2025-12-04T09:13:33.9912472Z Current runner version: '2.330.0' 2025-12-04T09:13:33.9918976Z Runner name: 'i-0ed9e7c329090f0b0' 2025-12-04T09:13:33.9919850Z Runner group name: 'default' 2025-12-04T09:13:33.9920819Z Machine name: 'ip-10-0-5-68' 2025-12-04T09:13:33.9923809Z ##[group]GITHUB_TOKEN Permissions 2025-12-04T09:13:33.9926282Z Contents: read 2025-12-04T09:13:33.9926963Z Metadata: read 2025-12-04T09:13:33.9927542Z ##[endgroup] 2025-12-04T09:13:33.9929674Z Secret source: Actions 2025-12-04T09:13:33.9930538Z Prepare workflow directory 2025-12-04T09:13:34.0467974Z Prