wise], 2025-08-26T23:22:16.5798288Z >>> device_mesh=device_mesh, 2025-08-26T23:22:16.5798319Z >>> ) 2025-08-26T23:22:16.5798351Z >>> 2025-08-26T23:22:16.5798391Z >>> W_dt = distribute_tensor( 2025-08-26T23:22:16.5798433Z ... W, device_mesh, (col_wise) 2025-08-26T23:22:16.5798478Z ... ) # col-wisely sharded W tensor 2025-08-26T23:22:16.5799537Z >>> X_dt = distribute_tensor( 2025-08-26T23:22:16.5799583Z ... X, device_mesh, (row_wise) 2025-08-26T23:22:16.5799628Z ... ) # row-wisely sharded X tensor 2025-08-26T23:22:16.5799673Z >>> Y_dt = local_mm_allreduce_forward( 2025-08-26T23:22:16.5799714Z ... device_mesh, W_dt, X_dt 2025-08-26T23:22:16.5799772Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-08-26T23:22:16.5799803Z 2025-08-26T23:22:16.5799881Z .. note:: This API is currently experimental and subject to change 2025-08-26T23:22:16.5799912Z 2025-08-26T23:22:16.5800003Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5800033Z 2025-08-26T23:22:16.5800072Z warnings.warn(msg) 2025-08-26T23:22:16.5800103Z 2025-08-26T23:22:16.5800194Z --- Parse Warning: 122 / 146 --- 2025-08-26T23:22:16.5800621Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-08-26T23:22:16.5800748Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5800778Z 2025-08-26T23:22:16.5800915Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-08-26T23:22:16.5801028Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-08-26T23:22:16.5801059Z 2025-08-26T23:22:16.5801093Z Keyword Args: 2025-08-26T23:22:16.5801169Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:22:16.5802316Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T23:22:16.5802445Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T23:22:16.5802529Z as a placeholder. default: None. 2025-08-26T23:22:16.5802614Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:22:16.5802743Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:22:16.5802882Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T23:22:16.5802934Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T23:22:16.5803063Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T23:22:16.5803101Z default: None 2025-08-26T23:22:16.5803164Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T23:22:16.5803289Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:22:16.5803376Z have the desired DTensor layouts. default: None. 2025-08-26T23:22:16.5803423Z use_local_output (bool, optional): 2025-08-26T23:22:16.5803547Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T23:22:16.5803580Z Returns: 2025-08-26T23:22:16.5803709Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-08-26T23:22:16.5803740Z 2025-08-26T23:22:16.5803776Z Example:: 2025-08-26T23:22:16.5803819Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:22:16.5803932Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-08-26T23:22:16.5804004Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:22:16.5805032Z >>> ... 2025-08-26T23:22:16.5805146Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:22:16.5805204Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:22:16.5805235Z >>> 2025-08-26T23:22:16.5805353Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-08-26T23:22:16.5805411Z >>> # and then redistributed to Replicated DTensor. 2025-08-26T23:22:16.5805453Z >>> parallelize_module( 2025-08-26T23:22:16.5805509Z >>> block, # this can be a submodule or module 2025-08-26T23:22:16.5805546Z >>> tp_mesh, 2025-08-26T23:22:16.5805588Z >>> parallelize_plan={ 2025-08-26T23:22:16.5805638Z >>> "attn": PrepareModuleInput( 2025-08-26T23:22:16.5805694Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T23:22:16.5805758Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-08-26T23:22:16.5805793Z >>> ), 2025-08-26T23:22:16.5805845Z >>> } 2025-08-26T23:22:16.5805877Z >>> ) 2025-08-26T23:22:16.5805908Z 2025-08-26T23:22:16.5805998Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5806029Z 2025-08-26T23:22:16.5806066Z warnings.warn(msg) 2025-08-26T23:22:16.5806097Z 2025-08-26T23:22:16.5806171Z --- Parse Warning: 123 / 146 --- 2025-08-26T23:22:16.5807499Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-08-26T23:22:16.5807595Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5807625Z 2025-08-26T23:22:16.5807763Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-08-26T23:22:16.5807900Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-08-26T23:22:16.5807933Z 2025-08-26T23:22:16.5807966Z Keyword Args: 2025-08-26T23:22:16.5808031Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:22:16.5808147Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T23:22:16.5808282Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T23:22:16.5808341Z ``None`` need to be specified as a placeholder. 2025-08-26T23:22:16.5808414Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:22:16.5808546Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T23:22:16.5808593Z have the desired DTensor layouts. 2025-08-26T23:22:16.5808657Z use_local_output (bool, optional): 2025-08-26T23:22:16.5808783Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T23:22:16.5808816Z Returns: 2025-08-26T23:22:16.5808919Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-08-26T23:22:16.5808951Z 2025-08-26T23:22:16.5808985Z Example:: 2025-08-26T23:22:16.5809028Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:22:16.5809160Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-08-26T23:22:16.5810218Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:22:16.5810251Z >>> ... 2025-08-26T23:22:16.5810548Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:22:16.5810602Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:22:16.5810636Z >>> 2025-08-26T23:22:16.5810779Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-08-26T23:22:16.5810833Z >>> # and then redistributed to Sharded DTensor. 2025-08-26T23:22:16.5810875Z >>> parallelize_module( 2025-08-26T23:22:16.5810929Z >>> block, # this can be a submodule or module 2025-08-26T23:22:16.5810965Z >>> tp_mesh, 2025-08-26T23:22:16.5811024Z >>> parallelize_plan = PrepareModuleOutput( 2025-08-26T23:22:16.5811070Z >>> output_layouts=Replicate(), 2025-08-26T23:22:16.5811118Z >>> desired_output_layouts=Shard(0) 2025-08-26T23:22:16.5811150Z >>> ) 2025-08-26T23:22:16.5811182Z >>> ) 2025-08-26T23:22:16.5811212Z 2025-08-26T23:22:16.5811302Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5811333Z 2025-08-26T23:22:16.5811371Z warnings.warn(msg) 2025-08-26T23:22:16.5811437Z 2025-08-26T23:22:16.5811513Z --- Parse Warning: 124 / 146 --- 2025-08-26T23:22:16.5812917Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-08-26T23:22:16.5813014Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5813044Z 2025-08-26T23:22:16.5813195Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-08-26T23:22:16.5813341Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-08-26T23:22:16.5813472Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-08-26T23:22:16.5813579Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-08-26T23:22:16.5813611Z 2025-08-26T23:22:16.5813645Z Keyword Args: 2025-08-26T23:22:16.5813719Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:22:16.5813834Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T23:22:16.5813958Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T23:22:16.5814007Z as a placeholder. default: None. 2025-08-26T23:22:16.5814089Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T23:22:16.5814219Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:22:16.5814355Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T23:22:16.5814434Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T23:22:16.5814563Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T23:22:16.5814602Z default: None 2025-08-26T23:22:16.5814663Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T23:22:16.5814811Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T23:22:16.5817389Z have the desired DTensor layouts. default: None. 2025-08-26T23:22:16.5817450Z use_local_input (bool, optional): 2025-08-26T23:22:16.5817577Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T23:22:16.5817639Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:22:16.5817760Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T23:22:16.5817894Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T23:22:16.5817950Z ``None`` need to be specified as a placeholder. 2025-08-26T23:22:16.5818023Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T23:22:16.5818156Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T23:22:16.5818203Z have the desired DTensor layouts. 2025-08-26T23:22:16.5818248Z use_local_output (bool, optional): 2025-08-26T23:22:16.5818371Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T23:22:16.5818404Z Returns: 2025-08-26T23:22:16.5818532Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-08-26T23:22:16.5818593Z 2025-08-26T23:22:16.5818631Z Example:: 2025-08-26T23:22:16.5818674Z >>> # xdoctest: +SKIP(failing) 2025-08-26T23:22:16.5818795Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-08-26T23:22:16.5818867Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T23:22:16.5818899Z >>> ... 2025-08-26T23:22:16.5819006Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T23:22:16.5819059Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T23:22:16.5820260Z >>> 2025-08-26T23:22:16.5820462Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-08-26T23:22:16.5820586Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-08-26T23:22:16.5820702Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-08-26T23:22:16.5820744Z >>> parallelize_module( 2025-08-26T23:22:16.5820798Z >>> block, # this can be a submodule or module 2025-08-26T23:22:16.5820835Z >>> tp_mesh, 2025-08-26T23:22:16.5820878Z >>> parallelize_plan={ 2025-08-26T23:22:16.5820933Z >>> "attn": PrepareModuleInputOutput( 2025-08-26T23:22:16.5820991Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T23:22:16.5821053Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-08-26T23:22:16.5821101Z >>> output_layouts=Replicate(), 2025-08-26T23:22:16.5821151Z >>> desired_output_layouts=Shard(0), 2025-08-26T23:22:16.5821186Z >>> ), 2025-08-26T23:22:16.5821217Z >>> } 2025-08-26T23:22:16.5821248Z >>> ) 2025-08-26T23:22:16.5821301Z 2025-08-26T23:22:16.5821393Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5821426Z 2025-08-26T23:22:16.5821463Z warnings.warn(msg) 2025-08-26T23:22:16.5821494Z 2025-08-26T23:22:16.5821586Z --- Parse Warning: 125 / 146 --- 2025-08-26T23:22:16.5822978Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-08-26T23:22:16.5823074Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5823105Z 2025-08-26T23:22:16.5823181Z Initialize rendezvous event object and record its operations. 2025-08-26T23:22:16.5823213Z 2025-08-26T23:22:16.5823245Z Args: 2025-08-26T23:22:16.5823296Z run_id (str): The run id of the rendezvous. 2025-08-26T23:22:16.5823357Z message (str): The message describing the event. 2025-08-26T23:22:16.5823454Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-08-26T23:22:16.5823524Z name (str): Event name. (E.g. Current action being performed). 2025-08-26T23:22:16.5823573Z hostname (str): Hostname of the node. 2025-08-26T23:22:16.5823628Z pid (Optional[int]): The process id of the node. 2025-08-26T23:22:16.5823719Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-08-26T23:22:16.5823817Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-08-26T23:22:16.5823880Z rank (Optional[int]): The rank of the node, if known. 2025-08-26T23:22:16.5823913Z Returns: 2025-08-26T23:22:16.5823946Z None 2025-08-26T23:22:16.5823978Z Example: 2025-08-26T23:22:16.5824029Z >>> # See DynamicRendezvousHandler class 2025-08-26T23:22:16.5824067Z >>> def _record( 2025-08-26T23:22:16.5824119Z ... self, 2025-08-26T23:22:16.5825152Z ... message: str, 2025-08-26T23:22:16.5825210Z ... node_state: NodeState = NodeState.RUNNING, 2025-08-26T23:22:16.5825254Z ... rank: Optional[int] = None, 2025-08-26T23:22:16.5825290Z ... ) -> None: 2025-08-26T23:22:16.5825337Z ... construct_and_record_rdzv_event( 2025-08-26T23:22:16.5825401Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-08-26T23:22:16.5825451Z ... run_id=self._settings.run_id, 2025-08-26T23:22:16.5825492Z ... message=message, 2025-08-26T23:22:16.5825534Z ... node_state=node_state, 2025-08-26T23:22:16.5825581Z ... hostname=self._this_node.addr, 2025-08-26T23:22:16.5825626Z ... pid=self._this_node.pid, 2025-08-26T23:22:16.5825676Z ... local_id=self._this_node.local_id, 2025-08-26T23:22:16.5825715Z ... rank=rank, 2025-08-26T23:22:16.5825749Z ... ) 2025-08-26T23:22:16.5825799Z 2025-08-26T23:22:16.5825890Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5825921Z 2025-08-26T23:22:16.5825959Z warnings.warn(msg) 2025-08-26T23:22:16.5825989Z 2025-08-26T23:22:16.5826062Z --- Parse Warning: 126 / 146 --- 2025-08-26T23:22:16.5826394Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-08-26T23:22:16.5826488Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5827507Z 2025-08-26T23:22:16.5827591Z RemoteModule instance can only be created after RPC initialization. 2025-08-26T23:22:16.5827622Z 2025-08-26T23:22:16.5827696Z It creates a user-specified module on a specified remote node. 2025-08-26T23:22:16.5827804Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T23:22:16.5827846Z executed on the remote node. 2025-08-26T23:22:16.5827930Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T23:22:16.5827990Z gradients back to the corresponding remote module. 2025-08-26T23:22:16.5828133Z It can be shared across processors using `RPC framework `__, 2025-08-26T23:22:16.5828209Z without incurring any overheads of copying the actual module, 2025-08-26T23:22:16.5828286Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-08-26T23:22:16.5828330Z pointing to the remote module. 2025-08-26T23:22:16.5828360Z 2025-08-26T23:22:16.5828434Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-08-26T23:22:16.5828508Z the ``forward`` method of the module returned by the ``module_cls``. 2025-08-26T23:22:16.5828541Z 2025-08-26T23:22:16.5828652Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-08-26T23:22:16.5828684Z 2025-08-26T23:22:16.5828773Z Particularly, to create a hybrid model, typically the local modules should be 2025-08-26T23:22:16.5828901Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-08-26T23:22:16.5828937Z Hybrid Example: 2025-08-26T23:22:16.5829970Z >>> class HybridModel(nn.Module): 2025-08-26T23:22:16.5830018Z >>> def __init__(self) -> None: 2025-08-26T23:22:16.5830063Z >>> nn.Module.__init__(self) 2025-08-26T23:22:16.5830118Z >>> self.remote_embedding = RemoteModule(...) 2025-08-26T23:22:16.5830169Z >>> self.local_linear = nn.Linear(...) 2025-08-26T23:22:16.5830200Z 2025-08-26T23:22:16.5830273Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T23:22:16.5830534Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T23:22:16.5830611Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-08-26T23:22:16.5830662Z ``def forward(input: Tensor) -> Tensor:`` and 2025-08-26T23:22:16.5830727Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-08-26T23:22:16.5830757Z 2025-08-26T23:22:16.5830791Z .. note:: 2025-08-26T23:22:16.5830851Z If the remote module is placed on a cuda device, 2025-08-26T23:22:16.5830934Z any input CPU tensors will be automatically moved to the same cuda device, 2025-08-26T23:22:16.5831073Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-08-26T23:22:16.5831103Z 2025-08-26T23:22:16.5831137Z Args: 2025-08-26T23:22:16.5831244Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:22:16.5831374Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T23:22:16.5831409Z formats: 2025-08-26T23:22:16.5831440Z 2025-08-26T23:22:16.5832497Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T23:22:16.5832558Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T23:22:16.5832588Z 2025-08-26T23:22:16.5832679Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:22:16.5832726Z module_cls (nn.Module): For example, 2025-08-26T23:22:16.5832771Z >>> class MyModule(nn.Module): 2025-08-26T23:22:16.5832812Z >>> def forward(input): 2025-08-26T23:22:16.5832854Z >>> return input + 1 2025-08-26T23:22:16.5832886Z >>> 2025-08-26T23:22:16.5832928Z >>> module_cls = MyModule 2025-08-26T23:22:16.5833029Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T23:22:16.5833104Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T23:22:16.5833203Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T23:22:16.5833291Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T23:22:16.5833370Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T23:22:16.5833478Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T23:22:16.5833509Z 2025-08-26T23:22:16.5833542Z Returns: 2025-08-26T23:22:16.5833630Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:22:16.5833714Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T23:22:16.5833812Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:22:16.5834942Z on the user-provided module on the remote side. 2025-08-26T23:22:16.5834977Z 2025-08-26T23:22:16.5835013Z Example:: 2025-08-26T23:22:16.5835072Z Run the following code in two different processes: 2025-08-26T23:22:16.5835102Z 2025-08-26T23:22:16.5835150Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5835188Z >>> # On worker 0: 2025-08-26T23:22:16.5835225Z >>> import torch 2025-08-26T23:22:16.5835278Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5835322Z >>> from torch import nn, Tensor 2025-08-26T23:22:16.5835403Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:22:16.5835435Z >>> 2025-08-26T23:22:16.5835491Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:22:16.5835539Z >>> remote_linear_module = RemoteModule( 2025-08-26T23:22:16.5835590Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:22:16.5835651Z >>> ) 2025-08-26T23:22:16.5835694Z >>> input = torch.randn(128, 20) 2025-08-26T23:22:16.5835755Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T23:22:16.5835795Z >>> ret = ret_fut.wait() 2025-08-26T23:22:16.5835834Z >>> rpc.shutdown() 2025-08-26T23:22:16.5835865Z 2025-08-26T23:22:16.5835900Z >>> # On worker 1: 2025-08-26T23:22:16.5836931Z >>> import torch 2025-08-26T23:22:16.5836984Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5837016Z >>> 2025-08-26T23:22:16.5837071Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:22:16.5837110Z >>> rpc.shutdown() 2025-08-26T23:22:16.5837140Z 2025-08-26T23:22:16.5837231Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5837262Z 2025-08-26T23:22:16.5837299Z warnings.warn(msg) 2025-08-26T23:22:16.5837329Z 2025-08-26T23:22:16.5837406Z --- Parse Warning: 127 / 146 --- 2025-08-26T23:22:16.5837781Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-08-26T23:22:16.5837875Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5837905Z 2025-08-26T23:22:16.5838019Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-08-26T23:22:16.5838050Z 2025-08-26T23:22:16.5838165Z This alternate initialization method can be particularly useful if we want to create multiple 2025-08-26T23:22:16.5838275Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-08-26T23:22:16.5838307Z 2025-08-26T23:22:16.5838405Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-08-26T23:22:16.5838499Z which is not supported. The recommended way is as follows: 2025-08-26T23:22:16.5838530Z 2025-08-26T23:22:16.5839564Z 1. the sender creates a RemoteModule; 2025-08-26T23:22:16.5839623Z 2. the sender sends its ``module_rref`` over RPC; 2025-08-26T23:22:16.5839741Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-08-26T23:22:16.5839771Z 2025-08-26T23:22:16.5839825Z Example:: 2025-08-26T23:22:16.5839884Z Run the following code in two different processes: 2025-08-26T23:22:16.5839914Z 2025-08-26T23:22:16.5839961Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5839997Z >>> # On worker 0: 2025-08-26T23:22:16.5840034Z >>> import torch 2025-08-26T23:22:16.5840083Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5840127Z >>> from torch import nn, Tensor 2025-08-26T23:22:16.5840213Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:22:16.5840246Z >>> 2025-08-26T23:22:16.5840300Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:22:16.5840403Z >>> remote_module = RemoteModule( 2025-08-26T23:22:16.5840457Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:22:16.5840489Z >>> ) 2025-08-26T23:22:16.5840521Z >>> 2025-08-26T23:22:16.5840566Z >>> remote_module1 = rpc.rpc_sync( 2025-08-26T23:22:16.5840608Z >>> "worker1/cpu", 2025-08-26T23:22:16.5841657Z >>> RemoteModule.init_from_module_rref, 2025-08-26T23:22:16.5841721Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-08-26T23:22:16.5841753Z >>> ) 2025-08-26T23:22:16.5841790Z >>> rpc.shutdown() 2025-08-26T23:22:16.5841820Z 2025-08-26T23:22:16.5841857Z >>> # On worker 1: 2025-08-26T23:22:16.5841892Z >>> import torch 2025-08-26T23:22:16.5841945Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5842012Z >>> 2025-08-26T23:22:16.5842067Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:22:16.5842104Z >>> rpc.shutdown() 2025-08-26T23:22:16.5842135Z 2025-08-26T23:22:16.5842166Z Args: 2025-08-26T23:22:16.5842274Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:22:16.5842375Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T23:22:16.5842411Z formats: 2025-08-26T23:22:16.5842441Z 2025-08-26T23:22:16.5842497Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T23:22:16.5842555Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T23:22:16.5842586Z 2025-08-26T23:22:16.5842675Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:22:16.5842786Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-08-26T23:22:16.5843814Z the created remote module. 2025-08-26T23:22:16.5843914Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T23:22:16.5843999Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T23:22:16.5844079Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T23:22:16.5844164Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T23:22:16.5844196Z 2025-08-26T23:22:16.5844228Z Returns: 2025-08-26T23:22:16.5844316Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:22:16.5844402Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-08-26T23:22:16.5844499Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:22:16.5844583Z on the user-provided module on the remote side. 2025-08-26T23:22:16.5844614Z 2025-08-26T23:22:16.5844704Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5844735Z 2025-08-26T23:22:16.5844773Z warnings.warn(msg) 2025-08-26T23:22:16.5844803Z 2025-08-26T23:22:16.5844877Z --- Parse Warning: 128 / 146 --- 2025-08-26T23:22:16.5845222Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-08-26T23:22:16.5845316Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5845346Z 2025-08-26T23:22:16.5845429Z A RemoteModule instance can only be created after RPC initialization. 2025-08-26T23:22:16.5845462Z 2025-08-26T23:22:16.5846522Z It creates a user-specified module on a specified remote node. 2025-08-26T23:22:16.5846610Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T23:22:16.5846653Z executed on the remote node. 2025-08-26T23:22:16.5846736Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T23:22:16.5846796Z gradients back to the corresponding remote module. 2025-08-26T23:22:16.5846826Z 2025-08-26T23:22:16.5846907Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-08-26T23:22:16.5846985Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-08-26T23:22:16.5847074Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-08-26T23:22:16.5847146Z and ``forward`` are the same as the ``forward`` method of the module 2025-08-26T23:22:16.5847190Z returned by the ``module_cls``. 2025-08-26T23:22:16.5847223Z 2025-08-26T23:22:16.5847315Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T23:22:16.5847406Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T23:22:16.5847486Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-08-26T23:22:16.5847517Z 2025-08-26T23:22:16.5847566Z | ``def forward(input: Tensor) -> Tensor:`` 2025-08-26T23:22:16.5847632Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-08-26T23:22:16.5847662Z 2025-08-26T23:22:16.5847695Z Args: 2025-08-26T23:22:16.5847802Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T23:22:16.5848909Z The format should be "/", where the device field can be parsed as torch.device type. 2025-08-26T23:22:16.5848967Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-08-26T23:22:16.5849077Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T23:22:16.5849167Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-08-26T23:22:16.5849199Z 2025-08-26T23:22:16.5849243Z >>> class MyModule(nn.Module): 2025-08-26T23:22:16.5849285Z >>> def forward(input): 2025-08-26T23:22:16.5849326Z >>> return input + 1 2025-08-26T23:22:16.5849359Z >>> 2025-08-26T23:22:16.5849401Z >>> module_cls = MyModule 2025-08-26T23:22:16.5849432Z 2025-08-26T23:22:16.5849506Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T23:22:16.5849577Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T23:22:16.5849607Z 2025-08-26T23:22:16.5849640Z Returns: 2025-08-26T23:22:16.5849728Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T23:22:16.5849830Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T23:22:16.5849927Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T23:22:16.5849984Z on the user-provided module on the remote side. 2025-08-26T23:22:16.5850015Z 2025-08-26T23:22:16.5850049Z Example:: 2025-08-26T23:22:16.5850107Z Run the following code in two different processes: 2025-08-26T23:22:16.5851197Z 2025-08-26T23:22:16.5851280Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5851318Z >>> # On worker 0: 2025-08-26T23:22:16.5851354Z >>> import torch 2025-08-26T23:22:16.5851404Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5851448Z >>> from torch import nn, Tensor 2025-08-26T23:22:16.5851530Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T23:22:16.5851563Z >>> 2025-08-26T23:22:16.5851618Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T23:22:16.5851672Z >>> remote_linear_module = RemoteModule( 2025-08-26T23:22:16.5851723Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T23:22:16.5851755Z >>> ) 2025-08-26T23:22:16.5851796Z >>> input = torch.randn(128, 20) 2025-08-26T23:22:16.5851855Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T23:22:16.5851895Z >>> ret = ret_fut.wait() 2025-08-26T23:22:16.5851933Z >>> rpc.shutdown() 2025-08-26T23:22:16.5851966Z 2025-08-26T23:22:16.5852003Z >>> # On worker 1: 2025-08-26T23:22:16.5852039Z >>> import torch 2025-08-26T23:22:16.5852088Z >>> import torch.distributed.rpc as rpc 2025-08-26T23:22:16.5852120Z >>> 2025-08-26T23:22:16.5853152Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T23:22:16.5853190Z >>> rpc.shutdown() 2025-08-26T23:22:16.5853220Z 2025-08-26T23:22:16.5853294Z Furthermore, a more practical example that is combined with 2025-08-26T23:22:16.5853487Z `DistributedDataParallel `__ (DDP) 2025-08-26T23:22:16.5853604Z can be found in this `tutorial `__. 2025-08-26T23:22:16.5853635Z 2025-08-26T23:22:16.5853725Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5853756Z 2025-08-26T23:22:16.5853796Z warnings.warn(msg) 2025-08-26T23:22:16.5853826Z 2025-08-26T23:22:16.5853901Z --- Parse Warning: 129 / 146 --- 2025-08-26T23:22:16.5854186Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/init.py line=142. 2025-08-26T23:22:16.5854286Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5854392Z Return the recommended gain value for the given nonlinearity function. 2025-08-26T23:22:16.5854423Z 2025-08-26T23:22:16.5854465Z The values are as follows: 2025-08-26T23:22:16.5854496Z 2025-08-26T23:22:16.5854543Z ================= ==================================================== 2025-08-26T23:22:16.5854584Z nonlinearity gain 2025-08-26T23:22:16.5854628Z ================= ==================================================== 2025-08-26T23:22:16.5854673Z Linear / Identity :math:`1` 2025-08-26T23:22:16.5855694Z Conv{1,2,3}D :math:`1` 2025-08-26T23:22:16.5855734Z Sigmoid :math:`1` 2025-08-26T23:22:16.5855780Z Tanh :math:`\frac{5}{3}` 2025-08-26T23:22:16.5855823Z ReLU :math:`\sqrt{2}` 2025-08-26T23:22:16.5855895Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-08-26T23:22:16.5855940Z SELU :math:`\frac{3}{4}` 2025-08-26T23:22:16.5856011Z ================= ==================================================== 2025-08-26T23:22:16.5856042Z 2025-08-26T23:22:16.5856079Z .. warning:: 2025-08-26T23:22:16.5856148Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-08-26T23:22:16.5856237Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-08-26T23:22:16.5856316Z This gives the initial weights a variance of ``1 / N``, 2025-08-26T23:22:16.5856398Z which is necessary to induce a stable fixed point in the forward pass. 2025-08-26T23:22:16.5856479Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-08-26T23:22:16.5856547Z effect for more stable gradient flow in rectangular layers. 2025-08-26T23:22:16.5856578Z 2025-08-26T23:22:16.5856610Z Args: 2025-08-26T23:22:16.5856682Z nonlinearity: the non-linear function (`nn.functional` name) 2025-08-26T23:22:16.5856753Z param: optional parameter for the non-linear function 2025-08-26T23:22:16.5856783Z 2025-08-26T23:22:16.5856818Z Examples: 2025-08-26T23:22:16.5856864Z >>> gain = nn.init.calculate_gain( 2025-08-26T23:22:16.5857888Z ... "leaky_relu", 0.2 2025-08-26T23:22:16.5857942Z ... ) # leaky_relu with negative_slope=0.2 2025-08-26T23:22:16.5857973Z 2025-08-26T23:22:16.5858145Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-08-26T23:22:16.5858177Z 2025-08-26T23:22:16.5858266Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5858298Z 2025-08-26T23:22:16.5858335Z warnings.warn(msg) 2025-08-26T23:22:16.5858365Z 2025-08-26T23:22:16.5858439Z --- Parse Warning: 130 / 146 --- 2025-08-26T23:22:16.5858772Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-08-26T23:22:16.5858887Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5858917Z 2025-08-26T23:22:16.5859002Z Context manager for training with uneven inputs across processes in DDP. 2025-08-26T23:22:16.5859032Z 2025-08-26T23:22:16.5859115Z This context manager will keep track of already-joined DDP processes, 2025-08-26T23:22:16.5859191Z and "shadow" the forward and backward passes by inserting collective 2025-08-26T23:22:16.5859275Z communication operations to match with the ones created by non-joined 2025-08-26T23:22:16.5859356Z DDP processes. This will ensure each collective call has a corresponding 2025-08-26T23:22:16.5859436Z call by already-joined DDP processes, preventing hangs or errors that 2025-08-26T23:22:16.5859530Z would otherwise happen when training with uneven inputs across 2025-08-26T23:22:16.5860671Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-08-26T23:22:16.5860749Z specified to be ``True``, all trainers will throw an error once one rank 2025-08-26T23:22:16.5860823Z runs out of inputs, allowing these errors to be caught and handled 2025-08-26T23:22:16.5860867Z according to application logic. 2025-08-26T23:22:16.5860899Z 2025-08-26T23:22:16.5860978Z Once all DDP processes have joined, the context manager will broadcast 2025-08-26T23:22:16.5861059Z the model corresponding to the last joined process to all processes to 2025-08-26T23:22:16.5861117Z ensure the model is the same across all processes 2025-08-26T23:22:16.5861162Z (which is guaranteed by DDP). 2025-08-26T23:22:16.5861192Z 2025-08-26T23:22:16.5861266Z To use this to enable training with uneven inputs across processes, 2025-08-26T23:22:16.5861376Z simply wrap this context manager around your training loop. No further 2025-08-26T23:22:16.5861448Z modifications to the model or data loading is required. 2025-08-26T23:22:16.5861478Z 2025-08-26T23:22:16.5861514Z .. warning:: 2025-08-26T23:22:16.5861590Z If the model or training loop this context manager is wrapped around 2025-08-26T23:22:16.5861659Z has additional distributed collective operations, such as 2025-08-26T23:22:16.5861745Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-08-26T23:22:16.5861820Z ``throw_on_early_termination`` must be enabled. This is because this 2025-08-26T23:22:16.5861896Z context manager is not aware of non-DDP collective communication. 2025-08-26T23:22:16.5861962Z This flag will cause all ranks to throw when any one rank 2025-08-26T23:22:16.5862038Z exhausts inputs, allowing these errors to be caught and recovered 2025-08-26T23:22:16.5863119Z from across all ranks. 2025-08-26T23:22:16.5863153Z 2025-08-26T23:22:16.5863187Z Args: 2025-08-26T23:22:16.5863260Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-08-26T23:22:16.5863333Z gradients by the initial ``world_size`` DDP training was launched 2025-08-26T23:22:16.5863397Z with. If ``False``, will compute the effective world size 2025-08-26T23:22:16.5863465Z (number of ranks that have not depleted their inputs yet) and 2025-08-26T23:22:16.5863525Z divide gradients by that during allreduce. Set 2025-08-26T23:22:16.5863591Z ``divide_by_initial_world_size=True`` to ensure every input 2025-08-26T23:22:16.5863667Z sample including the uneven inputs have equal weight in terms of 2025-08-26T23:22:16.5863731Z how much they contribute to the global gradient. This is 2025-08-26T23:22:16.5863796Z achieved by always dividing the gradient by the initial 2025-08-26T23:22:16.5863863Z ``world_size`` even when we encounter uneven inputs. If you set 2025-08-26T23:22:16.5863954Z this to ``False``, we divide the gradient by the remaining 2025-08-26T23:22:16.5864024Z number of nodes. This ensures parity with training on a smaller 2025-08-26T23:22:16.5864091Z ``world_size`` although it also means the uneven inputs would 2025-08-26T23:22:16.5864160Z contribute more towards the global gradient. Typically, you 2025-08-26T23:22:16.5864230Z would want to set this to ``True`` for cases where the last few 2025-08-26T23:22:16.5864300Z inputs of your training job are uneven. In extreme cases, where 2025-08-26T23:22:16.5864367Z there is a large discrepancy in the number of inputs, setting 2025-08-26T23:22:16.5864422Z this to ``False`` might provide better results. 2025-08-26T23:22:16.5865488Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-08-26T23:22:16.5865553Z in ``enable=False`` to disable in cases where you know that 2025-08-26T23:22:16.5865658Z inputs are even across participating processes. Default is 2025-08-26T23:22:16.5865693Z ``True``. 2025-08-26T23:22:16.5865762Z throw_on_early_termination (bool): Whether to throw an error 2025-08-26T23:22:16.5865826Z or continue training when at least one rank has exhausted 2025-08-26T23:22:16.5865893Z inputs. If ``True``, will throw upon the first rank reaching end 2025-08-26T23:22:16.5865957Z of data. If ``False``, will continue training with a smaller 2025-08-26T23:22:16.5866028Z effective world size until all ranks are joined. Note that if 2025-08-26T23:22:16.5866077Z this flag is specified, then the flag 2025-08-26T23:22:16.5866142Z ``divide_by_initial_world_size`` would be ignored. Default 2025-08-26T23:22:16.5866179Z is ``False``. 2025-08-26T23:22:16.5866211Z 2025-08-26T23:22:16.5866241Z 2025-08-26T23:22:16.5866290Z Example:: 2025-08-26T23:22:16.5866321Z 2025-08-26T23:22:16.5866369Z >>> # xdoctest: +SKIP("Distributed") 2025-08-26T23:22:16.5866407Z >>> import torch 2025-08-26T23:22:16.5866454Z >>> import torch.distributed as dist 2025-08-26T23:22:16.5866489Z >>> import os 2025-08-26T23:22:16.5866538Z >>> import torch.multiprocessing as mp 2025-08-26T23:22:16.5866580Z >>> import torch.nn as nn 2025-08-26T23:22:16.5867602Z >>> # On each spawned worker 2025-08-26T23:22:16.5867661Z >>> def worker(rank): 2025-08-26T23:22:16.5867729Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-08-26T23:22:16.5867776Z >>> torch.cuda.set_device(rank) 2025-08-26T23:22:16.5867830Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T23:22:16.5867901Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-08-26T23:22:16.5867957Z >>> model, device_ids=[rank], output_device=rank 2025-08-26T23:22:16.5867993Z >>> ) 2025-08-26T23:22:16.5868048Z >>> # Rank 1 gets one more input than rank 0. 2025-08-26T23:22:16.5868119Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-08-26T23:22:16.5868160Z >>> with model.join(): 2025-08-26T23:22:16.5868201Z >>> for _ in range(5): 2025-08-26T23:22:16.5868244Z >>> for inp in inputs: 2025-08-26T23:22:16.5868290Z >>> loss = model(inp).sum() 2025-08-26T23:22:16.5868335Z >>> loss.backward() 2025-08-26T23:22:16.5868406Z >>> # Without the join() API, the below synchronization will hang 2025-08-26T23:22:16.5868462Z >>> # blocking for rank 1's allreduce to complete. 2025-08-26T23:22:16.5868512Z >>> torch.cuda.synchronize(device=rank) 2025-08-26T23:22:16.5868544Z 2025-08-26T23:22:16.5868636Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5868668Z 2025-08-26T23:22:16.5868720Z warnings.warn(msg) 2025-08-26T23:22:16.5869735Z 2025-08-26T23:22:16.5869809Z --- Parse Warning: 131 / 146 --- 2025-08-26T23:22:16.5870168Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-08-26T23:22:16.5870264Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5870295Z 2025-08-26T23:22:16.5870460Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-08-26T23:22:16.5870492Z 2025-08-26T23:22:16.5870568Z Registers an optimizer with DDP such that the optimization for a 2025-08-26T23:22:16.5870644Z parameter will run immediately when that parameter's gradient is 2025-08-26T23:22:16.5870719Z finished with reduction, instead of waiting for all parameters' 2025-08-26T23:22:16.5870833Z gradients to finish reduction. This can result in a training speedup 2025-08-26T23:22:16.5870911Z depending on your workload since the optimizer can run while gradient 2025-08-26T23:22:16.5870992Z reduction for other parameters are still ongoing. In addition, this has 2025-08-26T23:22:16.5871071Z the potential to reduce peak memory consumption during training, as it 2025-08-26T23:22:16.5871146Z only needs to load the per-parameter optimizer states of a single 2025-08-26T23:22:16.5871223Z parameter at a time, instead of loading all per-parameter optimizer 2025-08-26T23:22:16.5871259Z states at once. 2025-08-26T23:22:16.5871290Z 2025-08-26T23:22:16.5871322Z Args: 2025-08-26T23:22:16.5871394Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-08-26T23:22:16.5871436Z as a fused optimizer. 2025-08-26T23:22:16.5872498Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-08-26T23:22:16.5872609Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-08-26T23:22:16.5872690Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-08-26T23:22:16.5872764Z Optimizers. If this is omitted, all DDP model parameters will be 2025-08-26T23:22:16.5872799Z optimized. 2025-08-26T23:22:16.5872872Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-08-26T23:22:16.5872920Z 2025-08-26T23:22:16.5872957Z .. warning :: 2025-08-26T23:22:16.5873033Z _register_fused_optim should only be called once on a DDP instance, 2025-08-26T23:22:16.5873108Z and registering multiple fused optimizers for the same DDP model 2025-08-26T23:22:16.5873158Z is not currently supported. Please ping 2025-08-26T23:22:16.5873240Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:22:16.5873280Z for your use case. 2025-08-26T23:22:16.5873311Z 2025-08-26T23:22:16.5873349Z .. warning :: 2025-08-26T23:22:16.5873419Z _register_fused_optim and register_comm_hook currently do not 2025-08-26T23:22:16.5873498Z compose together, meaning that custom DDP communication hooks are 2025-08-26T23:22:16.5873564Z not supported with overlapped optimizers. Please ping 2025-08-26T23:22:16.5873645Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:22:16.5873684Z for your use case. 2025-08-26T23:22:16.5873716Z 2025-08-26T23:22:16.5873749Z .. warning :: 2025-08-26T23:22:16.5874871Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-08-26T23:22:16.5874921Z with overlapped optimizer. Please ping 2025-08-26T23:22:16.5875002Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T23:22:16.5875039Z for your use case. 2025-08-26T23:22:16.5875071Z 2025-08-26T23:22:16.5875107Z Example:: 2025-08-26T23:22:16.5875162Z 2025-08-26T23:22:16.5875217Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-08-26T23:22:16.5875324Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-08-26T23:22:16.5875400Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-08-26T23:22:16.5875436Z >>> lr = 1e-2 2025-08-26T23:22:16.5875475Z >>> betas = (0.9, 0.99) 2025-08-26T23:22:16.5875511Z >>> eps = 1e-6 2025-08-26T23:22:16.5875596Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-08-26T23:22:16.5875644Z >>> # Example with subset of parameters 2025-08-26T23:22:16.5875698Z >>> params_to_opt = [list(net.parameters())[0]] 2025-08-26T23:22:16.5875740Z >>> net._register_fused_optim( 2025-08-26T23:22:16.5875826Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-08-26T23:22:16.5875860Z ... ) 2025-08-26T23:22:16.5875891Z 2025-08-26T23:22:16.5875995Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5877025Z 2025-08-26T23:22:16.5877063Z warnings.warn(msg) 2025-08-26T23:22:16.5877094Z 2025-08-26T23:22:16.5877168Z --- Parse Warning: 132 / 146 --- 2025-08-26T23:22:16.5877467Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/sparse.py line=272. 2025-08-26T23:22:16.5877560Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5877672Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-08-26T23:22:16.5877702Z 2025-08-26T23:22:16.5877817Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-08-26T23:22:16.5877878Z and with 2D inputs, this class 2025-08-26T23:22:16.5877911Z 2025-08-26T23:22:16.5878020Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-08-26T23:22:16.5878129Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-08-26T23:22:16.5878229Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-08-26T23:22:16.5878275Z 2025-08-26T23:22:16.5878398Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-08-26T23:22:16.5878433Z operations. 2025-08-26T23:22:16.5878463Z 2025-08-26T23:22:16.5878555Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-08-26T23:22:16.5878640Z pass. This scales the output of the Embedding before performing a weighted 2025-08-26T23:22:16.5878735Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-08-26T23:22:16.5878822Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-08-26T23:22:16.5879847Z :attr:`per_sample_weights`. 2025-08-26T23:22:16.5879879Z 2025-08-26T23:22:16.5879910Z Args: 2025-08-26T23:22:16.5879980Z num_embeddings (int): size of the dictionary of embeddings 2025-08-26T23:22:16.5880047Z embedding_dim (int): the size of each embedding vector 2025-08-26T23:22:16.5880158Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-08-26T23:22:16.5880216Z is renormalized to have norm :attr:`max_norm`. 2025-08-26T23:22:16.5880403Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-08-26T23:22:16.5880517Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-08-26T23:22:16.5880614Z the words in the mini-batch. Default ``False``. 2025-08-26T23:22:16.5880684Z Note: this option is not supported when ``mode="max"``. 2025-08-26T23:22:16.5880776Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-08-26T23:22:16.5880859Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-08-26T23:22:16.5880939Z into consideration. ``"mean"`` computes the average of the values 2025-08-26T23:22:16.5881005Z in the bag, ``"max"`` computes the max value over each bag. 2025-08-26T23:22:16.5881055Z Default: ``"mean"`` 2025-08-26T23:22:16.5881211Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-08-26T23:22:16.5881305Z Notes for more details regarding sparse gradients. Note: this option is not 2025-08-26T23:22:16.5881358Z supported when ``mode="max"``. 2025-08-26T23:22:16.5881489Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-08-26T23:22:16.5881570Z is equivalent to the size of `indices`. This matches the CSR format. 2025-08-26T23:22:16.5882683Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-08-26T23:22:16.5882784Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-08-26T23:22:16.5882873Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-08-26T23:22:16.5883002Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-08-26T23:22:16.5883089Z zeros, but can be updated to another value to be used as the padding vector. 2025-08-26T23:22:16.5883177Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-08-26T23:22:16.5883242Z reduction. 2025-08-26T23:22:16.5883275Z 2025-08-26T23:22:16.5883309Z Attributes: 2025-08-26T23:22:16.5883422Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-08-26T23:22:16.5883477Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-08-26T23:22:16.5883508Z 2025-08-26T23:22:16.5883545Z Examples:: 2025-08-26T23:22:16.5883576Z 2025-08-26T23:22:16.5883643Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-08-26T23:22:16.5883706Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-08-26T23:22:16.5883759Z >>> # a batch of 2 samples of 4 indices each 2025-08-26T23:22:16.5883830Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T23:22:16.5883888Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T23:22:16.5883947Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T23:22:16.5883995Z >>> embedding_sum(input, offsets) 2025-08-26T23:22:16.5884039Z tensor([[-0.8861, -5.4350, -0.0523], 2025-08-26T23:22:16.5885068Z [ 1.1306, -2.5798, -1.0044]]) 2025-08-26T23:22:16.5885099Z 2025-08-26T23:22:16.5885144Z >>> # Example with padding_idx 2025-08-26T23:22:16.5885219Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-08-26T23:22:16.5885290Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T23:22:16.5885364Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T23:22:16.5885410Z >>> embedding_sum(input, offsets) 2025-08-26T23:22:16.5885453Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-08-26T23:22:16.5885495Z [-0.7082, 3.2145, -2.6251]]) 2025-08-26T23:22:16.5885526Z 2025-08-26T23:22:16.5885592Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-08-26T23:22:16.5885650Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-08-26T23:22:16.5885710Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-08-26T23:22:16.5885754Z embedding.weight, 2025-08-26T23:22:16.5885807Z padding_idx=embedding.padding_idx, 2025-08-26T23:22:16.5885846Z mode='sum') 2025-08-26T23:22:16.5885878Z 2025-08-26T23:22:16.5885984Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5886016Z 2025-08-26T23:22:16.5886055Z warnings.warn(msg) 2025-08-26T23:22:16.5886085Z 2025-08-26T23:22:16.5887137Z --- Parse Warning: 133 / 146 --- 2025-08-26T23:22:16.5887455Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py line=186. 2025-08-26T23:22:16.5887551Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5887609Z Take in and process masked source/target sequences. 2025-08-26T23:22:16.5887641Z 2025-08-26T23:22:16.5887676Z .. note:: 2025-08-26T23:22:16.5887708Z 2025-08-26T23:22:16.5887846Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-08-26T23:22:16.5887925Z not allowed to participate in the attention, 2025-08-26T23:22:16.5887998Z which is the opposite of the definition for :attr:`attn_mask` 2025-08-26T23:22:16.5888069Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-08-26T23:22:16.5888099Z 2025-08-26T23:22:16.5888133Z Args: 2025-08-26T23:22:16.5888185Z src: the sequence to the encoder (required). 2025-08-26T23:22:16.5888251Z tgt: the sequence to the decoder (required). 2025-08-26T23:22:16.5888320Z src_mask: the additive mask for the src sequence (optional). 2025-08-26T23:22:16.5888385Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-08-26T23:22:16.5888460Z memory_mask: the additive mask for the encoder output (optional). 2025-08-26T23:22:16.5888542Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-08-26T23:22:16.5888626Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-08-26T23:22:16.5888719Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-08-26T23:22:16.5888794Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-08-26T23:22:16.5889834Z Default: ``None``; try to detect a causal mask. 2025-08-26T23:22:16.5889873Z Warning: 2025-08-26T23:22:16.5889938Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-08-26T23:22:16.5890002Z the causal mask. Providing incorrect hints can result in 2025-08-26T23:22:16.5890064Z incorrect execution, including forward and backward 2025-08-26T23:22:16.5890107Z compatibility. 2025-08-26T23:22:16.5890182Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-08-26T23:22:16.5890240Z Default: ``None``; try to detect a causal mask. 2025-08-26T23:22:16.5890300Z Warning: 2025-08-26T23:22:16.5890418Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-08-26T23:22:16.5890483Z the causal mask. Providing incorrect hints can result in 2025-08-26T23:22:16.5890543Z incorrect execution, including forward and backward 2025-08-26T23:22:16.5890583Z compatibility. 2025-08-26T23:22:16.5890650Z memory_is_causal: If specified, applies a causal mask as 2025-08-26T23:22:16.5890690Z ``memory_mask``. 2025-08-26T23:22:16.5890732Z Default: ``False``. 2025-08-26T23:22:16.5890768Z Warning: 2025-08-26T23:22:16.5890823Z ``memory_is_causal`` provides a hint that 2025-08-26T23:22:16.5890885Z ``memory_mask`` is the causal mask. Providing incorrect 2025-08-26T23:22:16.5890945Z hints can result in incorrect execution, including 2025-08-26T23:22:16.5891032Z forward and backward compatibility. 2025-08-26T23:22:16.5892057Z 2025-08-26T23:22:16.5892092Z Shape: 2025-08-26T23:22:16.5892186Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-08-26T23:22:16.5892236Z `(N, S, E)` if `batch_first=True`. 2025-08-26T23:22:16.5892324Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T23:22:16.5892369Z `(N, T, E)` if `batch_first=True`. 2025-08-26T23:22:16.5892442Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-08-26T23:22:16.5892511Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-08-26T23:22:16.5892558Z - memory_mask: :math:`(T, S)`. 2025-08-26T23:22:16.5892646Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T23:22:16.5892762Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-08-26T23:22:16.5892851Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T23:22:16.5892883Z 2025-08-26T23:22:16.5892997Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-08-26T23:22:16.5893095Z positions. If a BoolTensor is provided, positions with ``True`` 2025-08-26T23:22:16.5893189Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-08-26T23:22:16.5893253Z is provided, it will be added to the attention weight. 2025-08-26T23:22:16.5893361Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-08-26T23:22:16.5893438Z the attention. If a BoolTensor is provided, the positions with the 2025-08-26T23:22:16.5893552Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-08-26T23:22:16.5893584Z 2025-08-26T23:22:16.5893676Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T23:22:16.5894701Z `(N, T, E)` if `batch_first=True`. 2025-08-26T23:22:16.5894733Z 2025-08-26T23:22:16.5894824Z Note: Due to the multi-head attention architecture in the transformer model, 2025-08-26T23:22:16.5894910Z the output sequence length of a transformer is same as the input sequence 2025-08-26T23:22:16.5894959Z (i.e. target) length of the decoder. 2025-08-26T23:22:16.5894990Z 2025-08-26T23:22:16.5895104Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-08-26T23:22:16.5895160Z batch size, :math:`E` is the feature number 2025-08-26T23:22:16.5895232Z 2025-08-26T23:22:16.5895268Z Examples: 2025-08-26T23:22:16.5895310Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5895357Z >>> output = transformer_model( 2025-08-26T23:22:16.5895414Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-08-26T23:22:16.5895449Z ... ) 2025-08-26T23:22:16.5895481Z 2025-08-26T23:22:16.5895574Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5895605Z 2025-08-26T23:22:16.5895643Z warnings.warn(msg) 2025-08-26T23:22:16.5895673Z 2025-08-26T23:22:16.5895749Z --- Parse Warning: 134 / 146 --- 2025-08-26T23:22:16.5896047Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/pooling.py line=410. 2025-08-26T23:22:16.5897142Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5897204Z Computes a partial inverse of :class:`MaxPool2d`. 2025-08-26T23:22:16.5897237Z 2025-08-26T23:22:16.5897331Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-08-26T23:22:16.5897362Z 2025-08-26T23:22:16.5897443Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-08-26T23:22:16.5897531Z including the indices of the maximal values and computes a partial inverse 2025-08-26T23:22:16.5897589Z in which all non-maximal values are set to zero. 2025-08-26T23:22:16.5897620Z 2025-08-26T23:22:16.5897652Z Note: 2025-08-26T23:22:16.5897763Z This operation may behave nondeterministically when the input indices has repeat values. 2025-08-26T23:22:16.5897898Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-08-26T23:22:16.5897949Z 2025-08-26T23:22:16.5898035Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-08-26T23:22:16.5898099Z sizes. Hence, the inversion process can get ambiguous. 2025-08-26T23:22:16.5898168Z To accommodate this, you can provide the needed output size 2025-08-26T23:22:16.5898244Z as an additional argument :attr:`output_size` in the forward call. 2025-08-26T23:22:16.5898315Z See the Inputs and Example below. 2025-08-26T23:22:16.5898347Z 2025-08-26T23:22:16.5898379Z Args: 2025-08-26T23:22:16.5898447Z kernel_size (int or tuple): Size of the max pooling window. 2025-08-26T23:22:16.5898512Z stride (int or tuple): Stride of the max pooling window. 2025-08-26T23:22:16.5899547Z It is set to :attr:`kernel_size` by default. 2025-08-26T23:22:16.5899617Z padding (int or tuple): Padding that was added to the input 2025-08-26T23:22:16.5899651Z 2025-08-26T23:22:16.5899687Z Inputs: 2025-08-26T23:22:16.5899736Z - `input`: the input Tensor to invert 2025-08-26T23:22:16.5899815Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-08-26T23:22:16.5899875Z - `output_size` (optional): the targeted output size 2025-08-26T23:22:16.5899907Z 2025-08-26T23:22:16.5899940Z Shape: 2025-08-26T23:22:16.5900013Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-08-26T23:22:16.5900091Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-08-26T23:22:16.5900122Z 2025-08-26T23:22:16.5900158Z .. math:: 2025-08-26T23:22:16.5900257Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-08-26T23:22:16.5900288Z 2025-08-26T23:22:16.5900323Z .. math:: 2025-08-26T23:22:16.5900478Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-08-26T23:22:16.5900548Z 2025-08-26T23:22:16.5900611Z or as given by :attr:`output_size` in the call operator 2025-08-26T23:22:16.5900642Z 2025-08-26T23:22:16.5900676Z Example:: 2025-08-26T23:22:16.5901705Z 2025-08-26T23:22:16.5901770Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-08-26T23:22:16.5901823Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-08-26T23:22:16.5901877Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-08-26T23:22:16.5901922Z [ 5., 6., 7., 8.], 2025-08-26T23:22:16.5901967Z [ 9., 10., 11., 12.], 2025-08-26T23:22:16.5902011Z [13., 14., 15., 16.]]]]) 2025-08-26T23:22:16.5902060Z >>> output, indices = pool(input) 2025-08-26T23:22:16.5902103Z >>> unpool(output, indices) 2025-08-26T23:22:16.5902179Z tensor([[[[ 0., 0., 0., 0.], 2025-08-26T23:22:16.5902220Z [ 0., 6., 0., 8.], 2025-08-26T23:22:16.5902260Z [ 0., 0., 0., 0.], 2025-08-26T23:22:16.5902301Z [ 0., 14., 0., 16.]]]]) 2025-08-26T23:22:16.5902378Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-08-26T23:22:16.5902434Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-08-26T23:22:16.5902481Z [ 6., 7., 8., 9., 10.], 2025-08-26T23:22:16.5902524Z [11., 12., 13., 14., 15.], 2025-08-26T23:22:16.5902570Z [16., 17., 18., 19., 20.]]]]) 2025-08-26T23:22:16.5902617Z >>> output, indices = pool(input) 2025-08-26T23:22:16.5902682Z >>> # This call will not work without specifying output_size 2025-08-26T23:22:16.5902761Z >>> unpool(output, indices, output_size=input.size()) 2025-08-26T23:22:16.5902805Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-08-26T23:22:16.5903820Z [ 0., 7., 0., 9., 0.], 2025-08-26T23:22:16.5903861Z [ 0., 0., 0., 0., 0.], 2025-08-26T23:22:16.5903902Z [ 0., 17., 0., 19., 0.]]]]) 2025-08-26T23:22:16.5903934Z 2025-08-26T23:22:16.5903964Z 2025-08-26T23:22:16.5904019Z 2025-08-26T23:22:16.5904112Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5904143Z 2025-08-26T23:22:16.5904181Z warnings.warn(msg) 2025-08-26T23:22:16.5904211Z 2025-08-26T23:22:16.5904283Z --- Parse Warning: 135 / 146 --- 2025-08-26T23:22:16.5904611Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1798. 2025-08-26T23:22:16.5904709Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5904783Z Creates a criterion that measures the triplet loss given input 2025-08-26T23:22:16.5904856Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-08-26T23:22:16.5904933Z positive, and negative examples, respectively), and a nonnegative, 2025-08-26T23:22:16.5905027Z real-valued function ("distance function") used to compute the relationship 2025-08-26T23:22:16.5905107Z between the anchor and positive example ("positive distance") and the 2025-08-26T23:22:16.5905166Z anchor and negative example ("negative distance"). 2025-08-26T23:22:16.5905197Z 2025-08-26T23:22:16.5905274Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-08-26T23:22:16.5905314Z can be described as: 2025-08-26T23:22:16.5906331Z 2025-08-26T23:22:16.5906385Z .. math:: 2025-08-26T23:22:16.5906442Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-08-26T23:22:16.5906503Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-08-26T23:22:16.5906534Z 2025-08-26T23:22:16.5906624Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-08-26T23:22:16.5906731Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-08-26T23:22:16.5906817Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-08-26T23:22:16.5906904Z between the positive and negative distances that is required for the loss to 2025-08-26T23:22:16.5906987Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-08-26T23:22:16.5907036Z that the distance function can handle. 2025-08-26T23:22:16.5907070Z 2025-08-26T23:22:16.5907117Z If :attr:`reduction` is not ``'none'`` 2025-08-26T23:22:16.5907176Z (default ``'mean'``), then: 2025-08-26T23:22:16.5907208Z 2025-08-26T23:22:16.5907241Z .. math:: 2025-08-26T23:22:16.5907276Z \ell(x, y) = 2025-08-26T23:22:16.5907314Z \begin{cases} 2025-08-26T23:22:16.5907388Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-08-26T23:22:16.5907459Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-08-26T23:22:16.5907494Z \end{cases} 2025-08-26T23:22:16.5908503Z 2025-08-26T23:22:16.5908590Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-08-26T23:22:16.5908682Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-08-26T23:22:16.5908712Z 2025-08-26T23:22:16.5908745Z Args: 2025-08-26T23:22:16.5908843Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-08-26T23:22:16.5908941Z quantifies the closeness of two tensors. If not specified, 2025-08-26T23:22:16.5909006Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-08-26T23:22:16.5909102Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-08-26T23:22:16.5909197Z between the positive and negative distances required for the loss to be 0. Larger 2025-08-26T23:22:16.5909315Z margins penalize cases where the negative examples are not distant enough from the 2025-08-26T23:22:16.5909381Z anchors, relative to the positives. Default: :math:`1`. 2025-08-26T23:22:16.5909471Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-08-26T23:22:16.5909564Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-08-26T23:22:16.5909653Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-08-26T23:22:16.5909752Z negative example than the anchor is, swaps the positive example and the anchor in 2025-08-26T23:22:16.5909807Z the loss computation. Default: ``False``. 2025-08-26T23:22:16.5909906Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-08-26T23:22:16.5909977Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T23:22:16.5910044Z ``'mean'``: the sum of the output will be divided by the number of 2025-08-26T23:22:16.5910129Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-08-26T23:22:16.5910160Z 2025-08-26T23:22:16.5911239Z 2025-08-26T23:22:16.5911274Z Shape: 2025-08-26T23:22:16.5911365Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-08-26T23:22:16.5911418Z as supported by the distance function. 2025-08-26T23:22:16.5911551Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-08-26T23:22:16.5911588Z otherwise. 2025-08-26T23:22:16.5911619Z 2025-08-26T23:22:16.5911652Z Examples: 2025-08-26T23:22:16.5911683Z 2025-08-26T23:22:16.5911725Z >>> # Initialize embeddings 2025-08-26T23:22:16.5911771Z >>> embedding = nn.Embedding(1000, 128) 2025-08-26T23:22:16.5911825Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:22:16.5911878Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:22:16.5911928Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-08-26T23:22:16.5911974Z >>> anchor = embedding(anchor_ids) 2025-08-26T23:22:16.5912022Z >>> positive = embedding(positive_ids) 2025-08-26T23:22:16.5912067Z >>> negative = embedding(negative_ids) 2025-08-26T23:22:16.5912100Z >>> 2025-08-26T23:22:16.5912145Z >>> # Built-in Distance Function 2025-08-26T23:22:16.5912205Z >>> triplet_loss = \ 2025-08-26T23:22:16.5912305Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-08-26T23:22:16.5913349Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:22:16.5913393Z >>> output.backward() 2025-08-26T23:22:16.5913425Z >>> 2025-08-26T23:22:16.5913467Z >>> # Custom Distance Function 2025-08-26T23:22:16.5913509Z >>> def l_infinity(x1, x2): 2025-08-26T23:22:16.5913570Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-08-26T23:22:16.5913603Z >>> 2025-08-26T23:22:16.5913673Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-08-26T23:22:16.5913713Z >>> triplet_loss = ( 2025-08-26T23:22:16.5913811Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-08-26T23:22:16.5913871Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:22:16.5913947Z >>> output.backward() 2025-08-26T23:22:16.5913978Z >>> 2025-08-26T23:22:16.5914026Z >>> # Custom Distance Function (Lambda) 2025-08-26T23:22:16.5914063Z >>> triplet_loss = ( 2025-08-26T23:22:16.5914117Z >>> nn.TripletMarginWithDistanceLoss( 2025-08-26T23:22:16.5914197Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-08-26T23:22:16.5914274Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T23:22:16.5914314Z >>> output.backward() 2025-08-26T23:22:16.5914347Z 2025-08-26T23:22:16.5914381Z Reference: 2025-08-26T23:22:16.5914614Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-08-26T23:22:16.5915682Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-08-26T23:22:16.5915716Z 2025-08-26T23:22:16.5915810Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-08-26T23:22:16.5915846Z 2025-08-26T23:22:16.5915884Z warnings.warn(msg) 2025-08-26T23:22:16.5915915Z 2025-08-26T23:22:16.5915989Z --- Parse Warning: 136 / 146 --- 2025-08-26T23:22:16.5916278Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1933. 2025-08-26T23:22:16.5916373Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5916429Z The Connectionist Temporal Classification loss. 2025-08-26T23:22:16.5916460Z 2025-08-26T23:22:16.5916592Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-08-26T23:22:16.5916715Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-08-26T23:22:16.5916856Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-08-26T23:22:16.5916961Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-08-26T23:22:16.5916991Z 2025-08-26T23:22:16.5917023Z Args: 2025-08-26T23:22:16.5917087Z blank (int, optional): blank label. Default :math:`0`. 2025-08-26T23:22:16.5917176Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-08-26T23:22:16.5917247Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T23:22:16.5917322Z ``'mean'``: the output losses will be divided by the target lengths and 2025-08-26T23:22:16.5918403Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-08-26T23:22:16.5918444Z Default: ``'mean'`` 2025-08-26T23:22:16.5918491Z zero_infinity (bool, optional): 2025-08-26T23:22:16.5918582Z Whether to zero infinite losses and the associated gradients. 2025-08-26T23:22:16.5918623Z Default: ``False`` 2025-08-26T23:22:16.5918692Z Infinite losses mainly occur when the inputs are too short 2025-08-26T23:22:16.5918738Z to be aligned to the targets. 2025-08-26T23:22:16.5918769Z 2025-08-26T23:22:16.5918804Z Shape: 2025-08-26T23:22:16.5918875Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-08-26T23:22:16.5918925Z where :math:`T = \text{input length}`, 2025-08-26T23:22:16.5918972Z :math:`N = \text{batch size}`, and 2025-08-26T23:22:16.5919032Z :math:`C = \text{number of classes (including blank)}`. 2025-08-26T23:22:16.5919114Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-08-26T23:22:16.5919166Z :func:`torch.nn.functional.log_softmax`). 2025-08-26T23:22:16.5919246Z - Targets: Tensor of size :math:`(N, S)` or 2025-08-26T23:22:16.5919307Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-08-26T23:22:16.5919357Z where :math:`N = \text{batch size}` and 2025-08-26T23:22:16.5919420Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-08-26T23:22:16.5919491Z It represents the target sequences. Each element in the target 2025-08-26T23:22:16.5919590Z sequence is a class index. And the target index cannot be blank (default=0). 2025-08-26T23:22:16.5919652Z In the :math:`(N, S)` form, targets are padded to the 2025-08-26T23:22:16.5920763Z length of the longest sequence, and stacked. 2025-08-26T23:22:16.5920835Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-08-26T23:22:16.5920893Z the targets are assumed to be un-padded and 2025-08-26T23:22:16.5920942Z concatenated within 1 dimension. 2025-08-26T23:22:16.5921022Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T23:22:16.5921097Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-08-26T23:22:16.5921170Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-08-26T23:22:16.5921253Z for each sequence to achieve masking under the assumption that sequences 2025-08-26T23:22:16.5921300Z are padded to equal lengths. 2025-08-26T23:22:16.5921378Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T23:22:16.5921454Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-08-26T23:22:16.5921534Z Lengths are specified for each sequence to achieve masking under the 2025-08-26T23:22:16.5921621Z assumption that sequences are padded to equal lengths. If target shape is 2025-08-26T23:22:16.5921688Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-08-26T23:22:16.5921808Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-08-26T23:22:16.5921875Z each target in a batch. Lengths must each be :math:`\leq S` 2025-08-26T23:22:16.5921963Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-08-26T23:22:16.5922048Z targets, the target_lengths must add up to the total length of the tensor. 2025-08-26T23:22:16.5922119Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-08-26T23:22:16.5922204Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-08-26T23:22:16.5922276Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-08-26T23:22:16.5923291Z 2025-08-26T23:22:16.5923326Z Examples: 2025-08-26T23:22:16.5923358Z 2025-08-26T23:22:16.5923425Z >>> # Target are to be padded 2025-08-26T23:22:16.5923473Z >>> T = 50 # Input sequence length 2025-08-26T23:22:16.5923527Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:22:16.5923567Z >>> N = 16 # Batch size 2025-08-26T23:22:16.5923651Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-08-26T23:22:16.5923721Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-08-26T23:22:16.5923754Z >>> 2025-08-26T23:22:16.5923826Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T23:22:16.5923905Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T23:22:16.5923937Z >>> 2025-08-26T23:22:16.5924008Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:22:16.5924086Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-08-26T23:22:16.5924140Z >>> 2025-08-26T23:22:16.5924219Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T23:22:16.5924267Z >>> target_lengths = torch.randint( 2025-08-26T23:22:16.5924305Z ... low=S_min, 2025-08-26T23:22:16.5924343Z ... high=S, 2025-08-26T23:22:16.5924380Z ... size=(N,), 2025-08-26T23:22:16.5924438Z ... dtype=torch.long, 2025-08-26T23:22:16.5925446Z ... ) 2025-08-26T23:22:16.5925489Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:22:16.5925557Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:22:16.5925597Z >>> loss.backward() 2025-08-26T23:22:16.5925628Z >>> 2025-08-26T23:22:16.5925660Z >>> 2025-08-26T23:22:16.5925707Z >>> # Target are to be un-padded 2025-08-26T23:22:16.5925754Z >>> T = 50 # Input sequence length 2025-08-26T23:22:16.5925811Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:22:16.5925850Z >>> N = 16 # Batch size 2025-08-26T23:22:16.5925881Z >>> 2025-08-26T23:22:16.5925952Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T23:22:16.5926027Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T23:22:16.5926106Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T23:22:16.5926139Z >>> 2025-08-26T23:22:16.5926208Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:22:16.5926294Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-08-26T23:22:16.5926336Z >>> target = torch.randint( 2025-08-26T23:22:16.5926373Z ... low=1, 2025-08-26T23:22:16.5926411Z ... high=C, 2025-08-26T23:22:16.5926479Z ... size=(sum(target_lengths),), 2025-08-26T23:22:16.5926519Z ... dtype=torch.long, 2025-08-26T23:22:16.5927526Z ... ) 2025-08-26T23:22:16.5927566Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:22:16.5927634Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:22:16.5927673Z >>> loss.backward() 2025-08-26T23:22:16.5927705Z >>> 2025-08-26T23:22:16.5927737Z >>> 2025-08-26T23:22:16.5927806Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-08-26T23:22:16.5927850Z >>> T = 50 # Input sequence length 2025-08-26T23:22:16.5927903Z >>> C = 20 # Number of classes (including blank) 2025-08-26T23:22:16.5927934Z >>> 2025-08-26T23:22:16.5928005Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-08-26T23:22:16.5928059Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-08-26T23:22:16.5928153Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-08-26T23:22:16.5928213Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-08-26T23:22:16.5928245Z >>> 2025-08-26T23:22:16.5928314Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T23:22:16.5928396Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-08-26T23:22:16.5928440Z >>> target = torch.randint( 2025-08-26T23:22:16.5928476Z ... low=1, 2025-08-26T23:22:16.5928512Z ... high=C, 2025-08-26T23:22:16.5928556Z ... size=(target_lengths,), 2025-08-26T23:22:16.5929565Z ... dtype=torch.long, 2025-08-26T23:22:16.5929597Z ... ) 2025-08-26T23:22:16.5929638Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T23:22:16.5929705Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T23:22:16.5929768Z >>> loss.backward() 2025-08-26T23:22:16.5929799Z 2025-08-26T23:22:16.5929834Z Reference: 2025-08-26T23:22:16.5929901Z A. Graves et al.: Connectionist Temporal Classification: 2025-08-26T23:22:16.5929982Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-08-26T23:22:16.5930045Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-08-26T23:22:16.5930077Z 2025-08-26T23:22:16.5930122Z Note: 2025-08-26T23:22:16.5930211Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-08-26T23:22:16.5930302Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-08-26T23:22:16.5930445Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-08-26T23:22:16.5930490Z dtype :attr:`torch.int32`. 2025-08-26T23:22:16.5930520Z 2025-08-26T23:22:16.5930622Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-08-26T23:22:16.5930654Z 2025-08-26T23:22:16.5930685Z 2025-08-26T23:22:16.5930716Z Note: 2025-08-26T23:22:16.5930804Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-08-26T23:22:16.5931872Z may select a nondeterministic algorithm to increase performance. If this is 2025-08-26T23:22:16.5931962Z undesirable, you can try to make the operation deterministic (potentially at 2025-08-26T23:22:16.5932047Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-08-26T23:22:16.5932082Z True``. 2025-08-26T23:22:16.5932154Z Please see the notes on :doc:`/notes/randomness` for background. 2025-08-26T23:22:16.5932186Z 2025-08-26T23:22:16.5932277Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5932310Z 2025-08-26T23:22:16.5932347Z warnings.warn(msg) 2025-08-26T23:22:16.5932413Z 2025-08-26T23:22:16.5932487Z --- Parse Warning: 137 / 146 --- 2025-08-26T23:22:16.5932795Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=603. 2025-08-26T23:22:16.5932887Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5932957Z Applies Batch Normalization over a N-Dimensional input. 2025-08-26T23:22:16.5932988Z 2025-08-26T23:22:16.5933113Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-08-26T23:22:16.5933192Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-08-26T23:22:16.5933269Z Internal Covariate Shift `__ . 2025-08-26T23:22:16.5933301Z 2025-08-26T23:22:16.5933336Z .. math:: 2025-08-26T23:22:16.5933387Z 2025-08-26T23:22:16.5934450Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-08-26T23:22:16.5934481Z 2025-08-26T23:22:16.5934564Z The mean and standard-deviation are calculated per-dimension over all 2025-08-26T23:22:16.5934650Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-08-26T23:22:16.5934739Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-08-26T23:22:16.5934806Z By default, the elements of :math:`\gamma` are sampled from 2025-08-26T23:22:16.5934881Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-08-26T23:22:16.5934972Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-08-26T23:22:16.5935019Z `torch.var(input, unbiased=False)`. 2025-08-26T23:22:16.5935050Z 2025-08-26T23:22:16.5935159Z Also by default, during training this layer keeps running estimates of its 2025-08-26T23:22:16.5935245Z computed mean and variance, which are then used for normalization during 2025-08-26T23:22:16.5935330Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-08-26T23:22:16.5935364Z of 0.1. 2025-08-26T23:22:16.5935394Z 2025-08-26T23:22:16.5935475Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-08-26T23:22:16.5935573Z keep running estimates, and batch statistics are instead used during 2025-08-26T23:22:16.5935617Z evaluation time as well. 2025-08-26T23:22:16.5935647Z 2025-08-26T23:22:16.5935681Z .. note:: 2025-08-26T23:22:16.5935760Z This :attr:`momentum` argument is different from one used in optimizer 2025-08-26T23:22:16.5935841Z classes and the conventional notion of momentum. Mathematically, the 2025-08-26T23:22:16.5936869Z update rule for running statistics here is 2025-08-26T23:22:16.5936974Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-08-26T23:22:16.5937050Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-08-26T23:22:16.5937089Z new observed value. 2025-08-26T23:22:16.5937120Z 2025-08-26T23:22:16.5937227Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-08-26T23:22:16.5937320Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-08-26T23:22:16.5937389Z Normalization or Spatio-temporal Batch Normalization. 2025-08-26T23:22:16.5937420Z 2025-08-26T23:22:16.5937477Z Currently :class:`SyncBatchNorm` only supports 2025-08-26T23:22:16.5937579Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-08-26T23:22:16.5937657Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-08-26T23:22:16.5937753Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-08-26T23:22:16.5937793Z Network with DDP. 2025-08-26T23:22:16.5937823Z 2025-08-26T23:22:16.5937855Z Args: 2025-08-26T23:22:16.5937920Z num_features: :math:`C` from an expected input of size 2025-08-26T23:22:16.5937961Z :math:`(N, C, +)` 2025-08-26T23:22:16.5938031Z eps: a value added to the denominator for numerical stability. 2025-08-26T23:22:16.5938071Z Default: ``1e-5`` 2025-08-26T23:22:16.5938143Z momentum: the value used for the running_mean and running_var 2025-08-26T23:22:16.5938219Z computation. Can be set to ``None`` for cumulative moving average 2025-08-26T23:22:16.5939233Z (i.e. simple average). Default: 0.1 2025-08-26T23:22:16.5939307Z affine: a boolean value that when set to ``True``, this module has 2025-08-26T23:22:16.5939390Z learnable affine parameters. Default: ``True`` 2025-08-26T23:22:16.5939469Z track_running_stats: a boolean value that when set to ``True``, this 2025-08-26T23:22:16.5939553Z module tracks the running mean and variance, and when set to ``False``, 2025-08-26T23:22:16.5939634Z this module does not track such statistics, and initializes statistics 2025-08-26T23:22:16.5939709Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-08-26T23:22:16.5939791Z When these buffers are ``None``, this module always uses batch statistics. 2025-08-26T23:22:16.5939851Z in both training and eval modes. Default: ``True`` 2025-08-26T23:22:16.5939941Z process_group: synchronization of stats happen within each process group 2025-08-26T23:22:16.5940020Z individually. Default behavior is synchronization across the whole 2025-08-26T23:22:16.5940071Z world 2025-08-26T23:22:16.5940104Z 2025-08-26T23:22:16.5940140Z Shape: 2025-08-26T23:22:16.5940184Z - Input: :math:`(N, C, +)` 2025-08-26T23:22:16.5940241Z - Output: :math:`(N, C, +)` (same shape as input) 2025-08-26T23:22:16.5940273Z 2025-08-26T23:22:16.5940306Z .. note:: 2025-08-26T23:22:16.5940453Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-08-26T23:22:16.5940558Z synchronization is disabled when ``model.eval()`` is set or if 2025-08-26T23:22:16.5940611Z ``self.training`` is otherwise ``False``. 2025-08-26T23:22:16.5941630Z 2025-08-26T23:22:16.5941667Z Examples:: 2025-08-26T23:22:16.5941698Z 2025-08-26T23:22:16.5941739Z >>> # xdoctest: +SKIP 2025-08-26T23:22:16.5941783Z >>> # With Learnable Parameters 2025-08-26T23:22:16.5941826Z >>> m = nn.SyncBatchNorm(100) 2025-08-26T23:22:16.5941877Z >>> # creating process group (optional) 2025-08-26T23:22:16.5941939Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T23:22:16.5941981Z >>> ranks = list(range(8)) 2025-08-26T23:22:16.5942025Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T23:22:16.5942083Z >>> # Note: every rank calls into new_group for every 2025-08-26T23:22:16.5942141Z >>> # process group created, even if that rank is not 2025-08-26T23:22:16.5942183Z >>> # part of the group. 2025-08-26T23:22:16.5942276Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T23:22:16.5942352Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T23:22:16.5942397Z >>> # Without Learnable Parameters 2025-08-26T23:22:16.5942472Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-08-26T23:22:16.5942523Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-08-26T23:22:16.5942567Z >>> output = m(input) 2025-08-26T23:22:16.5942631Z 2025-08-26T23:22:16.5942679Z >>> # network is nn.BatchNorm layer 2025-08-26T23:22:16.5942777Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-08-26T23:22:16.5943812Z >>> # only single gpu per process is currently supported 2025-08-26T23:22:16.5943895Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-08-26T23:22:16.5943943Z >>> sync_bn_network, 2025-08-26T23:22:16.5943995Z >>> device_ids=[args.local_rank], 2025-08-26T23:22:16.5944046Z >>> output_device=args.local_rank) 2025-08-26T23:22:16.5944078Z 2025-08-26T23:22:16.5944168Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5944199Z 2025-08-26T23:22:16.5944238Z warnings.warn(msg) 2025-08-26T23:22:16.5944270Z 2025-08-26T23:22:16.5944368Z --- Parse Warning: 138 / 146 --- 2025-08-26T23:22:16.5944709Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=830. 2025-08-26T23:22:16.5944801Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5944914Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-08-26T23:22:16.5944944Z 2025-08-26T23:22:16.5944978Z Args: 2025-08-26T23:22:16.5945066Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-08-26T23:22:16.5945144Z process_group (optional): process group to scope synchronization, 2025-08-26T23:22:16.5945189Z default is the whole world 2025-08-26T23:22:16.5945238Z 2025-08-26T23:22:16.5945272Z Returns: 2025-08-26T23:22:16.5946342Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-08-26T23:22:16.5946422Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-08-26T23:22:16.5946499Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-08-26T23:22:16.5946534Z instead. 2025-08-26T23:22:16.5946565Z 2025-08-26T23:22:16.5946620Z Example:: 2025-08-26T23:22:16.5946652Z 2025-08-26T23:22:16.5946702Z >>> # Network with nn.BatchNorm layer 2025-08-26T23:22:16.5946759Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5946807Z >>> module = torch.nn.Sequential( 2025-08-26T23:22:16.5946857Z >>> torch.nn.Linear(20, 100), 2025-08-26T23:22:16.5946906Z >>> torch.nn.BatchNorm1d(100), 2025-08-26T23:22:16.5946948Z >>> ).cuda() 2025-08-26T23:22:16.5947003Z >>> # creating process group (optional) 2025-08-26T23:22:16.5947060Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T23:22:16.5947103Z >>> ranks = list(range(8)) 2025-08-26T23:22:16.5947148Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T23:22:16.5947206Z >>> # Note: every rank calls into new_group for every 2025-08-26T23:22:16.5947266Z >>> # process group created, even if that rank is not 2025-08-26T23:22:16.5947309Z >>> # part of the group. 2025-08-26T23:22:16.5947358Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T23:22:16.5947450Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T23:22:16.5948499Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T23:22:16.5948609Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-08-26T23:22:16.5948660Z 2025-08-26T23:22:16.5948691Z 2025-08-26T23:22:16.5948781Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5948812Z 2025-08-26T23:22:16.5948849Z warnings.warn(msg) 2025-08-26T23:22:16.5948880Z 2025-08-26T23:22:16.5948952Z --- Parse Warning: 139 / 146 --- 2025-08-26T23:22:16.5949244Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/flatten.py line=66. 2025-08-26T23:22:16.5949337Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5949368Z 2025-08-26T23:22:16.5949480Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-08-26T23:22:16.5949512Z 2025-08-26T23:22:16.5949624Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-08-26T23:22:16.5949707Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-08-26T23:22:16.5949737Z 2025-08-26T23:22:16.5949848Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-08-26T23:22:16.5949942Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-08-26T23:22:16.5950009Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-08-26T23:22:16.5950039Z 2025-08-26T23:22:16.5951115Z Shape: 2025-08-26T23:22:16.5951198Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-08-26T23:22:16.5951289Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-08-26T23:22:16.5951371Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-08-26T23:22:16.5951461Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-08-26T23:22:16.5951491Z 2025-08-26T23:22:16.5951524Z Args: 2025-08-26T23:22:16.5951583Z dim (Union[int, str]): Dimension to be unflattened 2025-08-26T23:22:16.5951705Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-08-26T23:22:16.5951736Z 2025-08-26T23:22:16.5951769Z Examples: 2025-08-26T23:22:16.5951832Z >>> input = torch.randn(2, 50) 2025-08-26T23:22:16.5951873Z >>> # With tuple of ints 2025-08-26T23:22:16.5951913Z >>> m = nn.Sequential( 2025-08-26T23:22:16.5951953Z >>> nn.Linear(50, 50), 2025-08-26T23:22:16.5951998Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-08-26T23:22:16.5952030Z >>> ) 2025-08-26T23:22:16.5952071Z >>> output = m(input) 2025-08-26T23:22:16.5952109Z >>> output.size() 2025-08-26T23:22:16.5952150Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:22:16.5952192Z >>> # With torch.Size 2025-08-26T23:22:16.5952230Z >>> m = nn.Sequential( 2025-08-26T23:22:16.5953249Z >>> nn.Linear(50, 50), 2025-08-26T23:22:16.5953302Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-08-26T23:22:16.5953333Z >>> ) 2025-08-26T23:22:16.5953372Z >>> output = m(input) 2025-08-26T23:22:16.5953409Z >>> output.size() 2025-08-26T23:22:16.5953450Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:22:16.5953499Z >>> # With namedshape (tuple of tuples) 2025-08-26T23:22:16.5953558Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-08-26T23:22:16.5953635Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-08-26T23:22:16.5953678Z >>> output = unflatten(input) 2025-08-26T23:22:16.5953717Z >>> output.size() 2025-08-26T23:22:16.5953754Z torch.Size([2, 2, 5, 5]) 2025-08-26T23:22:16.5953787Z 2025-08-26T23:22:16.5953877Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5953933Z 2025-08-26T23:22:16.5953970Z warnings.warn(msg) 2025-08-26T23:22:16.5954001Z 2025-08-26T23:22:16.5954074Z --- Parse Warning: 140 / 146 --- 2025-08-26T23:22:16.5954396Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/parametrize.py line=424. 2025-08-26T23:22:16.5954556Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5954617Z Register a parametrization to a tensor in a module. 2025-08-26T23:22:16.5954648Z 2025-08-26T23:22:16.5955735Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-08-26T23:22:16.5955836Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-08-26T23:22:16.5955958Z If the original tensor requires a gradient, the backward pass will differentiate 2025-08-26T23:22:16.5956061Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-08-26T23:22:16.5956092Z 2025-08-26T23:22:16.5956201Z The first time that a module registers a parametrization, this function will add an attribute 2025-08-26T23:22:16.5956289Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-08-26T23:22:16.5956320Z 2025-08-26T23:22:16.5956410Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-08-26T23:22:16.5956462Z ``module.parametrizations.weight``. 2025-08-26T23:22:16.5956493Z 2025-08-26T23:22:16.5956547Z The original tensor will be accessible under 2025-08-26T23:22:16.5956606Z ``module.parametrizations.weight.original``. 2025-08-26T23:22:16.5956654Z 2025-08-26T23:22:16.5956748Z Parametrizations may be concatenated by registering several parametrizations 2025-08-26T23:22:16.5956790Z on the same attribute. 2025-08-26T23:22:16.5956820Z 2025-08-26T23:22:16.5956905Z The training mode of a registered parametrization is updated on registration 2025-08-26T23:22:16.5956958Z to match the training mode of the host module 2025-08-26T23:22:16.5956989Z 2025-08-26T23:22:16.5957115Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-08-26T23:22:16.5958141Z using the context manager :func:`cached`. 2025-08-26T23:22:16.5958172Z 2025-08-26T23:22:16.5958260Z A :attr:`parametrization` may optionally implement a method with signature 2025-08-26T23:22:16.5958290Z 2025-08-26T23:22:16.5958333Z .. code-block:: python 2025-08-26T23:22:16.5958363Z 2025-08-26T23:22:16.5958442Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-08-26T23:22:16.5958474Z 2025-08-26T23:22:16.5958572Z This method is called on the unparametrized tensor when the first parametrization 2025-08-26T23:22:16.5958649Z is registered to compute the initial value of the original tensor. 2025-08-26T23:22:16.5958755Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-08-26T23:22:16.5958785Z 2025-08-26T23:22:16.5958897Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-08-26T23:22:16.5958998Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-08-26T23:22:16.5959030Z 2025-08-26T23:22:16.5959110Z It is possible for the first parametrization to depend on several inputs. 2025-08-26T23:22:16.5959197Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-08-26T23:22:16.5959281Z (see the example implementation of a ``RankOne`` parametrization below). 2025-08-26T23:22:16.5959337Z 2025-08-26T23:22:16.5959457Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-08-26T23:22:16.5959507Z with names ``original0``, ``original1``,... 2025-08-26T23:22:16.5959539Z 2025-08-26T23:22:16.5960604Z .. note:: 2025-08-26T23:22:16.5960636Z 2025-08-26T23:22:16.5960734Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-08-26T23:22:16.5960794Z once to perform a number of consistency checks. 2025-08-26T23:22:16.5960893Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-08-26T23:22:16.5960942Z and nothing will be called otherwise. 2025-08-26T23:22:16.5960972Z 2025-08-26T23:22:16.5961006Z .. note:: 2025-08-26T23:22:16.5961036Z 2025-08-26T23:22:16.5961111Z In most situations, ``right_inverse`` will be a function such that 2025-08-26T23:22:16.5961197Z ``forward(right_inverse(X)) == X`` (see 2025-08-26T23:22:16.5961300Z `right inverse `_). 2025-08-26T23:22:16.5961390Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-08-26T23:22:16.5961428Z to relax this. 2025-08-26T23:22:16.5961458Z 2025-08-26T23:22:16.5961494Z .. warning:: 2025-08-26T23:22:16.5961524Z 2025-08-26T23:22:16.5961623Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-08-26T23:22:16.5961715Z will register a number of new parameters. If such parametrization is registered 2025-08-26T23:22:16.5961811Z after the optimizer is created, these new parameters will need to be added manually 2025-08-26T23:22:16.5961884Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-08-26T23:22:16.5962897Z 2025-08-26T23:22:16.5962955Z Args: 2025-08-26T23:22:16.5963034Z module (nn.Module): module on which to register the parametrization 2025-08-26T23:22:16.5963113Z tensor_name (str): name of the parameter or buffer on which to register 2025-08-26T23:22:16.5963156Z the parametrization 2025-08-26T23:22:16.5963231Z parametrization (nn.Module): the parametrization to register 2025-08-26T23:22:16.5963267Z Keyword args: 2025-08-26T23:22:16.5963365Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-08-26T23:22:16.5963437Z may change the dtype and shape of the tensor. Default: `False` 2025-08-26T23:22:16.5963532Z Warning: the parametrization is not checked for consistency upon registration. 2025-08-26T23:22:16.5963580Z Enable this flag at your own risk. 2025-08-26T23:22:16.5963612Z 2025-08-26T23:22:16.5963644Z Raises: 2025-08-26T23:22:16.5963747Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-08-26T23:22:16.5963782Z 2025-08-26T23:22:16.5963818Z Examples: 2025-08-26T23:22:16.5963876Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T23:22:16.5963916Z >>> import torch 2025-08-26T23:22:16.5963958Z >>> import torch.nn as nn 2025-08-26T23:22:16.5964015Z >>> import torch.nn.utils.parametrize as P 2025-08-26T23:22:16.5964047Z >>> 2025-08-26T23:22:16.5964093Z >>> class Symmetric(nn.Module): 2025-08-26T23:22:16.5965105Z >>> def forward(self, X): 2025-08-26T23:22:16.5965177Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-08-26T23:22:16.5965209Z >>> 2025-08-26T23:22:16.5965256Z >>> def right_inverse(self, A): 2025-08-26T23:22:16.5965297Z >>> return A.triu() 2025-08-26T23:22:16.5965329Z >>> 2025-08-26T23:22:16.5965370Z >>> m = nn.Linear(5, 5) 2025-08-26T23:22:16.5965462Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-08-26T23:22:16.5965550Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-08-26T23:22:16.5965582Z True 2025-08-26T23:22:16.5965623Z >>> A = torch.rand(5, 5) 2025-08-26T23:22:16.5965668Z >>> A = A + A.T # A is now symmetric 2025-08-26T23:22:16.5965744Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-08-26T23:22:16.5965791Z >>> print(torch.allclose(m.weight, A)) 2025-08-26T23:22:16.5965824Z True 2025-08-26T23:22:16.5965855Z 2025-08-26T23:22:16.5965898Z >>> class RankOne(nn.Module): 2025-08-26T23:22:16.5965941Z >>> def forward(self, x, y): 2025-08-26T23:22:16.5965998Z >>> # Form a rank 1 matrix multiplying two vectors 2025-08-26T23:22:16.5966053Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-08-26T23:22:16.5966088Z >>> 2025-08-26T23:22:16.5966148Z >>> def right_inverse(self, Z): 2025-08-26T23:22:16.5967169Z >>> # Project Z onto the rank 1 matrices 2025-08-26T23:22:16.5967229Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-08-26T23:22:16.5967276Z >>> # Return rescaled singular vectors 2025-08-26T23:22:16.5967326Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-08-26T23:22:16.5967384Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-08-26T23:22:16.5967416Z >>> 2025-08-26T23:22:16.5967475Z >>> linear_rank_one = P.register_parametrization( 2025-08-26T23:22:16.5967526Z ... nn.Linear(4, 4), "weight", RankOne() 2025-08-26T23:22:16.5967558Z ... ) 2025-08-26T23:22:16.5967632Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-08-26T23:22:16.5967681Z 1 2025-08-26T23:22:16.5967712Z 2025-08-26T23:22:16.5967745Z 2025-08-26T23:22:16.5967836Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5967867Z 2025-08-26T23:22:16.5967905Z warnings.warn(msg) 2025-08-26T23:22:16.5967935Z 2025-08-26T23:22:16.5968011Z --- Parse Warning: 141 / 146 --- 2025-08-26T23:22:16.5968363Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=14. 2025-08-26T23:22:16.5968456Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5968536Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-08-26T23:22:16.5969546Z 2025-08-26T23:22:16.5969644Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T23:22:16.5969749Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T23:22:16.5969839Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T23:22:16.5969950Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T23:22:16.5969980Z 2025-08-26T23:22:16.5970015Z .. note:: 2025-08-26T23:22:16.5970103Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-08-26T23:22:16.5970185Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-08-26T23:22:16.5970262Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T23:22:16.5970454Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T23:22:16.5970534Z One place we are confident in is that NHWC(channels_last) conversion for 2025-08-26T23:22:16.5970614Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-08-26T23:22:16.5970719Z even in cases where we have to apply permutation to input tensors. 2025-08-26T23:22:16.5970751Z 2025-08-26T23:22:16.5970831Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T23:22:16.5970879Z channels_last. This ensures that; 2025-08-26T23:22:16.5970958Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T23:22:16.5971040Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T23:22:16.5971123Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T23:22:16.5971168Z from memory_format conversion. 2025-08-26T23:22:16.5971199Z 2025-08-26T23:22:16.5972279Z The optimal case is that, layers between convolution layers are channels 2025-08-26T23:22:16.5972388Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T23:22:16.5972471Z encounters the first convolution layer and stay in that memory format. 2025-08-26T23:22:16.5972554Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T23:22:16.5972586Z 2025-08-26T23:22:16.5972664Z In case where a channels last incompatible layer is between convolution 2025-08-26T23:22:16.5972742Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T23:22:16.5972822Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T23:22:16.5972902Z contiguous format and be permuted to channels last when it encounters 2025-08-26T23:22:16.5972976Z another convolution layer. There's no point in propagating that 2025-08-26T23:22:16.5973053Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T23:22:16.5973110Z ``memory_format``. 2025-08-26T23:22:16.5973143Z 2025-08-26T23:22:16.5973224Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T23:22:16.5973301Z there might have been a better spot to fuse the permutation other than 2025-08-26T23:22:16.5973348Z immediately before a convolution. 2025-08-26T23:22:16.5973379Z 2025-08-26T23:22:16.5973412Z Args: 2025-08-26T23:22:16.5973509Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-08-26T23:22:16.5973553Z ``nn.Module`` 2025-08-26T23:22:16.5973611Z memory_format: user specified ``memory_format``, 2025-08-26T23:22:16.5974658Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T23:22:16.5974689Z 2025-08-26T23:22:16.5974724Z Returns: 2025-08-26T23:22:16.5974780Z The original module with updated ``nn.Conv2d`` 2025-08-26T23:22:16.5974813Z 2025-08-26T23:22:16.5974848Z Example: 2025-08-26T23:22:16.5974905Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5974966Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T23:22:16.5975010Z >>> input = torch.randint( 2025-08-26T23:22:16.5975066Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T23:22:16.5975100Z ... ) 2025-08-26T23:22:16.5975143Z >>> model = nn.Sequential( 2025-08-26T23:22:16.5975191Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-08-26T23:22:16.5975232Z >>> # This is identical to: 2025-08-26T23:22:16.5975321Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-08-26T23:22:16.5975385Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-08-26T23:22:16.5975430Z ... model, torch.channels_last 2025-08-26T23:22:16.5975464Z ... ) 2025-08-26T23:22:16.5975530Z >>> out = model(input) 2025-08-26T23:22:16.5975562Z 2025-08-26T23:22:16.5975653Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5975684Z 2025-08-26T23:22:16.5976695Z warnings.warn(msg) 2025-08-26T23:22:16.5976728Z 2025-08-26T23:22:16.5976803Z --- Parse Warning: 142 / 146 --- 2025-08-26T23:22:16.5977138Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=93. 2025-08-26T23:22:16.5977230Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5977309Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-08-26T23:22:16.5977405Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T23:22:16.5977523Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T23:22:16.5977613Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T23:22:16.5977723Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T23:22:16.5977753Z 2025-08-26T23:22:16.5977787Z .. note:: 2025-08-26T23:22:16.5977875Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-08-26T23:22:16.5977955Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-08-26T23:22:16.5978029Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T23:22:16.5978108Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T23:22:16.5978191Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-08-26T23:22:16.5978287Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-08-26T23:22:16.5978359Z even in cases where we have to apply permutation to input tensors. 2025-08-26T23:22:16.5978391Z 2025-08-26T23:22:16.5978471Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T23:22:16.5979494Z channels_last_3d. This ensures that; 2025-08-26T23:22:16.5979596Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T23:22:16.5979679Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T23:22:16.5979761Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T23:22:16.5979807Z from memory_format conversion. 2025-08-26T23:22:16.5979838Z 2025-08-26T23:22:16.5979918Z The optimal case is that, layers between convolution layers are channels 2025-08-26T23:22:16.5980005Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T23:22:16.5980086Z encounters the first convolution layer and stay in that memory format. 2025-08-26T23:22:16.5980169Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T23:22:16.5980201Z 2025-08-26T23:22:16.5980277Z In case where a channels last incompatible layer is between convolution 2025-08-26T23:22:16.5980421Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T23:22:16.5980500Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T23:22:16.5980579Z contiguous format and be permuted to channels last when it encounters 2025-08-26T23:22:16.5980653Z another convolution layer. There's no point in propagating that 2025-08-26T23:22:16.5980729Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T23:22:16.5980794Z ``memory_format``. 2025-08-26T23:22:16.5980826Z 2025-08-26T23:22:16.5980907Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T23:22:16.5980984Z there might have been a better spot to fuse the permutation other than 2025-08-26T23:22:16.5981032Z immediately before a convolution. 2025-08-26T23:22:16.5982046Z 2025-08-26T23:22:16.5982080Z Args: 2025-08-26T23:22:16.5982160Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-08-26T23:22:16.5982203Z ``nn.Module`` 2025-08-26T23:22:16.5982260Z memory_format: user specified ``memory_format``, 2025-08-26T23:22:16.5982327Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T23:22:16.5982357Z 2025-08-26T23:22:16.5982391Z Returns: 2025-08-26T23:22:16.5982446Z The original module with updated ``nn.Conv3d`` 2025-08-26T23:22:16.5982479Z 2025-08-26T23:22:16.5982543Z Example: 2025-08-26T23:22:16.5982598Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T23:22:16.5982659Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T23:22:16.5982702Z >>> input = torch.randint( 2025-08-26T23:22:16.5982760Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T23:22:16.5982793Z ... ) 2025-08-26T23:22:16.5982835Z >>> model = nn.Sequential( 2025-08-26T23:22:16.5982882Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-08-26T23:22:16.5982925Z >>> # This is identical to: 2025-08-26T23:22:16.5983017Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-08-26T23:22:16.5983080Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-08-26T23:22:16.5984097Z ... model, torch.channels_last_3d 2025-08-26T23:22:16.5984153Z ... ) 2025-08-26T23:22:16.5984196Z >>> out = model(input) 2025-08-26T23:22:16.5984229Z 2025-08-26T23:22:16.5984320Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5984351Z 2025-08-26T23:22:16.5984388Z warnings.warn(msg) 2025-08-26T23:22:16.5984419Z 2025-08-26T23:22:16.5984494Z --- Parse Warning: 143 / 146 --- 2025-08-26T23:22:16.5984810Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/rnn.py line=350. 2025-08-26T23:22:16.5984902Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5984961Z Pad a packed batch of variable length sequences. 2025-08-26T23:22:16.5984992Z 2025-08-26T23:22:16.5985060Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-08-26T23:22:16.5985094Z 2025-08-26T23:22:16.5985198Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-08-26T23:22:16.5985287Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-08-26T23:22:16.5985334Z sequence and ``B`` is the batch size. 2025-08-26T23:22:16.5985364Z 2025-08-26T23:22:16.5985398Z Example: 2025-08-26T23:22:16.5985486Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-08-26T23:22:16.5985544Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-08-26T23:22:16.5986561Z >>> lens = [2, 1, 3] 2025-08-26T23:22:16.5986610Z >>> packed = pack_padded_sequence( 2025-08-26T23:22:16.5986669Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-08-26T23:22:16.5986702Z ... ) 2025-08-26T23:22:16.5986737Z >>> packed 2025-08-26T23:22:16.5986829Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-08-26T23:22:16.5986932Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-08-26T23:22:16.5987022Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-08-26T23:22:16.5987061Z >>> seq_unpacked 2025-08-26T23:22:16.5987099Z tensor([[1, 2, 0], 2025-08-26T23:22:16.5987138Z [3, 0, 0], 2025-08-26T23:22:16.5987174Z [4, 5, 6]]) 2025-08-26T23:22:16.5987213Z >>> lens_unpacked 2025-08-26T23:22:16.5987250Z tensor([2, 1, 3]) 2025-08-26T23:22:16.5987281Z 2025-08-26T23:22:16.5987315Z .. note:: 2025-08-26T23:22:16.5987374Z :attr:`total_length` is useful to implement the 2025-08-26T23:22:16.5987455Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-08-26T23:22:16.5987555Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-08-26T23:22:16.5987642Z See :ref:`this FAQ section ` for 2025-08-26T23:22:16.5987676Z details. 2025-08-26T23:22:16.5987706Z 2025-08-26T23:22:16.5988705Z Args: 2025-08-26T23:22:16.5988759Z sequence (PackedSequence): batch to pad 2025-08-26T23:22:16.5988848Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-08-26T23:22:16.5988894Z format, ``T x B x *`` otherwise. 2025-08-26T23:22:16.5988966Z padding_value (float, optional): values for padded elements. 2025-08-26T23:22:16.5989051Z total_length (int, optional): if not ``None``, the output will be padded to 2025-08-26T23:22:16.5989137Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-08-26T23:22:16.5989206Z if :attr:`total_length` is less than the max sequence length in 2025-08-26T23:22:16.5989271Z :attr:`sequence`. 2025-08-26T23:22:16.5989302Z 2025-08-26T23:22:16.5989335Z Returns: 2025-08-26T23:22:16.5989406Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-08-26T23:22:16.5989478Z containing the list of lengths of each sequence in the batch. 2025-08-26T23:22:16.5989558Z Batch elements will be re-ordered as they were ordered originally when 2025-08-26T23:22:16.5989653Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-08-26T23:22:16.5989686Z 2025-08-26T23:22:16.5989773Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5989805Z 2025-08-26T23:22:16.5989842Z warnings.warn(msg) 2025-08-26T23:22:16.5989873Z 2025-08-26T23:22:16.5989947Z --- Parse Warning: 144 / 146 --- 2025-08-26T23:22:16.5991293Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=979. 2025-08-26T23:22:16.5991391Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5991502Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-08-26T23:22:16.5991533Z 2025-08-26T23:22:16.5991619Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-08-26T23:22:16.5991698Z by removing the specified ``amount`` of (currently unpruned) channels 2025-08-26T23:22:16.5991766Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-08-26T23:22:16.5991838Z Modifies module in place (and also return the modified module) 2025-08-26T23:22:16.5991872Z by: 2025-08-26T23:22:16.5991903Z 2025-08-26T23:22:16.5991979Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:22:16.5992095Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:22:16.5992172Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:22:16.5992247Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:22:16.5992287Z ``name+'_orig'``. 2025-08-26T23:22:16.5992317Z 2025-08-26T23:22:16.5992350Z Args: 2025-08-26T23:22:16.5992418Z module (nn.Module): module containing the tensor to prune 2025-08-26T23:22:16.5992487Z name (str): parameter name within ``module`` on which pruning 2025-08-26T23:22:16.5992525Z will act. 2025-08-26T23:22:16.5992589Z amount (int or float): quantity of parameters to prune. 2025-08-26T23:22:16.5992653Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T23:22:16.5993725Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T23:22:16.5993802Z absolute number of parameters to prune. 2025-08-26T23:22:16.5993874Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-08-26T23:22:16.5993935Z entries for argument ``p`` in :func:`torch.norm`. 2025-08-26T23:22:16.5994008Z dim (int): index of the dim along which we define channels to prune. 2025-08-26T23:22:16.5994092Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-08-26T23:22:16.5994161Z shape as module parameter) used to compute mask for pruning. 2025-08-26T23:22:16.5994241Z The values in this tensor indicate the importance of the corresponding 2025-08-26T23:22:16.5994292Z elements in the parameter being pruned. 2025-08-26T23:22:16.5994374Z If unspecified or None, the module parameter will be used in its place. 2025-08-26T23:22:16.5994405Z 2025-08-26T23:22:16.5994514Z Returns: 2025-08-26T23:22:16.5994597Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T23:22:16.5994629Z 2025-08-26T23:22:16.5994663Z Examples: 2025-08-26T23:22:16.5994712Z >>> from torch.nn.utils import prune 2025-08-26T23:22:16.5994755Z >>> m = prune.ln_structured( 2025-08-26T23:22:16.5994825Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-08-26T23:22:16.5994857Z ... ) 2025-08-26T23:22:16.5994907Z 2025-08-26T23:22:16.5994996Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.5996018Z 2025-08-26T23:22:16.5996056Z warnings.warn(msg) 2025-08-26T23:22:16.5996087Z 2025-08-26T23:22:16.5996159Z --- Parse Warning: 145 / 146 --- 2025-08-26T23:22:16.5996462Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1026. 2025-08-26T23:22:16.5996557Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.5996588Z 2025-08-26T23:22:16.5996740Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-08-26T23:22:16.5996771Z 2025-08-26T23:22:16.5996815Z Modifies modules in place by: 2025-08-26T23:22:16.5996848Z 2025-08-26T23:22:16.5996926Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:22:16.5997003Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:22:16.5997080Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:22:16.5997155Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:22:16.5997192Z ``name+'_orig'``. 2025-08-26T23:22:16.5997223Z 2025-08-26T23:22:16.5997275Z Args: 2025-08-26T23:22:16.5997353Z parameters (Iterable of (module, name) tuples): parameters of 2025-08-26T23:22:16.5997423Z the model to prune in a global fashion, i.e. by aggregating all 2025-08-26T23:22:16.5997497Z weights prior to deciding which ones to prune. module must be of 2025-08-26T23:22:16.5997557Z type :class:`nn.Module`, and name must be a string. 2025-08-26T23:22:16.5998622Z pruning_method (function): a valid pruning function from this module, 2025-08-26T23:22:16.5998690Z or a custom one implemented by the user that satisfies the 2025-08-26T23:22:16.5998769Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-08-26T23:22:16.5998852Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-08-26T23:22:16.5998929Z the corresponding parameter's importance scores tensor. The tensor 2025-08-26T23:22:16.5999024Z should be the same shape as the parameter, and is used for computing 2025-08-26T23:22:16.5999064Z mask for pruning. 2025-08-26T23:22:16.5999139Z If unspecified or None, the parameter will be used in place of its 2025-08-26T23:22:16.5999179Z importance scores. 2025-08-26T23:22:16.5999228Z kwargs: other keyword arguments such as: 2025-08-26T23:22:16.5999297Z amount (int or float): quantity of parameters to prune across the 2025-08-26T23:22:16.5999341Z specified parameters. 2025-08-26T23:22:16.5999406Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T23:22:16.5999479Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T23:22:16.5999527Z absolute number of parameters to prune. 2025-08-26T23:22:16.5999559Z 2025-08-26T23:22:16.5999591Z Raises: 2025-08-26T23:22:16.5999651Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-08-26T23:22:16.5999707Z 2025-08-26T23:22:16.5999740Z Note: 2025-08-26T23:22:16.5999819Z Since global structured pruning doesn't make much sense unless the 2025-08-26T23:22:16.5999891Z norm is normalized by the size of the parameter, we now limit the 2025-08-26T23:22:16.6000997Z scope of global pruning to unstructured methods. 2025-08-26T23:22:16.6001027Z 2025-08-26T23:22:16.6001062Z Examples: 2025-08-26T23:22:16.6001108Z >>> from torch.nn.utils import prune 2025-08-26T23:22:16.6001183Z >>> from collections import OrderedDict 2025-08-26T23:22:16.6001226Z >>> net = nn.Sequential( 2025-08-26T23:22:16.6001265Z ... OrderedDict( 2025-08-26T23:22:16.6001298Z ... [ 2025-08-26T23:22:16.6001349Z ... ("first", nn.Linear(10, 4)), 2025-08-26T23:22:16.6001397Z ... ("second", nn.Linear(4, 1)), 2025-08-26T23:22:16.6001430Z ... ] 2025-08-26T23:22:16.6001461Z ... ) 2025-08-26T23:22:16.6001496Z ... ) 2025-08-26T23:22:16.6001542Z >>> parameters_to_prune = ( 2025-08-26T23:22:16.6001583Z ... (net.first, "weight"), 2025-08-26T23:22:16.6001624Z ... (net.second, "weight"), 2025-08-26T23:22:16.6001655Z ... ) 2025-08-26T23:22:16.6001700Z >>> prune.global_unstructured( 2025-08-26T23:22:16.6001740Z ... parameters_to_prune, 2025-08-26T23:22:16.6001793Z ... pruning_method=prune.L1Unstructured, 2025-08-26T23:22:16.6001832Z ... amount=10, 2025-08-26T23:22:16.6002844Z ... ) 2025-08-26T23:22:16.6002926Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-08-26T23:22:16.6002961Z tensor(10) 2025-08-26T23:22:16.6002991Z 2025-08-26T23:22:16.6003022Z 2025-08-26T23:22:16.6003111Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.6003142Z 2025-08-26T23:22:16.6003179Z warnings.warn(msg) 2025-08-26T23:22:16.6003211Z 2025-08-26T23:22:16.6003316Z --- Parse Warning: 146 / 146 --- 2025-08-26T23:22:16.6003609Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1149. 2025-08-26T23:22:16.6003702Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T23:22:16.6003844Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-08-26T23:22:16.6003874Z 2025-08-26T23:22:16.6003952Z Modifies module in place (and also return the modified module) by: 2025-08-26T23:22:16.6003982Z 2025-08-26T23:22:16.6004057Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T23:22:16.6004137Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T23:22:16.6004230Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T23:22:16.6004309Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T23:22:16.6004346Z ``name+'_orig'``. 2025-08-26T23:22:16.6004378Z 2025-08-26T23:22:16.6005383Z Args: 2025-08-26T23:22:16.6005452Z module (nn.Module): module containing the tensor to prune 2025-08-26T23:22:16.6005520Z name (str): parameter name within ``module`` on which pruning 2025-08-26T23:22:16.6005558Z will act. 2025-08-26T23:22:16.6005625Z mask (Tensor): binary mask to be applied to the parameter. 2025-08-26T23:22:16.6005656Z 2025-08-26T23:22:16.6005689Z Returns: 2025-08-26T23:22:16.6005767Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T23:22:16.6005797Z 2025-08-26T23:22:16.6005832Z Examples: 2025-08-26T23:22:16.6005879Z >>> from torch.nn.utils import prune 2025-08-26T23:22:16.6005950Z >>> m = prune.custom_from_mask( 2025-08-26T23:22:16.6006015Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-08-26T23:22:16.6006048Z ... ) 2025-08-26T23:22:16.6006089Z >>> print(m.bias_mask) 2025-08-26T23:22:16.6006128Z tensor([0., 1., 0.]) 2025-08-26T23:22:16.6006158Z 2025-08-26T23:22:16.6006189Z 2025-08-26T23:22:16.6006323Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T23:22:16.6006354Z 2025-08-26T23:22:16.6006392Z warnings.warn(msg) 2025-08-26T23:22:16.6006421Z 2025-08-26T23:22:16.6007453Z  2025-08-26T23:22:16.6007523Z === Found 8 run-time warnings === 2025-08-26T23:22:16.6007592Z --- Runtime Warning: 1 / 8 --- 2025-08-26T23:22:16.6007687Z example = 2025-08-26T23:22:16.6008130Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/_tensor.py:1351: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /var/lib/jenkins/workspace/c10/core/TensorImpl.h:1971.) 2025-08-26T23:22:16.6008178Z return super().refine_names(names) 2025-08-26T23:22:16.6008209Z 2025-08-26T23:22:16.6008276Z --- Runtime Warning: 2 / 8 --- 2025-08-26T23:22:16.6008389Z example = 2025-08-26T23:22:16.6008599Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/library.py:282: UserWarning: Warning only once for all operators, other operators may also be overridden. 2025-08-26T23:22:16.6008711Z Overriding a previously registered kernel for the same operator and the same dispatch key 2025-08-26T23:22:16.6008788Z operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor 2025-08-26T23:22:16.6008916Z registered at /var/lib/jenkins/workspace/build/aten/src/ATen/RegisterSchema.cpp:6 2025-08-26T23:22:16.6008955Z dispatch key: CPU 2025-08-26T23:22:16.6009105Z previous kernel: registered at /var/lib/jenkins/workspace/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079 2025-08-26T23:22:16.6009294Z new kernel: registered at /dev/null:811 (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/core/dispatch/OperatorEntry.cpp:218.) 2025-08-26T23:22:16.6009360Z impl_fn(self.ns, name.split("::")[-1], dispatch_key) 2025-08-26T23:22:16.6009391Z 2025-08-26T23:22:16.6009458Z --- Runtime Warning: 3 / 8 --- 2025-08-26T23:22:16.6009545Z example = 2025-08-26T23:22:16.6010159Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nested/__init__.py:117: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. We recommend specifying layout=torch.jagged when constructing a nested tensor, as this layout receives active development, has better operator coverage, and works with torch.compile. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/NestedTensorImpl.cpp:178.) 2025-08-26T23:22:16.6011362Z return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None) 2025-08-26T23:22:16.6011394Z 2025-08-26T23:22:16.6011464Z --- Runtime Warning: 4 / 8 --- 2025-08-26T23:22:16.6011576Z example = 2025-08-26T23:22:16.6012106Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/fx/experimental/const_fold.py:271: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add the necessary submodule, GraphModule.add_parameter to add the necessary Parameter, or nn.Module.register_buffer to add the necessary buffer 2025-08-26T23:22:16.6012211Z new_node = root_const_gm.graph.get_attr(in_node.target) 2025-08-26T23:22:16.6012243Z 2025-08-26T23:22:16.6012314Z --- Runtime Warning: 5 / 8 --- 2025-08-26T23:22:16.6012420Z example = 2025-08-26T23:22:16.6012804Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-08-26T23:22:16.6012843Z warnings.warn( 2025-08-26T23:22:16.6012874Z 2025-08-26T23:22:16.6012939Z --- Runtime Warning: 6 / 8 --- 2025-08-26T23:22:16.6013057Z example = 2025-08-26T23:22:16.6013414Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-08-26T23:22:16.6013451Z warnings.warn( 2025-08-26T23:22:16.6013483Z 2025-08-26T23:22:16.6013548Z --- Runtime Warning: 7 / 8 --- 2025-08-26T23:22:16.6013649Z example = 2025-08-26T23:22:16.6013929Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-08-26T23:22:16.6013978Z WeightNorm.apply(module, name, dim) 2025-08-26T23:22:16.6015000Z 2025-08-26T23:22:16.6015069Z --- Runtime Warning: 8 / 8 --- 2025-08-26T23:22:16.6015177Z example = 2025-08-26T23:22:16.6015472Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-08-26T23:22:16.6015519Z WeightNorm.apply(module, name, dim) 2025-08-26T23:22:16.6015550Z 2025-08-26T23:22:16.6015663Z === 338 passed, 393 skipped, 154 warnings in 21.56 seconds === 2025-08-26T23:22:16.6015745Z Running test_foreach 1/1 ... [2025-08-26 23:22:16.501899] 2025-08-26T23:22:16.6015792Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:22:16.6016083Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_foreach.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:22:16.502206] 2025-08-26T23:25:28.5936548Z 2025-08-26T23:25:28.5941996Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_738b92f38ab87f8e_.log 2025-08-26T23:25:28.6421943Z Running 3577 items in this shard: test/test_foreach.py::TestForeachCUDA::test_0dim_tensor_overload_cpu_ok_cuda, test/test_foreach.py::TestForeachCUDA::test_0dim_tensor_overload_exception_cuda, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_add_scalar_with_empty_list_and_empty_tensor_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_abs_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_acos_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_add_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcdiv_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_addcmul_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_asin_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_atan_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_ceil_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_max_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_clamp_min_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_copy_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cos_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_cosh_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_div_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erf_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_erfc_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_exp_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_expm1_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_floor_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_frac_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lerp_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_lgamma_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log10_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log1p_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log2_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_log_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_max_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_maximum_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_minimum_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_mul_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_neg_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_norm_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_pow_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_reciprocal_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_round_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_rsqrt_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sigmoid_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sign_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sin_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sinh_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sqrt_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_sub_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tan_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_tanh_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_trunc_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_all_zero_size_tensors_do_not_launch_kernel__foreach_zero_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_abs_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_abs_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_abs_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_abs_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_acos_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_acos_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_acos_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_acos_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_add_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_add_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_add_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_add_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcdiv_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcdiv_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcdiv_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcdiv_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcmul_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcmul_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcmul_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_addcmul_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_asin_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_asin_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_asin_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_asin_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_atan_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_atan_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_atan_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_atan_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_ceil_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_ceil_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_ceil_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_ceil_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_max_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_max_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_max_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_max_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_min_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_min_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_min_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_clamp_min_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_copy_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_copy_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_copy_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_copy_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cos_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cos_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cos_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cos_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cosh_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cosh_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cosh_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_cosh_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_div_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_div_inplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_div_outplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_div_outplace_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_erf_inplace_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_autodiff__foreach_erf_inplace_cuda_float64, 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test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sin_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sinh_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_sqrt_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tan_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_tanh_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_trunc_cuda_uint8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_bfloat16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_bool, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_complex128, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_complex64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_float16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_float32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_float64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_int16, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_int32, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_int64, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_int8, test/test_foreach.py::TestForeachCUDA::test_unary_op_tensors_on_different_devices__foreach_zero_cuda_uint8 2025-08-26T23:25:28.6876660Z 2025-08-26T23:25:28.6876750Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-26 23:25:28.596867] 2025-08-26T23:25:28.6881709Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:28.6882116Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:28.597053] 2025-08-26T23:25:31.6172311Z 2025-08-26T23:25:31.6173289Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_9dcffcecafe448df_.log 2025-08-26T23:25:31.6174827Z Running 5 items in this shard: test/lazy/test_ts_opinfo.py::TestLazyTensor::testConvolutionBackward, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_tensor_ctr, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_view_mark_step_preserved, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_adaptiveavgpool3d_dynamic, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_nonzero_dynamic 2025-08-26T23:25:31.6175937Z 2025-08-26T23:25:31.6176069Z Running nn/test_load_state_dict 1/1 ... [2025-08-26 23:25:31.617089] 2025-08-26T23:25:31.6176315Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:31.6176935Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'nn/test_load_state_dict.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:31.617306] 2025-08-26T23:25:35.0895484Z 2025-08-26T23:25:35.0897275Z nn/test_load_state_dict 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_load_state_dict_1.1_a279699a31b94f50_.log 2025-08-26T23:25:35.0903432Z Running 27 items in this shard: test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_BC_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_False_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_meta_swap_True_keep_vars_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_shape_stride_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_assign_with_optimizer_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_child_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_custom_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_invalid_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_ref_cycle_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_type_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_warn_assign_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_False, test/nn/test_load_state_dict.py::TestLoadStateDict::test_load_state_dict_with_unexpected_key_swap_True, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_False, test/nn/test_load_state_dict.py::TestLoadStateDictSwap::test_swap_subclass_swap_True_assign_True 2025-08-26T23:25:35.0908121Z 2025-08-26T23:25:35.0908239Z Running profiler/test_execution_trace 1/1 ... [2025-08-26 23:25:35.089449] 2025-08-26T23:25:35.0908475Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:35.0908998Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'profiler/test_execution_trace.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:35.089640] 2025-08-26T23:25:41.2295058Z 2025-08-26T23:25:41.2296091Z profiler/test_execution_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_execution_trace_1.1_9853664c68fa3692_.log 2025-08-26T23:25:41.2298407Z Running 13 items in this shard: test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_alone_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_env_disabled_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_env_enabled_with_kineto_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_env_enabled_with_pt2_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_nested_tensor_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_no_capture_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_record_integral_tensor_data_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_record_integral_tensor_range_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_repeat_in_loop_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_start_stop_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_with_kineto_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_execution_trace_with_pt2_cuda, test/profiler/test_execution_trace.py::TestExecutionTraceCUDA::test_triton_fx_graph_with_et_cuda 2025-08-26T23:25:41.2300721Z 2025-08-26T23:25:41.2304892Z Running profiler/test_record_function 1/1 ... [2025-08-26 23:25:41.229553] 2025-08-26T23:25:41.2305092Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:41.2306072Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'profiler/test_record_function.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:41.229781] 2025-08-26T23:25:43.7003396Z 2025-08-26T23:25:43.7004208Z profiler/test_record_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_record_function_1.1_a887a2e69b49d3f9_.log 2025-08-26T23:25:43.7005120Z Running 4 items in this shard: test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_delegation_with_profiler, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function_fork, test/profiler/test_record_function.py::TestRecordFunction::test_record_function 2025-08-26T23:25:43.7005726Z 2025-08-26T23:25:43.7006087Z Running test_cuda_sanitizer 1/1 ... [2025-08-26 23:25:43.700395] 2025-08-26T23:25:43.7011731Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:43.7012235Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_cuda_sanitizer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:43.700656] 2025-08-26T23:25:46.2723793Z 2025-08-26T23:25:46.2724919Z test_cuda_sanitizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_sanitizer_1.1_a2dbf29e99576cc0_.log 2025-08-26T23:25:46.2728347Z Running 31 items in this shard: test/test_cuda_sanitizer.py::TestArgumentHandler::test_add, test/test_cuda_sanitizer.py::TestArgumentHandler::test_cat, test/test_cuda_sanitizer.py::TestArgumentHandler::test_inplace, test/test_cuda_sanitizer.py::TestArgumentHandler::test_nonzero, test/test_cuda_sanitizer.py::TestArgumentHandler::test_out, test/test_cuda_sanitizer.py::TestArgumentHandler::test_split, test/test_cuda_sanitizer.py::TestArgumentHandler::test_tensor_names, test/test_cuda_sanitizer.py::TestEventHandler::test_all_reads_checked_failing, test/test_cuda_sanitizer.py::TestEventHandler::test_all_reads_checked_passing, test/test_cuda_sanitizer.py::TestEventHandler::test_branch_sync, test/test_cuda_sanitizer.py::TestEventHandler::test_chain_sync, test/test_cuda_sanitizer.py::TestEventHandler::test_correct_state_merging, test/test_cuda_sanitizer.py::TestEventHandler::test_deleted_record, test/test_cuda_sanitizer.py::TestEventHandler::test_device_synchronization_expired, test/test_cuda_sanitizer.py::TestEventHandler::test_device_synchronize, test/test_cuda_sanitizer.py::TestEventHandler::test_empty_kernel_launch, test/test_cuda_sanitizer.py::TestEventHandler::test_event_synchronize, test/test_cuda_sanitizer.py::TestEventHandler::test_expired_record, test/test_cuda_sanitizer.py::TestEventHandler::test_multiple_errors, test/test_cuda_sanitizer.py::TestEventHandler::test_multiple_wait, test/test_cuda_sanitizer.py::TestEventHandler::test_new_stream_is_synchronized, test/test_cuda_sanitizer.py::TestEventHandler::test_reads_check_last_write, test/test_cuda_sanitizer.py::TestEventHandler::test_record_override, test/test_cuda_sanitizer.py::TestEventHandler::test_simple_error, test/test_cuda_sanitizer.py::TestEventHandler::test_simple_passing, test/test_cuda_sanitizer.py::TestEventHandler::test_simple_sync, test/test_cuda_sanitizer.py::TestEventHandler::test_stream_synchronize, test/test_cuda_sanitizer.py::TestMessages::test_ensure_does_not_exist, test/test_cuda_sanitizer.py::TestMessages::test_ensure_exists, test/test_cuda_sanitizer.py::TestMessages::test_error_message, test/test_cuda_sanitizer.py::TestMessages::test_subclass 2025-08-26T23:25:46.2731542Z 2025-08-26T23:25:46.2731615Z Running test_cuda_trace 1/1 ... [2025-08-26 23:25:46.272329] 2025-08-26T23:25:46.2737066Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:25:46.2737476Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_cuda_trace.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:25:46.272597] 2025-08-26T23:26:16.8434091Z 2025-08-26T23:26:16.8434881Z test_cuda_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_trace_1.1_08022bdc3f9aeb4e_.log 2025-08-26T23:26:16.8436433Z Running 12 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_all_trace_callbacks_called, test/test_cuda_trace.py::TestCudaTrace::test_device_synchronization_callback, test/test_cuda_trace.py::TestCudaTrace::test_event_creation_callback, test/test_cuda_trace.py::TestCudaTrace::test_event_deletion_callback, test/test_cuda_trace.py::TestCudaTrace::test_event_record_callback, test/test_cuda_trace.py::TestCudaTrace::test_event_synchronization_callback, test/test_cuda_trace.py::TestCudaTrace::test_event_wait_callback, test/test_cuda_trace.py::TestCudaTrace::test_memcpy_synchronization, test/test_cuda_trace.py::TestCudaTrace::test_memory_allocation_callback, test/test_cuda_trace.py::TestCudaTrace::test_memory_deallocation_callback, test/test_cuda_trace.py::TestCudaTrace::test_stream_creation_callback, test/test_cuda_trace.py::TestCudaTrace::test_stream_synchronization_callback 2025-08-26T23:26:16.8438085Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_all_trace_callbacks_called 2025-08-26T23:26:16.8438368Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_device_synchronization_callback 2025-08-26T23:26:16.8438644Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_event_creation_callback 2025-08-26T23:26:16.8438903Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_event_deletion_callback 2025-08-26T23:26:16.8439168Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_event_record_callback 2025-08-26T23:26:16.8439435Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_event_synchronization_callback 2025-08-26T23:26:16.8439768Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_event_wait_callback 2025-08-26T23:26:16.8445313Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_memcpy_synchronization 2025-08-26T23:26:16.8445592Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_memory_allocation_callback 2025-08-26T23:26:16.8445861Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_memory_deallocation_callback 2025-08-26T23:26:16.8446133Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_stream_creation_callback 2025-08-26T23:26:16.8446404Z Running 1 items in this shard: test/test_cuda_trace.py::TestCudaTrace::test_stream_synchronization_callback 2025-08-26T23:26:16.8446569Z 2025-08-26T23:26:16.8446663Z Running test_fake_tensor 1/1 ... [2025-08-26 23:26:16.843254] 2025-08-26T23:26:16.8446816Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:26:16.8447281Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_fake_tensor.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:26:16.843450] 2025-08-26T23:26:28.7504184Z 2025-08-26T23:26:28.7504948Z test_fake_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fake_tensor_1.1_21c4c4ffd02d674d_.log 2025-08-26T23:26:28.7541190Z Running 279 items in this shard: test/test_fake_tensor.py::FakeTensorTest::test__adaptive_avg_pool2d_backward, test/test_fake_tensor.py::FakeTensorTest::test_alias_call, test/test_fake_tensor.py::FakeTensorTest::test_allow_meta, test/test_fake_tensor.py::FakeTensorTest::test_aten_copy_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_index_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_slice_scatter_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_basic, test/test_fake_tensor.py::FakeTensorTest::test_batch_tensor, test/test_fake_tensor.py::FakeTensorTest::test_binary_op_type_promotion, test/test_fake_tensor.py::FakeTensorTest::test_constructor, test/test_fake_tensor.py::FakeTensorTest::test_convert_fake_to_real, test/test_fake_tensor.py::FakeTensorTest::test_cpu_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cuda_initialized, test/test_fake_tensor.py::FakeTensorTest::test_cuda_lstm, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_with_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_without_fallback, test/test_fake_tensor.py::FakeTensorTest::test_custom_op_fallback, test/test_fake_tensor.py::FakeTensorTest::test_data_dependent_operator, test/test_fake_tensor.py::FakeTensorTest::test_deepcopy, test/test_fake_tensor.py::FakeTensorTest::test_device_inplace_copy, test/test_fake_tensor.py::FakeTensorTest::test_embedding_bag_meta, test/test_fake_tensor.py::FakeTensorTest::test_export_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fake_device, test/test_fake_tensor.py::FakeTensorTest::test_fake_dispatch_keys, test/test_fake_tensor.py::FakeTensorTest::test_fake_grad_copy, test/test_fake_tensor.py::FakeTensorTest::test_fake_mode_error, test/test_fake_tensor.py::FakeTensorTest::test_fast_div, test/test_fake_tensor.py::FakeTensorTest::test_from_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fsdp_flat_param, test/test_fake_tensor.py::FakeTensorTest::test_full, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex128, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int16, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int8, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_uint8, test/test_fake_tensor.py::FakeTensorTest::test_index_put_error, test/test_fake_tensor.py::FakeTensorTest::test_jagged_fake_to_fake_preserved, test/test_fake_tensor.py::FakeTensorTest::test_like_constructor, test/test_fake_tensor.py::FakeTensorTest::test_mixed_real_and_fake_inputs, test/test_fake_tensor.py::FakeTensorTest::test_mode, test/test_fake_tensor.py::FakeTensorTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorTest::test_nanmean_out, test/test_fake_tensor.py::FakeTensorTest::test_new, test/test_fake_tensor.py::FakeTensorTest::test_no_tag_func, test/test_fake_tensor.py::FakeTensorTest::test_non_kwarg_device, test/test_fake_tensor.py::FakeTensorTest::test_non_overlapping_stride_zero, test/test_fake_tensor.py::FakeTensorTest::test_non_parameter_grad, test/test_fake_tensor.py::FakeTensorTest::test_normalize_device, test/test_fake_tensor.py::FakeTensorTest::test_op_with_zero_dim_bypassed, test/test_fake_tensor.py::FakeTensorTest::test_out_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_parameter_instantiation, test/test_fake_tensor.py::FakeTensorTest::test_parameter_view, test/test_fake_tensor.py::FakeTensorTest::test_print_in_fake_mode, test/test_fake_tensor.py::FakeTensorTest::test_randperm, test/test_fake_tensor.py::FakeTensorTest::test_recursive_invocation, test/test_fake_tensor.py::FakeTensorTest::test_repr, test/test_fake_tensor.py::FakeTensorTest::test_same_shape_env_preserved, test/test_fake_tensor.py::FakeTensorTest::test_scalar_inputs, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_False, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_True, test/test_fake_tensor.py::FakeTensorTest::test_setitem, test/test_fake_tensor.py::FakeTensorTest::test_shape_take_not_device, test/test_fake_tensor.py::FakeTensorTest::test_split_return_self, test/test_fake_tensor.py::FakeTensorTest::test_throw, test/test_fake_tensor.py::FakeTensorTest::test_tolist, test/test_fake_tensor.py::FakeTensorTest::test_type_as, test/test_fake_tensor.py::FakeTensorTest::test_unbind_copy_out, test/test_fake_tensor.py::FakeTensorTest::test_unsqueeze_copy, test/test_fake_tensor.py::FakeTensorTest::test_upsample_bilinear_small_channels, test/test_fake_tensor.py::FakeTensorTest::test_zero_dim, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test__adaptive_avg_pool2d_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_alias_call_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_allow_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_copy_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_index_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_slice_scatter_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_basic_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_batch_tensor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_binary_op_type_promotion_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_convert_fake_to_real_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cpu_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_initialized_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_lstm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_with_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_without_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_custom_op_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_data_dependent_operator_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_deepcopy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_device_inplace_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_embedding_bag_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_export_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_dispatch_keys_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_grad_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fast_div_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_from_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fsdp_flat_param_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_full_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex128_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int16_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_uint8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_put_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_jagged_fake_to_fake_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_like_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mixed_real_and_fake_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nanmean_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_no_tag_func_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_overlapping_stride_zero_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_parameter_grad_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_normalize_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_op_with_zero_dim_bypassed_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_out_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_instantiation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_print_in_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_randperm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_recursive_invocation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_repr_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_same_shape_env_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scalar_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_False_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_True_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_setitem_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_shape_take_not_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_split_return_self_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_throw_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_tolist_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_type_as_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unbind_copy_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unsqueeze_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_upsample_bilinear_small_channels_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_zero_dim_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorConstHandling::test_aliased_const_write, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_propagate_through_functions, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_batch_norm_cpu, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_in_intlist_repro, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_add, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_view_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storage_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storages, test/test_fake_tensor.py::FakeTensorConstHandling::test_simple, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_aliased_const_write_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_propagate_through_functions_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_batch_norm_cpu_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_in_intlist_repro_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_add_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_view_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storage_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storages_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_simple_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyCatCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyCubeCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyMulCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyMulScalarCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyNMSCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyNonzeroCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpySortCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpySplitCopyCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpySplitCopyWithIntCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyTakeCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCUDA::test_fake_NumpyViewCopyCustomOp_cuda_float32, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_key, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_weak_ref, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_from_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_to_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_multiple_modes, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_active_mode, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_ref_cycle, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_mode_error, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_non_view, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_view, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_key_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_weak_ref_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_from_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_to_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_multiple_modes_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_active_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_ref_cycle_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_non_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_view_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_conv_c1_backward, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_cross_entropy_loss, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_embedding_bag_private, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_fake_gpu_no_init, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_flash_attention, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_like_ops, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_no_dispatch_with_like_function, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_non_kwarg_only_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_sparse_new, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_str_storage, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_new, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_conv_c1_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_cross_entropy_loss_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_embedding_bag_private_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_fake_gpu_no_init_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_flash_attention_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_like_ops_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_module_to_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_no_dispatch_with_like_function_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_non_kwarg_only_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_sparse_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_str_storage_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_new_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args, test/test_fake_tensor.py::FakeTensorPropTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorPropTest::test_nonzero_stride, test/test_fake_tensor.py::FakeTensorPropTest::test_torch_load_with_fake_mode, test/test_fake_tensor.py::FakeTensorPropTest::test_unbacked_shape_realloc, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nonzero_stride_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_torch_load_with_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_unbacked_shape_realloc_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization_with_tracing, test/test_fake_tensor.py::FakeTensorDispatchCache::test__upsample_bilinear2d_aa_backward_dynamic_shapes, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_aten_index, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_bypass, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_dispatch_key_set, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_hit, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_inplace_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_constants, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_conj, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_inference, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_neg, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_memory_format, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_requires_grad, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_shape, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_storage_offset, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_stride, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_tuple_outputs, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_view_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_fft_hfft2_issue145522, test/test_fake_tensor.py::FakeTensorDispatchCache::test_from_buffer, test/test_fake_tensor.py::FakeTensorDispatchCache::test_inference_mode, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph_cacheable_inplace, test/test_fake_tensor.py::FakeTensorDispatchCache::test_meta_tensor_to_fake_cpu, test/test_fake_tensor.py::FakeTensorDispatchCache::test_shape_env_settings, test/test_fake_tensor.py::FakeTensorDispatchCache::test_unbacked_output, test/test_fake_tensor.py::FakeTensorDispatchCache::test_wrapper_tensor_subclass_different_device, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type_cpu_only 2025-08-26T23:26:28.7581026Z 2025-08-26T23:26:28.7581100Z Running test_file_check 1/1 ... [2025-08-26 23:26:28.750746] 2025-08-26T23:26:28.7581252Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:26:28.7581620Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_file_check.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:26:28.750973] 2025-08-26T23:26:32.1291417Z 2025-08-26T23:26:32.1292602Z test_file_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_file_check_1.1_7bacdf91b407f7fa_.log 2025-08-26T23:26:32.1293804Z Running 2 items in this shard: test/test_file_check.py::TestFileCheck::test_all_python_api, test/test_file_check.py::TestFileCheck::test_not_run 2025-08-26T23:26:32.1294737Z 2025-08-26T23:26:32.1294955Z Running test_flop_counter 1/1 ... [2025-08-26 23:26:32.128885] 2025-08-26T23:26:32.1295386Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:26:32.1296306Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_flop_counter.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:26:32.129096] 2025-08-26T23:26:48.2890652Z 2025-08-26T23:26:48.2891798Z test_flop_counter 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_flop_counter_1.1_a43e8d4bb2d9dfa8_.log 2025-08-26T23:26:48.2894740Z Running 22 items in this shard: test/test_flop_counter.py::TestFlopCounter::test_addmm_out, test/test_flop_counter.py::TestFlopCounter::test_autograd_op, test/test_flop_counter.py::TestFlopCounter::test_backward, test/test_flop_counter.py::TestFlopCounter::test_backward_reset, test/test_flop_counter.py::TestFlopCounter::test_conv_backwards_as_decomposition, test/test_flop_counter.py::TestFlopCounter::test_conv_transpose_loop, test/test_flop_counter.py::TestFlopCounter::test_convs, test/test_flop_counter.py::TestFlopCounter::test_custom, test/test_flop_counter.py::TestFlopCounter::test_custom_op, test/test_flop_counter.py::TestFlopCounter::test_flop_counter_variety, test/test_flop_counter.py::TestFlopCounter::test_hook_registration, test/test_flop_counter.py::TestFlopCounter::test_inference_mode, test/test_flop_counter.py::TestFlopCounter::test_module, test/test_flop_counter.py::TestFlopCounter::test_nested_attention_fake_tensors, test/test_flop_counter.py::TestFlopCounter::test_noop, test/test_flop_counter.py::TestFlopCounter::test_op, test/test_flop_counter.py::TestFlopCounter::test_pytrees, test/test_flop_counter.py::TestFlopCounter::test_scaled_mm, test/test_flop_counter.py::TestFlopCounter::test_sdpa, test/test_flop_counter.py::TestFlopCounter::test_sdpa_nested_tensor, test/test_flop_counter.py::TestFlopCounter::test_torchscript, test/test_flop_counter.py::TestFlopCounter::test_warning 2025-08-26T23:26:48.2897271Z 2025-08-26T23:26:48.2897382Z Running test_function_schema 1/1 ... [2025-08-26 23:26:48.288846] 2025-08-26T23:26:48.2897582Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:26:48.2898113Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_function_schema.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:26:48.289056] 2025-08-26T23:26:51.0613302Z 2025-08-26T23:26:51.0614534Z test_function_schema 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_function_schema_1.1_0eeb825c293206de_.log 2025-08-26T23:26:51.0616657Z Running 15 items in this shard: test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_arguments, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_outputs, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_structure, test/test_function_schema.py::TestFunctionSchema::test_backward_compatible_with_smart_serialization, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_real_use_case, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_with_out, test/test_function_schema.py::TestFunctionSchema::test_forward_compatible_arguments_without_out, test/test_function_schema.py::TestFunctionSchema::test_hash_schema, test/test_function_schema.py::TestFunctionSchema::test_out_schema, test/test_function_schema.py::TestFunctionSchema::test_schema_error, test/test_function_schema.py::TestFunctionSchema::test_serialize_and_deserialize, test/test_function_schema.py::TestFunctionSchema::test_string_optional_parameter_default_value, test/test_function_schema.py::TestFunctionSchema::test_sym_int_argument_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_list_alias_annotation_properly_parsed, test/test_function_schema.py::TestFunctionSchema::test_tensor_option_arguments_properly_parsed 2025-08-26T23:26:51.0618841Z 2025-08-26T23:26:51.0642634Z Running test_functionalization 1/1 ... [2025-08-26 23:26:51.061278] 2025-08-26T23:26:51.0642835Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:26:51.0644121Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_functionalization.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:26:51.061465] 2025-08-26T23:27:01.2887894Z 2025-08-26T23:27:01.2888900Z test_functionalization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functionalization_1.1_7cb1e470272b30ad_.log 2025-08-26T23:27:01.2904233Z Running 112 items in this shard: test/test_functionalization.py::TestFunctionalization::test_advanced_indexing, test/test_functionalization.py::TestFunctionalization::test_advanced_indexing_correct_strides, test/test_functionalization.py::TestFunctionalization::test_aliases_maintained_after_pass_when_reapplying_views, test/test_functionalization.py::TestFunctionalization::test_as_strided, test/test_functionalization.py::TestFunctionalization::test_batch_norm, test/test_functionalization.py::TestFunctionalization::test_cat, test/test_functionalization.py::TestFunctionalization::test_channels_last_contiguous, test/test_functionalization.py::TestFunctionalization::test_copy_, test/test_functionalization.py::TestFunctionalization::test_copy_stride_mismatch, test/test_functionalization.py::TestFunctionalization::test_diagonal, test/test_functionalization.py::TestFunctionalization::test_diagonal_mutated_input, test/test_functionalization.py::TestFunctionalization::test_everything, test/test_functionalization.py::TestFunctionalization::test_expand_symint, test/test_functionalization.py::TestFunctionalization::test_fill_, test/test_functionalization.py::TestFunctionalization::test_freeze, test/test_functionalization.py::TestFunctionalization::test_index_mutation_on_non_input, test/test_functionalization.py::TestFunctionalization::test_inplace_on_non_view, test/test_functionalization.py::TestFunctionalization::test_instance_norm, test/test_functionalization.py::TestFunctionalization::test_metadata_change, test/test_functionalization.py::TestFunctionalization::test_metadata_change_out_op, test/test_functionalization.py::TestFunctionalization::test_mixed_wrappers_invalid, test/test_functionalization.py::TestFunctionalization::test_mixed_wrappers_valid, test/test_functionalization.py::TestFunctionalization::test_multi_out, test/test_functionalization.py::TestFunctionalization::test_multiple_views_of_same_base, test/test_functionalization.py::TestFunctionalization::test_mutable_op_not_inplace_or_other, test/test_functionalization.py::TestFunctionalization::test_mutation_overlapping_mem, test/test_functionalization.py::TestFunctionalization::test_nested_functions_propagate_updates, test/test_functionalization.py::TestFunctionalization::test_only_one_view, test/test_functionalization.py::TestFunctionalization::test_optional_tensor_list, test/test_functionalization.py::TestFunctionalization::test_python_functionalization, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_conj, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_is_conj, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_is_neg, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_lift_fresh, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_lift_fresh_storage, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_neg, test/test_functionalization.py::TestFunctionalization::test_python_functionalization_zero_tensor, test/test_functionalization.py::TestFunctionalization::test_reapply_views_simple, test/test_functionalization.py::TestFunctionalization::test_resize_larger_invalid, test/test_functionalization.py::TestFunctionalization::test_resize_larger_valid, test/test_functionalization.py::TestFunctionalization::test_resize_same_size_diff_rank, test/test_functionalization.py::TestFunctionalization::test_resize_smaller, test/test_functionalization.py::TestFunctionalization::test_save_for_backwards_segfault, test/test_functionalization.py::TestFunctionalization::test_scalars, test/test_functionalization.py::TestFunctionalization::test_set_, test/test_functionalization.py::TestFunctionalization::test_simple, test/test_functionalization.py::TestFunctionalization::test_simple_out, test/test_functionalization.py::TestFunctionalization::test_slice, test/test_functionalization.py::TestFunctionalization::test_split, test/test_functionalization.py::TestFunctionalization::test_split_with_sizes, test/test_functionalization.py::TestFunctionalization::test_tensor_ctr, test/test_functionalization.py::TestFunctionalization::test_tensor_list_composite, test/test_functionalization.py::TestFunctionalization::test_tensor_list_mixed_functional_nonfunctional, test/test_functionalization.py::TestFunctionalization::test_unbind, test/test_functionalization.py::TestFunctionalization::test_view_clone_view_inplace, test/test_functionalization.py::TestFunctionalization::test_view_inplace, test/test_functionalization.py::TestCrossRefFunctionalization::test_advanced_indexing, test/test_functionalization.py::TestCrossRefFunctionalization::test_advanced_indexing_correct_strides, test/test_functionalization.py::TestCrossRefFunctionalization::test_aliases_maintained_after_pass_when_reapplying_views, test/test_functionalization.py::TestCrossRefFunctionalization::test_as_strided, test/test_functionalization.py::TestCrossRefFunctionalization::test_batch_norm, test/test_functionalization.py::TestCrossRefFunctionalization::test_cat, test/test_functionalization.py::TestCrossRefFunctionalization::test_channels_last_contiguous, test/test_functionalization.py::TestCrossRefFunctionalization::test_copy_, test/test_functionalization.py::TestCrossRefFunctionalization::test_copy_stride_mismatch, test/test_functionalization.py::TestCrossRefFunctionalization::test_diagonal, test/test_functionalization.py::TestCrossRefFunctionalization::test_diagonal_mutated_input, test/test_functionalization.py::TestCrossRefFunctionalization::test_everything, test/test_functionalization.py::TestCrossRefFunctionalization::test_expand_symint, test/test_functionalization.py::TestCrossRefFunctionalization::test_fill_, test/test_functionalization.py::TestCrossRefFunctionalization::test_freeze, test/test_functionalization.py::TestCrossRefFunctionalization::test_index_mutation_on_non_input, test/test_functionalization.py::TestCrossRefFunctionalization::test_inplace_on_non_view, test/test_functionalization.py::TestCrossRefFunctionalization::test_instance_norm, test/test_functionalization.py::TestCrossRefFunctionalization::test_metadata_change, test/test_functionalization.py::TestCrossRefFunctionalization::test_metadata_change_out_op, test/test_functionalization.py::TestCrossRefFunctionalization::test_mixed_wrappers_invalid, test/test_functionalization.py::TestCrossRefFunctionalization::test_mixed_wrappers_valid, test/test_functionalization.py::TestCrossRefFunctionalization::test_multi_out, test/test_functionalization.py::TestCrossRefFunctionalization::test_multiple_views_of_same_base, test/test_functionalization.py::TestCrossRefFunctionalization::test_mutable_op_not_inplace_or_other, test/test_functionalization.py::TestCrossRefFunctionalization::test_mutation_overlapping_mem, test/test_functionalization.py::TestCrossRefFunctionalization::test_nested_functions_propagate_updates, test/test_functionalization.py::TestCrossRefFunctionalization::test_only_one_view, test/test_functionalization.py::TestCrossRefFunctionalization::test_optional_tensor_list, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_conj, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_is_conj, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_is_neg, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_lift_fresh, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_lift_fresh_storage, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_neg, test/test_functionalization.py::TestCrossRefFunctionalization::test_python_functionalization_zero_tensor, test/test_functionalization.py::TestCrossRefFunctionalization::test_reapply_views_simple, test/test_functionalization.py::TestCrossRefFunctionalization::test_resize_larger_invalid, test/test_functionalization.py::TestCrossRefFunctionalization::test_resize_larger_valid, test/test_functionalization.py::TestCrossRefFunctionalization::test_resize_same_size_diff_rank, test/test_functionalization.py::TestCrossRefFunctionalization::test_resize_smaller, test/test_functionalization.py::TestCrossRefFunctionalization::test_save_for_backwards_segfault, test/test_functionalization.py::TestCrossRefFunctionalization::test_scalars, test/test_functionalization.py::TestCrossRefFunctionalization::test_set_, test/test_functionalization.py::TestCrossRefFunctionalization::test_simple, test/test_functionalization.py::TestCrossRefFunctionalization::test_simple_out, test/test_functionalization.py::TestCrossRefFunctionalization::test_slice, test/test_functionalization.py::TestCrossRefFunctionalization::test_split, test/test_functionalization.py::TestCrossRefFunctionalization::test_split_with_sizes, test/test_functionalization.py::TestCrossRefFunctionalization::test_tensor_ctr, test/test_functionalization.py::TestCrossRefFunctionalization::test_tensor_list_composite, test/test_functionalization.py::TestCrossRefFunctionalization::test_tensor_list_mixed_functional_nonfunctional, test/test_functionalization.py::TestCrossRefFunctionalization::test_unbind, test/test_functionalization.py::TestCrossRefFunctionalization::test_view_clone_view_inplace, test/test_functionalization.py::TestCrossRefFunctionalization::test_view_inplace 2025-08-26T23:27:01.2917712Z 2025-08-26T23:27:01.2917788Z Running test_fx_passes 1/1 ... [2025-08-26 23:27:01.288717] 2025-08-26T23:27:01.2917941Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:27:01.2918340Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_fx_passes.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:27:01.288907] 2025-08-26T23:27:03.9661618Z 2025-08-26T23:27:03.9662423Z test_fx_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_passes_1.1_e7b8d746e00ec9d3_.log 2025-08-26T23:27:03.9669527Z Running 53 items in this shard: test/test_fx_passes.py::TestFXGraphPasses::test_fuser_pass_deep_model, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition10, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition11, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition4, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition5, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition6, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition7, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition8, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_partition9, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition0, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition1, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition2, test/test_fx_passes.py::TestFXGraphPasses::test_fuser_util_xfail_partition3, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn0_expected_partition0_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn10_expected_partition10_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn11_expected_partition11_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn12_expected_partition12_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn13_expected_partition13_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn14_expected_partition14_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn15_expected_partition15_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn16_expected_partition16_bookend_non_compute_pass_True, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn17_expected_partition17_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn18_expected_partition18_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn1_expected_partition1_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn2_expected_partition2_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn3_expected_partition3_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn4_expected_partition4_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn5_expected_partition5_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn6_expected_partition6_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn7_expected_partition7_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn8_expected_partition8_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_fn9_expected_partition9_bookend_non_compute_pass_False, test/test_fx_passes.py::TestFXGraphPasses::test_partitioner_independent_output_fn0_expected_partition0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model0, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model1, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model10, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model11, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model12, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model13, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model14, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model15, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model2, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model3, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model4, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model5, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model6, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model7, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model8, test/test_fx_passes.py::TestFXMatcherUtils::test_subgraph_matcher_test_model9 2025-08-26T23:27:03.9677333Z 2025-08-26T23:27:03.9677548Z Running test_fx_reinplace_pass 1/1 ... [2025-08-26 23:27:03.963129] 2025-08-26T23:27:03.9677905Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:27:03.9678618Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_fx_reinplace_pass.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:27:03.963340] 2025-08-26T23:27:07.4358242Z 2025-08-26T23:27:07.4358870Z test_fx_reinplace_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_reinplace_pass_1.1_391618d89a708bf8_.log 2025-08-26T23:27:07.4361062Z Running 12 items in this shard: test/test_fx_reinplace_pass.py::TestReinplacePass::test_out_node_updated, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_basic, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_different_metadata, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_index_mutation, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_overlapping_memory, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_op, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid2, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_valid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_sym_input, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_with_view 2025-08-26T23:27:07.4362626Z 2025-08-26T23:27:07.4362709Z Running test_jit_llga_fuser 1/1 ... [2025-08-26 23:27:07.435627] 2025-08-26T23:27:07.4362870Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:27:07.4363257Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_jit_llga_fuser.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:27:07.435807] 2025-08-26T23:27:58.5862319Z 2025-08-26T23:27:58.5865285Z test_jit_llga_fuser 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_llga_fuser_1.1_cda174ec2902ed1a_.log 2025-08-26T23:27:58.5877495Z Running 107 items in this shard: test/test_jit_llga_fuser.py::TestEnableDisableLlgaFuser::test_context_manager, test/test_jit_llga_fuser.py::TestDynamoAOT::test_dynamo_aot_ts_onednn, test/test_jit_llga_fuser.py::TestModel::test_vision_alexnet_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_alexnet_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet121_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet121_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet161_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet161_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet169_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet169_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet201_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_densenet201_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b1_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b1_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b2_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b3_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b3_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b4_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b4_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b5_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b5_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b6_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b6_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b7_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_efficientnet_b7_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_googlenet_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_googlenet_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mnasnet1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mnasnet1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v2_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v3_large_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_mobilenet_v3_large_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_regnet_y_400mf_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_regnet_y_400mf_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnet50_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnet50_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext101_32x8d_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext101_32x8d_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext50_32x4d_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_resnext50_32x4d_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_shufflenet_v2_x1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_shufflenet_v2_x1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_squeezenet1_0_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_squeezenet1_0_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_vgg16_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_vgg16_float32, test/test_jit_llga_fuser.py::TestModel::test_vision_wide_resnet50_2_bfloat16, test/test_jit_llga_fuser.py::TestModel::test_vision_wide_resnet50_2_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_bn2d_eltwise_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_bn2d_eltwise_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_bn_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_bn_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_bn_relu_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_bn_relu_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_clamp_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_clamp_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_eltwise_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_eltwise_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_silu_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_silu_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_sum_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_conv2d_sum_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_ensure_tensor_is_rewrapped_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_ensure_tensor_is_rewrapped_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_linear_eltwise_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_linear_eltwise_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_rewrap_tensor_input_to_pytorch_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_rewrap_tensor_input_to_pytorch_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_wildcard_cuda_bfloat16, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_wildcard_cuda_float32, test/test_jit_llga_fuser.py::TestFusionPatternCUDA::test_wildcard_unsupported_dtype_cuda_int32, test/test_jit_llga_fuser.py::TestOpCUDA::test_add_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_add_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_add_scalar_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_add_scalar_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_addmm_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_addmm_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_avg_pool2d_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_avg_pool2d_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_bn2d_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_bn2d_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_cat_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_cat_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_conv2d_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_conv2d_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_eltwise_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_eltwise_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_identity_binary_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_identity_binary_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_layer_norm_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_layer_norm_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_linear_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_linear_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_max_pool2d_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_max_pool2d_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_mul_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_mul_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_softmax_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_softmax_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_typecheck_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_typecheck_cuda_float32, test/test_jit_llga_fuser.py::TestOpCUDA::test_variable_kernel_avg_pool2d_cuda_bfloat16, test/test_jit_llga_fuser.py::TestOpCUDA::test_variable_kernel_avg_pool2d_cuda_float32 2025-08-26T23:27:58.5888046Z 2025-08-26T23:27:58.5888117Z Running test_meta 2/2 ... [2025-08-26 23:27:58.586417] 2025-08-26T23:27:58.5888268Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:27:58.5894004Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_meta.py', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:27:58.586727] 2025-08-26T23:35:45.3104412Z 2025-08-26T23:35:45.3105618Z test_meta 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_meta_2.2_9299ffe4a0765c0c_.log 2025-08-26T23:35:45.5528337Z Running 20396 items in this shard: test/test_meta.py::TestMetaConverter::test_channels_last, test/test_meta.py::TestMetaConverter::test_channels_last_leaf, test/test_meta.py::TestMetaConverter::test_channels_last_non_leaf, test/test_meta.py::TestMetaConverter::test_empty_strided_non_dense_leaf, test/test_meta.py::TestMetaConverter::test_imag, test/test_meta.py::TestMetaConverter::test_non_leaf_torture, test/test_meta.py::TestMetaConverter::test_view_dtype, test/test_meta.py::TestMetaConverter::test_view_of_view_of_leaf, test/test_meta.py::TestMetaCUDA::test_batch_norm_backward_output_mask2_cuda, test/test_meta.py::TestMetaCUDA::test_batch_norm_backward_output_mask3_cuda, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype___radd___cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype___rdiv___cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype___rmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype___rpow___cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype___rsub___cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs__conversions_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs__conversions_polar_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_div_no_rounding_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_eq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_float_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_fmod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_nextafter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_rsub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_special_zeta_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype__refs_sub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_atan2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_clamp_min_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_copysign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_eq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_float_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_fmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_gt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_jiterator_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_ldexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_lt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_min_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_minimum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_mul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_ne_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_nextafter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_u_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_chebyshev_polynomial_v_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_hermite_polynomial_he_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_laguerre_polynomial_l_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_shifted_chebyshev_polynomial_w_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_special_zeta_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_sub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_binary_ufuncs_mixed_dtype_true_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_H_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_H_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_H_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_H_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_T_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___getitem___cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___radd___cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___radd___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___radd___cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rand___cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rand___cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rdiv___cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmatmul___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmod___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmod___cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmod___cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmod___cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmul___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmul___cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmul___cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rmul___cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___ror___cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___ror___cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___ror___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rpow___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rpow___cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rpow___cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rpow___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rsub___cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rsub___cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rxor___cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace___rxor___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__batch_norm_with_update_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__batch_norm_with_update_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__batch_norm_with_update_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__chunk_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__chunk_cat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__chunk_cat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__chunk_cat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__chunk_cat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_abs_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_abs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_acos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcdiv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcdiv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcdiv_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcdiv_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcdiv_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_addcmul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_asin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_atan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_ceil_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_ceil_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_ceil_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_max_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_max_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_max_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_clamp_min_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cos_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace__foreach_cosh_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_abs_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_abs_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_abs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_acosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addbmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addbmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addbmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addbmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcdiv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcdiv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcdiv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcdiv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addcmul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmm_decomposed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmm_decomposed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmm_decomposed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addmv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addr_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addr_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_addr_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_alias_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_all_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_allclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_allclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_allclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_allclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_aminmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_aminmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_angle_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_angle_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_angle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_angle_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_any_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_any_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_any_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_any_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_arange_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_arange_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_arange_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_arange_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_arange_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argsort_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argwhere_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argwhere_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argwhere_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argwhere_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_argwhere_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_partial_views_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_as_strided_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_asinh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_2d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_baddbmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_baddbmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_baddbmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_baddbmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bernoulli_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bernoulli_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bfloat16_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bfloat16_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bfloat16_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bfloat16_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bfloat16_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bincount_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bincount_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_and_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_left_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_left_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_left_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_or_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_right_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_right_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bitwise_right_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_block_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bool_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bool_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bool_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bool_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_bool_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_shapes_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_broadcast_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_byte_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cauchy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cdouble_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ceil_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cfloat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_char_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_char_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_char_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_char_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_inverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_inverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cholesky_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_chunk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_max_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_max_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_min_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_min_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clamp_min_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_clone_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_column_stack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_combinations_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_contiguous_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_copysign_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_copysign_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_copysign_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_copysign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_copysign_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_corrcoef_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_count_nonzero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_count_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_count_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_count_nonzero_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cov_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cross_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cummin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumprod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumprod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumprod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumsum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_cumulative_trapezoid_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_deg2rad_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_embed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_embed_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diag_embed_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagflat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagflat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagflat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagflat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagflat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_diff_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_digamma_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_digamma_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_digamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_digamma_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_digamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dist_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dist_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dist_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_floor_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_no_rounding_mode_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_div_trunc_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_double_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_dstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_einsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_einsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_einsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_permuted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_empty_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eq_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_equal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfinv_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfinv_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfinv_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_erfinv_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expand_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expm1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expm1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expm1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expm1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_expm1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exponential_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exponential_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_float8_e4m3fnuz, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_float8_e5m2fnuz, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_eye_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftshift_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftshift_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftshift_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_fftshift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_hfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftshift_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftshift_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftshift_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ifftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_ihfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_irfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fft_rfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flip_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fliplr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_flipud_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_float_power_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_divide_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_floor_divide_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_fmod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_frac_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_frexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_uint32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_full_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gather_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gather_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gather_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gather_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gather_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gcd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ge_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ge_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ge_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ge_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geometric_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geometric_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geometric_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geometric_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geqrf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geqrf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_geqrf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gradient_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gradient_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gradient_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gradient_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_grid_sampler_2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_grid_sampler_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_grid_sampler_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_grid_sampler_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_gt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hash_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hash_tensor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hash_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hash_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_heaviside_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_histc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_histc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hsplit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_hypot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_i0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_i0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_i0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_i0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_imag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_imag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_mean_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_mean_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_reduce_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_index_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_inner_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_inner_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_inner_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_int_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isclose_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isfinite_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isinf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isnan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isneginf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isneginf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isneginf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isneginf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isposinf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_isreal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_item_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_item_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_item_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_item_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_item_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_2inputs_2outputs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_4inputs_with_extra_args_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_4inputs_with_extra_args_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_4inputs_with_extra_args_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_4inputs_with_extra_args_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_4inputs_with_extra_args_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_return_by_ref_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_return_by_ref_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_return_by_ref_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_binary_return_by_ref_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_unary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_unary_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_unary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_unary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_jiterator_unary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kron_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kron_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kron_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kron_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kron_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kthvalue_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kthvalue_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kthvalue_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_kthvalue_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lcm_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lcm_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lcm_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ldexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_le_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lerp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lerp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lgamma_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lgamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lgamma_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lgamma_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lgamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cholesky_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cond_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cond_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_det_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_det_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_det_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eig_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eig_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigvalsh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_eigvalsh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_householder_product_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_inv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_inv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_ldl_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_ldl_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_ldl_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lstsq_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lstsq_grad_oriented_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_factor_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_lu_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_rank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_rank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_rank_hermitian_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_matrix_rank_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_multi_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_subgradients_at_zero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_norm_subgradients_at_zero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_hermitian_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_singular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_pinv_singular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_qr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_slogdet_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_slogdet_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_slogdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_triangular_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_triangular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_solve_triangular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_svd_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_svd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_svd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_svdvals_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_svdvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_tensorsolve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_tensorsolve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vander_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vecdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vecdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vecdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vecdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vecdot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vector_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vector_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vector_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vector_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linalg_vector_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_linspace_tensor_overload_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log10_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log10_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log10_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log10_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log1p_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_with_dtype_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_with_dtype_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_log_softmax_with_dtype_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logaddexp2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logaddexp2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logaddexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logaddexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logaddexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logcumsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logdet_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_or_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logical_xor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_tensor_overload_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logsumexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_long_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_long_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_unpack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_unpack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_lu_unpack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mH_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mH_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mH_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mH_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mT_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_argmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumprod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_cumsum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_log_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_log_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logsumexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logsumexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_normalize_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_normalize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_normalize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_select_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_softmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_std_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_std_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_std_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_masked_var_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matmul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matmul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matmul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_matrix_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_pool2d_with_indices_backward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_no_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_with_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_with_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_with_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_max_reduction_with_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_maximum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_median_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_list_of_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_variadic_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_meshgrid_variadic_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_no_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_no_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_no_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_min_reduction_with_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_minimum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_minimum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mode_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_movedim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_movedim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_movedim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_movedim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_movedim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_msort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_msort_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mul_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_multinomial_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_multinomial_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nan_to_num_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nan_to_num_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nan_to_num_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nan_to_num_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmedian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmedian_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmedian_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nanmedian_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nansum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_narrow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_batch_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_batch_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_batch_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_dropout_backward_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_layer_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_native_layer_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ne_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ne_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ne_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ne_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_neg_cuda_uint8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_full_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_full_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_ones_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_zeros_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_zeros_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_new_zeros_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nextafter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_max_pool2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_max_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_adaptive_max_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_alpha_dropout_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_alpha_dropout_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_avg_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_binary_cross_entropy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_channel_shuffle_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose2d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose3d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_conv_transpose3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cosine_embedding_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cross_entropy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cross_entropy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_cross_entropy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_dropout2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_dropout2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_dropout3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_dropout_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_dropout_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_elu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_embedding_bag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_embedding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_embedding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_with_train_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_fractional_max_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_fractional_max_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_fractional_max_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_gaussian_nll_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_gaussian_nll_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_gelu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_gelu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_gelu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_glu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_glu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_group_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardshrink_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardshrink_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardshrink_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardswish_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardtanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_hardtanh_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_instance_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_instance_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_area_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_area_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_bicubic_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_bicubic_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_interpolate_linear_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_unfold_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_upsample_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nn_functional_upsample_nearest_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_nonzero_static_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_fro_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_fro_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_fro_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_fro_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_inf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_norm_nuc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_normal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_normal_in_place_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_normal_number_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_normal_number_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ones_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ormqr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_outer_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pca_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pca_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pca_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_permute_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pinverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pinverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polar_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_4_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_4_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_4_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_polygamma_polygamma_n_4_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_positive_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_positive_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_positive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_positive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_pow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_prod_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_qr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_quantile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rad2deg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rad2deg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rad2deg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rad2deg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rad2deg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rand_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rand_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randint_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_randn_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_ravel_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_real_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reciprocal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_remainder_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_renorm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_renorm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_renorm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_as_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_reshape_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resize_as__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_conj_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_conj_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_conj_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_resolve_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_roll_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_roll_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_roll_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rot90_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rot90_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rot90_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rot90_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rot90_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_round_decimals_neg_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsqrt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsub_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsub_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsub_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsub_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_rsub_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scalar_tensor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_sum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_scatter_reduce_sum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_searchsorted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_searchsorted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_searchsorted_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_searchsorted_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_searchsorted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_select_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sgn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_short_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sigmoid_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sigmoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sigmoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sign_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_bartlett_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_general_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_hamming_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_hamming_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_kaiser_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signal_windows_nuttall_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signbit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signbit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signbit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_signbit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sinh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_slice_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_softmax_with_dtype_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sparse_mm_reduce_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sparse_mm_reduce_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sparse_mm_reduce_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_sparse_sampled_addmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_airy_ai_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_airy_ai_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_airy_ai_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_j1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_bessel_y1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_t_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_t_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_t_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_t_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_u_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_v_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_v_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_v_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_w_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_w_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_chebyshev_polynomial_w_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_erfcx_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_erfcx_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_erfcx_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_hermite_polynomial_h_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_hermite_polynomial_he_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_hermite_polynomial_he_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_hermite_polynomial_he_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_hermite_polynomial_he_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_i0e_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_special_i0e_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_svd_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_svd_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_t_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_along_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_take_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tanh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tanh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensor_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensor_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensor_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensor_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensordot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensordot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensordot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensordot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tensordot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tile_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_to_sparse_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_topk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch__scaled_mm_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__efficient_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__flash_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_transpose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trapz_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triangular_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_tril_indices_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_triu_indices_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_true_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trunc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trunc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trunc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trunc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_trunc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unbind_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unflatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unfold_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_uniform_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_uniform_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_consecutive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_consecutive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_consecutive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_consecutive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_consecutive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_uint64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unique_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unravel_index_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unravel_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsafe_split_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_unsqueeze_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_mean_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_var_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vdot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_view_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_inplace_vsplit_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_decomposed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_decomposed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_decomposed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmm_decomposed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addmv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addr_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_addr_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_alias_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_all_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_allclose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_allclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_allclose_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_aminmax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_aminmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_aminmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_aminmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_aminmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_angle_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_angle_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_angle_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_any_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_arange_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_arange_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_arange_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argsort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_argwhere_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_partial_views_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_as_strided_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_asinh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atanh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_1d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_2d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_3d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_baddbmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_baddbmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_baddbmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_baddbmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bernoulli_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bernoulli_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bfloat16_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bincount_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bincount_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bincount_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_and_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_and_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_left_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_left_shift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_not_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_right_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_right_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_xor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_xor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_xor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bitwise_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_block_diag_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_block_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_block_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bool_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bool_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bool_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bool_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bool_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_broadcast_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bucketize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bucketize_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bucketize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bucketize_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_bucketize_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_byte_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cartesian_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cauchy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cdouble_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ceil_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cfloat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chalf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chalf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chalf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chalf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_char_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_char_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_char_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_char_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_inverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cholesky_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_max_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_max_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_max_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clamp_min_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clone_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clone_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clone_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clone_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_clone_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_column_stack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_column_stack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_column_stack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_column_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_combinations_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_combinations_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_combinations_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_conj_physical_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_constant_pad_nd_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_constant_pad_nd_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_constant_pad_nd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_contiguous_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_copysign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_copysign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_copysign_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_copysign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_copysign_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_corrcoef_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_corrcoef_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_corrcoef_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_corrcoef_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cos_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_count_nonzero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cov_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cov_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cov_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cov_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cov_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cross_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cummin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumprod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumsum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_cumulative_trapezoid_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_deg2rad_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_deg2rad_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_deg2rad_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diag_embed_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagflat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diagonal_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_diff_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_digamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_digamma_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_digamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dist_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dist_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_floor_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_floor_rounding_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_no_rounding_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_trunc_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_trunc_rounding_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_div_trunc_rounding_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_double_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_double_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dsplit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_dstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_einsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_einsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_permuted_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_empty_strided_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eq_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_equal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfinv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfinv_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_erfinv_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expand_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_expm1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exponential_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eye_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eye_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eye_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eye_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_eye_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_fftshift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_hfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ifftshift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_ihfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_irfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fft_rfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flatten_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flatten_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flip_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fliplr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flipud_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flipud_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flipud_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flipud_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_flipud_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_power_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_power_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_float_power_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_divide_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_floor_divide_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_fmod_cuda_int32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_full_like_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gather_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gcd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gcd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ge_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geometric_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geometric_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geometric_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geometric_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geqrf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geqrf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_geqrf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gradient_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_grid_sampler_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_grid_sampler_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_gt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_half_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_half_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_half_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hash_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hash_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hash_tensor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hash_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hash_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_heaviside_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_histc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_histc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_histc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_histc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hsplit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hypot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_hypot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_i0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_i0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_i0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_i0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_i0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_igammac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_imag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_copy_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_mean_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_reduce_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_index_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_inner_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_inner_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_inner_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_int_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_int_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_int_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_int_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_int_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isclose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isclose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isfinite_cuda_int16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isinf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isinf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isnan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isneginf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isposinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isposinf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isposinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isposinf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isposinf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_isreal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_istft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_item_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_2inputs_2outputs_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_2inputs_2outputs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_2inputs_2outputs_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_2inputs_2outputs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_2inputs_2outputs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_4inputs_with_extra_args_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_4inputs_with_extra_args_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_4inputs_with_extra_args_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_4inputs_with_extra_args_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_binary_return_by_ref_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_unary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_unary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_unary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_unary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_jiterator_unary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kron_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kthvalue_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kthvalue_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kthvalue_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_kthvalue_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lcm_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lcm_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ldexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_le_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lerp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lerp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lerp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lgamma_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cholesky_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cholesky_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cond_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cond_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cross_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_cross_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eig_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eig_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eigh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eigvals_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eigvalsh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_eigvalsh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_householder_product_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_inv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_inv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_inv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_inv_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_inv_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_factor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_factor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_factor_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_factor_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_ldl_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_lstsq_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_lstsq_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_hermitian_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_matrix_rank_hermitian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_multi_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_multi_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_multi_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_subgradients_at_zero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_subgradients_at_zero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_norm_subgradients_at_zero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_hermitian_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_hermitian_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_singular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_pinv_singular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_slogdet_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_slogdet_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_slogdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_solve_triangular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_svd_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_svd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_svdvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_svdvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_svdvals_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorinv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorinv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorsolve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorsolve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorsolve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_tensorsolve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vander_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vander_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vander_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vander_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vecdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vecdot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vecdot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vector_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linalg_vector_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_tensor_overload_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_linspace_tensor_overload_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log10_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log10_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log1p_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_log_softmax_with_dtype_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logaddexp2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logaddexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logaddexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logcumsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logdet_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_and_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_and_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_or_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_or_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_or_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_or_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logical_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_tensor_overload_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_long_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_unpack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_unpack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_lu_unpack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mH_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mH_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mH_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mH_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mH_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mT_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mT_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mT_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_argmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumsum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_log_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_logsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_median_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_normalize_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_normalize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_softmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_softmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_std_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_std_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_std_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_std_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_sum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_sum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_sum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_masked_var_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matmul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matrix_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matrix_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matrix_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_matrix_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_binary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_pool2d_with_indices_backward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_pool2d_with_indices_backward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_no_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_no_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_no_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_with_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_with_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_max_reduction_with_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_maximum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_maximum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_maximum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_maximum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_median_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_median_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_median_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_list_of_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_list_of_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_list_of_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_list_of_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_list_of_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_meshgrid_variadic_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_no_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_no_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_with_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_with_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_with_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_min_reduction_with_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_minimum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_minimum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_minimum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_minimum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mode_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mode_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_movedim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_movedim_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_movedim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_movedim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_movedim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_msort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mul_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mul_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mul_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_multinomial_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_multinomial_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nan_to_num_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nan_to_num_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nan_to_num_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nan_to_num_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nan_to_num_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmedian_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmedian_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmedian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmedian_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nanmedian_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nansum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_narrow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_batch_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_batch_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_dropout_backward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_dropout_backward_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_layer_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_native_layer_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ne_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_neg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_empty_cuda_int32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_full_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_new_ones_cuda_int8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_nonzero_static_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_fro_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_fro_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_fro_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_inf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_inf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_norm_nuc_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_permute_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pinverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polar_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_4_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_4_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_polygamma_polygamma_n_4_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_positive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_pow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rad2deg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rad2deg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rand_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rand_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randint_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_randn_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_ravel_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_real_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reciprocal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_remainder_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_remainder_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_remainder_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_remainder_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_renorm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_renorm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_renorm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_renorm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_interleave_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_interleave_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_interleave_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_as_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_reshape_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resize_as__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_conj_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_resolve_neg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_roll_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rot90_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_decimals_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_round_decimals_neg_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsqrt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_rsub_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scalar_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_scatter_reduce_prod_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tile_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tile_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tile_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_sparse_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_sparse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_sparse_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_sparse_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_to_sparse_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_topk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_topk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_topk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_topk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_topk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__efficient_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__flash_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_transpose_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapezoid_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapz_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapz_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapz_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trapz_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triangular_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triangular_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_tril_indices_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_triu_indices_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_true_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_true_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_true_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_true_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_true_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trunc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trunc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_trunc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unbind_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unflatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unfold_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_uniform_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_uniform_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_uniform_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_uniform_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_uniform_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_consecutive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_consecutive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_consecutive_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_consecutive_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_uint32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unique_cuda_uint64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unravel_index_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unravel_index_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unravel_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unravel_index_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsafe_split_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_unsqueeze_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_mean_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_var_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vdot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vdot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_as_real_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_view_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_vstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_where_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_where_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_where_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_where_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_meta_outplace_where_cuda_uint8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_addr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_alias_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_H_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_T_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides___getitem___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides___rdiv___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides___rmatmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides___rmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides___rpow___cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__batch_norm_with_update_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__chunk_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_addcdiv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_addcmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_clamp_min_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_div_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_lgamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_log10_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_minimum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_mul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_reciprocal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_sign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_sin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_sqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_sub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_tan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__foreach_zero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__native_batch_norm_legit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__segment_reduce_lengths_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__segment_reduce_offsets_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__softmax_backward_data_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__unsafe_masked_index_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides__unsafe_masked_index_put_accumulate_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_addcdiv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_addcmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_addmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_addmm_decomposed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_addr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_all_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_allclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_aminmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_angle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_any_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_as_strided_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_atan2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_atleast_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bernoulli_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bfloat16_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bincount_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bitwise_left_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bitwise_right_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bitwise_xor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_bool_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_broadcast_shapes_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_broadcast_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_broadcast_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cfloat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_chalf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_char_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cholesky_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_chunk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_column_stack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_combinations_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_conj_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_constant_pad_nd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_copysign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_corrcoef_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_count_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cov_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cummin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cumprod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_cumsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_diag_embed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_div_floor_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_dstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_empty_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_erf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_erfinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_expand_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_fft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_fftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_fftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_hfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_ifft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_ifftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_irfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_irfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_rfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fft_rfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_flatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_float_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_float_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_floor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_fmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_frexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_geqrf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_grid_sampler_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_gt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_hsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_i0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_index_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_isin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_isneginf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_item_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_jiterator_2inputs_2outputs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_jiterator_4inputs_with_extra_args_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_kthvalue_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_lcm_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_ldexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_cholesky_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_eig_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_eigh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_eigvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_eigvalsh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_householder_product_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_inv_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_ldl_factor_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_ldl_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_lstsq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_lu_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_matrix_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_qr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_solve_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linalg_solve_triangular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_linspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_log10_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_log2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logaddexp2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logdet_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_lt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mH_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_cumprod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_cumsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_logsumexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_softmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_std_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_masked_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_matrix_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_max_reduction_no_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_max_reduction_with_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_meshgrid_list_of_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_min_reduction_no_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_minimum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mvlgamma_mvlgamma_p_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nanquantile_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_celu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_channel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_conv2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_conv3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_conv_transpose1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_conv_transpose2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_cosine_embedding_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_ctc_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_dropout3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_dropout_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_elu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_embedding_bag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_embedding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_gaussian_nll_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_grid_sample_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_group_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_hardtanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_hinge_embedding_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_instance_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_area_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_linear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_nearest-exact_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_interpolate_trilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_l1_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_layer_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_leaky_relu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_margin_ranking_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_max_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_max_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_max_unpool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_max_unpool3d_grad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_multi_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_multilabel_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_multilabel_soft_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_one_hot_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_pad_replicate_negative_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_prelu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_rms_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_rrelu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_smooth_l1_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_softplus_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_softshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_softsign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_threshold_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_triplet_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nn_functional_upsample_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_norm_fro_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_norm_inf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_norm_nuc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_normal_in_place_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_normal_number_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_ormqr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_polygamma_polygamma_n_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_polygamma_polygamma_n_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_polygamma_polygamma_n_4_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_pow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_qr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_quantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_rad2deg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_randint_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_randn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_real_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_reshape_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_resize__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_rot90_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_round_decimals_neg_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_select_scatter_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_signal_windows_hamming_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_signal_windows_hann_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_signal_windows_nuttall_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_signbit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_slice_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_softmax_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_sort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_all_strides_special_bessel_j0_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_any_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_any_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_arange_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argsort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_argwhere_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_partial_views_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_partial_views_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_partial_views_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_partial_views_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_as_strided_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asinh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asinh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asinh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_asinh_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_1d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_2d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_baddbmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_baddbmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_baddbmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_baddbmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bernoulli_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bernoulli_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bernoulli_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bfloat16_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bincount_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bincount_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_left_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_left_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_left_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_or_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_right_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_right_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_xor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bitwise_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_block_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_block_diag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_block_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_block_diag_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bool_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bool_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bool_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_broadcast_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bucketize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bucketize_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bucketize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bucketize_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_bucketize_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_byte_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_byte_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_byte_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_byte_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_byte_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cartesian_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cauchy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cauchy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cauchy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cdouble_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ceil_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cfloat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cfloat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cfloat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cfloat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_char_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cholesky_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cholesky_inverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cholesky_inverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cholesky_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cholesky_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_max_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_max_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_max_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_min_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clamp_min_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_clone_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_combinations_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_combinations_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_combinations_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_combinations_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_combinations_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_conj_physical_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_constant_pad_nd_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_constant_pad_nd_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_constant_pad_nd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_constant_pad_nd_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_contiguous_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_contiguous_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_contiguous_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_contiguous_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_contiguous_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_copysign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_copysign_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_corrcoef_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_corrcoef_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_corrcoef_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_corrcoef_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_corrcoef_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cos_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cosh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cosh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_count_nonzero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cov_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cov_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cov_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cov_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cummin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumprod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumprod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumprod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumulative_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_cumulative_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_deg2rad_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_deg2rad_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_deg2rad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_deg2rad_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diag_embed_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagflat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diff_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diff_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diff_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_diff_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_digamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dist_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dist_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_floor_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_floor_rounding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_floor_rounding_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_no_rounding_mode_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_no_rounding_mode_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_no_rounding_mode_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_no_rounding_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_no_rounding_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_trunc_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_trunc_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_trunc_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_div_trunc_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_double_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_dstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_einsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_einsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_permuted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_permuted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_permuted_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_permuted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_empty_strided_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_eq_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_eq_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_eq_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_eq_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_float_power_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_floor_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_fmod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frac_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_frexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_full_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gather_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gcd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ge_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geometric_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geometric_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geometric_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geometric_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geometric_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geqrf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_geqrf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gradient_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gradient_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gradient_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_grid_sampler_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_grid_sampler_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_grid_sampler_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_gt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hash_tensor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_heaviside_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_heaviside_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_heaviside_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_heaviside_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_histc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_histc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_histc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_histc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_histc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hypot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_hypot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_i0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_igamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_igammac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_imag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_put_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_reduce_mean_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_select_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_select_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_index_select_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_inner_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_inner_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_int_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isclose_cuda_int8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isinf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isinf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isinf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isnan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isnan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isnan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isnan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_isnan_cuda_int16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_item_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_item_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_item_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_item_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_jiterator_2inputs_2outputs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_jiterator_2inputs_2outputs_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_jiterator_2inputs_2outputs_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_jiterator_2inputs_2outputs_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_jiterator_2inputs_2outputs_cuda_int64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kron_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kron_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_kthvalue_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lcm_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lcm_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lcm_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ldexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_le_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lerp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lgamma_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cholesky_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_det_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_det_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_det_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eig_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eig_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eig_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigvals_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigvals_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_eigvalsh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_householder_product_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_householder_product_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_inv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_inv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_inv_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_inv_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_ldl_factor_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_ldl_solve_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_matrix_power_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_matrix_rank_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_matrix_rank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_matrix_rank_hermitian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_multi_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_norm_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_pinv_singular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_qr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_qr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_slogdet_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_triangular_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_triangular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_solve_triangular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_svd_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_svd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_svd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_svdvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_linalg_tensorinv_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log10_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log10_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log1p_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_log2_cuda_bfloat16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_not_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_or_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_or_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_or_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_xor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_xor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_xor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_xor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logical_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_tensor_overload_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logspace_tensor_overload_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_unpack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_lu_unpack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mH_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mH_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mH_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mH_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mH_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mT_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mT_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mT_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mT_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_amax_cuda_int8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_normalize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_normalize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_masked_scatter_cuda_bool, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_median_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_median_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_list_of_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_variadic_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_variadic_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_variadic_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_variadic_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_meshgrid_variadic_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_no_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_no_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_with_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_min_reduction_with_dim_cuda_int8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mode_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_movedim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_movedim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_movedim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_movedim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_movedim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_msort_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_multinomial_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nan_to_num_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nan_to_num_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nan_to_num_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nan_to_num_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmedian_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmedian_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmedian_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanmedian_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanquantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nanquantile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nansum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_narrow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_batch_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_dropout_backward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_layer_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_layer_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_native_layer_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ne_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ne_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ne_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_empty_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_full_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_ones_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_zeros_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_zeros_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_zeros_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_new_zeros_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nextafter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nextafter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nextafter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nextafter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_max_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_adaptive_max_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_alpha_dropout_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_avg_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_batch_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_binary_cross_entropy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_binary_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_celu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_celu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_channel_shuffle_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv3d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose2d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose3d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_conv_transpose3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_embedding_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_embedding_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_embedding_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_embedding_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_similarity_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_similarity_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cosine_similarity_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_cross_entropy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_ctc_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_dropout2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_dropout2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_dropout3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_dropout3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_dropout_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_elu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_elu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_elu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_elu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_embedding_bag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_embedding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_embedding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_embedding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_with_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_feature_alpha_dropout_without_train_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_gaussian_nll_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_gaussian_nll_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_gaussian_nll_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_gelu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_gelu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_glu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_glu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_glu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_grid_sample_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_grid_sample_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_grid_sample_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_unfold_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_upsample_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_upsample_nearest_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_upsample_nearest_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nn_functional_upsample_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_nonzero_static_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_fro_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_fro_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_fro_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_fro_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_inf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_nuc_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_norm_nuc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_in_place_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_in_place_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_in_place_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_in_place_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_number_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_normal_number_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ones_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ormqr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ormqr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_outer_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pca_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pca_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_permute_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pinverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polar_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polar_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_3_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_polygamma_polygamma_n_4_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_positive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_pow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_put_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_quantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rad2deg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rad2deg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rad2deg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rad2deg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rad2deg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rand_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rand_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rand_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rand_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randint_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_randn_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ravel_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ravel_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ravel_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ravel_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_ravel_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_real_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_real_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_real_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_real_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reciprocal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reciprocal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reciprocal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reciprocal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reciprocal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_remainder_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_renorm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_renorm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_reshape_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resize_as__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_conj_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_conj_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_conj_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_resolve_neg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_roll_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rot90_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rot90_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rot90_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rot90_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rot90_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_decimals_0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_decimals_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_decimals_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_decimals_neg_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_round_decimals_neg_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsqrt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsqrt_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsqrt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsub_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsub_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsub_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_rsub_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scalar_tensor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_scatter_reduce_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_searchsorted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_searchsorted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_searchsorted_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_searchsorted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_select_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sgn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_short_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sigmoid_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sign_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_bartlett_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_bartlett_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_blackman_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_blackman_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_exponential_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_gaussian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_gaussian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_general_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_general_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_general_hamming_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_kaiser_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_kaiser_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signal_windows_nuttall_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_signbit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sin_cuda_uint8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_split_with_sizes_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_split_with_sizes_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_split_with_sizes_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sqrt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_square_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_square_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_square_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_square_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_square_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_squeeze_multiple_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_mean_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_std_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_stft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sub_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sub_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sub_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sub_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_sum_to_size_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_lowrank_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_svd_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_t_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_along_dim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_along_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_along_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_take_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensor_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensordot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensordot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensordot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tensordot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tile_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_to_sparse_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_topk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch__scaled_mm_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__efficient_attention_forward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_transpose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapezoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trapz_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triangular_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_indices_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_tril_indices_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_triu_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_true_divide_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_true_divide_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_true_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_true_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_true_divide_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trunc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_trunc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unbind_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unflatten_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unflatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unflatten_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unflatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unflatten_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unfold_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_uniform_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_uniform_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_uniform_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_consecutive_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_consecutive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_uint64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unique_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unravel_index_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unravel_index_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsafe_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_unsqueeze_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_mean_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_mean_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_mean_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_var_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vdot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vdot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_as_real_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_view_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_vstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_where_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_xlogy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zero__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_inplace_zeros_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_H_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_H_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_H_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_T_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace___getitem___cuda_bool, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_clamp_max_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_column_stack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_combinations_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_corrcoef_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_cummin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_cumulative_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_deg2rad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_diagonal_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_diagonal_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_div_no_rounding_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_dstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_empty_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_eq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_erfinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_expand_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_expand_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_expand_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_expm1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_eye_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_ge_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_hash_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_hsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_hypot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_index_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_index_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_index_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_isin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_isinf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_isneginf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_istft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_item_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_jiterator_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_jiterator_binary_return_by_ref_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_jiterator_unary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_kron_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_lgamma_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_norm_subgradients_at_zero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_pinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_pinv_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_pinv_singular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_svd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_linalg_tensorsolve_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_multilabel_soft_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_nll_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_normalize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_one_hot_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pad_circular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pad_reflect_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pad_replicate_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pad_replicate_negative_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pixel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_pixel_unshuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_poisson_nll_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_prelu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_rms_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_scaled_dot_product_attention_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_selu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_silu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_softmin_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_softshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_softsign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_tanhshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_triplet_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nn_functional_upsample_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_nonzero_static_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_norm_fro_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_norm_nuc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_normal_in_place_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_ones_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_outer_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_polygamma_polygamma_n_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_polygamma_polygamma_n_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_polygamma_polygamma_n_2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_polygamma_polygamma_n_4_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_positive_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_qr_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_scatter_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_scatter_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_scatter_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_searchsorted_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_select_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_sgn_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_sinc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_slice_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_sort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_sparse_sampled_addmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_bessel_y0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_chebyshev_polynomial_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_chebyshev_polynomial_u_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_chebyshev_polynomial_v_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_erfcx_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_hermite_polynomial_h_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_hermite_polynomial_he_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_i1e_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_laguerre_polynomial_l_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_legendre_polynomial_p_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_all_strides_special_log_ndtr_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_any_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_any_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_arange_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_arange_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_arange_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argsort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argsort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argsort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argsort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_argwhere_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_partial_views_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_as_strided_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_asinh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atanh_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_1d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_1d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_1d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_2d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bernoulli_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bernoulli_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bfloat16_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bincount_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bincount_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_and_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_and_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_left_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_left_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_left_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_left_shift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_not_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_not_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_or_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_or_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_right_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_right_shift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_right_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bitwise_xor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_block_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bool_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_tensors_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_to_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_to_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_broadcast_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bucketize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bucketize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bucketize_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bucketize_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_bucketize_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_byte_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_byte_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_byte_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cartesian_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cauchy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cauchy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cdouble_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ceil_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ceil_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cfloat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cfloat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cfloat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cfloat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cfloat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chalf_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chalf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chalf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chalf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_char_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cholesky_inverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cholesky_inverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cholesky_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cholesky_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_max_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_max_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_max_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clamp_min_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_clone_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_combinations_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_physical_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_physical_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_physical_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_conj_physical_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_constant_pad_nd_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_constant_pad_nd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_constant_pad_nd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_constant_pad_nd_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_contiguous_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_copysign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_corrcoef_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_corrcoef_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_corrcoef_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_count_nonzero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cov_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cross_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cummin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cumprod_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_cumulative_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_deg2rad_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_deg2rad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_deg2rad_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_deg2rad_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_deg2rad_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diag_embed_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagflat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_copy_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diagonal_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_diff_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_digamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_digamma_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_digamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dist_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dist_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_floor_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_floor_rounding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_floor_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_floor_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_no_rounding_mode_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_trunc_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_trunc_rounding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_trunc_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_div_trunc_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_double_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_dstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_einsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_einsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_einsum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_permuted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_empty_strided_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_eq_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_eq_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_equal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_erf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_erf_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_exp_cuda_uint8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_float_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_float_power_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_floor_divide_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_fmod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_frac_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_frexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_frexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_frexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_full_like_cuda_uint32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gather_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gcd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gcd_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ge_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_geometric_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_geqrf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_geqrf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_geqrf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gradient_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gradient_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gradient_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_grid_sampler_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_grid_sampler_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_grid_sampler_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_gt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_half_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_half_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_half_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_half_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hash_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hash_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hash_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hash_tensor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hash_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_heaviside_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_histc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_histc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_histc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_histc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_histc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hsplit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_hypot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_i0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_igammac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_imag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_imag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_put_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_mean_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_index_select_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_inner_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_inner_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_inner_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_int_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_int_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_int_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isclose_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isfinite_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isinf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isinf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isinf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isinf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isnan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isnan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_isnan_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linalg_vecdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linalg_vector_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linalg_vector_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_tensor_overload_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_linspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log10_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log10_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log10_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log1p_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log1p_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log1p_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log1p_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log1p_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_normal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_normal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_softmax_with_dtype_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_softmax_with_dtype_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_log_softmax_with_dtype_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logspace_tensor_overload_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_unpack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_lu_unpack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mH_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mT_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_argmin_cuda_int64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_cumsum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_log_softmax_cuda_bfloat16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_normalize_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_normalize_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_normalize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_normalize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_softmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_softmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_std_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_masked_sum_cuda_int8, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_max_reduction_with_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_maximum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_maximum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_median_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_median_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_list_of_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_list_of_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_list_of_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_list_of_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_list_of_tensors_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_variadic_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_meshgrid_variadic_tensors_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_binary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_no_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_no_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_no_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_with_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_min_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_minimum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_minimum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_minimum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_minimum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_minimum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_movedim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_multinomial_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nan_to_num_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nan_to_num_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nan_to_num_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nan_to_num_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nan_to_num_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmedian_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmedian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nanmedian_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nansum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_narrow_cuda_complex32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_batch_norm_without_cudnn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_binary_cross_entropy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_binary_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_binary_cross_entropy_with_logits_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_cross_entropy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_ctc_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_dropout_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_elu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_elu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_embedding_bag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_embedding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_embedding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_feature_alpha_dropout_with_train_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_feature_alpha_dropout_with_train_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_threshold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_threshold_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_threshold_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_threshold_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_nearest_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_nearest_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nn_functional_upsample_nearest_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_static_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_static_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_static_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_static_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_nonzero_static_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_fro_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_fro_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_inf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_inf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_norm_nuc_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ormqr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_outer_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pca_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_permute_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pinverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pinverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pinverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_polygamma_polygamma_n_4_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_positive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_pow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_qr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_quantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rad2deg_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rad2deg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rad2deg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rand_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rand_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rand_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rand_like_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_randn_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ravel_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ravel_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ravel_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ravel_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_ravel_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_real_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reciprocal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_remainder_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_remainder_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_remainder_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_remainder_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_remainder_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_renorm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_renorm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_reshape_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize_as__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize_as__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize_as__cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize_as__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resize_as__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_conj_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_resolve_neg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_roll_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rot90_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rot90_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rot90_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_neg_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_round_decimals_neg_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsqrt_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsqrt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsqrt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsqrt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsub_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_rsub_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scalar_tensor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_scatter_reduce_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_searchsorted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_select_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_sgn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_short_cuda_int32, 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test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_to_sparse_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_to_sparse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_to_sparse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_to_sparse_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_to_sparse_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_topk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_torch__scaled_mm_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_torch_ops_aten__efficient_attention_forward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_transpose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapezoid_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trapz_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triangular_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triangular_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triangular_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_tril_indices_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triu_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triu_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_triu_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_true_divide_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_true_divide_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_true_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_true_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_true_divide_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trunc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trunc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_trunc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unbind_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unflatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unfold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_uniform_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_uniform_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_consecutive_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_consecutive_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_consecutive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unique_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unravel_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsafe_split_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_unsqueeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_mean_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_mean_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_mean_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_var_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_as_real_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_view_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vsplit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_vstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_where_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_xlogy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_xlogy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_xlogy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_xlogy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zero__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_dispatch_symbolic_meta_outplace_zeros_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_embedding_bag_dense_backward_mode_1_cuda, test/test_meta.py::TestMetaCUDA::test_embedding_bag_dense_backward_per_sample_weights_cuda, test/test_meta.py::TestMetaCUDA::test_fill_stride_cuda, test/test_meta.py::TestMetaCUDA::test_group_norm_backward_output_mask1_cuda, test/test_meta.py::TestMetaCUDA::test_group_norm_backward_output_mask4_cuda, test/test_meta.py::TestMetaCUDA::test_index_select_out_cuda, test/test_meta.py::TestMetaCUDA::test_inplace_bin_ops_error_cuda, test/test_meta.py::TestMetaCUDA::test_inplace_masked_fill_error_cuda, test/test_meta.py::TestMetaCUDA::test_layer_norm_backward_output_mask0_cuda, test/test_meta.py::TestMetaCUDA::test_layer_norm_backward_output_mask1_cuda, test/test_meta.py::TestMetaCUDA::test_layer_norm_backward_output_mask4_cuda, test/test_meta.py::TestMetaCUDA::test_layer_norm_backward_output_mask5_cuda, test/test_meta.py::TestMetaCUDA::test_layer_norm_backward_output_mask6_cuda, test/test_meta.py::TestMetaCUDA::test_local_scalar_dense_call_cuda, test/test_meta.py::TestMetaCUDA::test_meta_inplace_H_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_H_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_H_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_H_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_T_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_T_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_T_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_T_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace___getitem___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace___getitem___cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace___getitem___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___getitem___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace___radd___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rand___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rand___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rand___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rand___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rdiv___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmatmul___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmatmul___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmatmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmod___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmod___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rmul___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___ror___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___ror___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___ror___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rpow___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rpow___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rpow___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rpow___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rpow___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rsub___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rxor___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rxor___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rxor___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rxor___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace___rxor___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__batch_norm_with_update_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__batch_norm_with_update_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__batch_norm_with_update_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__batch_norm_with_update_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__chunk_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__chunk_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__chunk_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__chunk_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_abs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_acos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_acos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_acos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcdiv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcdiv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcdiv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcdiv_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcdiv_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_addcmul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_asin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_atan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_ceil_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_max_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_min_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_min_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_min_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_clamp_min_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_cosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_div_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erfc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_erfc_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_expm1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_expm1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_expm1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_floor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_frac_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_frac_cuda_int64, 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test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_tanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_trunc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__foreach_zero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__native_batch_norm_legit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__native_batch_norm_legit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__segment_reduce_lengths_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__segment_reduce_offsets_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__segment_reduce_offsets_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__softmax_backward_data_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__softmax_backward_data_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_put_accumulate_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_put_accumulate_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_put_accumulate_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace__unsafe_masked_index_put_accumulate_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_abs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_acosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addbmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcdiv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcdiv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcdiv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcmul_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addcmul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmm_decomposed_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmm_decomposed_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmm_decomposed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addmv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_addr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_alias_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_alias_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_alias_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_alias_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_alias_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_all_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_all_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_all_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_all_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_allclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_allclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_allclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_aminmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_aminmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_aminmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_aminmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_aminmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_angle_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_angle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_angle_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_angle_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_any_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_arange_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_arange_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_arange_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_arange_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argmin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argsort_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argsort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argsort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argwhere_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argwhere_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argwhere_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_argwhere_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_partial_views_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_partial_views_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_partial_views_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_as_strided_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_asinh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_1d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_2d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_baddbmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_baddbmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_baddbmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bernoulli_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bernoulli_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bernoulli_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bfloat16_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bfloat16_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bfloat16_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bfloat16_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bfloat16_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bincount_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bincount_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bincount_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_left_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_left_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_not_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_not_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_or_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_or_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_right_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_right_shift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_xor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bitwise_xor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_block_diag_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_block_diag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_block_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_block_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bool_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_shapes_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_broadcast_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bucketize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bucketize_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bucketize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bucketize_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_bucketize_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_byte_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_byte_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_byte_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_byte_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cauchy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cauchy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cauchy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cauchy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cdouble_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ceil_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cfloat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cfloat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cfloat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cfloat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_char_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_inverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_inverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cholesky_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_max_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_max_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_max_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_max_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clamp_min_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_clone_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_column_stack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_combinations_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_physical_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_physical_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_physical_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_conj_physical_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_constant_pad_nd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_constant_pad_nd_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_constant_pad_nd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_contiguous_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_copysign_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_copysign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_copysign_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_copysign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_copysign_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_corrcoef_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_corrcoef_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_corrcoef_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_corrcoef_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_corrcoef_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cos_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cosh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_count_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_count_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_count_nonzero_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_count_nonzero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cov_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cross_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cummin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumprod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumsum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_cumulative_trapezoid_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_deg2rad_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_deg2rad_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_deg2rad_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diag_embed_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagflat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diagonal_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_diff_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_digamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_digamma_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_floor_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_floor_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_floor_rounding_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_floor_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_no_rounding_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_no_rounding_mode_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_no_rounding_mode_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_no_rounding_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_no_rounding_mode_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_div_trunc_rounding_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_double_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_double_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_double_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_double_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dsplit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_dstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_permuted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_permuted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_permuted_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_permuted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_permuted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_empty_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eq_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eq_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eq_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eq_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eq_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_equal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_equal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_equal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_equal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfinv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfinv_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_erfinv_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expand_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_expm1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exponential_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exponential_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_float8_e5m2, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_float8_e5m2fnuz, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_eye_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_fftshift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_hfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ifftshift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_ihfftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_irfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fft_rfftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flip_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fliplr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_flipud_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_float_power_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_floor_divide_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_fmod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_frac_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_frac_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_frac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_frexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_frexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_full_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gather_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gcd_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ge_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ge_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ge_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geometric_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geqrf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_geqrf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gradient_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_grid_sampler_2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_grid_sampler_2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_grid_sampler_3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_grid_sampler_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_grid_sampler_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_gt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hash_tensor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hash_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hash_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hash_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hash_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_heaviside_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_heaviside_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_heaviside_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_heaviside_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_histc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hstack_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hypot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_hypot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_i0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_i0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_igamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_igammac_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_mean_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_mean_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_reduce_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_index_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_inner_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_int_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isclose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isfinite_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isinf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isnan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isnan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isnan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isnan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isnan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isneginf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isposinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isposinf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isposinf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isposinf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_isreal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_istft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_istft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_item_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_2inputs_2outputs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_4inputs_with_extra_args_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_binary_return_by_ref_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_jiterator_unary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kron_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kthvalue_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kthvalue_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kthvalue_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kthvalue_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_kthvalue_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lcm_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ldexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_le_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_le_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_le_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_le_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lerp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lerp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lerp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lgamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lgamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lgamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lgamma_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lgamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cond_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cond_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_cross_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_det_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_det_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eig_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eig_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eigh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eigh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eigvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eigvalsh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_eigvalsh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_householder_product_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_householder_product_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_householder_product_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_inv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_inv_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_inv_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_inv_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_ldl_factor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_ldl_factor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_ldl_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_ldl_factor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_ldl_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lstsq_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lstsq_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lstsq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lstsq_grad_oriented_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_factor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_factor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_lu_factor_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_power_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_rank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_rank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_rank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_matrix_rank_hermitian_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_multi_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_multi_dot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_multi_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_multi_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_subgradients_at_zero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_subgradients_at_zero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_norm_subgradients_at_zero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_hermitian_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_hermitian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_singular_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_singular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_singular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_pinv_singular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_qr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_slogdet_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_solve_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_solve_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_solve_triangular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_svd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_svd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_svdvals_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_svdvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_svdvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_tensorinv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_tensorinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_tensorsolve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_tensorsolve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_vander_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_vecdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_vector_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_vector_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linalg_vector_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_linspace_tensor_overload_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log10_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log1p_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_normal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_with_dtype_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_with_dtype_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_with_dtype_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_log_softmax_with_dtype_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logaddexp2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logaddexp2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logaddexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logaddexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logcumsumexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logcumsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logcumsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logdet_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_and_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_not_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_or_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_xor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_xor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_xor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logical_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_tensor_overload_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_long_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lu_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lu_unpack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_lu_unpack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mH_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mH_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mH_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mT_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumprod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_cumsum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_log_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_log_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_normalize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_normalize_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_normalize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_select_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_softmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_softmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_softmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_std_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_std_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_std_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_std_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_sum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_sum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_masked_var_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matmul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matrix_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matrix_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_matrix_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_binary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_pool2d_with_indices_backward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_pool2d_with_indices_backward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_pool2d_with_indices_backward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_no_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_no_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_max_reduction_with_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_maximum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_median_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_list_of_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_list_of_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_list_of_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_variadic_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_variadic_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_variadic_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_meshgrid_variadic_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_binary_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_binary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_no_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_no_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_min_reduction_with_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_minimum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_minimum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_minimum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_minimum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mode_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mode_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mode_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mode_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_movedim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_msort_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_msort_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mul_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_multinomial_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_mvlgamma_mvlgamma_p_5_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nan_to_num_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmean_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmedian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nanmedian_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nansum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_narrow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_native_batch_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_native_batch_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_native_dropout_backward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_native_dropout_backward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_native_layer_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ne_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_empty_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_full_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_ones_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_zeros_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_zeros_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_zeros_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_new_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nextafter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nextafter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_avg_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_avg_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_avg_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_avg_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_adaptive_max_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_alpha_dropout_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool1d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_avg_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_batch_norm_without_cudnn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_binary_cross_entropy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_binary_cross_entropy_with_logits_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_binary_cross_entropy_with_logits_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_celu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_celu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_celu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_channel_shuffle_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_channel_shuffle_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_channel_shuffle_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_channel_shuffle_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv1d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose1d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose1d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_conv_transpose2d_cuda_complex64, 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test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu6_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_relu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rms_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rms_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rms_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rms_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rrelu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_rrelu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_scaled_dot_product_attention_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_selu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_silu_complex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_silu_complex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_silu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_silu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_silu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_smooth_l1_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_smooth_l1_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_soft_margin_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_soft_margin_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_soft_margin_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softmin_with_dtype_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softplus_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softplus_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softshrink_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softshrink_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_softsign_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_tanhshrink_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_threshold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_threshold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_threshold_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_threshold_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_triplet_margin_with_distance_loss_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_nearest_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_nearest_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nn_functional_upsample_nearest_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_nonzero_static_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_fro_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_fro_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_fro_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_inf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_inf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_nuc_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_nuc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_norm_nuc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_in_place_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_in_place_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_in_place_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_in_place_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_number_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_normal_number_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ones_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ormqr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_outer_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pca_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pca_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pca_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_permute_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pinverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pinverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pinverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polar_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_3_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_3_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_4_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_4_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_4_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_polygamma_polygamma_n_4_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_positive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_pow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_put_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_quantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_quantile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rad2deg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rad2deg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rad2deg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rad2deg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rad2deg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rand_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rand_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randint_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_randn_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ravel_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ravel_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ravel_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ravel_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_ravel_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_real_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reciprocal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reciprocal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reciprocal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reciprocal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reciprocal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_remainder_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_remainder_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_remainder_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_remainder_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_renorm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_renorm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_renorm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_as_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_reshape_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize__cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize__cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resize_as__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_conj_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_neg_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_neg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_resolve_neg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_roll_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_roll_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rot90_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rot90_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rot90_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rot90_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_decimals_0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_decimals_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_decimals_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_decimals_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_round_decimals_neg_3_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsqrt_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsqrt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsqrt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsqrt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsub_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_rsub_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scalar_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_add_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_prod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_sum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_sum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_scatter_reduce_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_searchsorted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_searchsorted_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_select_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sgn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_short_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sigmoid_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sign_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_bartlett_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_blackman_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_blackman_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_exponential_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_gaussian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_general_cosine_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_general_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_general_hamming_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_kaiser_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_kaiser_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_nuttall_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signal_windows_nuttall_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_signbit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sinh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_slice_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_softmax_with_dtype_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_softmax_with_dtype_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_softmax_with_dtype_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_softmax_with_dtype_cuda_int64, 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test/test_meta.py::TestMetaCUDA::test_meta_inplace_sqrt_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sqrt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sqrt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sqrt_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_square_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_multiple_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_multiple_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_multiple_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_multiple_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_squeeze_multiple_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_mean_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_std_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_stft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sub_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sub_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sub_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_sum_to_size_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_svd_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_svd_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_svd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_svd_lowrank_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_svd_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_t_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_along_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_take_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tanh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensor_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensordot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensordot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tensordot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tile_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_sparse_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_sparse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_sparse_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_sparse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_to_sparse_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_topk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch__scaled_mm_cuda_float8_e4m3fn, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_torch_ops_aten__safe_softmax_default_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_transpose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapezoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapezoid_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapezoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapz_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapz_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapz_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trapz_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triangular_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triangular_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_tril_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_triu_indices_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_true_divide_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trunc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trunc_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trunc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trunc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_trunc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unbind_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unflatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unfold_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_uniform_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_uniform_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_uniform_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_uniform_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_consecutive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_consecutive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_consecutive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_consecutive_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_consecutive_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_uint32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unique_cuda_uint64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unravel_index_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unravel_index_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsafe_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_unsqueeze_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_mean_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_var_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vdot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_complex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_as_real_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_view_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_vstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_where_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_xlogy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zero__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_inplace_zeros_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_H_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_T_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace___getitem___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___radd___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___radd___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___radd___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___radd___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rand___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rand___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rand___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rand___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rdiv___cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmatmul___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmatmul___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmod___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmod___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmod___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rmul___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___ror___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___ror___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___ror___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rpow___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rpow___cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rpow___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rsub___cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rxor___cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rxor___cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rxor___cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace___rxor___cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__batch_norm_with_update_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__batch_norm_with_update_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__chunk_cat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_abs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_acos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_acos_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_acos_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_acos_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcdiv_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcmul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcmul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_addcmul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_asin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_atan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_atan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_ceil_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_clamp_max_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_clamp_max_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__foreach_clamp_min_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__unsafe_masked_index_put_accumulate_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace__upsample_bilinear2d_aa_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__upsample_bilinear2d_aa_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace__upsample_bilinear2d_aa_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace__upsample_bilinear2d_aa_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_abs_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acos_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acosh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acosh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acosh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_acosh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addbmm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addbmm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcdiv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcdiv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcdiv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcmul_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcmul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcmul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addcmul_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_decomposed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_decomposed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmm_decomposed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addmv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addr_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addr_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_addr_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_alias_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_all_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_aminmax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_aminmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_aminmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_aminmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_angle_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_angle_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_angle_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_any_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_arange_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argsort_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_argwhere_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_partial_views_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_as_strided_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_asinh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atan_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atanh_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_1d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_2d_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_atleast_3d_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_baddbmm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_baddbmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bernoulli_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bernoulli_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bfloat16_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bincount_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bincount_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bincount_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bincount_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bincount_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_and_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_left_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_not_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_not_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_not_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_or_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_or_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_or_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_or_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_right_shift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_right_shift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_right_shift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_right_shift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_right_shift_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_xor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_xor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bitwise_xor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_block_diag_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_block_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_block_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bmm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bmm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bmm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bool_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_shapes_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_broadcast_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bucketize_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bucketize_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bucketize_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_bucketize_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_byte_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_byte_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cartesian_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cauchy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cdouble_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ceil_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ceil_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ceil_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ceil_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ceil_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cfloat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chalf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_char_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_inverse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_inverse_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_inverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cholesky_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chunk_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_max_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_max_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_max_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_max_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_max_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clamp_min_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_clone_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_column_stack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_combinations_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_combinations_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_combinations_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_combinations_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_combinations_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_complex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_conj_physical_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_constant_pad_nd_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_constant_pad_nd_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_constant_pad_nd_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_constant_pad_nd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_constant_pad_nd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_contiguous_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_copysign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_copysign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_copysign_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_copysign_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_copysign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_corrcoef_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cos_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cosh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_count_nonzero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_count_nonzero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_count_nonzero_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_count_nonzero_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cov_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cross_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cross_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummax_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cummin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumprod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumprod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumprod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumsum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumsum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumulative_trapezoid_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumulative_trapezoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_cumulative_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_deg2rad_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_deg2rad_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_deg2rad_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diag_embed_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagflat_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diagonal_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_diff_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_digamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_digamma_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_digamma_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_digamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dist_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dist_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dist_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dist_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_floor_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_no_rounding_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_no_rounding_mode_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_no_rounding_mode_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_trunc_rounding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_trunc_rounding_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_trunc_rounding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_trunc_rounding_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_div_trunc_rounding_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_double_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dsplit_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dsplit_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_dstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_einsum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_einsum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_einsum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_einsum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_permuted_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_empty_strided_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eq_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_equal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfc_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfinv_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfinv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfinv_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_erfinv_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_as_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_as_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expand_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_expm1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_exponential_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_float8_e4m3fnuz, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_float8_e5m2, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_eye_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_fftshift_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfft_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_hfftn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ifftshift_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfftn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_ihfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft2_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft2_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft2_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfft_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfftn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfftn_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfftn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_irfftn_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft2_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft2_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfft_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfftn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fft_rfftn_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flip_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fliplr_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_flipud_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_power_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_power_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_float_power_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_divide_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_divide_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_divide_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_floor_divide_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_fmod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_frac_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_frac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_frexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_frexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_full_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gather_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gather_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gather_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gather_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gcd_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gcd_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gcd_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gcd_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ge_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ge_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ge_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ge_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ge_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geometric_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geometric_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geometric_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geometric_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geometric_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_geqrf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gradient_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_grid_sampler_3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gt_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_gt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_half_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hash_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hash_tensor_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hash_tensor_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hash_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hash_tensor_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_heaviside_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_heaviside_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_heaviside_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_heaviside_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_heaviside_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_histc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_histc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_histc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_histc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_histc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hsplit_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hsplit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hypot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hypot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_hypot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_i0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_i0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_i0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_i0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_i0_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_igamma_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_igamma_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_igammac_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_imag_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_imag_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_add_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_fill_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_put_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_amin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_mean_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_reduce_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_index_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_inner_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_inner_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_inner_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_int_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_int_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_int_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_int_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_int_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isclose_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isfinite_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isfinite_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isfinite_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isinf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isnan_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isneginf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isneginf_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isneginf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isneginf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isneginf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isposinf_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_isreal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_istft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_item_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_item_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_item_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_item_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_item_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_2inputs_2outputs_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_4inputs_with_extra_args_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_binary_return_by_ref_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_unary_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_unary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_unary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_unary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_jiterator_unary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kron_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kthvalue_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kthvalue_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_kthvalue_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lcm_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lcm_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ldexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_le_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lerp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lerp_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lerp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lerp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lerp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lgamma_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lgamma_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lgamma_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cholesky_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cholesky_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cholesky_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cholesky_ex_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cond_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cond_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cond_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_cross_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_det_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_det_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_det_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_diagonal_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eig_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eig_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eig_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eig_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigh_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigvals_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigvals_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigvalsh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_eigvalsh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_householder_product_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_householder_product_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_householder_product_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_householder_product_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_inv_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_ldl_factor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_ldl_factor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_ldl_factor_ex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_ldl_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lstsq_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lstsq_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lstsq_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lstsq_grad_oriented_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_factor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_factor_ex_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_factor_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_lu_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_power_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_power_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_matrix_rank_hermitian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_multi_dot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_multi_dot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_multi_dot_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_subgradients_at_zero_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_subgradients_at_zero_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_subgradients_at_zero_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_norm_subgradients_at_zero_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_hermitian_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_hermitian_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_hermitian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_hermitian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_singular_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_singular_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_singular_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_pinv_singular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_slogdet_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_slogdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_solve_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_solve_ex_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_solve_triangular_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_svd_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_svdvals_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_svdvals_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_tensorinv_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_tensorsolve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_tensorsolve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_tensorsolve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vander_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vander_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vander_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vander_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vander_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vecdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vecdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vecdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vector_norm_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vector_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linalg_vector_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_linspace_tensor_overload_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log10_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log10_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log10_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log1p_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log2_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log2_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_normal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_normal_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_with_dtype_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_with_dtype_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_with_dtype_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_with_dtype_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_log_softmax_with_dtype_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logaddexp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logcumsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logcumsumexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logdet_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logdet_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_and_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_not_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_not_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_not_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_not_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_not_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_or_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_or_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_or_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_or_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_or_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_xor_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_xor_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_xor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logical_xor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_tensor_overload_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_tensor_overload_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_tensor_overload_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_tensor_overload_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logspace_tensor_overload_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_logsumexp_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_long_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lt_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_solve_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_unpack_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_unpack_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_lu_unpack_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mH_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mH_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mH_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mH_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mH_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mT_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mT_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_amin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmin_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmin_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmin_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_argmin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumprod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumprod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumprod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumprod_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumprod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumsum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_cumsum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_fill_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_fill_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_fill_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_fill_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_log_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_log_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_log_softmax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logaddexp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_logsumexp_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_median_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_normalize_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_scatter_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_select_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_softmax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_softmax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_softmax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_softmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_std_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_masked_var_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matmul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matmul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matmul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matmul_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matmul_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matrix_exp_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matrix_exp_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matrix_exp_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matrix_exp_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_matrix_exp_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_pool2d_with_indices_backward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_pool2d_with_indices_backward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_pool2d_with_indices_backward_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_pool2d_with_indices_backward_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_no_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_no_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_no_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_no_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_no_dim_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_max_reduction_with_dim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_maximum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_median_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_median_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_median_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_median_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_median_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_list_of_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_meshgrid_variadic_tensors_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_binary_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_binary_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_binary_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_binary_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_binary_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_no_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_no_dim_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_no_dim_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_no_dim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_with_dim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_with_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_min_reduction_with_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_minimum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mode_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mode_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mode_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mode_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_movedim_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_msort_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mul_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_multinomial_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_multinomial_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mv_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mv_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_3_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_mvlgamma_mvlgamma_p_5_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nan_to_num_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmean_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanmedian_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nanquantile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nansum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_narrow_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_native_batch_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_native_batch_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_native_dropout_backward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_native_dropout_backward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ne_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ne_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ne_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ne_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_neg_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_neg_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_neg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_empty_strided_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_full_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_ones_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_new_zeros_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nextafter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nextafter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_avg_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_avg_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_avg_pool2d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_avg_pool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_avg_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_max_pool2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_max_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_max_pool3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_max_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_adaptive_max_pool3d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_alpha_dropout_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_alpha_dropout_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_alpha_dropout_cuda_float64, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_binary_cross_entropy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_celu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_celu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_celu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_channel_shuffle_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv1d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv1d_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv2d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv2d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv3d_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv3d_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv3d_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv3d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_conv_transpose1d_cuda_complex128, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_elu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_elu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_elu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_bag_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_bag_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_bag_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_embedding_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_feature_alpha_dropout_with_train_cuda_float16, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_grid_sample_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_grid_sample_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_group_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_group_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardsigmoid_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardsigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardsigmoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardswish_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardswish_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hardtanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hinge_embedding_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_hinge_embedding_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_huber_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_instance_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_instance_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_area_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_area_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_bicubic_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_bicubic_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_bilinear_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_linear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_linear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_interpolate_nearest-exact_cuda_bfloat16, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_layer_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_layer_norm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_leaky_relu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_linear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_linear_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_linear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_local_response_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_local_response_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_logsigmoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_logsigmoid_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_logsigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_logsigmoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_margin_ranking_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_margin_ranking_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_margin_ranking_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_margin_ranking_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_margin_ranking_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_pool1d_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_pool1d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_pool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_pool3d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool1d_grad_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool1d_grad_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool2d_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool2d_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool2d_grad_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool2d_grad_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool2d_grad_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_max_unpool3d_grad_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_mish_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pad_replicate_negative_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pairwise_distance_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pdist_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pdist_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_shuffle_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_shuffle_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_shuffle_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_shuffle_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_shuffle_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_unshuffle_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_unshuffle_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_unshuffle_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_pixel_unshuffle_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_poisson_nll_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_poisson_nll_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_poisson_nll_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_poisson_nll_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_prelu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_prelu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu6_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_relu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rms_norm_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rms_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rms_norm_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rms_norm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rrelu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rrelu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_rrelu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_scaled_dot_product_attention_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_selu_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_silu_complex_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_silu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_smooth_l1_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_smooth_l1_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_smooth_l1_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_smooth_l1_loss_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_soft_margin_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_soft_margin_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softmin_with_dtype_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softplus_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softplus_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softshrink_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softsign_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softsign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softsign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softsign_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_softsign_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_tanhshrink_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_tanhshrink_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_tanhshrink_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_tanhshrink_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_threshold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_threshold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_threshold_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_threshold_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_loss_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_loss_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_triplet_margin_with_distance_loss_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_unfold_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_bilinear_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_bilinear_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_bilinear_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_nearest_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_nearest_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nn_functional_upsample_nearest_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_nonzero_static_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_fro_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_inf_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_inf_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_inf_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_inf_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_nuc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_norm_nuc_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_in_place_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_in_place_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_in_place_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_number_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_normal_number_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ones_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ormqr_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_outer_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pca_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pca_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_permute_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pinverse_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pinverse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polar_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polar_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_0_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_0_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_1_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_2_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_2_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_2_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_2_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_2_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_3_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_3_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_4_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_4_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_4_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_polygamma_polygamma_n_4_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_positive_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_positive_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_positive_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_positive_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_positive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_pow_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_prod_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_put_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_qr_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_qr_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_quantile_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_quantile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rad2deg_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rand_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rand_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rand_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_like_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_like_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randint_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_like_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_like_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_randn_like_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_ravel_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_real_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reciprocal_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reciprocal_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reciprocal_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_remainder_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_renorm_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_renorm_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_repeat_interleave_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_as_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_reshape_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize_as__cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize_as__cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resize_as__cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_conj_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_conj_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_conj_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_neg_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_neg_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_neg_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_neg_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_resolve_neg_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_roll_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_roll_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_roll_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_roll_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_roll_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rot90_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_decimals_3_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_decimals_neg_3_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_round_decimals_neg_3_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsqrt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_rsub_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scalar_tensor_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_add_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amax_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_amin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_mean_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_mean_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_mean_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_prod_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_prod_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_prod_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_sum_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_sum_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_scatter_reduce_sum_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_searchsorted_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_searchsorted_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_searchsorted_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_select_scatter_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sgn_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_short_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_short_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_short_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_short_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_short_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sigmoid_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sign_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_blackman_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_exponential_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_gaussian_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_general_cosine_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_general_hamming_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_general_hamming_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_hamming_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_hann_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_kaiser_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_kaiser_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_nuttall_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signal_windows_nuttall_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_signbit_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sin_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinc_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinc_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinc_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinc_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinh_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinh_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinh_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sinh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_scatter_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_slice_scatter_cuda_bool, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_i1e_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_laguerre_polynomial_l_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_laguerre_polynomial_l_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_laguerre_polynomial_l_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_laguerre_polynomial_l_cuda_uint8, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_i0_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_i0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_i1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_i1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_i1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_k0_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_k0_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_k0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_modified_bessel_k1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_ndtr_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_ndtr_cuda_float32, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_polygamma_special_polygamma_n_0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k0_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k0_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k0_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k0_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k1_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k1_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k1_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_scaled_modified_bessel_k1_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_shifted_chebyshev_polynomial_t_cuda_int64, 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test/test_meta.py::TestMetaCUDA::test_meta_outplace_special_zeta_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_list_args_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_list_args_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_list_args_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_list_args_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_list_args_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_split_with_sizes_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sqrt_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_square_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_square_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_square_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_squeeze_multiple_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_mean_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_unbiased_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_std_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stft_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stft_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_stft_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sub_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sub_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sub_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sub_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sub_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_sum_to_size_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_svd_lowrank_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_svd_lowrank_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_svd_lowrank_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_svd_lowrank_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_t_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_along_dim_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_along_dim_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_along_dim_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_along_dim_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_along_dim_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_take_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tan_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tanh_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensor_split_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensordot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensordot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tensordot_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tile_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tile_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tile_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tile_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tile_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_sparse_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_sparse_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_sparse_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_to_sparse_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_topk_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_topk_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_topk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__efficient_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__flash_attention_forward_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__flash_attention_forward_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_torch_ops_aten__safe_softmax_default_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trace_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_transpose_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapezoid_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapezoid_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapezoid_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapezoid_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapezoid_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapz_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapz_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapz_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapz_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trapz_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triangular_solve_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triangular_solve_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_tril_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_triu_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_true_divide_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trunc_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trunc_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_trunc_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unbind_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unflatten_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unfold_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_uniform_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_uniform_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_uniform_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_consecutive_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_consecutive_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_consecutive_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_consecutive_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_uint16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_uint64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unique_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unravel_index_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unravel_index_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_chunk_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsafe_split_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_unsqueeze_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_unbiased_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_unbiased_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_mean_unbiased_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_unbiased_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_var_unbiased_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vdot_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vdot_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vdot_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vdot_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_complex_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_real_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_as_real_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_copy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_view_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vsplit_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_vstack_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_where_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_where_cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_where_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_where_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_where_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_xlogy_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_xlogy_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_xlogy_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_xlogy_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_complex128, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_float16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zero__cuda_uint8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_bfloat16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_complex64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_float64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_int16, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_bool, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_complex32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_float32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_int32, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_int64, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_int8, test/test_meta.py::TestMetaCUDA::test_meta_outplace_zeros_like_cuda_uint8, test/test_meta.py::TestMetaCUDA::test_nan_to_num_cuda, test/test_meta.py::TestMetaCUDA::test_quantized_embedding_bag_cuda, test/test_meta.py::TestMetaCUDA::test_stride_for_index_Tensor_cuda 2025-08-26T23:35:45.7784100Z 2025-08-26T23:35:45.7784230Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T23:35:45.7784419Z Uploading artifacts took 0.00 seconds 2025-08-26T23:35:45.7784587Z Running test_autoload_disable 1/1 ... [2025-08-26 23:35:45.325305] 2025-08-26T23:35:46.9368851Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:35:46.9369566Z import pkg_resources 2025-08-26T23:35:46.9498386Z /var/lib/jenkins/pytorch/test/cpp_extensions/cuda_extension.cpp -> /var/lib/jenkins/pytorch/test/cpp_extensions/cuda_extension.cpp [skipped, no changes] 2025-08-26T23:35:46.9501574Z /var/lib/jenkins/pytorch/test/cpp_extensions/cuda_extension_kernel.cu -> /var/lib/jenkins/pytorch/test/cpp_extensions/hip_extension_kernel.hip [ok] 2025-08-26T23:35:46.9504325Z /var/lib/jenkins/pytorch/test/cpp_extensions/cuda_extension_kernel2.cu -> /var/lib/jenkins/pytorch/test/cpp_extensions/hip_extension_kernel2.hip [ok] 2025-08-26T23:35:46.9505052Z Successfully preprocessed all matching files. 2025-08-26T23:35:46.9505236Z Total number of unsupported CUDA function calls: 0 2025-08-26T23:35:46.9505341Z 2025-08-26T23:35:46.9505343Z 2025-08-26T23:35:46.9505404Z Total number of replaced kernel launches: 2 2025-08-26T23:35:46.9511909Z /var/lib/jenkins/pytorch/test/cpp_extensions/torch_library.cu -> /var/lib/jenkins/pytorch/test/cpp_extensions/torch_library.cu [skipped, no changes] 2025-08-26T23:35:46.9512251Z Successfully preprocessed all matching files. 2025-08-26T23:35:46.9513520Z Total number of unsupported CUDA function calls: 0 2025-08-26T23:35:46.9513797Z 2025-08-26T23:35:46.9513815Z 2025-08-26T23:35:46.9513908Z Total number of replaced kernel launches: 0 2025-08-26T23:35:46.9692464Z running install 2025-08-26T23:35:46.9693417Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T23:35:46.9693935Z !! 2025-08-26T23:35:46.9694034Z 2025-08-26T23:35:46.9694129Z ******************************************************************************** 2025-08-26T23:35:46.9694377Z Please avoid running ``setup.py`` directly. 2025-08-26T23:35:46.9694635Z Instead, use pypa/build, pypa/installer or other 2025-08-26T23:35:46.9694872Z standards-based tools. 2025-08-26T23:35:46.9694997Z 2025-08-26T23:35:46.9695147Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T23:35:46.9695467Z or your builds will no longer be supported. 2025-08-26T23:35:46.9695618Z 2025-08-26T23:35:46.9695834Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T23:35:46.9696162Z ******************************************************************************** 2025-08-26T23:35:46.9696668Z 2025-08-26T23:35:46.9696911Z !! 2025-08-26T23:35:46.9697070Z self.initialize_options() 2025-08-26T23:35:46.9749575Z running build 2025-08-26T23:35:46.9750790Z running build_py 2025-08-26T23:35:46.9783647Z creating build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension 2025-08-26T23:35:46.9784963Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension 2025-08-26T23:35:46.9786637Z running build_ext 2025-08-26T23:35:46.9798186Z building 'torch_test_cpp_extension.cpp' extension 2025-08-26T23:35:46.9799033Z creating build/temp.linux-x86_64-cpython-312 2025-08-26T23:35:46.9801805Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c extension.cpp -o build/temp.linux-x86_64-cpython-312/extension.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cpp -std=c++17 2025-08-26T23:36:01.9903145Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/Exceptions.h:12, 2025-08-26T23:36:01.9903698Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11, 2025-08-26T23:36:01.9904110Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:9, 2025-08-26T23:36:01.9904690Z from extension.cpp:1: 2025-08-26T23:36:01.9905602Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_’: 2025-08-26T23:36:01.9911967Z extension.cpp:45:53: required from here 2025-08-26T23:36:01.9915513Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/pybind11/pybind11.h:2041:7: warning: ‘pybind11::class_’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes] 2025-08-26T23:36:01.9916090Z 2041 | class class_ : public detail::generic_type { 2025-08-26T23:36:01.9916225Z | ^~~~~~ 2025-08-26T23:36:01.9916784Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< , >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’: 2025-08-26T23:36:01.9917245Z extension.cpp:45:53: required from here 2025-08-26T23:36:01.9918144Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/pybind11/pybind11.h:2139:28: warning: ‘pybind11::class_::class_<>(pybind11::handle, const char*)::’ declared with greater visibility than the type of its field ‘pybind11::class_::class_<>(pybind11::handle, const char*)::::’ [-Wattributes] 2025-08-26T23:36:01.9918776Z 2139 | with_internals([&](internals &internals) { 2025-08-26T23:36:01.9918919Z | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:01.9919106Z 2140 | auto &instances = record.module_local ? get_local_internals().registered_types_cpp 2025-08-26T23:36:01.9919302Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:01.9919469Z 2141 | : internals.registered_types_cpp; 2025-08-26T23:36:01.9919624Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:01.9919781Z 2142 | instances[std::type_index(typeid(type_alias))] 2025-08-26T23:36:01.9919929Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:01.9920076Z 2143 | = instances[std::type_index(typeid(type))]; 2025-08-26T23:36:01.9920222Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:01.9920701Z 2144 | }); 2025-08-26T23:36:01.9920814Z | ~ 2025-08-26T23:36:01.9965173Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib build/temp.linux-x86_64-cpython-312/extension.o -L/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-x86_64-linux-gnu.so 2025-08-26T23:36:02.2652256Z building 'torch_test_cpp_extension.maia' extension 2025-08-26T23:36:02.2654369Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-312/maia_extension.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=maia -std=c++17 2025-08-26T23:36:17.4102591Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib build/temp.linux-x86_64-cpython-312/maia_extension.o -L/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/maia.cpython-312-x86_64-linux-gnu.so 2025-08-26T23:36:17.6693114Z building 'torch_test_cpp_extension.rng' extension 2025-08-26T23:36:17.6703532Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-312/rng_extension.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=rng -std=c++17 2025-08-26T23:36:33.6145583Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T23:36:33.6146259Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T23:36:33.6146734Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T23:36:33.6154813Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T23:36:33.6155255Z from rng_extension.cpp:6: 2025-08-26T23:36:33.6156163Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T23:36:33.6156646Z 1478 | #pragma unroll 2025-08-26T23:36:33.6156807Z | 2025-08-26T23:36:33.6157095Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4, 2025-08-26T23:36:33.6157486Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530, 2025-08-26T23:36:33.6158016Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T23:36:33.6158619Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T23:36:33.6159020Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T23:36:33.6159401Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T23:36:33.6159694Z from rng_extension.cpp:6: 2025-08-26T23:36:33.6160107Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T23:36:33.6160585Z 59 | #pragma unroll 2025-08-26T23:36:33.6160713Z | 2025-08-26T23:36:33.6161164Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T23:36:33.6161494Z 72 | #pragma unroll 2025-08-26T23:36:33.6161611Z | 2025-08-26T23:36:33.6161970Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T23:36:33.6162307Z 87 | #pragma unroll 2025-08-26T23:36:33.6162421Z | 2025-08-26T23:36:33.6162731Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531, 2025-08-26T23:36:33.6163127Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T23:36:33.6163492Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T23:36:33.6163845Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T23:36:33.6164244Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T23:36:33.6164535Z from rng_extension.cpp:6: 2025-08-26T23:36:33.6164943Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T23:36:33.6165280Z 160 | #pragma unroll 2025-08-26T23:36:33.6165390Z | 2025-08-26T23:36:33.6165606Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6165963Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6166305Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6166620Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6166871Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6167161Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6167489Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6167810Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6168111Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6168421Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6168848Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6169160Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6169373Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6169900Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6170546Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6171190Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6171809Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6172452Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6173178Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6185290Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6188868Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6190950Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6191285Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6191433Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6193574Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6195865Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6196303Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6196460Z | ^~~~~~~~ 2025-08-26T23:36:33.6196680Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6197014Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6197313Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6197590Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6197965Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6198248Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6198603Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6198977Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6199354Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6199720Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6200092Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6200511Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6200793Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6200989Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6201311Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6201573Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6201710Z | ^~~~ 2025-08-26T23:36:33.6201916Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6202243Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6202521Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6202793Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6203072Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6203358Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6203671Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6203966Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6204260Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6204574Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6204892Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6205172Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6205358Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6205703Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6206225Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6206797Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6207379Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6208007Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6208682Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6210723Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6214003Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6215929Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6216249Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6216396Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6218335Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6220515Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6220960Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6221108Z | ^~~~~~~~ 2025-08-26T23:36:33.6221327Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6221659Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6221963Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6222263Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6222525Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6222807Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6223178Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6223556Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6223933Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6224303Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6224641Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6224961Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6225246Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6225440Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6225735Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6226003Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6226134Z | ^~~~ 2025-08-26T23:36:33.6226336Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6226622Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6226895Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6227163Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6227416Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6227696Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6228003Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6228296Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6228593Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6228925Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6229259Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6229538Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6229729Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6230073Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6230677Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6231283Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6231884Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6232507Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6233176Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6235196Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6238696Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6240734Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6241050Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6241218Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6243286Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6245384Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6245807Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6245956Z | ^~~~~~~~ 2025-08-26T23:36:33.6246173Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6246505Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6246805Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6247081Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6247338Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6247619Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6247963Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6248336Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6248714Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6249106Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6249457Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6249773Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6250053Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6250244Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6250626Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6250903Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6251031Z | ^~~~ 2025-08-26T23:36:33.6251235Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6251522Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6251817Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6252084Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6252331Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6252613Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6252925Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6253222Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6253519Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6253832Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6254151Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6254432Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6254621Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6254969Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6255493Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6256063Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6256641Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6257261Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6257962Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6259901Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6263179Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6264999Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6265313Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6265455Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6267439Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6269468Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6269888Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6270037Z | ^~~~~~~~ 2025-08-26T23:36:33.6270254Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6270661Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6270962Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6271239Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6271518Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6271800Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6272147Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6272521Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6272899Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6273270Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6273605Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6273919Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6274201Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6274391Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6274832Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6275133Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6275308Z | ^~~~ 2025-08-26T23:36:33.6275576Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6275892Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6276207Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6276527Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6276815Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6277136Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6277505Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6277955Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6278316Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6278681Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6279039Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6279373Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6279632Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6280006Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6280656Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6281303Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6281927Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6282612Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6283318Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6285291Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6288599Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6290571Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6290967Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6291153Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6293149Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6295252Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6295704Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6295916Z | ^~~~~~~~ 2025-08-26T23:36:33.6296181Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6296559Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6296908Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6297229Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6297538Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6297859Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6298237Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6298764Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6299205Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6299636Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6300032Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6300445Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6300786Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6301015Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6301359Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6301672Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6301842Z | ^~~~ 2025-08-26T23:36:33.6302094Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6302448Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6302764Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6303087Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6303374Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6303692Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6304064Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6304404Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6304747Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6305102Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6305462Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6305795Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6306035Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6306410Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6306996Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6307608Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6308233Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6308908Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6309635Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6311817Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6315301Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6317272Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6317688Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6317880Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6320013Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6322286Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6322771Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6322975Z | ^~~~~~~~ 2025-08-26T23:36:33.6323239Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6323626Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6324005Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6324324Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6329075Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6329362Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6329711Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6330090Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6330584Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6330949Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6331282Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6331594Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6331879Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6332073Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6332378Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6332634Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6332765Z | ^~~~ 2025-08-26T23:36:33.6332965Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6333248Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6333516Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6333781Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6334029Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6334367Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6334699Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6334992Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6335285Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6335593Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6335926Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6336204Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6336391Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6336761Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6337286Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6337855Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6338435Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6340598Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6341277Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6343184Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6346414Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6348277Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6348593Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6348765Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6350780Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6354062Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6354483Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6354630Z | ^~~~~~~~ 2025-08-26T23:36:33.6354849Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6355182Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6355479Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6355749Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6355999Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6356275Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6356670Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6358224Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6358604Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6358967Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6359299Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6359610Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6359936Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6360126Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6360473Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6360760Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6360887Z | ^~~~ 2025-08-26T23:36:33.6361084Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6362443Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6362711Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6362975Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6363223Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6363501Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6363805Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6364096Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6364382Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6364690Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6365008Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6365288Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6366517Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6366868Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6367395Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6367956Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6368532Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6369201Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6369884Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6371975Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6375370Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6380551Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6380882Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6381023Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6383128Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6385279Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6385701Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6385848Z | ^~~~~~~~ 2025-08-26T23:36:33.6386103Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6386437Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6388011Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6388301Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6388560Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6388842Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6389192Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6389564Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6389938Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6390303Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6390710Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6391022Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6392307Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6392502Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6392795Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6393049Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6393177Z | ^~~~ 2025-08-26T23:36:33.6393377Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6393661Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6393978Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6394259Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6394509Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6394787Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6396004Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6396303Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6396632Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6396944Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6397263Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6397563Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6397838Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6398189Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6398712Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6399286Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6399868Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6401499Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6402171Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6404083Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6407325Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6409203Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6409518Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6409661Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6411661Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6414685Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6415109Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6415260Z | ^~~~~~~~ 2025-08-26T23:36:33.6415479Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6415811Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6416108Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6416381Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6416631Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6416939Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6417307Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6418604Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6418982Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6419348Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6419705Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6420019Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6420324Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6420596Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6420885Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6421136Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6421262Z | ^~~~ 2025-08-26T23:36:33.6421461Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6422654Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6422930Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6423194Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6423444Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6423723Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6424029Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6424321Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6424614Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6424926Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6425245Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6425527Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6426641Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6426990Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6427515Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6428119Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6428717Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6429336Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6429999Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6432018Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6435202Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6438098Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6438415Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6438556Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6440596Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6442654Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6443075Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6443245Z | ^~~~~~~~ 2025-08-26T23:36:33.6443463Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6443795Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6444090Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6444364Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6444617Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6444897Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6446225Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6446599Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6446973Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6447344Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6447677Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6447991Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6448272Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6448460Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6448747Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6448997Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6449123Z | ^~~~ 2025-08-26T23:36:33.6450230Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6450571Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6450872Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6451153Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6451402Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6451682Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6451987Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6452279Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6452591Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6452902Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6454146Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6454428Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6454615Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6454961Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6455485Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6456058Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6456714Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6457369Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6458035Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6459951Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6464317Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6466179Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6466491Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6466632Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6468579Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6470666Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6471089Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6471236Z | ^~~~~~~~ 2025-08-26T23:36:33.6471452Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6472821Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6473119Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6473394Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6473678Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6473976Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6474321Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6474693Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6475065Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6475451Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6475782Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6477047Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6477355Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6477544Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6477889Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6478140Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6478267Z | ^~~~ 2025-08-26T23:36:33.6478468Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6478749Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6479021Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6479288Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6479535Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6480816Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6481125Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6481416Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6481710Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6482021Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6482340Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6482618Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6482805Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6483149Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6483674Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6484278Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6485831Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6486454Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6487117Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6489072Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6492316Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6494132Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6494445Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6494586Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6496554Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6499596Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6500046Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6500195Z | ^~~~~~~~ 2025-08-26T23:36:33.6500485Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6500815Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6501107Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6501380Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6501635Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6501913Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6502260Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6503574Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6503946Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6504311Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6504642Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6504957Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6505239Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6505427Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6505714Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6505963Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6506090Z | ^~~~ 2025-08-26T23:36:33.6506317Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6507541Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6507830Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6508092Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6508337Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6508613Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6508917Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6509211Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6509502Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6509810Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6510146Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6511631Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6511822Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6512171Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6512694Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6513262Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6513842Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6514462Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6515128Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6517189Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6520772Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6523672Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6523986Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6524130Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6526189Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6528294Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6528715Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6528861Z | ^~~~~~~~ 2025-08-26T23:36:33.6529077Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6529437Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6530813Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6531106Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6531358Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6531635Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6531980Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6532350Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6532725Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6533090Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6533440Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6533751Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6534029Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6534218Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6535454Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6535749Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6535932Z | ^~~~ 2025-08-26T23:36:33.6536137Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6536425Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6536694Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6536955Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6537202Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6537477Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6537784Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6539056Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6539352Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6539657Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6539970Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6540247Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6540541Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6540889Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6541436Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6542020Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6542599Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6543217Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6544814Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6546904Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6550394Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6552357Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6552698Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6552859Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6554981Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6557100Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6558563Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6558712Z | ^~~~~~~~ 2025-08-26T23:36:33.6558930Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6559266Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6559561Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6559830Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6560081Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6560416Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6560763Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6561139Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6562444Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6562814Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6563142Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6563483Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6563762Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6563969Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6564284Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6564537Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6564663Z | ^~~~ 2025-08-26T23:36:33.6564861Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6565140Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6566322Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6566589Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6566837Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6567116Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6567445Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6567737Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6568026Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6568334Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6568651Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6568931Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6569118Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6570425Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6570951Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6571518Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6572099Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6572724Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6573390Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6575480Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6578981Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6581926Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6582245Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6582385Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6584479Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6586646Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6587086Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6587232Z | ^~~~~~~~ 2025-08-26T23:36:33.6587448Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6587778Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6588073Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6589293Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6589555Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6589834Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6590206Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6590645Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6591015Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6591378Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6591708Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6592018Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6592298Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6592484Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6592773Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6593023Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6593148Z | ^~~~ 2025-08-26T23:36:33.6593346Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6602794Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6603098Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6603410Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6603754Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6604096Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6604418Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6604790Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6605097Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6605439Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6605786Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6607987Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6608199Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6608591Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6609142Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6609738Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6610443Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6611076Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6611760Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6613838Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6617467Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6620922Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6621265Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6621418Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6623584Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6625875Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6626470Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6626762Z | ^~~~~~~~ 2025-08-26T23:36:33.6629241Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6629600Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6632175Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6632479Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6632757Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6633056Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6633474Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6633932Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6634351Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6634759Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6635113Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6635424Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6637175Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6637370Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6637768Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6638024Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6638163Z | ^~~~ 2025-08-26T23:36:33.6638366Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6638682Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6638951Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6639211Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6639458Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6639738Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6641138Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6641438Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6641730Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6642038Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6642360Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6642644Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6642833Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6643194Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6643727Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6644293Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6644871Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6646593Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6647310Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6649421Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6652966Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6654914Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6655229Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6655371Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6657476Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6660829Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6661261Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6661412Z | ^~~~~~~~ 2025-08-26T23:36:33.6661632Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6661996Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6662291Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6662562Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6662814Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6663093Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6663439Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6664761Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6665137Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6665502Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6665831Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6666146Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6666427Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6666615Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6666906Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6667158Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6667283Z | ^~~~ 2025-08-26T23:36:33.6668382Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6668667Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6668934Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6669223Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6669489Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6669785Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6670091Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6670465Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6670755Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6671065Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6671381Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6672574Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6672765Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6673308Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6673831Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6674396Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6674977Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6675597Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6676264Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6678380Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6682988Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6684988Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6685303Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6685444Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6687537Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6689665Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6690089Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6690235Z | ^~~~~~~~ 2025-08-26T23:36:33.6690524Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6690856Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6691171Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6692450Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6692736Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6693034Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6693378Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6693749Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6694249Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6694618Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6694949Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6695290Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6695569Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6696727Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6697028Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6697281Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6697410Z | ^~~~ 2025-08-26T23:36:33.6697608Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6697891Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6698161Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6698424Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6698669Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6698945Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6699248Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6700528Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6700829Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6701140Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6701457Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6701734Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6701919Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6702266Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6702826Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6703415Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6704011Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6704632Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6706227Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6708304Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6711823Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6713759Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6714095Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6714236Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6716358Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6719535Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6719959Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6720107Z | ^~~~~~~~ 2025-08-26T23:36:33.6720325Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6720728Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6721024Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6721297Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6721546Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6721820Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6722165Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6722535Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6723868Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6724257Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6724586Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6724895Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6725172Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6725378Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6725669Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6725921Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6726048Z | ^~~~ 2025-08-26T23:36:33.6726246Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6726548Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6727742Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6728004Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6728250Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6728530Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6728837Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6729130Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6729421Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6729727Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6730041Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6730320Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6730572Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6731822Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6732353Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6732919Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6733496Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6734154Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6734845Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6736928Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6740454Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6743385Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6743703Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6743846Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6745969Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6748108Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6748548Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6748698Z | ^~~~~~~~ 2025-08-26T23:36:33.6748935Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6749266Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6749561Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6749832Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6750087Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6750436Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6750783Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6751157Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6752511Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6752882Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6753210Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6753522Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6753802Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6753989Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6754279Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6754530Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6754657Z | ^~~~ 2025-08-26T23:36:33.6754856Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6755139Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6756307Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6756605Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6756870Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6757148Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6757450Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6757793Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6758082Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6758415Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6758732Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6759011Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6759217Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6760573Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6761099Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6761669Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6762253Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6762875Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6763539Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6765597Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6769101Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6772114Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6772432Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6772574Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6774782Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6776908Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6777326Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6777473Z | ^~~~~~~~ 2025-08-26T23:36:33.6777690Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6778023Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6778322Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6779591Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6779870Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6780149Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6780570Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6780942Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6781314Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6781698Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6782036Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6782363Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6782643Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6782829Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6784050Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6784304Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6784431Z | ^~~~ 2025-08-26T23:36:33.6784629Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6784914Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6785185Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6785447Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6785694Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6785971Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6786274Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6786566Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6787766Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6788078Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6788395Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6788673Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6788859Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6789203Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6789758Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6790415Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6790992Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6791610Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6793225Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6795170Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6798408Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6800235Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6800615Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6800756Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6802718Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6804776Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6806212Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6806360Z | ^~~~~~~~ 2025-08-26T23:36:33.6806580Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6806910Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6807207Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6807479Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6807733Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6808014Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6808358Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6808730Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6809106Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6809472Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6809802Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6810115Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6810449Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6810637Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6810925Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6812134Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6812263Z | ^~~~ 2025-08-26T23:36:33.6812459Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6812773Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6812910Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6813020Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6813124Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6813267Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6813423Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6813554Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6813682Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6813847Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6813984Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6814091Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6814137Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6814404Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6814703Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6815923Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6816232Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6816586Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6816956Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6818722Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6820782Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6821081Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6821146Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6821195Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6823204Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6823633Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6823712Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6823749Z | ^~~~~~~~ 2025-08-26T23:36:33.6823951Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6824115Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6824236Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6824354Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6824456Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6824597Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6824787Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6825896Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6826072Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6826248Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6826389Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6826524Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6826634Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6826679Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6826886Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6826942Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6826981Z | ^~~~ 2025-08-26T23:36:33.6827112Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6827229Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6827344Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6827452Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6827557Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6827700Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6827831Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6827961Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6828088Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6828233Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6828371Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6829354Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6829422Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6829703Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6829999Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6830314Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6830691Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6831073Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6831465Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6833200Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6835182Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6835486Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6835549Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6835596Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6837618Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6838111Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6838189Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6838226Z | ^~~~~~~~ 2025-08-26T23:36:33.6838385Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6838527Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6839565Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6839685Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6839789Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6839934Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6840110Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6840276Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6840510Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6840665Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6840806Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6840983Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6841115Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6841161Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6841370Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6841424Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6841463Z | ^~~~ 2025-08-26T23:36:33.6841592Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6841730Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6841845Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6841957Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6842086Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6842227Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6843234Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6843366Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6843494Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6843643Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6843780Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6843889Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6843934Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6844199Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6844490Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6844809Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6845116Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6845473Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6845838Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6847597Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6849596Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6849877Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6849938Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6849985Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6852092Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6853952Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6854059Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6854110Z | ^~~~~~~~ 2025-08-26T23:36:33.6854326Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6854497Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6854619Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6854739Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6854860Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6855004Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6855179Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6855345Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6855521Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6855681Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6855824Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6855962Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6856070Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6856115Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6856324Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6856381Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6856419Z | ^~~~ 2025-08-26T23:36:33.6856551Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6857572Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6857692Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6857801Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6857904Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6858046Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6858177Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6858336Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6858483Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6858631Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6858766Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6858873Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6858919Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6859199Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6859497Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6859832Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6860138Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6860563Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6860933Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6862527Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6864356Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6865554Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6865644Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6865690Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6867574Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6868007Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6868083Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6868119Z | ^~~~~~~~ 2025-08-26T23:36:33.6868275Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6868417Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6868538Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6868655Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6868758Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6868899Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6869071Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6869239Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6869413Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6869588Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6869746Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6869883Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6869989Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6870035Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6871200Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6871285Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6871323Z | ^~~~ 2025-08-26T23:36:33.6871456Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T23:36:33.6871575Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T23:36:33.6871712Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T23:36:33.6871821Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T23:36:33.6871925Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T23:36:33.6872065Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T23:36:33.6872197Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T23:36:33.6872328Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T23:36:33.6872457Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T23:36:33.6872605Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T23:36:33.6872742Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T23:36:33.6872850Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6872896Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6873161Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T23:36:33.6873456Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T23:36:33.6873772Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T23:36:33.6874077Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T23:36:33.6874430Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T23:36:33.6875699Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T23:36:33.6877477Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T23:36:33.6879485Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T23:36:33.6879765Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T23:36:33.6879827Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T23:36:33.6879875Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T23:36:33.6881958Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T23:36:33.6882407Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T23:36:33.6882503Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T23:36:33.6882539Z | ^~~~~~~~ 2025-08-26T23:36:33.6882697Z In file included from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T23:36:33.6882861Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T23:36:33.6882981Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T23:36:33.6883097Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T23:36:33.6883198Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T23:36:33.6883339Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T23:36:33.6883514Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T23:36:33.6883682Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T23:36:33.6883858Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T23:36:33.6884931Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T23:36:33.6885074Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T23:36:33.6885209Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T23:36:33.6885320Z from /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/extension.h:5, 2025-08-26T23:36:33.6885366Z from rng_extension.cpp:1: 2025-08-26T23:36:33.6885573Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T23:36:33.6885628Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T23:36:33.6885669Z | ^~~~ 2025-08-26T23:36:33.6886697Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib build/temp.linux-x86_64-cpython-312/rng_extension.o -L/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/rng.cpython-312-x86_64-linux-gnu.so 2025-08-26T23:36:33.9082126Z building 'torch_test_cpp_extension.cuda' extension 2025-08-26T23:36:33.9083312Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/THH -I/opt/rocm/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c cuda_extension.cpp -o build/temp.linux-x86_64-cpython-312/cuda_extension.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cuda -std=c++17 2025-08-26T23:36:48.2885502Z /opt/rocm/bin/hipcc -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/THH -I/opt/rocm/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c hip_extension_kernel.hip -o build/temp.linux-x86_64-cpython-312/hip_extension_kernel.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -DCUDA_HAS_FP16=1 -D__HIP_NO_HALF_OPERATORS__=1 -D__HIP_NO_HALF_CONVERSIONS__=1 -DHIP_ENABLE_WARP_SYNC_BUILTINS=1 -O2 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cuda --offload-arch=gfx90a --offload-arch=gfx942 -fno-gpu-rdc -std=c++17 2025-08-26T23:36:59.2415335Z /opt/rocm/bin/hipcc -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/THH -I/opt/rocm/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c hip_extension_kernel2.hip -o build/temp.linux-x86_64-cpython-312/hip_extension_kernel2.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -DCUDA_HAS_FP16=1 -D__HIP_NO_HALF_OPERATORS__=1 -D__HIP_NO_HALF_CONVERSIONS__=1 -DHIP_ENABLE_WARP_SYNC_BUILTINS=1 -O2 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cuda --offload-arch=gfx90a --offload-arch=gfx942 -fno-gpu-rdc -std=c++17 2025-08-26T23:37:09.6826554Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib build/temp.linux-x86_64-cpython-312/cuda_extension.o build/temp.linux-x86_64-cpython-312/hip_extension_kernel.o build/temp.linux-x86_64-cpython-312/hip_extension_kernel2.o -L/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib -L/opt/rocm/lib -L/opt/rocm/hip/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -lamdhip64 -lc10_hip -ltorch_hip -o build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/cuda.cpython-312-x86_64-linux-gnu.so 2025-08-26T23:37:09.9931673Z building 'torch_test_cpp_extension.torch_library' extension 2025-08-26T23:37:09.9933506Z /opt/rocm/bin/hipcc -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/include/THH -I/opt/rocm/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.12/include/python3.12 -c torch_library.cu -o build/temp.linux-x86_64-cpython-312/torch_library.o -D__HIP_PLATFORM_AMD__=1 -DUSE_ROCM=1 -DHIPBLAS_V2 -fPIC -DCUDA_HAS_FP16=1 -D__HIP_NO_HALF_OPERATORS__=1 -D__HIP_NO_HALF_CONVERSIONS__=1 -DHIP_ENABLE_WARP_SYNC_BUILTINS=1 -O2 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=torch_library --offload-arch=gfx90a --offload-arch=gfx942 -fno-gpu-rdc -std=c++17 2025-08-26T23:37:35.6078937Z g++ -pthread -B /opt/conda/envs/py_3.12/compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -fPIC -O2 -isystem /opt/conda/envs/py_3.12/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.12/lib -Wl,-rpath-link,/opt/conda/envs/py_3.12/lib -L/opt/conda/envs/py_3.12/lib build/temp.linux-x86_64-cpython-312/torch_library.o -L/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib -L/opt/rocm/lib -L/opt/rocm/hip/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -lamdhip64 -lc10_hip -ltorch_hip -o build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/torch_library.cpython-312-x86_64-linux-gnu.so 2025-08-26T23:37:35.7925840Z running install_lib 2025-08-26T23:37:35.7963996Z creating install/opt/conda/envs/py_3.12/lib/python3.12/site-packages 2025-08-26T23:37:35.7966345Z creating install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.7972594Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/rng.cpython-312-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8006921Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/cuda.cpython-312-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8039208Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/__init__.py -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8039749Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8080194Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/torch_library.cpython-312-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8082423Z copying build/lib.linux-x86_64-cpython-312/torch_test_cpp_extension/maia.cpython-312-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension 2025-08-26T23:37:35.8129229Z byte-compiling ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension/__init__.py to __init__.cpython-312.pyc 2025-08-26T23:37:35.8131251Z running install_egg_info 2025-08-26T23:37:35.8214248Z running egg_info 2025-08-26T23:37:35.8242441Z creating torch_test_cpp_extension.egg-info 2025-08-26T23:37:35.8243280Z writing torch_test_cpp_extension.egg-info/PKG-INFO 2025-08-26T23:37:35.8247869Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt 2025-08-26T23:37:35.8248157Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt 2025-08-26T23:37:35.8248385Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt 2025-08-26T23:37:35.8248597Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T23:37:35.8278925Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T23:37:35.8282620Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T23:37:35.8283548Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info 2025-08-26T23:37:35.8286735Z running install_scripts 2025-08-26T23:37:37.8747474Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:37:37.8754786Z import pkg_resources 2025-08-26T23:37:37.8904091Z 2025-08-26T23:37:37.8904283Z Running tests... 2025-08-26T23:37:37.8904440Z ---------------------------------------------------------------------- 2025-08-26T23:37:38.2104538Z . 2025-08-26T23:37:38.2104895Z ---------------------------------------------------------------------- 2025-08-26T23:37:38.2105299Z Ran 1 test in 0.320s 2025-08-26T23:37:38.2105477Z 2025-08-26T23:37:38.2105567Z OK 2025-08-26T23:37:38.2105906Z 2025-08-26T23:37:38.2106035Z Generating XML reports... 2025-08-26T23:37:39.0500011Z Running test_mkldnn_verbose 1/1 ... [2025-08-26 23:37:39.049477] 2025-08-26T23:37:39.0500237Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:37:39.0506131Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_mkldnn_verbose.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:37:39.049901] 2025-08-26T23:37:43.5744309Z 2025-08-26T23:37:43.5746089Z test_mkldnn_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_verbose_1.1_f19c9e915af0b992_.log 2025-08-26T23:37:43.5747360Z Running 2 items in this shard: test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_off, test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_on 2025-08-26T23:37:43.5748015Z 2025-08-26T23:37:43.5748276Z Running test_namedtuple_return_api 1/1 ... [2025-08-26 23:37:43.574325] 2025-08-26T23:37:43.5748793Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:37:43.5749873Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:37:43.574544] 2025-08-26T23:37:46.7011640Z 2025-08-26T23:37:46.7012954Z test_namedtuple_return_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtuple_return_api_1.1_f27e403a21191320_.log 2025-08-26T23:37:46.7019548Z Running 3 items in this shard: test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_import_return_types, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_namedtuple_return, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_native_functions_yaml 2025-08-26T23:37:46.7020239Z 2025-08-26T23:37:46.7021498Z Running test_native_functions 1/1 ... [2025-08-26 23:37:46.701254] 2025-08-26T23:37:46.7021895Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:37:46.7022586Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_native_functions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:37:46.701492] 2025-08-26T23:37:49.2195235Z 2025-08-26T23:37:49.2196482Z test_native_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_functions_1.1_2ab26654407380f0_.log 2025-08-26T23:37:49.2201200Z Running 11 items in this shard: test/test_native_functions.py::TestNativeFunctions::test_intlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_optional_filled_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist, test/test_native_functions.py::TestNativeFunctions::test_optional_floatlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist, test/test_native_functions.py::TestNativeFunctions::test_optional_intlist_invalid, test/test_native_functions.py::TestNativeFunctions::test_string_defaults, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload, test/test_native_functions.py::TestNativeFunctions::test_symintlist_error_with_overload_but_is_unique, test/test_native_functions.py::TestNativeFunctions::test_vararg_symintlist_error 2025-08-26T23:37:49.2204126Z 2025-08-26T23:37:49.2204261Z Running test_numa_binding 1/1 ... [2025-08-26 23:37:49.219626] 2025-08-26T23:37:49.2204523Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:37:49.2205147Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_numa_binding.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:37:49.219871] 2025-08-26T23:37:52.9411546Z 2025-08-26T23:37:52.9412401Z test_numa_binding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numa_binding_1.1_001b9d585e1d5f95_.log 2025-08-26T23:37:52.9416958Z Running 20 items in this shard: test/test_numa_binding.py::NumaBindingTest::test_binds_to_node_0_if_node_stored_as_minus_one, test/test_numa_binding.py::NumaBindingTest::test_callable_entrypoint_basic, test/test_numa_binding.py::NumaBindingTest::test_core_complex_numa_binding_with_extra_l3, test/test_numa_binding.py::NumaBindingTest::test_core_complex_numa_binding_with_fewer_l3_than_gpu, test/test_numa_binding.py::NumaBindingTest::test_core_complex_prefers_caches_with_more_cpus, test/test_numa_binding.py::NumaBindingTest::test_core_complex_tiebreak_prefers_lower_cache_key, test/test_numa_binding.py::NumaBindingTest::test_default_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_exclusive_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_exclusive_raises_if_too_few_physical_cores, test/test_numa_binding.py::NumaBindingTest::test_explicit_numa_options_overrides_default, test/test_numa_binding.py::NumaBindingTest::test_fallback, test/test_numa_binding.py::NumaBindingTest::test_get_range_str_from_ints, test/test_numa_binding.py::NumaBindingTest::test_get_set_of_int_from_ranges_str, test/test_numa_binding.py::NumaBindingTest::test_no_numa_binding_if_numa_options_not_provided, test/test_numa_binding.py::NumaBindingTest::test_node_numa_binding, test/test_numa_binding.py::NumaBindingTest::test_nproc_must_equal_cuda_device_count_to_use_default_numa_options, test/test_numa_binding.py::NumaBindingTest::test_parallel_start_does_not_call_get_default_numa_options, test/test_numa_binding.py::NumaBindingTest::test_raises_if_binding_to_empty_set, test/test_numa_binding.py::NumaBindingTest::test_socket_numa_binding_with_multiple_numa_per_socket, test/test_numa_binding.py::NumaBindingTest::test_socket_numa_binding_with_single_numa_per_socket 2025-08-26T23:37:52.9421044Z 2025-08-26T23:37:52.9421190Z Running test_ops_fwd_gradients 1/1 ... [2025-08-26 23:37:52.941185] 2025-08-26T23:37:52.9421467Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:37:52.9422097Z Executing ['/opt/conda/envs/py_3.12/bin/python', '-bb', 'test_ops_fwd_gradients.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 23:37:52.941405] 2025-08-26T23:45:24.6686811Z 2025-08-26T23:45:24.6687636Z test_ops_fwd_gradients 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_fwd_gradients_1.1_98efb715df65ac49_.log 2025-08-26T23:45:24.7148595Z Running 3195 items in this shard: test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_H_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_H_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_T_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_T_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___getitem___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___getitem___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___radd___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___radd___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rdiv___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rdiv___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rmatmul___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rmatmul___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rmod___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rmul___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rmul___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rpow___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rpow___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rsub___cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad___rsub___cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__batch_norm_with_update_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__chunk_cat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__chunk_cat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__native_batch_norm_legit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__segment_reduce_lengths_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__segment_reduce_offsets_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__softmax_backward_data_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__unsafe_masked_index_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__unsafe_masked_index_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__unsafe_masked_index_put_accumulate_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__unsafe_masked_index_put_accumulate_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad__upsample_bilinear2d_aa_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_abs_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_abs_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_acos_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_acos_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_acosh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_acosh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_add_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_add_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addbmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addbmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addcdiv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addcdiv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addcmul_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addcmul_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmm_decomposed_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmm_decomposed_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addmv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_addr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_alias_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_alias_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_all_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_all_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_allclose_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_allclose_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_amax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_amin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_aminmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_angle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_angle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_any_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_any_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_arange_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_argmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_argmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_argsort_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_argwhere_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_argwhere_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_partial_views_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_partial_views_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_scatter_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_as_strided_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_asin_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_asin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_asinh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_asinh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atan2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atan_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atan_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atanh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_atleast_3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_baddbmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_baddbmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bernoulli_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bfloat16_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bfloat16_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_block_diag_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_block_diag_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bool_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bool_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_broadcast_tensors_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_broadcast_tensors_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_broadcast_to_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_broadcast_to_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_bucketize_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_byte_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_byte_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cartesian_prod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cartesian_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cauchy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cdist_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cdouble_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cdouble_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_ceil_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cfloat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cfloat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_chalf_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_chalf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_char_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_char_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cholesky_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_cholesky_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_clone_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_clone_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_column_stack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_column_stack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_combinations_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_combinations_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_complex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_conj_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_conj_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_sub_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_sum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_sum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_sum_to_size_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_sum_to_size_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_svd_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_svd_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_svd_lowrank_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_svd_lowrank_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_t_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_t_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_t_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_t_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_take_along_dim_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_take_along_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_take_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_take_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tan_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tan_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tanh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tensor_split_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tensor_split_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tensordot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tensordot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tile_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tile_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_to_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_to_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_to_sparse_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_to_sparse_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_topk_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trace_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trace_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_transpose_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_transpose_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_transpose_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_transpose_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trapezoid_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trapezoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trapz_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trapz_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_triangular_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_triangular_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tril_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_tril_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_triu_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_triu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_true_divide_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_true_divide_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_trunc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unbind_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unbind_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unbind_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unbind_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unflatten_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unflatten_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unfold_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unfold_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unfold_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unfold_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_uniform_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_uniform_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unique_consecutive_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unique_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsafe_chunk_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsafe_chunk_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsafe_split_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsafe_split_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsqueeze_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsqueeze_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsqueeze_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_unsqueeze_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_mean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_mean_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_mean_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_var_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vdot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vdot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_as_complex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_as_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_as_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_as_real_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_view_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vsplit_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vsplit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vstack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_vstack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_where_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_where_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_xlogy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zero__cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zero__cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zeros_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zeros_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zeros_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_fn_fwgrad_bwgrad_zeros_like_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD__unsafe_masked_index_put_accumulate_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD__unsafe_masked_index_put_accumulate_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD__upsample_bilinear2d_aa_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_abs_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_abs_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_acos_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_acos_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_acosh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_acosh_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_native_dropout_backward_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_native_layer_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_ne_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_ne_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_neg_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_neg_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_empty_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_empty_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_empty_strided_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_empty_strided_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_full_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_full_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_ones_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_ones_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_zeros_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_new_zeros_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nextafter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_avg_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_avg_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_avg_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_max_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_adaptive_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_alpha_dropout_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_avg_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_avg_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_avg_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_batch_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_batch_norm_without_cudnn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_binary_cross_entropy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_binary_cross_entropy_with_logits_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_celu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_channel_shuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_channel_shuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_conv_transpose3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_cosine_embedding_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_cosine_similarity_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_cross_entropy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_ctc_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_dropout2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_dropout3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_dropout_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_elu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_embedding_bag_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_embedding_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_feature_alpha_dropout_with_train_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_fractional_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_fractional_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_gaussian_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_gelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_glu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_grid_sample_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_group_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_hardshrink_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_hardsigmoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_hardswish_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_hardtanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_hinge_embedding_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_huber_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_instance_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_area_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_bicubic_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_linear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_nearest-exact_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_nearest_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_interpolate_trilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_kl_div_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_l1_loss_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_l1_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_layer_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_leaky_relu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_linear_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_linear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_local_response_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_logsigmoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_margin_ranking_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool1d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool2d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_max_unpool3d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_mish_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_mse_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_multi_head_attention_forward_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_multi_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_multilabel_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_multilabel_soft_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_normalize_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_normalize_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_circular_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_circular_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_constant_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_constant_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_reflect_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_reflect_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_replicate_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_replicate_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_replicate_negative_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pad_replicate_negative_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pairwise_distance_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pairwise_distance_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pdist_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pixel_shuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pixel_shuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pixel_unshuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_pixel_unshuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_poisson_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_prelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_relu6_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_relu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_rms_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_rms_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_rrelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_scaled_dot_product_attention_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_selu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_silu_complex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_silu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_smooth_l1_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_soft_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softmin_with_dtype_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softmin_with_dtype_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softplus_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softshrink_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softsign_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_softsign_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_unfold_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_upsample_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nn_functional_upsample_nearest_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nonzero_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nonzero_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nonzero_static_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_nonzero_static_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_forward_mode_AD_norm_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addbmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addcdiv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addcdiv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addcmul_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addcmul_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmm_decomposed_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmm_decomposed_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addmv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_addr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_alias_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_alias_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_all_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_all_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_allclose_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_allclose_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_amax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_amin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_aminmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_angle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_angle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_any_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_any_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_arange_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_argmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_argmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_argsort_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_argwhere_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_argwhere_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_partial_views_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_partial_views_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_scatter_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_as_strided_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_asin_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_asin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_asinh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_asinh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atan2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atan_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atan_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atanh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_atleast_3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_baddbmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_baddbmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bernoulli_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bfloat16_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bfloat16_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_block_diag_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_block_diag_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bool_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bool_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_broadcast_tensors_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_broadcast_tensors_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_broadcast_to_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_broadcast_to_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_bucketize_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_byte_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_byte_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cartesian_prod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cartesian_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cauchy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cdist_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cdouble_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cdouble_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ceil_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cfloat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cfloat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_chalf_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_chalf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_char_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_char_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_inverse_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_inverse_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cholesky_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_chunk_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_chunk_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_clamp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_clamp_max_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_clamp_min_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_clone_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_clone_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_column_stack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_column_stack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_combinations_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_combinations_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_complex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_conj_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_conj_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_conj_physical_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_conj_physical_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_constant_pad_nd_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_constant_pad_nd_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_contiguous_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_contiguous_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_copysign_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_corrcoef_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_corrcoef_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cos_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cos_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cosh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cosh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_count_nonzero_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_count_nonzero_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cov_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cov_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cross_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cross_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cummax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cummin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumprod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumprod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumsum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumsum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumulative_trapezoid_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_cumulative_trapezoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_deg2rad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diag_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diag_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diag_embed_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diag_embed_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagflat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagflat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_scatter_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diagonal_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diff_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_diff_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_digamma_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_dist_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_dist_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_dsplit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_dstack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_dstack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_einsum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_einsum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_permuted_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_permuted_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_strided_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_empty_strided_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_eq_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_eq_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_equal_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_equal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_erf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_erfc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_erfinv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_exp2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_exp2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_exp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_exp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_as_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_as_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expand_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expm1_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_expm1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_exponential_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_eye_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_eye_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fft2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fftn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fftshift_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_fftshift_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfft2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfftn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_hfftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifft2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifftn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifftshift_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ifftshift_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ihfft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ihfft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_ihfftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfft2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfftn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_irfftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_rfft2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_rfft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fft_rfftn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fill_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fill_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flatten_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flatten_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flip_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flip_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fliplr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fliplr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flipud_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_flipud_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_float_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_float_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_float_power_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_float_power_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_floor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_floor_divide_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_fmod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_frac_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_frexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_full_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_full_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_full_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_full_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_gather_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_gather_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ge_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_geometric_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_geqrf_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_geqrf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_gradient_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_gradient_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_grid_sampler_2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_grid_sampler_3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_gt_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_half_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_half_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hash_tensor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_heaviside_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_histc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hsplit_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hsplit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hstack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hstack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_hypot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_i0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_igamma_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_igammac_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_imag_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_add_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_add_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_fill_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_fill_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_put_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_put_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_reduce_amax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_reduce_amin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_reduce_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_reduce_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_select_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_index_select_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_inner_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_inner_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_int_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_int_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isclose_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isclose_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isfinite_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isfinite_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isinf_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isinf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isnan_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isnan_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isneginf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isposinf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isreal_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_isreal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_istft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_item_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_item_cuda_float64, 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test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_jiterator_binary_return_by_ref_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_jiterator_unary_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_jiterator_unary_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_kron_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_kron_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_kthvalue_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ldexp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ldexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_le_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lerp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lerp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lgamma_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cholesky_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cholesky_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cholesky_ex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cholesky_ex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cond_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cond_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cross_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_cross_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_det_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_det_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_diagonal_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_diagonal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eig_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eig_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigvals_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigvals_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigvalsh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_eigvalsh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_householder_product_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_householder_product_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_inv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_inv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_inv_ex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_inv_ex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_factor_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_factor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_factor_ex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_factor_ex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_ldl_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lstsq_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lstsq_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lstsq_grad_oriented_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lstsq_grad_oriented_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_factor_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_factor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_factor_ex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_factor_ex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_lu_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_power_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_power_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_rank_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_rank_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_rank_hermitian_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_matrix_rank_hermitian_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_multi_dot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_multi_dot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_norm_subgradients_at_zero_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_norm_subgradients_at_zero_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_hermitian_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_hermitian_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_singular_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_pinv_singular_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_qr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_qr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_slogdet_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_slogdet_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_ex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_ex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_triangular_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_solve_triangular_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_svd_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_svd_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_svdvals_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_svdvals_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_tensorinv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_tensorinv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_tensorsolve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_tensorsolve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vander_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vander_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vecdot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vecdot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vector_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linalg_vector_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linspace_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linspace_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linspace_tensor_overload_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_linspace_tensor_overload_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log10_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log10_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log1p_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log1p_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log2_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_normal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_softmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_softmax_with_dtype_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_log_softmax_with_dtype_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logaddexp2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logaddexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logcumsumexp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logcumsumexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logdet_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logdet_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_and_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_and_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_not_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_not_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_or_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_or_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_xor_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logical_xor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logspace_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logspace_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logspace_tensor_overload_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logspace_tensor_overload_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logsumexp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_logsumexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_long_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_long_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lt_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_unpack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_lu_unpack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mH_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mH_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mT_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mT_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_amax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_amin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_argmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_argmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_cumprod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_cumprod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_cumsum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_cumsum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_fill_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_fill_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_log_softmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_logaddexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_logsumexp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_logsumexp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_mean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_median_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_normalize_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_normalize_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_prod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_scatter_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_select_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_select_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_softmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_softmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_std_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_std_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_sum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_sum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_var_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_masked_var_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_matmul_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_matmul_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_matrix_exp_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_matrix_exp_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_max_binary_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_max_pool2d_with_indices_backward_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_max_reduction_no_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_max_reduction_with_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_maximum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_median_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_meshgrid_list_of_tensors_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_meshgrid_list_of_tensors_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_meshgrid_variadic_tensors_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_meshgrid_variadic_tensors_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_min_binary_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_min_reduction_no_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_min_reduction_with_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_minimum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mode_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_movedim_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_movedim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_msort_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mul_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mul_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_multinomial_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mv_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mv_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_3_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_mvlgamma_mvlgamma_p_5_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nan_to_num_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nanmean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nanmean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nanmedian_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nanquantile_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nansum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nansum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_narrow_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_narrow_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_narrow_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_narrow_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_native_batch_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_native_dropout_backward_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_native_layer_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ne_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ne_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_neg_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_neg_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_empty_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_empty_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_empty_strided_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_empty_strided_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_full_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_full_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_ones_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_ones_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_zeros_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_new_zeros_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nextafter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_avg_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_adaptive_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_alpha_dropout_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_avg_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_avg_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_avg_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_batch_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_batch_norm_without_cudnn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_binary_cross_entropy_with_logits_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_celu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_channel_shuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_conv_transpose3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_cosine_embedding_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_cosine_similarity_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_cross_entropy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_ctc_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_dropout2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_dropout3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_dropout_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_elu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_embedding_bag_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_embedding_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_with_train_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_feature_alpha_dropout_without_train_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_fractional_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_gaussian_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_gelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_glu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_grid_sample_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_group_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_hardshrink_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_hardsigmoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_hardswish_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_hardtanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_hinge_embedding_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_huber_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_instance_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_area_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_bicubic_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_linear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest-exact_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_nearest_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_interpolate_trilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_kl_div_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_l1_loss_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_l1_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_layer_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_leaky_relu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_linear_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_linear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_local_response_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_logsigmoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_margin_ranking_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_pool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_pool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_pool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool1d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool2d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_max_unpool3d_grad_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_mish_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_mse_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_multi_head_attention_forward_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_multi_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_multilabel_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_multilabel_soft_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_normalize_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_normalize_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_circular_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_circular_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_constant_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_constant_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_reflect_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_replicate_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pad_replicate_negative_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pairwise_distance_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pdist_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pixel_shuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_pixel_unshuffle_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_poisson_nll_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_prelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_relu6_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_relu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_rms_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_rms_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_rrelu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_scaled_dot_product_attention_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_selu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_silu_complex_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_silu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_smooth_l1_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_soft_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softmin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softmin_with_dtype_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softplus_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softshrink_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softsign_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_softsign_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_tanhshrink_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_threshold_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_triplet_margin_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_triplet_margin_with_distance_loss_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_unfold_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_unfold_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_upsample_bilinear_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nn_functional_upsample_nearest_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nonzero_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nonzero_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nonzero_static_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_nonzero_static_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_fro_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_fro_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_inf_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_inf_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_nuc_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_norm_nuc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_normal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_normal_in_place_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_normal_in_place_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_normal_number_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ones_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ones_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ones_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ones_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ormqr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ormqr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_outer_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_outer_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pca_lowrank_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pca_lowrank_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_permute_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_permute_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_permute_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_permute_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pinverse_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pinverse_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polar_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polygamma_polygamma_n_0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polygamma_polygamma_n_1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polygamma_polygamma_n_2_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polygamma_polygamma_n_3_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_polygamma_polygamma_n_4_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_positive_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_positive_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pow_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_pow_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_prod_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_put_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_put_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_qr_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_qr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_quantile_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rad2deg_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rand_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rand_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randint_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randint_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randn_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_randn_like_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ravel_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_ravel_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_real_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_real_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reciprocal_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reciprocal_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_remainder_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_renorm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_renorm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_repeat_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_repeat_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_repeat_interleave_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_repeat_interleave_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reshape_as_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reshape_as_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reshape_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_reshape_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resize__cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resize__cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resize_as__cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resize_as__cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resolve_conj_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resolve_conj_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resolve_neg_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_resolve_neg_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_roll_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_roll_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rot90_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rot90_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_round_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_round_decimals_0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_round_decimals_3_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_round_decimals_neg_3_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rsqrt_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rsqrt_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rsub_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_rsub_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scalar_tensor_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scalar_tensor_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_add_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_add_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_reduce_amax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_reduce_amin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_reduce_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_reduce_prod_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_scatter_reduce_sum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_searchsorted_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_select_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_select_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_select_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sgn_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sgn_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_short_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_short_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sigmoid_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sigmoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sign_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_bartlett_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_blackman_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_cosine_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_exponential_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_gaussian_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_general_cosine_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_general_hamming_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_hamming_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_hann_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_kaiser_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signal_windows_nuttall_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_signbit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sin_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sin_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sinc_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sinc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sinh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sinh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_slice_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_slice_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_slice_scatter_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_softmax_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_softmax_with_dtype_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_softmax_with_dtype_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sort_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sparse_mm_reduce_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sparse_sampled_addmm_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sparse_sampled_addmm_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_airy_ai_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_bessel_j0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_bessel_j1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_bessel_y0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_bessel_y1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_chebyshev_polynomial_t_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_chebyshev_polynomial_u_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_chebyshev_polynomial_v_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_chebyshev_polynomial_w_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_entr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_erfcx_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_hermite_polynomial_h_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_hermite_polynomial_he_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_i0e_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_i1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_i1e_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_laguerre_polynomial_l_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_legendre_polynomial_p_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_log_ndtr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_modified_bessel_i0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_modified_bessel_i1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_modified_bessel_k0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_modified_bessel_k1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_ndtr_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_ndtri_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_polygamma_special_polygamma_n_0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_scaled_modified_bessel_k1_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_t_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_u_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_v_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_shifted_chebyshev_polynomial_w_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_spherical_bessel_j0_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_xlog1py_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_special_zeta_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_list_args_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_list_args_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_with_sizes_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_with_sizes_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_with_sizes_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_split_with_sizes_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sqrt_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sqrt_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_square_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_square_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_multiple_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_squeeze_multiple_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_stack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_stack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_mean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_mean_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_mean_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_std_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_stft_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_stft_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sub_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sub_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sum_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sum_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sum_to_size_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_sum_to_size_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_svd_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_svd_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_svd_lowrank_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_svd_lowrank_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_t_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_t_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_t_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_t_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_take_along_dim_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_take_along_dim_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_take_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_take_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tan_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tan_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tanh_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tanh_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tensor_split_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tensor_split_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tensordot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tensordot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tile_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tile_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_to_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_to_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_to_sparse_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_to_sparse_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_topk_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_torch_ops_aten__safe_softmax_default_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trace_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trace_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_transpose_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_transpose_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_transpose_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_transpose_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trapezoid_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trapezoid_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trapz_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trapz_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_triangular_solve_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_triangular_solve_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tril_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_tril_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_triu_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_triu_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_true_divide_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_true_divide_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_trunc_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unbind_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unbind_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unbind_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unbind_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unflatten_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unflatten_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unfold_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unfold_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unfold_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unfold_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_uniform_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_uniform_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unique_consecutive_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unique_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsafe_chunk_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsafe_chunk_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsafe_split_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsafe_split_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsqueeze_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsqueeze_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsqueeze_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_unsqueeze_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_mean_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_mean_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_mean_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_mean_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_unbiased_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_var_unbiased_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vdot_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vdot_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_as_complex_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_as_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_as_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_as_real_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_copy_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_copy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_view_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vsplit_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vsplit_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vstack_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_vstack_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_where_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_where_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_xlogy_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zero__cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zero__cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zeros_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zeros_cuda_float64, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zeros_like_cuda_complex128, test/test_ops_fwd_gradients.py::TestFwdGradientsCUDA::test_inplace_forward_mode_AD_zeros_like_cuda_float64 2025-08-26T23:45:24.7578775Z 2025-08-26T23:45:26.2486184Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:45:26.2487547Z import pkg_resources 2025-08-26T23:45:27.2222577Z Running test batch 'tests to run' cost 12831.23 seconds 2025-08-26T23:45:28.0666443Z 2025-08-26T23:45:28.0666734Z real 213m54.833s 2025-08-26T23:45:28.0670211Z user 5958m7.267s 2025-08-26T23:45:28.0672044Z sys 70m18.407s 2025-08-26T23:45:28.0672440Z + assert_git_not_dirty 2025-08-26T23:45:28.0672822Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T23:45:28.0673194Z + test_libtorch 2 2025-08-26T23:45:28.0673448Z + local SHARD=2 2025-08-26T23:45:28.0673706Z + [[ default != \s\l\o\w ]] 2025-08-26T23:45:28.0681521Z + echo 'Testing libtorch' 2025-08-26T23:45:28.0681687Z Testing libtorch 2025-08-26T23:45:28.0682072Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libbackend_with_compiler.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0690910Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libjitbackend_test.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0702487Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libcaffe2_nvrtc.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0713709Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libc10_hip.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0724648Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libshm /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libshm.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libshm_windows /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0734537Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_hip.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorchbind_test.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0744267Z + ln -sf '/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libnvfuser*' /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0751452Z + export CPP_TESTS_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0753926Z + CPP_TESTS_DIR=/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:28.0754118Z + [[ -z 2 ]] 2025-08-26T23:45:28.0754212Z + [[ 2 == \1 ]] 2025-08-26T23:45:28.0754303Z + [[ -z 2 ]] 2025-08-26T23:45:28.0754383Z + [[ 2 == \2 ]] 2025-08-26T23:45:28.0754468Z + test_libtorch_jit 2025-08-26T23:45:28.0754556Z + pushd test 2025-08-26T23:45:28.0754770Z ~/pytorch/test ~/pytorch 2025-08-26T23:45:28.0754939Z + python cpp/jit/tests_setup.py setup 2025-08-26T23:45:29.0422252Z + popd 2025-08-26T23:45:29.0423684Z ~/pytorch 2025-08-26T23:45:29.0424114Z + [[ linux-noble-rocm-py3.12-mi300 == *cuda* ]] 2025-08-26T23:45:29.0424764Z + python test/run_test.py --cpp --verbose -i cpp/test_jit cpp/test_lazy -k 'not CUDA' 2025-08-26T23:45:30.5590183Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:45:30.5591615Z import pkg_resources 2025-08-26T23:45:31.3191891Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/pytorch/test/.pytorch-disabled-tests.json 2025-08-26T23:45:31.4797469Z Ignoring disabled issues: [''] 2025-08-26T23:45:31.4871407Z Found test times from artifacts 2025-08-26T23:45:31.5121658Z Found test times from artifacts 2025-08-26T23:45:31.5125407Z Running all tests 2025-08-26T23:45:31.5125885Z Running parallel tests on 1 processes 2025-08-26T23:45:31.5126606Z Name: tests to run (est. time: 0.0min) 2025-08-26T23:45:31.5126957Z Serial tests (2): 2025-08-26T23:45:31.5127228Z cpp/test_jit 1/1 2025-08-26T23:45:31.5127489Z cpp/test_lazy 1/1 2025-08-26T23:45:31.5134926Z Parallel tests (0): 2025-08-26T23:45:31.5135105Z Name: excluded (est. time: 0.0min) 2025-08-26T23:45:31.5135238Z Serial tests (0): 2025-08-26T23:45:31.5135351Z Parallel tests (0): 2025-08-26T23:45:31.5135507Z Running cpp/test_jit 1/1 ... [2025-08-26 23:45:31.512759] 2025-08-26T23:45:31.5135799Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:45:31.5136295Z Executing ['pytest', '/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin/test_jit', '-v', '-vv', '-rfEX', '-n', '1', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-4ee917a8c2b13b62.xml', '-k', 'not CUDA', '-x', '--reruns=2'] ... [2025-08-26 23:45:31.513096] 2025-08-26T23:45:32.2292947Z 2025-08-26T23:45:32.2294153Z cpp/test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_jit_1.1_ef51359adf3756ee_.log 2025-08-26T23:45:32.2294764Z 2025-08-26T23:45:32.2295044Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading 2025-08-26T23:45:32.2295559Z Uploading artifacts took 0.00 seconds 2025-08-26T23:45:32.2303648Z Running cpp/test_lazy 1/1 ... [2025-08-26 23:45:32.229216] 2025-08-26T23:45:32.2303889Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set 2025-08-26T23:45:32.2304583Z Executing ['pytest', '/opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin/test_lazy', '-v', '-vv', '-rfEX', '-n', '1', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-bb0124af39c5ae06.xml', '-k', 'not CUDA', '-x', '--reruns=2'] ... [2025-08-26 23:45:32.229536] 2025-08-26T23:45:32.6451873Z 2025-08-26T23:45:32.6452634Z cpp/test_lazy 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_lazy_1.1_e94339cd1df62a7f_.log 2025-08-26T23:45:32.6452900Z 2025-08-26T23:45:34.1154193Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:45:34.1155712Z import pkg_resources 2025-08-26T23:45:34.9341040Z Running test batch 'tests to run' cost 3.42 seconds 2025-08-26T23:45:35.5431140Z + pushd test 2025-08-26T23:45:35.5431624Z ~/pytorch/test ~/pytorch 2025-08-26T23:45:35.5432934Z + python cpp/jit/tests_setup.py shutdown 2025-08-26T23:45:36.3582447Z + popd 2025-08-26T23:45:36.3582756Z ~/pytorch 2025-08-26T23:45:36.3583012Z + assert_git_not_dirty 2025-08-26T23:45:36.3583723Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T23:45:36.3584189Z + test_aot_compilation 2025-08-26T23:45:36.3584504Z + echo 'Testing Ahead of Time compilation' 2025-08-26T23:45:36.3584869Z Testing Ahead of Time compilation 2025-08-26T23:45:36.3593666Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libc10_hip.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:36.3599466Z + ln -sf /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_hip.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/lib/libtorchbind_test.so /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin 2025-08-26T23:45:36.3615691Z + '[' -f /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin/test_mobile_nnc ']' 2025-08-26T23:45:36.3616027Z + '[' -f /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/bin/aot_model_compiler_test ']' 2025-08-26T23:45:36.3616239Z + test_custom_script_ops 2025-08-26T23:45:36.3616357Z + echo 'Testing custom script operators' 2025-08-26T23:45:36.3616482Z Testing custom script operators 2025-08-26T23:45:36.3616610Z + [[ linux-noble-rocm-py3.12-mi300 == *s390x* ]] 2025-08-26T23:45:36.3616813Z + CUSTOM_OP_BUILD=/var/lib/jenkins/pytorch/build/custom_test_artifacts/custom-op-build 2025-08-26T23:45:36.3617000Z + pushd test/custom_operator 2025-08-26T23:45:36.3617121Z ~/pytorch/test/custom_operator ~/pytorch 2025-08-26T23:45:36.3619324Z + cp -a /var/lib/jenkins/pytorch/build/custom_test_artifacts/custom-op-build build 2025-08-26T23:45:36.3699233Z + python test_custom_ops.py -v 2025-08-26T23:45:37.8652482Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:45:37.8672115Z import pkg_resources 2025-08-26T23:45:37.8941251Z Test results will be stored in test-reports/python-unittest/test_custom_ops 2025-08-26T23:45:37.8941405Z 2025-08-26T23:45:37.8942637Z Running tests... 2025-08-26T23:45:37.8981230Z ---------------------------------------------------------------------- 2025-08-26T23:45:38.2299672Z test_abstract_impl_pystub_faketensor (__main__.TestCustomOperators.test_abstract_impl_pystub_faketensor) ... /var/lib/jenkins/pytorch/test/custom_operator/my_custom_ops.py:13: FutureWarning: `create_unbacked_symint` is deprecated, please use `new_dynamic_size` instead 2025-08-26T23:45:38.2305755Z nnz = ctx.create_unbacked_symint() 2025-08-26T23:45:38.2342064Z ok (0.341s) 2025-08-26T23:45:38.2365627Z test_abstract_impl_pystub_meta (__main__.TestCustomOperators.test_abstract_impl_pystub_meta) ... ok (0.002s) 2025-08-26T23:45:38.2378133Z test_calling_custom_op (__main__.TestCustomOperators.test_calling_custom_op) ... ok (0.001s) 2025-08-26T23:45:38.2581060Z test_calling_custom_op_inside_script_module (__main__.TestCustomOperators.test_calling_custom_op_inside_script_module) ... ok (0.020s) 2025-08-26T23:45:38.2581719Z test_calling_custom_op_string (__main__.TestCustomOperators.test_calling_custom_op_string) ... ok (0.000s) 2025-08-26T23:45:38.2593462Z test_calling_custom_op_with_autograd (__main__.TestCustomOperators.test_calling_custom_op_with_autograd) ... /opt/conda/envs/py_3.12/lib/python3.12/site-packages/torch/autograd/graph.py:841: UserWarning: Using backward() with create_graph=True will create a reference cycle between the parameter and its gradient which can cause a memory leak. We recommend using autograd.grad when creating the graph to avoid this. If you have to use this function, make sure to reset the .grad fields of your parameters to None after use to break the cycle and avoid the leak. (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/autograd/engine.cpp:1291.) 2025-08-26T23:45:38.2594551Z return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass 2025-08-26T23:45:38.2599337Z ok (0.002s) 2025-08-26T23:45:38.2602911Z test_calling_custom_op_with_autograd_in_nograd_mode (__main__.TestCustomOperators.test_calling_custom_op_with_autograd_in_nograd_mode) ... ok (0.000s) 2025-08-26T23:45:38.2609191Z test_custom_library_is_loaded (__main__.TestCustomOperators.test_custom_library_is_loaded) ... ok (0.000s) 2025-08-26T23:45:38.2937711Z test_dynamo_pystub_suggestion (__main__.TestCustomOperators.test_dynamo_pystub_suggestion) ... ok (0.033s) 2025-08-26T23:45:38.2941738Z test_op_with_incorrect_abstract_impl_pystub (__main__.TestCustomOperators.test_op_with_incorrect_abstract_impl_pystub) ... ok (0.000s) 2025-08-26T23:45:38.2944581Z test_op_with_no_abstract_impl_pystub (__main__.TestCustomOperators.test_op_with_no_abstract_impl_pystub) ... ok (0.000s) 2025-08-26T23:45:38.2985783Z test_saving_and_loading_script_module_with_custom_op (__main__.TestCustomOperators.test_saving_and_loading_script_module_with_custom_op) ... ok (0.004s) 2025-08-26T23:45:38.2986025Z 2025-08-26T23:45:38.2986099Z ---------------------------------------------------------------------- 2025-08-26T23:45:38.2986250Z Ran 12 tests in 0.406s 2025-08-26T23:45:38.2986315Z 2025-08-26T23:45:38.2986351Z OK 2025-08-26T23:45:38.2986395Z 2025-08-26T23:45:38.2986446Z Generating XML reports... 2025-08-26T23:45:38.3005868Z Generated XML report: test-reports/python-unittest/test_custom_ops/TEST-TestCustomOperators-20250826234537.xml 2025-08-26T23:45:39.1618322Z + python model.py --export-script-module=model.pt 2025-08-26T23:45:39.9912864Z + build/test_custom_ops ./model.pt 2025-08-26T23:45:40.1671453Z [W826 23:45:40.214447603 engine.cpp:1291] Warning: Using backward() with create_graph=True will create a reference cycle between the parameter and its gradient which can cause a memory leak. We recommend using autograd.grad when creating the graph to avoid this. If you have to use this function, make sure to reset the .grad fields of your parameters to None after use to break the cycle and avoid the leak. (function operator()) 2025-08-26T23:45:40.3709484Z ok 2025-08-26T23:45:40.4635940Z + popd 2025-08-26T23:45:40.4636162Z ~/pytorch 2025-08-26T23:45:40.4636348Z + assert_git_not_dirty 2025-08-26T23:45:40.4643353Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T23:45:40.4643590Z + test_custom_backend 2025-08-26T23:45:40.4643780Z + echo 'Testing custom backends' 2025-08-26T23:45:40.4644010Z Testing custom backends 2025-08-26T23:45:40.4644343Z + CUSTOM_BACKEND_BUILD=/var/lib/jenkins/pytorch/build/custom_test_artifacts/custom-backend-build 2025-08-26T23:45:40.4644696Z + pushd test/custom_backend 2025-08-26T23:45:40.4644915Z ~/pytorch/test/custom_backend ~/pytorch 2025-08-26T23:45:40.4645262Z + cp -a /var/lib/jenkins/pytorch/build/custom_test_artifacts/custom-backend-build build 2025-08-26T23:45:40.4682283Z + python test_custom_backend.py -v 2025-08-26T23:45:41.9327405Z /opt/conda/envs/py_3.12/lib/python3.12/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T23:45:41.9333040Z import pkg_resources 2025-08-26T23:45:41.9452123Z Test results will be stored in test-reports/python-unittest/test_custom_backend 2025-08-26T23:45:41.9455394Z 2025-08-26T23:45:41.9455557Z Running tests... 2025-08-26T23:45:41.9455689Z ---------------------------------------------------------------------- 2025-08-26T23:45:41.9458293Z test_execute (__main__.TestCustomBackend.test_execute) 2025-08-26T23:45:41.9697665Z Test execution using the custom backend. ... ok (0.024s) 2025-08-26T23:45:41.9699612Z test_save_load (__main__.TestCustomBackend.test_save_load) 2025-08-26T23:45:41.9787913Z Test that a lowered module can be executed correctly ... ok (0.009s) 2025-08-26T23:45:41.9788626Z 2025-08-26T23:45:41.9789268Z ---------------------------------------------------------------------- 2025-08-26T23:45:41.9795242Z Ran 2 tests in 0.033s 2025-08-26T23:45:41.9795364Z 2025-08-26T23:45:41.9795415Z OK 2025-08-26T23:45:41.9795495Z 2025-08-26T23:45:41.9795570Z Generating XML reports... 2025-08-26T23:45:41.9802512Z Generated XML report: test-reports/python-unittest/test_custom_backend/TEST-TestCustomBackend-20250826234541.xml 2025-08-26T23:45:42.4250941Z + python backend.py --export-module-to=model.pt 2025-08-26T23:45:43.2819993Z + build/test_custom_backend ./model.pt 2025-08-26T23:45:43.4544595Z Testing custom_backend 2025-08-26T23:45:43.4793906Z OK 2025-08-26T23:45:43.5521225Z + rm -f ./model.pt 2025-08-26T23:45:43.5542421Z + popd 2025-08-26T23:45:43.5542894Z ~/pytorch 2025-08-26T23:45:43.5543055Z + assert_git_not_dirty 2025-08-26T23:45:43.5543244Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T23:45:43.5543441Z + test_torch_function_benchmark 2025-08-26T23:45:43.5543816Z + echo 'Testing __torch_function__ benchmarks' 2025-08-26T23:45:43.5544005Z Testing __torch_function__ benchmarks 2025-08-26T23:45:43.5544173Z + pushd benchmarks/overrides_benchmark 2025-08-26T23:45:43.5544364Z ~/pytorch/benchmarks/overrides_benchmark ~/pytorch 2025-08-26T23:45:43.5544568Z + python bench.py -n 1 -m 2 2025-08-26T23:45:44.1936182Z Type tensor had a minimum time of 0.0030994415283203125 us and a standard deviation of 0.5581928417086601 us. 2025-08-26T23:45:44.1937092Z Type SubTensor had a minimum time of 0.00667572021484375 us and a standard deviation of 0.03085149364778772 us. 2025-08-26T23:45:44.1937929Z Type WithTorchFunction had a minimum time of 0.0026226043701171875 us and a standard deviation of 0.004720447122963378 us. 2025-08-26T23:45:44.1938809Z Type SubWithTorchFunction had a minimum time of 0.003814697265625 us and a standard deviation of 0.0025288109100074507 us. 2025-08-26T23:45:44.3702162Z + python pyspybench.py Tensor -n 1 2025-08-26T23:45:45.1996347Z + python pyspybench.py SubTensor -n 1 2025-08-26T23:45:46.0986754Z + python pyspybench.py WithTorchFunction -n 1 2025-08-26T23:45:46.9208455Z + python pyspybench.py SubWithTorchFunction -n 1 2025-08-26T23:45:47.7979227Z + popd 2025-08-26T23:45:47.7979477Z ~/pytorch 2025-08-26T23:45:47.7979647Z + assert_git_not_dirty 2025-08-26T23:45:47.7979914Z + [[ linux-noble-rocm-py3.12-mi300 != *rocm* ]] 2025-08-26T23:45:47.7980207Z + sccache_epilogue 2025-08-26T23:45:47.7980635Z + echo '::group::Sccache Compilation Log' 2025-08-26T23:45:47.7981237Z ##[group]Sccache Compilation Log 2025-08-26T23:45:47.7981513Z + echo '=================== sccache compilation log ===================' 2025-08-26T23:45:47.7981814Z =================== sccache compilation log =================== 2025-08-26T23:45:47.7982236Z + python /var/lib/jenkins/pytorch/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log 2025-08-26T23:45:47.8061903Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ===========' 2025-08-26T23:45:47.8062308Z =========== If your build fails, please take a look at the log above for possible reasons =========== 2025-08-26T23:45:47.8062607Z + sccache --show-stats 2025-08-26T23:45:47.8083375Z Compile requests 8502 2025-08-26T23:45:47.8083608Z Compile requests executed 190 2025-08-26T23:45:47.8083790Z Cache hits 32 2025-08-26T23:45:47.8083970Z Cache hits (C/C++) 32 2025-08-26T23:45:47.8084141Z Cache misses 158 2025-08-26T23:45:47.8084324Z Cache misses (C/C++) 149 2025-08-26T23:45:47.8084500Z Cache misses (HIP) 9 2025-08-26T23:45:47.8084683Z Cache hits rate 16.84 % 2025-08-26T23:45:47.8085268Z Cache hits rate (C/C++) 17.68 % 2025-08-26T23:45:47.8085510Z Cache hits rate (HIP) 0.00 % 2025-08-26T23:45:47.8085691Z Cache timeouts 0 2025-08-26T23:45:47.8085875Z Cache read errors 0 2025-08-26T23:45:47.8086045Z Forced recaches 0 2025-08-26T23:45:47.8086227Z Cache write errors 0 2025-08-26T23:45:47.8086394Z Cache errors 0 2025-08-26T23:45:47.8086556Z Compilations 158 2025-08-26T23:45:47.8086730Z Compilation failures 0 2025-08-26T23:45:47.8086909Z Non-cacheable compilations 0 2025-08-26T23:45:47.8087081Z Non-cacheable calls 118 2025-08-26T23:45:47.8087322Z Non-compilation calls 8194 2025-08-26T23:45:47.8087496Z Unsupported compiler calls 0 2025-08-26T23:45:47.8087678Z Average cache write 0.000 s 2025-08-26T23:45:47.8087855Z Average compiler 3.370 s 2025-08-26T23:45:47.8088040Z Average cache read hit 0.000 s 2025-08-26T23:45:47.8088230Z Failed distributed compilations 0 2025-08-26T23:45:47.8088346Z 2025-08-26T23:45:47.8088409Z Non-cacheable reasons: 2025-08-26T23:45:47.8088643Z unknown source language 65 2025-08-26T23:45:47.8088812Z -E 53 2025-08-26T23:45:47.8088923Z 2025-08-26T23:45:47.8089057Z Cache location Local disk: "/var/lib/jenkins/.cache/sccache" 2025-08-26T23:45:47.8089309Z Use direct/preprocessor mode? yes 2025-08-26T23:45:47.8089469Z Version (client) 0.10.0 2025-08-26T23:45:47.8089634Z Cache size 24 MiB 2025-08-26T23:45:47.8089794Z Max cache size 10 GiB 2025-08-26T23:45:47.8089953Z + sccache --stop-server 2025-08-26T23:45:47.8096625Z Stopping sccache server... 2025-08-26T23:45:47.8098976Z Compile requests 8502 2025-08-26T23:45:47.8099320Z Compile requests executed 190 2025-08-26T23:45:47.8099522Z Cache hits 32 2025-08-26T23:45:47.8106298Z Cache hits (C/C++) 32 2025-08-26T23:45:47.8106477Z Cache misses 158 2025-08-26T23:45:47.8106705Z Cache misses (C/C++) 149 2025-08-26T23:45:47.8106934Z Cache misses (HIP) 9 2025-08-26T23:45:47.8107164Z Cache hits rate 16.84 % 2025-08-26T23:45:47.8107373Z Cache hits rate (C/C++) 17.68 % 2025-08-26T23:45:47.8107539Z Cache hits rate (HIP) 0.00 % 2025-08-26T23:45:47.8107689Z Cache timeouts 0 2025-08-26T23:45:47.8107833Z Cache read errors 0 2025-08-26T23:45:47.8107982Z Forced recaches 0 2025-08-26T23:45:47.8108135Z Cache write errors 0 2025-08-26T23:45:47.8110459Z Cache errors 0 2025-08-26T23:45:47.8110639Z Compilations 158 2025-08-26T23:45:47.8110790Z Compilation failures 0 2025-08-26T23:45:47.8110911Z Non-cacheable compilations 0 2025-08-26T23:45:47.8111027Z Non-cacheable calls 118 2025-08-26T23:45:47.8111139Z Non-compilation calls 8194 2025-08-26T23:45:47.8111256Z Unsupported compiler calls 0 2025-08-26T23:45:47.8111373Z Average cache write 0.000 s 2025-08-26T23:45:47.8111543Z Average compiler 3.370 s 2025-08-26T23:45:47.8111723Z Average cache read hit 0.000 s 2025-08-26T23:45:47.8111892Z Failed distributed compilations 0 2025-08-26T23:45:47.8113211Z 2025-08-26T23:45:47.8113257Z Non-cacheable reasons: 2025-08-26T23:45:47.8113362Z unknown source language 65 2025-08-26T23:45:47.8113475Z -E 53 2025-08-26T23:45:47.8113558Z 2025-08-26T23:45:47.8113632Z Cache location Local disk: "/var/lib/jenkins/.cache/sccache" 2025-08-26T23:45:47.8113792Z Use direct/preprocessor mode? yes 2025-08-26T23:45:47.8114142Z Version (client) 0.10.0 2025-08-26T23:45:47.8114313Z Cache size 24 MiB 2025-08-26T23:45:47.8114433Z Max cache size 10 GiB 2025-08-26T23:45:47.8114570Z + echo ::endgroup:: 2025-08-26T23:45:47.8114861Z ##[endgroup] 2025-08-26T23:45:47.8188754Z ##[group]Run # copy test results back to the mounted workspace, needed sudo, resulting permissions were correct 2025-08-26T23:45:47.8189064Z # copy test results back to the mounted workspace, needed sudo, resulting permissions were correct 2025-08-26T23:45:47.8189431Z docker exec -t "96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8" sh -c "cd ../pytorch && sudo cp -R test/test-reports ../workspace/test" 2025-08-26T23:45:47.8195154Z shell: /usr/bin/bash -e {0} 2025-08-26T23:45:47.8195262Z env: 2025-08-26T23:45:47.8195353Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:47.8195481Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:47.8195653Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:47.8195816Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:47.8196208Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:47.8196560Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:47.8196669Z AWS_REGION: us-east-1 2025-08-26T23:45:47.8196828Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:47.8196970Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:47.8199147Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:47.8199436Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:47.8199626Z ##[endgroup] 2025-08-26T23:45:47.9084151Z ##[group]Run docker exec -t "96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8" sh -c "sudo chown -R 1001:1001 test" 2025-08-26T23:45:47.9084546Z docker exec -t "96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8" sh -c "sudo chown -R 1001:1001 test" 2025-08-26T23:45:47.9090150Z shell: /usr/bin/bash -e {0} 2025-08-26T23:45:47.9090260Z env: 2025-08-26T23:45:47.9090573Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:47.9090707Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:47.9090882Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:47.9091047Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:47.9091418Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:47.9091824Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:47.9091940Z AWS_REGION: us-east-1 2025-08-26T23:45:47.9092102Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:47.9092249Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:47.9096419Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:47.9096602Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:47.9096778Z ##[endgroup] 2025-08-26T23:45:47.9972433Z ##[group]Run cat test/**/*_toprint.log || true 2025-08-26T23:45:47.9972603Z cat test/**/*_toprint.log || true 2025-08-26T23:45:47.9977807Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:47.9977952Z env: 2025-08-26T23:45:47.9978047Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:47.9978183Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:47.9978353Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:47.9978517Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:47.9978900Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:47.9979261Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:47.9979461Z AWS_REGION: us-east-1 2025-08-26T23:45:47.9979628Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:47.9979795Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:47.9982007Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:47.9982175Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:47.9982350Z ##[endgroup] 2025-08-26T23:45:48.0054416Z cat: 'test/**/*_toprint.log': No such file or directory 2025-08-26T23:45:48.0130819Z Prepare all required actions 2025-08-26T23:45:48.0131135Z Getting action download info 2025-08-26T23:45:48.2321189Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-08-26T23:45:48.6620685Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-08-26T23:45:49.0812321Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-08-26T23:45:49.0812562Z with: 2025-08-26T23:45:49.0812701Z use-gha: true 2025-08-26T23:45:49.0812942Z file-suffix: test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439 2025-08-26T23:45:49.0813245Z s3-bucket: gha-artifacts 2025-08-26T23:45:49.0813413Z env: 2025-08-26T23:45:49.0813551Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:49.0813764Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:49.0814050Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:49.0814338Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:49.0814979Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:49.0815606Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:49.0815785Z AWS_REGION: us-east-1 2025-08-26T23:45:49.0816017Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:49.0816245Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:49.0819989Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:49.0820266Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:49.0820772Z ##[endgroup] 2025-08-26T23:45:49.0921883Z ##[group]Run actions/upload-artifact@v4 2025-08-26T23:45:49.0922064Z with: 2025-08-26T23:45:49.0922316Z name: test-jsons-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip 2025-08-26T23:45:49.0922525Z retention-days: 14 2025-08-26T23:45:49.0922632Z if-no-files-found: warn 2025-08-26T23:45:49.0924817Z path: test/**/*.json 2025-08-26T23:45:49.0924927Z compression-level: 6 2025-08-26T23:45:49.0925021Z overwrite: false 2025-08-26T23:45:49.0925117Z include-hidden-files: false 2025-08-26T23:45:49.0925222Z env: 2025-08-26T23:45:49.0925306Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:49.0925434Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:49.0925603Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:49.0925758Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:49.0926132Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:49.0926486Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:49.0928376Z AWS_REGION: us-east-1 2025-08-26T23:45:49.0928514Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:49.0928658Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:49.0930860Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:49.0931025Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:49.0931200Z ##[endgroup] 2025-08-26T23:45:49.4782121Z With the provided path, there will be 7 files uploaded 2025-08-26T23:45:49.4785355Z Artifact name is valid! 2025-08-26T23:45:49.4786169Z Root directory input is valid! 2025-08-26T23:45:49.5754118Z Beginning upload of artifact content to blob storage 2025-08-26T23:45:49.8602156Z Uploaded bytes 45935 2025-08-26T23:45:49.9131744Z Finished uploading artifact content to blob storage! 2025-08-26T23:45:49.9132727Z SHA256 digest of uploaded artifact zip is 5dc2afd32043b897773f4ec0c47f1cad0dc384f95292f7090de0e750470350c8 2025-08-26T23:45:49.9133677Z Finalizing artifact upload 2025-08-26T23:45:50.0005208Z Artifact test-jsons-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip.zip successfully finalized. Artifact ID 3858801037 2025-08-26T23:45:50.0015132Z Artifact test-jsons-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip has been successfully uploaded! Final size is 45935 bytes. Artifact ID is 3858801037 2025-08-26T23:45:50.0015988Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/17248463563/artifacts/3858801037 2025-08-26T23:45:50.0140320Z ##[group]Run actions/upload-artifact@v4 2025-08-26T23:45:50.0140861Z with: 2025-08-26T23:45:50.0141044Z name: test-reports-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip 2025-08-26T23:45:50.0141255Z retention-days: 14 2025-08-26T23:45:50.0141360Z if-no-files-found: ignore 2025-08-26T23:45:50.0141475Z path: test/**/*.xml test/**/*.csv 2025-08-26T23:45:50.0141592Z compression-level: 6 2025-08-26T23:45:50.0141693Z overwrite: false 2025-08-26T23:45:50.0141793Z include-hidden-files: false 2025-08-26T23:45:50.0141902Z env: 2025-08-26T23:45:50.0141989Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:50.0142134Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:50.0142307Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:50.0142466Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:50.0142852Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:50.0143210Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:50.0143321Z AWS_REGION: us-east-1 2025-08-26T23:45:50.0143486Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:50.0143635Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:50.0145663Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:50.0145833Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:50.0146010Z ##[endgroup] 2025-08-26T23:45:50.4454870Z With the provided path, there will be 109 files uploaded 2025-08-26T23:45:50.4456307Z Artifact name is valid! 2025-08-26T23:45:50.4458356Z Root directory input is valid! 2025-08-26T23:45:50.5478277Z Beginning upload of artifact content to blob storage 2025-08-26T23:45:50.8926062Z Uploaded bytes 621916 2025-08-26T23:45:50.9254365Z Finished uploading artifact content to blob storage! 2025-08-26T23:45:50.9255825Z SHA256 digest of uploaded artifact zip is 9692ba441e786c67bf299567a1eb791758da140731c83dd8e2eebca599f0eb62 2025-08-26T23:45:50.9256272Z Finalizing artifact upload 2025-08-26T23:45:51.0181110Z Artifact test-reports-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip.zip successfully finalized. Artifact ID 3858801111 2025-08-26T23:45:51.0181868Z Artifact test-reports-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip has been successfully uploaded! Final size is 621916 bytes. Artifact ID is 3858801111 2025-08-26T23:45:51.0189259Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/17248463563/artifacts/3858801111 2025-08-26T23:45:51.0351848Z ##[group]Run actions/upload-artifact@v4 2025-08-26T23:45:51.0352079Z with: 2025-08-26T23:45:51.0352345Z name: logs-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip 2025-08-26T23:45:51.0352668Z retention-days: 14 2025-08-26T23:45:51.0352839Z if-no-files-found: ignore 2025-08-26T23:45:51.0353029Z path: usage_log.txt test/**/*.log 2025-08-26T23:45:51.0353226Z compression-level: 6 2025-08-26T23:45:51.0356087Z overwrite: false 2025-08-26T23:45:51.0356257Z include-hidden-files: false 2025-08-26T23:45:51.0356578Z env: 2025-08-26T23:45:51.0356719Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:51.0356935Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:51.0357227Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:51.0357500Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:51.0358260Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:51.0358874Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:51.0359059Z AWS_REGION: us-east-1 2025-08-26T23:45:51.0362177Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:51.0362421Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:51.0366153Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:51.0366430Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:51.0366732Z ##[endgroup] 2025-08-26T23:45:51.4685045Z Multiple search paths detected. Calculating the least common ancestor of all paths 2025-08-26T23:45:51.4685529Z The least common ancestor is /home/runner/_work/pytorch/pytorch. This will be the root directory of the artifact 2025-08-26T23:45:51.4685780Z With the provided path, there will be 94 files uploaded 2025-08-26T23:45:51.4686935Z Artifact name is valid! 2025-08-26T23:45:51.4687166Z Root directory input is valid! 2025-08-26T23:45:51.5704220Z Beginning upload of artifact content to blob storage 2025-08-26T23:45:51.9233089Z Uploaded bytes 948987 2025-08-26T23:45:51.9521535Z Finished uploading artifact content to blob storage! 2025-08-26T23:45:51.9530108Z SHA256 digest of uploaded artifact zip is 77ab6abf87723c7aba0f445ec5d0a0febb1a923e54793f60c9c9674675cf2869 2025-08-26T23:45:51.9530499Z Finalizing artifact upload 2025-08-26T23:45:52.0630162Z Artifact logs-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip.zip successfully finalized. Artifact ID 3858801179 2025-08-26T23:45:52.0631792Z Artifact logs-runattempt1-test-default-2-6-linux.rocm.gpu.gfx942.1_48946667439.zip has been successfully uploaded! Final size is 948987 bytes. Artifact ID is 3858801179 2025-08-26T23:45:52.0634959Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/17248463563/artifacts/3858801179 2025-08-26T23:45:52.0786651Z ##[group]Run # shellcheck disable=SC2156 2025-08-26T23:45:52.0786840Z # shellcheck disable=SC2156 2025-08-26T23:45:52.0787080Z find . -iname "core.[1-9]*" -exec docker exec "${CONTAINER_NAME}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-08-26T23:45:52.0795362Z shell: /usr/bin/bash -e {0} 2025-08-26T23:45:52.0795509Z env: 2025-08-26T23:45:52.0795604Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:52.0795768Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:52.0795951Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:52.0796119Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:52.0796512Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:52.0796877Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:52.0797006Z AWS_REGION: us-east-1 2025-08-26T23:45:52.0799362Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:52.0799531Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:52.0801668Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:52.0801845Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:52.0802028Z ##[endgroup] 2025-08-26T23:45:52.2450890Z ##[group]Run aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 2025-08-26T23:45:52.2451095Z with: 2025-08-26T23:45:52.2451255Z role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_upload-benchmark-results 2025-08-26T23:45:52.2451447Z role-duration-seconds: 18000 2025-08-26T23:45:52.2451641Z aws-region: us-east-1 2025-08-26T23:45:52.2451752Z audience: sts.amazonaws.com 2025-08-26T23:45:52.2451864Z env: 2025-08-26T23:45:52.2451954Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:52.2453963Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:52.2454152Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:52.2454319Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:52.2454713Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:52.2455141Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:52.2455257Z AWS_REGION: us-east-1 2025-08-26T23:45:52.2455398Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:52.2455552Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:52.2457598Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:52.2459522Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:52.2459704Z ##[endgroup] 2025-08-26T23:45:52.4303217Z Assuming role with OIDC 2025-08-26T23:45:52.5661046Z Authenticated as assumedRoleId AROAUPVRELQNA5GQHA6IA:GitHubActions 2025-08-26T23:45:52.6165599Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main 2025-08-26T23:45:52.6165896Z with: 2025-08-26T23:45:52.6166060Z benchmark-results-dir: test/test-reports 2025-08-26T23:45:52.6166263Z dry-run: false 2025-08-26T23:45:52.6166416Z schema-version: v3 2025-08-26T23:45:52.6166747Z github-token: *** 2025-08-26T23:45:52.6166847Z env: 2025-08-26T23:45:52.6166958Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:52.6167103Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:52.6167294Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:52.6167466Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:52.6167866Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:52.6168249Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:52.6168375Z AWS_REGION: us-east-1 2025-08-26T23:45:52.6168502Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:52.6168658Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:52.6170712Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:52.6170895Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:52.6171084Z ##[endgroup] 2025-08-26T23:45:52.6181371Z ##[group]Run set -eux 2025-08-26T23:45:52.6181564Z set -eux 2025-08-26T23:45:52.6181797Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-08-26T23:45:52.6182059Z  2025-08-26T23:45:52.6182208Z DEVICE_NAME="" 2025-08-26T23:45:52.6182381Z DEVICE_TYPE="" 2025-08-26T23:45:52.6182550Z  2025-08-26T23:45:52.6182710Z if command -v nvidia-smi; then 2025-08-26T23:45:52.6182986Z  # NB: I'm using PyTorch here to get the device name, however, it needs to 2025-08-26T23:45:52.6183330Z  # install the correct version of PyTorch manually for now. Any PyTorch 2025-08-26T23:45:52.6183620Z  # version is fine, I just use 2.7.1 to satify PYPIDEP linter 2025-08-26T23:45:52.6183793Z  python3 -mpip install torch==2.7.1 2025-08-26T23:45:52.6188096Z elif command -v rocminfo; then 2025-08-26T23:45:52.6188279Z  # NB: Installing torch on ROCm runner with pip here causes CI to fail 2025-08-26T23:45:52.6188499Z  # with a memoryview is too large error only on MI300 runners. Is pip 2025-08-26T23:45:52.6188714Z  # version on ROCm runner there too old? As a workaround, let's use the 2025-08-26T23:45:52.6188909Z  # GPU device name coming from rocminfo instead 2025-08-26T23:45:52.6189148Z  DEVICE_NAME=rocm 2025-08-26T23:45:52.6189347Z  DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs) 2025-08-26T23:45:52.6189534Z fi 2025-08-26T23:45:52.6189634Z  2025-08-26T23:45:52.6189756Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV 2025-08-26T23:45:52.6189922Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-08-26T23:45:52.6195784Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:52.6195938Z env: 2025-08-26T23:45:52.6196037Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:52.6196224Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:52.6196591Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:52.6196807Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:52.6197346Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:52.6197894Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:52.6198021Z AWS_REGION: us-east-1 2025-08-26T23:45:52.6198159Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:52.6198390Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:52.6200499Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:52.6200676Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:52.6200861Z ##[endgroup] 2025-08-26T23:45:52.6225056Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-08-26T23:45:52.7650739Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T23:45:53.2337801Z Collecting boto3==1.35.33 2025-08-26T23:45:53.3500233Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-08-26T23:45:53.4023214Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 2.6 MB/s eta 0:00:00 2025-08-26T23:45:53.4949784Z Collecting psutil==7.0.0 2025-08-26T23:45:53.5179308Z Downloading psutil-7.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (277 kB) 2025-08-26T23:45:53.5452071Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 10.4 MB/s eta 0:00:00 2025-08-26T23:45:53.5803117Z Collecting pynvml==12.0.0 2025-08-26T23:45:53.6024580Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-08-26T23:45:53.9487233Z Collecting botocore<1.36.0,>=1.35.33 2025-08-26T23:45:53.9719011Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-08-26T23:45:54.0943442Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 158.5 MB/s eta 0:00:00 2025-08-26T23:45:54.1462081Z Collecting s3transfer<0.11.0,>=0.10.0 2025-08-26T23:45:54.1695248Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-08-26T23:45:54.1715491Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 35.9 MB/s eta 0:00:00 2025-08-26T23:45:54.2055466Z Collecting jmespath<2.0.0,>=0.7.1 2025-08-26T23:45:54.2275261Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-08-26T23:45:54.2747639Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-08-26T23:45:54.2966803Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-08-26T23:45:54.2996175Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 20.0 MB/s eta 0:00:00 2025-08-26T23:45:54.3381209Z Collecting python-dateutil<3.0.0,>=2.1 2025-08-26T23:45:54.3602975Z Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl (229 kB) 2025-08-26T23:45:54.3633459Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 229.9/229.9 KB 110.9 MB/s eta 0:00:00 2025-08-26T23:45:54.3646273Z Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /home/runner/.local/lib/python3.10/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.26.20) 2025-08-26T23:45:54.4215279Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.16.0) 2025-08-26T23:45:54.4886520Z Installing collected packages: nvidia-ml-py, python-dateutil, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-08-26T23:45:54.8425868Z Successfully installed boto3-1.35.33 botocore-1.35.99 jmespath-1.0.1 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 python-dateutil-2.9.0.post0 s3transfer-0.10.4 2025-08-26T23:45:54.9093292Z + DEVICE_NAME= 2025-08-26T23:45:54.9093524Z /usr/bin/rocminfo 2025-08-26T23:45:54.9093772Z + DEVICE_TYPE= 2025-08-26T23:45:54.9094008Z + command -v nvidia-smi 2025-08-26T23:45:54.9094243Z + command -v rocminfo 2025-08-26T23:45:54.9094473Z + DEVICE_NAME=rocm 2025-08-26T23:45:54.9104216Z ++ rocminfo 2025-08-26T23:45:54.9104662Z ++ grep 'Marketing Name' 2025-08-26T23:45:54.9105061Z ++ tail -n1 2025-08-26T23:45:54.9105367Z ++ awk -F: '{print $2}' 2025-08-26T23:45:54.9105699Z ++ xargs 2025-08-26T23:45:54.9783694Z + DEVICE_TYPE='AMD Instinct Mi325X VF' 2025-08-26T23:45:54.9784225Z + echo DEVICE_NAME=rocm 2025-08-26T23:45:54.9784612Z + echo 'DEVICE_TYPE=AMD Instinct Mi325X VF' 2025-08-26T23:45:54.9817599Z ##[group]Run set -eux 2025-08-26T23:45:54.9817752Z set -eux 2025-08-26T23:45:54.9817873Z  2025-08-26T23:45:54.9818006Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-08-26T23:45:54.9818312Z  echo "Missing github-token input" 2025-08-26T23:45:54.9818468Z  exit 1 2025-08-26T23:45:54.9820857Z fi 2025-08-26T23:45:54.9826224Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:54.9826379Z env: 2025-08-26T23:45:54.9826483Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:54.9826628Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:54.9826829Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:54.9827004Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:54.9827392Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:54.9829656Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:54.9829789Z AWS_REGION: us-east-1 2025-08-26T23:45:54.9829961Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:54.9830127Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:54.9832208Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:54.9832394Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:54.9832580Z DEVICE_NAME: rocm 2025-08-26T23:45:54.9832692Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:54.9834658Z GITHUB_TOKEN: *** 2025-08-26T23:45:54.9834776Z ##[endgroup] 2025-08-26T23:45:54.9862566Z + [[ -z *** ]] 2025-08-26T23:45:54.9908711Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-08-26T23:45:54.9908909Z with: 2025-08-26T23:45:54.9911249Z github-token: *** 2025-08-26T23:45:54.9911368Z env: 2025-08-26T23:45:54.9911471Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:54.9911634Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:54.9911833Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:54.9912012Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:54.9912421Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:54.9912799Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:54.9912929Z AWS_REGION: us-east-1 2025-08-26T23:45:54.9914824Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:54.9915107Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:54.9917104Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:54.9917291Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:54.9917479Z DEVICE_NAME: rocm 2025-08-26T23:45:54.9917592Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:54.9917798Z ##[endgroup] 2025-08-26T23:45:54.9932346Z ##[group]Run set -eux 2025-08-26T23:45:54.9932473Z set -eux 2025-08-26T23:45:54.9932572Z  2025-08-26T23:45:54.9932770Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-08-26T23:45:54.9940812Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:54.9940968Z env: 2025-08-26T23:45:54.9941065Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:54.9941211Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:54.9941401Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:54.9941579Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:54.9941969Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:54.9942344Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:54.9944482Z AWS_REGION: us-east-1 2025-08-26T23:45:54.9944623Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:54.9944782Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:54.9946763Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:54.9947087Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:54.9947275Z DEVICE_NAME: rocm 2025-08-26T23:45:54.9947390Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:54.9947572Z GITHUB_TOKEN: *** 2025-08-26T23:45:54.9949511Z ##[endgroup] 2025-08-26T23:45:54.9974218Z + python3 /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17248463563 linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln 2025-08-26T23:45:55.5372459Z setting job-id=48946667439 2025-08-26T23:45:55.5373120Z setting job-name=linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T23:45:55.5451570Z ##[group]Run set -eux 2025-08-26T23:45:55.5451730Z set -eux 2025-08-26T23:45:55.5451837Z  2025-08-26T23:45:55.5452009Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-08-26T23:45:55.5452241Z  --schema-version "${SCHEMA_VERSION}" \ 2025-08-26T23:45:55.5454829Z  --repo "${REPO}" \ 2025-08-26T23:45:55.5454974Z  --head-branch "${HEAD_BRANCH}" \ 2025-08-26T23:45:55.5455117Z  --head-sha "${HEAD_SHA}" \ 2025-08-26T23:45:55.5455264Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-08-26T23:45:55.5455415Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-08-26T23:45:55.5455551Z  --job-id "${JOB_ID}" \ 2025-08-26T23:45:55.5455693Z  --job-name "${JOB_NAME}" 2025-08-26T23:45:55.5461476Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:55.5463823Z env: 2025-08-26T23:45:55.5463931Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.5464079Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.5464272Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.5464447Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.5464843Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.5465214Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.5465344Z AWS_REGION: us-east-1 2025-08-26T23:45:55.5467395Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.5467566Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.5469684Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.5469869Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.5470054Z DEVICE_NAME: rocm 2025-08-26T23:45:55.5470165Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.5470293Z SCHEMA_VERSION: v3 2025-08-26T23:45:55.5470580Z REPO: pytorch/pytorch 2025-08-26T23:45:55.5470693Z HEAD_BRANCH: refs/heads/main 2025-08-26T23:45:55.5472644Z HEAD_SHA: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T23:45:55.5472793Z WORKFLOW_RUN_ID: 17248463563 2025-08-26T23:45:55.5472916Z RUN_ATTEMPT: 1 2025-08-26T23:45:55.5473017Z JOB_ID: 48946667439 2025-08-26T23:45:55.5473194Z JOB_NAME: linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1) 2025-08-26T23:45:55.5473386Z ##[endgroup] 2025-08-26T23:45:55.5497345Z + python3 /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 262640fd220236042fbf4443cc163c8838c84c3d --workflow-id 17248463563 --run-attempt 1 --job-id 48946667439 --job-name 'linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1)' 2025-08-26T23:45:55.5659526Z ##[group]Run set -eux 2025-08-26T23:45:55.5659656Z set -eux 2025-08-26T23:45:55.5659756Z  2025-08-26T23:45:55.5659925Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-08-26T23:45:55.5665944Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:55.5666103Z env: 2025-08-26T23:45:55.5666203Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.5666351Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.5666540Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.5666715Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.5667106Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.5667491Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.5667616Z AWS_REGION: us-east-1 2025-08-26T23:45:55.5669501Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.5669662Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.5671764Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.5671947Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.5672140Z DEVICE_NAME: rocm 2025-08-26T23:45:55.5672253Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.5672382Z ##[endgroup] 2025-08-26T23:45:55.5699074Z + python3 /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-08-26T23:45:55.5907757Z INFO:root:Fail to import torch to get the device name 2025-08-26T23:45:55.5970643Z ##[group]Run set -eux 2025-08-26T23:45:55.5974168Z set -eux 2025-08-26T23:45:55.5974288Z  2025-08-26T23:45:55.5974407Z # TODO (huydhn): Implement this part 2025-08-26T23:45:55.5974571Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-08-26T23:45:55.5980136Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:55.5980296Z env: 2025-08-26T23:45:55.5980517Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.5980668Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.5983200Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.5983380Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.5983769Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.5984253Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.5984380Z AWS_REGION: us-east-1 2025-08-26T23:45:55.5984558Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.5984717Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.5986742Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.5986928Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.5989180Z DEVICE_NAME: rocm 2025-08-26T23:45:55.5989296Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.5989430Z ##[endgroup] 2025-08-26T23:45:55.6006649Z + echo 'dependencies={}' 2025-08-26T23:45:55.6030448Z ##[group]Run set -eux 2025-08-26T23:45:55.6030598Z set -eux 2025-08-26T23:45:55.6030699Z  2025-08-26T23:45:55.6030824Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-08-26T23:45:55.6031019Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-08-26T23:45:55.6031212Z  # We don't want the job to fail if the directory doesn't exist 2025-08-26T23:45:55.6031371Z  exit 0 2025-08-26T23:45:55.6033902Z fi 2025-08-26T23:45:55.6034004Z  2025-08-26T23:45:55.6034111Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-08-26T23:45:55.6034308Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-08-26T23:45:55.6034545Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-08-26T23:45:55.6034719Z  --metadata "${BENCHMARK_METADATA}" \ 2025-08-26T23:45:55.6034866Z  --runners "${RUNNER_INFO}" \ 2025-08-26T23:45:55.6035171Z  --dependencies "${DEPENDENCIES}" \ 2025-08-26T23:45:55.6035310Z  --dry-run 2025-08-26T23:45:55.6035418Z else 2025-08-26T23:45:55.6035573Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-08-26T23:45:55.6037590Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-08-26T23:45:55.6037758Z  --metadata "${BENCHMARK_METADATA}" \ 2025-08-26T23:45:55.6037907Z  --runners "${RUNNER_INFO}" \ 2025-08-26T23:45:55.6038046Z  --dependencies "${DEPENDENCIES}" 2025-08-26T23:45:55.6038174Z fi 2025-08-26T23:45:55.6043833Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:55.6043988Z env: 2025-08-26T23:45:55.6044089Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.6046120Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.6046309Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.6046488Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.6046873Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.6047245Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.6047370Z AWS_REGION: us-east-1 2025-08-26T23:45:55.6047546Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.6047703Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.6051432Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.6051622Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.6051807Z DEVICE_NAME: rocm 2025-08-26T23:45:55.6051922Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.6052062Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-08-26T23:45:55.6052195Z DRY_RUN: false 2025-08-26T23:45:55.6052661Z BENCHMARK_METADATA: {"timestamp": 1756251955, "schema_version": "v3", "name": "linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "262640fd220236042fbf4443cc163c8838c84c3d", "workflow_id": 17248463563, "run_attempt": 1, "job_id": 48946667439} 2025-08-26T23:45:55.6053314Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 160, "avail_mem_in_gb": 1255, "extra_info": {"hostname": "linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln"}, "name": "rocm", "type": "AMD Instinct Mi325X VF"}] 2025-08-26T23:45:55.6053692Z DEPENDENCIES: {} 2025-08-26T23:45:55.6055380Z ##[endgroup] 2025-08-26T23:45:55.6075678Z + [[ ! -d test/test-reports ]] 2025-08-26T23:45:55.6075841Z + [[ false == \t\r\u\e ]] 2025-08-26T23:45:55.6076964Z + python3 /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1756251955, "schema_version": "v3", "name": "linux-noble-rocm-py3.12-mi300 / test (default, 2, 6, linux.rocm.gpu.gfx942.1)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "262640fd220236042fbf4443cc163c8838c84c3d", "workflow_id": 17248463563, "run_attempt": 1, "job_id": 48946667439}' --runners '[{"cpu_info": "x86_64", "cpu_count": 160, "avail_mem_in_gb": 1255, "extra_info": {"hostname": "linux.rocm.gpu.gfx942.1-ccq8d-runner-pb9ln"}, "name": "rocm", "type": "AMD Instinct Mi325X VF"}]' --dependencies '{}' 2025-08-26T23:45:55.6696446Z /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/test_jit'}, {'test_file': 'cpp/test_lazy'}], 'excluded': []} from test/test-reports/td_exclusions-fd98125671b313b30c66.json is not a benchmark record, skipping 2025-08-26T23:45:55.6697765Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T23:45:55.6720848Z /home/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'inductor/test_flex_attention'}, {'test_file': 'inductor/test_max_autotune'}, {'test_file': 'inductor/test_aot_inductor'}, {'test_file': 'inductor/test_flex_decoding'}, {'test_file': 'inductor/test_aot_inductor_arrayref'}, {'test_file': 'inductor/test_perf'}, {'test_file': 'inductor/test_torchinductor'}, {'test_file': 'inductor/test_compiled_autograd'}, {'test_file': 'inductor/test_torchinductor_opinfo'}, {'test_file': 'inductor/test_torchinductor_dynamic_shapes'}, {'test_file': 'inductor/test_inplace_padding'}, {'test_file': 'dynamo/test_fx_graph_runnable'}, {'test_file': 'inductor/test_halide'}, {'test_file': 'inductor/test_snode_runtime'}, {'test_file': 'export/test_export_training_ir_to_run_decomp'}, {'test_file': 'inductor/test_fused_attention'}, {'test_file': 'inductor/test_extension_backend'}, {'test_file': 'inductor/test_pattern_matcher'}, {'test_file': 'dynamo/test_ctx_manager'}, {'test_file': 'inductor/test_mps_basic'}, {'test_file': 'inductor/test_kernel_benchmark'}, {'test_file': 'dynamo/test_backends'}, {'test_file': 'dynamo/test_decorators'}, {'test_file': 'test_model_exports_to_core_aten'}, {'test_file': 'inductor/test_provenance_tracing'}, {'test_file': 'inductor/test_torchinductor_codegen_dynamic_shapes'}, {'test_file': 'inductor/test_codecache'}, {'test_file': 'inductor/test_analysis'}, {'test_file': 'inductor/test_torchinductor_strided_blocks'}, {'test_file': 'inductor/test_memory_planning'}, {'test_file': 'inductor/test_triton_cpu_backend'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'inductor/test_best_config'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'inductor/test_triton_heuristics'}, {'test_file': 'inductor/test_cpu_repro'}, {'test_file': 'inductor/test_cudacodecache'}, {'test_file': 'dynamo/test_structured_trace'}, {'test_file': 'inductor/test_async_compile'}, {'test_file': 'inductor/test_padding'}, {'test_file': 'inductor/test_indexing'}, {'test_file': 'inductor/test_triton_kernels'}, {'test_file': 'inductor/test_control_flow'}, {'test_file': 'inductor/test_fxir_backend'}, {'test_file': 'dynamo/test_base_hop'}, {'test_file': 'inductor/test_compiled_optimizers'}, {'test_file': 'inductor/test_select_algorithm'}, {'test_file': 'inductor/test_compile_subprocess'}, {'test_file': 'dynamo/test_repros'}, {'test_file': 'inductor/test_compile_worker'}, {'test_file': 'inductor/test_triton_extension_backend'}, {'test_file': 'dynamo/test_callback'}, {'test_file': 'dynamo/test_einops'}, {'test_file': 'dynamo/test_misc'}, {'test_file': 'export/test_export_with_inline_and_install'}, {'test_file': 'export/test_functionalized_assertions'}, {'test_file': 'dynamo/test_exceptions'}, {'test_file': 'dynamo/test_generator'}, {'test_file': 'dynamo/test_utils'}, {'test_file': 'dynamo/test_recompiles'}, {'test_file': 'inductor/test_mkldnn_pattern_matcher'}, {'test_file': 'dynamo/test_higher_order_ops'}, {'test_file': 'nn/test_multihead_attention'}, {'test_file': 'inductor/test_loop_ordering'}, {'test_file': 'inductor/test_inductor_scheduler'}, {'test_file': 'inductor/test_scatter_optimization'}, {'test_file': 'dynamo/test_compiler_bisector'}, {'test_file': 'export/test_converter'}, {'test_file': 'inductor/test_inductor_freezing'}, {'test_file': 'dynamo/test_modules'}, {'test_file': 'inductor/test_cudagraph_trees'}, {'test_file': 'dynamo/test_unittest'}, {'test_file': 'inductor/test_cutlass_backend'}, {'test_file': 'inductor/test_aot_inductor_custom_ops'}, {'test_file': 'inductor/test_aot_inductor_package'}, {'test_file': 'inductor/test_cuda_repro'}, {'test_file': 'inductor/test_multi_kernel'}, {'test_file': 'inductor/test_auto_functionalize'}, {'test_file': 'inductor/test_cpu_select_algorithm'}, {'test_file': 'dynamo/test_cudagraphs_expandable_segments'}, {'test_file': 'inductor/test_cudagraph_trees_expandable_segments'}, {'test_file': 'inductor/test_fp8'}, {'test_file': 'inductor/test_group_batch_fusion'}, {'test_file': 'inductor/test_mmdecomp'}, {'test_file': 'inductor/test_ordered_set'}, {'test_file': 'inductor/test_pad_mm'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'dynamo/test_subclasses'}, {'test_file': 'inductor/test_triton_syntax'}, {'test_file': 'inductor/test_profiler'}, {'test_file': 'inductor/test_benchmark_fusion'}, {'test_file': 'inductor/test_ck_backend'}, {'test_file': 'inductor/test_debug_trace'}, {'test_file': 'inductor/test_distributed_patterns'}, {'test_file': 'inductor/test_external_callables'}, {'test_file': 'inductor/test_gpu_cpp_wrapper'}, {'test_file': 'inductor/test_metrics'}, {'test_file': 'inductor/test_minifier'}, {'test_file': 'inductor/test_utils'}, {'test_file': 'export/test_draft_export'}, {'test_file': 'export/test_passes'}, {'test_file': 'inductor/test_inplacing_pass'}, {'test_file': 'dynamo/test_aot_autograd'}, {'test_file': 'dynamo/test_autograd_function'}, {'test_file': 'dynamo/test_pre_dispatch'}, {'test_file': 'dynamo/test_export'}, {'test_file': 'dynamo/test_functions'}, {'test_file': 'dynamo/test_python_autograd'}, {'test_file': 'dynamo/test_reconstruct'}, {'test_file': 'dynamo/test_trace_rules'}, {'test_file': 'export/test_lift_unlift'}, {'test_file': 'inductor/test_cooperative_reductions'}, {'test_file': 'inductor/test_fuzzer'}, {'test_file': 'inductor/test_torchinductor_codegen_config_overrides'}, {'test_file': 'export/test_experimental'}, {'test_file': 'export/test_export'}, {'test_file': 'export/test_torchbind'}, {'test_file': 'export/test_unflatten'}, {'test_file': 'inductor/test_decompose_mem_bound_mm'}, {'test_file': 'inductor/test_dependencies'}, {'test_file': 'inductor/test_move_constructors_to_cuda'}, {'test_file': 'inductor/test_split_cat_fx_passes'}, {'test_file': 'inductor/test_triton_wrapper'}, {'test_file': 'inductor/test_unbacked_symints'}, {'test_file': 'dynamo/test_after_aot'}, {'test_file': 'dynamo/test_aot_autograd_cache'}, {'test_file': 'dynamo/test_backward_higher_order_ops'}, {'test_file': 'dynamo/test_base_output'}, {'test_file': 'dynamo/test_buffers_override'}, {'test_file': 'dynamo/test_bytecode_utils'}, {'test_file': 'dynamo/test_compile'}, {'test_file': 'dynamo/test_comptime'}, {'test_file': 'dynamo/test_config'}, {'test_file': 'dynamo/test_cudagraphs'}, {'test_file': 'dynamo/test_debug_utils'}, {'test_file': 'dynamo/test_deque_reconstruct'}, {'test_file': 'dynamo/test_deviceguard'}, {'test_file': 'dynamo/test_dicts'}, {'test_file': 'dynamo/test_error_messages'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 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{'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarinherit'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'torch_np/test_binary_ufuncs'}, {'test_file': 'torch_np/test_dtype'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'torch_np/test_indexing'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'torch_np/test_nep50_examples'}, {'test_file': 'torch_np/test_random'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'torch_np/test_ufuncs_basic'}, {'test_file': 'torch_np/test_unary_ufuncs'}, {'test_file': 'typing/test_python_operators'}, {'test_file': 'xpu/test_conv'}, {'test_file': 'xpu/test_fusion'}, {'test_file': 'xpu/test_gemm'}], 'excluded': []} from test/test-reports/td_exclusions-e5364040b6dbcc8ed2a8.json is not a benchmark record, skipping 2025-08-26T23:45:55.6743420Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T23:45:55.6811211Z Prepare all required actions 2025-08-26T23:45:55.6811452Z Getting action download info 2025-08-26T23:45:55.6828902Z ##[group]Run ./.github/actions/teardown-rocm 2025-08-26T23:45:55.6829042Z env: 2025-08-26T23:45:55.6829142Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.6829291Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.6829484Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.6829659Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.6830048Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.6830517Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.6830643Z AWS_REGION: us-east-1 2025-08-26T23:45:55.6830780Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.6830954Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.6832927Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.6833109Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.6833295Z DEVICE_NAME: rocm 2025-08-26T23:45:55.6833411Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.6833538Z ##[endgroup] 2025-08-26T23:45:55.6840217Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T23:45:55.6840546Z # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T23:45:55.6840721Z # shellcheck disable=SC2046 2025-08-26T23:45:55.6840877Z docker stop $(docker ps -q) || true 2025-08-26T23:45:55.6841035Z # Prune all stopped containers. 2025-08-26T23:45:55.6841180Z docker container prune -f 2025-08-26T23:45:55.6844889Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:45:55.6845047Z env: 2025-08-26T23:45:55.6845161Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:45:55.6845322Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:45:55.6845578Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:45:55.6845767Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:45:55.6846164Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:45:55.6846604Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:45:55.6846740Z AWS_REGION: us-east-1 2025-08-26T23:45:55.6846887Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:45:55.6847053Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:45:55.6849043Z AWS_SESSION_TOKEN: *** 2025-08-26T23:45:55.6853412Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:45:55.6853601Z DEVICE_NAME: rocm 2025-08-26T23:45:55.6853714Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:45:55.6853849Z ##[endgroup] 2025-08-26T23:46:06.0634232Z 96e14bb2e863 2025-08-26T23:46:10.7564076Z Deleted Containers: 2025-08-26T23:46:10.7564503Z 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:46:10.7564692Z 2025-08-26T23:46:10.7564760Z Total reclaimed space: 12.03GB 2025-08-26T23:46:10.7604021Z Prepare all required actions 2025-08-26T23:46:10.7626876Z ##[group]Run ./.github/actions/diskspace-cleanup 2025-08-26T23:46:10.7627034Z with: 2025-08-26T23:46:10.7627151Z diskspace-cutoff: 70 2025-08-26T23:46:10.7627274Z env: 2025-08-26T23:46:10.7627382Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:46:10.7627542Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:46:10.7627742Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:46:10.7627933Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:46:10.7630626Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:46:10.7631020Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:46:10.7631145Z AWS_REGION: us-east-1 2025-08-26T23:46:10.7631322Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:46:10.7631483Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:46:10.7633465Z AWS_SESSION_TOKEN: *** 2025-08-26T23:46:10.7633646Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:46:10.7633836Z DEVICE_NAME: rocm 2025-08-26T23:46:10.7635417Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:46:10.7635554Z ##[endgroup] 2025-08-26T23:46:10.7649103Z ##[group]Run set -ex 2025-08-26T23:46:10.7649240Z set -ex 2025-08-26T23:46:10.7649349Z diskspace_cutoff=70 2025-08-26T23:46:10.7651265Z docker_root_dir=$(docker info -f '{{.DockerRootDir}}') 2025-08-26T23:46:10.7651453Z if [ ! -d "$docker_root_dir" ]; then 2025-08-26T23:46:10.7651670Z  echo "Docker root directory ($docker_root_dir) does not exist. Skipping disk space check." 2025-08-26T23:46:10.7651868Z  exit 0 2025-08-26T23:46:10.7651974Z fi 2025-08-26T23:46:10.7652149Z diskspace=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //') 2025-08-26T23:46:10.7652493Z msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified" 2025-08-26T23:46:10.7652791Z if [[ "$diskspace" -ge "$diskspace_cutoff" ]] ; then 2025-08-26T23:46:10.7652984Z  docker system prune -af 2025-08-26T23:46:10.7654715Z  diskspace_new=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //') 2025-08-26T23:46:10.7654968Z  if [[ "$diskspace_new" -gt "$diskspace_cutoff" ]] ; then 2025-08-26T23:46:10.7655204Z  echo "Error: Available diskspace is less than $diskspace_cutoff percent. Not enough diskspace." 2025-08-26T23:46:10.7655495Z  echo "$msg" 2025-08-26T23:46:10.7655617Z  exit 1 2025-08-26T23:46:10.7655727Z  else 2025-08-26T23:46:10.7655859Z  difference=$((diskspace - diskspace_new)) 2025-08-26T23:46:10.7656030Z  echo "Diskspace saved: $difference percent" 2025-08-26T23:46:10.7656216Z  fi 2025-08-26T23:46:10.7656315Z fi 2025-08-26T23:46:10.7663344Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T23:46:10.7663507Z env: 2025-08-26T23:46:10.7663606Z GIT_DEFAULT_BRANCH: main 2025-08-26T23:46:10.7663753Z RUNNER_ARTIFACT_DIR: /home/runner/_work/_temp/artifacts 2025-08-26T23:46:10.7663941Z RUNNER_TEST_RESULTS_DIR: /home/runner/_work/_temp/test-results 2025-08-26T23:46:10.7664116Z RUNNER_DOCS_DIR: /home/runner/_work/_temp/docs 2025-08-26T23:46:10.7664510Z GPU_FLAG: --device=/dev/mem --device=/dev/kfd --group-add 992 --device /dev/dri/renderD177 --group-add video --group-add 109 --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host 2025-08-26T23:46:10.7664883Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T23:46:10.7665008Z AWS_REGION: us-east-1 2025-08-26T23:46:10.7666583Z AWS_ACCESS_KEY_ID: *** 2025-08-26T23:46:10.7666748Z AWS_SECRET_ACCESS_KEY: *** 2025-08-26T23:46:10.7668839Z AWS_SESSION_TOKEN: *** 2025-08-26T23:46:10.7669021Z CONTAINER_NAME: 96e14bb2e8637d4db68885f31e9fc8cd3fef43eeb8d21009f2084da56f893cb8 2025-08-26T23:46:10.7669210Z DEVICE_NAME: rocm 2025-08-26T23:46:10.7669322Z DEVICE_TYPE: AMD Instinct Mi325X VF 2025-08-26T23:46:10.7669451Z ##[endgroup] 2025-08-26T23:46:10.7694280Z + diskspace_cutoff=70 2025-08-26T23:46:10.7695766Z ++ docker info -f '{{.DockerRootDir}}' 2025-08-26T23:46:10.8090926Z + docker_root_dir=/home/runner/docker-data 2025-08-26T23:46:10.8097825Z + '[' '!' -d /home/runner/docker-data ']' 2025-08-26T23:46:10.8097982Z ++ sed -n 2p 2025-08-26T23:46:10.8098424Z ++ df -H --output=pcent /home/runner/docker-data 2025-08-26T23:46:10.8098592Z ++ sed s/%// 2025-08-26T23:46:10.8098696Z ++ sed 's/ //' 2025-08-26T23:46:10.8112621Z + diskspace=17 2025-08-26T23:46:10.8112916Z + msg='Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified' 2025-08-26T23:46:10.8113193Z + [[ 17 -ge 70 ]] 2025-08-26T23:46:10.8144512Z Post job cleanup. 2025-08-26T23:46:10.8177927Z Post job cleanup. 2025-08-26T23:46:10.8827180Z Post job cleanup. 2025-08-26T23:46:10.9068870Z Logging out of registry 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T23:46:10.9287232Z Post job cleanup. 2025-08-26T23:46:11.0010659Z Post job cleanup. 2025-08-26T23:46:11.0050836Z Post job cleanup. 2025-08-26T23:46:11.0563550Z [command]/usr/bin/git version 2025-08-26T23:46:11.0594413Z git version 2.51.0 2025-08-26T23:46:11.0606804Z Copying '/home/runner/.gitconfig' to '/home/runner/_work/_temp/17c3ecfb-2044-4826-94f2-5f9fc3697d5a/.gitconfig' 2025-08-26T23:46:11.0611293Z Temporarily overriding HOME='/home/runner/_work/_temp/17c3ecfb-2044-4826-94f2-5f9fc3697d5a' before making global git config changes 2025-08-26T23:46:11.0613128Z Adding repository directory to the temporary git global config as a safe directory 2025-08-26T23:46:11.0614177Z [command]/usr/bin/git config --global --add safe.directory /home/runner/_work/pytorch/pytorch 2025-08-26T23:46:11.0639597Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-08-26T23:46:11.0659004Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-08-26T23:46:11.0849783Z Entering 'android/libs/fbjni' 2025-08-26T23:46:11.0878952Z Entering 'third_party/FP16' 2025-08-26T23:46:11.0913268Z Entering 'third_party/FXdiv' 2025-08-26T23:46:11.0949077Z Entering 'third_party/NNPACK' 2025-08-26T23:46:11.0980800Z Entering 'third_party/NVTX' 2025-08-26T23:46:11.1020075Z Entering 'third_party/VulkanMemoryAllocator' 2025-08-26T23:46:11.1051965Z Entering 'third_party/XNNPACK' 2025-08-26T23:46:11.1094096Z Entering 'third_party/aiter' 2025-08-26T23:46:11.1129544Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T23:46:11.1166297Z Entering 'third_party/benchmark' 2025-08-26T23:46:11.1212095Z Entering 'third_party/composable_kernel' 2025-08-26T23:46:11.1259521Z Entering 'third_party/cpp-httplib' 2025-08-26T23:46:11.1297654Z Entering 'third_party/cpuinfo' 2025-08-26T23:46:11.1334266Z Entering 'third_party/cudnn_frontend' 2025-08-26T23:46:11.1369394Z Entering 'third_party/cutlass' 2025-08-26T23:46:11.1408791Z Entering 'third_party/fbgemm' 2025-08-26T23:46:11.1442283Z Entering 'third_party/fbgemm/external/asmjit' 2025-08-26T23:46:11.1476380Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-08-26T23:46:11.1519555Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-08-26T23:46:11.1560606Z Entering 'third_party/fbgemm/external/cutlass' 2025-08-26T23:46:11.1601619Z Entering 'third_party/fbgemm/external/googletest' 2025-08-26T23:46:11.1641489Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-08-26T23:46:11.1671178Z Entering 'third_party/fbgemm/external/json' 2025-08-26T23:46:11.1708530Z Entering 'third_party/flash-attention' 2025-08-26T23:46:11.1750649Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T23:46:11.1779636Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-08-26T23:46:11.1816020Z Entering 'third_party/flatbuffers' 2025-08-26T23:46:11.1846716Z Entering 'third_party/fmt' 2025-08-26T23:46:11.1877731Z Entering 'third_party/gemmlowp/gemmlowp' 2025-08-26T23:46:11.1909269Z Entering 'third_party/gloo' 2025-08-26T23:46:11.1938950Z Entering 'third_party/googletest' 2025-08-26T23:46:11.1965959Z Entering 'third_party/ideep' 2025-08-26T23:46:11.1996252Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T23:46:11.2030746Z Entering 'third_party/ittapi' 2025-08-26T23:46:11.2060585Z Entering 'third_party/kineto' 2025-08-26T23:46:11.2085463Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T23:46:11.2116566Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T23:46:11.2145092Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T23:46:11.2168807Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T23:46:11.2193638Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T23:46:11.2220166Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T23:46:11.2249098Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T23:46:11.2274745Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T23:46:11.2300658Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T23:46:11.2334876Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T23:46:11.2361494Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T23:46:11.2402848Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T23:46:11.2428132Z Entering 'third_party/kleidiai' 2025-08-26T23:46:11.2457657Z Entering 'third_party/mimalloc' 2025-08-26T23:46:11.2487909Z Entering 'third_party/nlohmann' 2025-08-26T23:46:11.2515827Z Entering 'third_party/onnx' 2025-08-26T23:46:11.2553610Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T23:46:11.2584408Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T23:46:11.2613829Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T23:46:11.2644741Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T23:46:11.2669334Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T23:46:11.2694585Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T23:46:11.2721130Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T23:46:11.2746550Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T23:46:11.2784442Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T23:46:11.2815666Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T23:46:11.2850398Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T23:46:11.2886390Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T23:46:11.2921543Z Entering 'third_party/pocketfft' 2025-08-26T23:46:11.2948112Z Entering 'third_party/protobuf' 2025-08-26T23:46:11.2976107Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T23:46:11.3001779Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T23:46:11.3030894Z Entering 'third_party/psimd' 2025-08-26T23:46:11.3058818Z Entering 'third_party/pthreadpool' 2025-08-26T23:46:11.3090271Z Entering 'third_party/pybind11' 2025-08-26T23:46:11.3117027Z Entering 'third_party/python-peachpy' 2025-08-26T23:46:11.3145374Z Entering 'third_party/sleef' 2025-08-26T23:46:11.3176536Z Entering 'third_party/tensorpipe' 2025-08-26T23:46:11.3204044Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T23:46:11.3226766Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T23:46:11.3252642Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T23:46:11.3280131Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T23:46:11.3311195Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T23:46:11.3359387Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-08-26T23:46:11.3376277Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3382822Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-08-26T23:46:11.3403642Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-08-26T23:46:11.3607746Z Entering 'android/libs/fbjni' 2025-08-26T23:46:11.3623759Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3644821Z Entering 'third_party/FP16' 2025-08-26T23:46:11.3660783Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3680919Z Entering 'third_party/FXdiv' 2025-08-26T23:46:11.3697589Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3717924Z Entering 'third_party/NNPACK' 2025-08-26T23:46:11.3734012Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3754162Z Entering 'third_party/NVTX' 2025-08-26T23:46:11.3778240Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3799975Z Entering 'third_party/VulkanMemoryAllocator' 2025-08-26T23:46:11.3817090Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3843416Z Entering 'third_party/XNNPACK' 2025-08-26T23:46:11.3865796Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3893265Z Entering 'third_party/aiter' 2025-08-26T23:46:11.3912139Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3941403Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T23:46:11.3959316Z http.https://github.com/.extraheader 2025-08-26T23:46:11.3985021Z Entering 'third_party/benchmark' 2025-08-26T23:46:11.4000261Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4021474Z Entering 'third_party/composable_kernel' 2025-08-26T23:46:11.4033537Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4059325Z Entering 'third_party/cpp-httplib' 2025-08-26T23:46:11.4079628Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4101383Z Entering 'third_party/cpuinfo' 2025-08-26T23:46:11.4117250Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4137006Z Entering 'third_party/cudnn_frontend' 2025-08-26T23:46:11.4152775Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4173719Z Entering 'third_party/cutlass' 2025-08-26T23:46:11.4188842Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4213507Z Entering 'third_party/fbgemm' 2025-08-26T23:46:11.4232997Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4264005Z Entering 'third_party/fbgemm/external/asmjit' 2025-08-26T23:46:11.4278962Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4297916Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-08-26T23:46:11.4313687Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4334829Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-08-26T23:46:11.4350878Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4372335Z Entering 'third_party/fbgemm/external/cutlass' 2025-08-26T23:46:11.4389051Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4416574Z Entering 'third_party/fbgemm/external/googletest' 2025-08-26T23:46:11.4432319Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4458157Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-08-26T23:46:11.4484654Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4509878Z Entering 'third_party/fbgemm/external/json' 2025-08-26T23:46:11.4528366Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4557507Z Entering 'third_party/flash-attention' 2025-08-26T23:46:11.4575271Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4598162Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T23:46:11.4614387Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4646190Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-08-26T23:46:11.4668637Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4692488Z Entering 'third_party/flatbuffers' 2025-08-26T23:46:11.4708212Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4729699Z Entering 'third_party/fmt' 2025-08-26T23:46:11.4747976Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4767531Z Entering 'third_party/gemmlowp/gemmlowp' 2025-08-26T23:46:11.4787973Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4808542Z Entering 'third_party/gloo' 2025-08-26T23:46:11.4824548Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4849919Z Entering 'third_party/googletest' 2025-08-26T23:46:11.4865530Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4884950Z Entering 'third_party/ideep' 2025-08-26T23:46:11.4909430Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4927680Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T23:46:11.4945798Z http.https://github.com/.extraheader 2025-08-26T23:46:11.4965566Z Entering 'third_party/ittapi' 2025-08-26T23:46:11.4980981Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5007921Z Entering 'third_party/kineto' 2025-08-26T23:46:11.5031403Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5052874Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T23:46:11.5066683Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5090027Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T23:46:11.5106165Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5128714Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T23:46:11.5147689Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5169272Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T23:46:11.5184280Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5215393Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T23:46:11.5233371Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5259294Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T23:46:11.5276380Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5306087Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T23:46:11.5320648Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5340925Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T23:46:11.5357158Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5376249Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T23:46:11.5391857Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5420966Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T23:46:11.5436078Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5463254Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T23:46:11.5477311Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5502624Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T23:46:11.5518950Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5543235Z Entering 'third_party/kleidiai' 2025-08-26T23:46:11.5565917Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5587915Z Entering 'third_party/mimalloc' 2025-08-26T23:46:11.5611183Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5637536Z Entering 'third_party/nlohmann' 2025-08-26T23:46:11.5657499Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5680873Z Entering 'third_party/onnx' 2025-08-26T23:46:11.5703169Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5738142Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T23:46:11.5762902Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5782124Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T23:46:11.5800055Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5822416Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T23:46:11.5847471Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5870645Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T23:46:11.5888072Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5913296Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T23:46:11.5933245Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5951847Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T23:46:11.5977403Z http.https://github.com/.extraheader 2025-08-26T23:46:11.5998976Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T23:46:11.6016348Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6041863Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T23:46:11.6066322Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6096321Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T23:46:11.6105085Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6124950Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T23:46:11.6140603Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6160564Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T23:46:11.6176599Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6196560Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T23:46:11.6213544Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6247022Z Entering 'third_party/pocketfft' 2025-08-26T23:46:11.6261424Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6288943Z Entering 'third_party/protobuf' 2025-08-26T23:46:11.6305579Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6327876Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T23:46:11.6343200Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6361576Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T23:46:11.6377501Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6399640Z Entering 'third_party/psimd' 2025-08-26T23:46:11.6419105Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6439840Z Entering 'third_party/pthreadpool' 2025-08-26T23:46:11.6456726Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6477374Z Entering 'third_party/pybind11' 2025-08-26T23:46:11.6502897Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6524786Z Entering 'third_party/python-peachpy' 2025-08-26T23:46:11.6543376Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6571379Z Entering 'third_party/sleef' 2025-08-26T23:46:11.6591356Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6613335Z Entering 'third_party/tensorpipe' 2025-08-26T23:46:11.6629107Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6649468Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T23:46:11.6666461Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6687275Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T23:46:11.6702891Z http.https://github.com/.extraheader 2025-08-26T23:46:11.6724641Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T23:46:11.6747121Z http.https://github.com/.extraheader 2025-08-26T23:46:11.7148332Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T23:46:11.7170751Z http.https://github.com/.extraheader 2025-08-26T23:46:11.7198831Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T23:46:11.7214814Z http.https://github.com/.extraheader 2025-08-26T23:46:11.7389488Z Cleaning up orphan processes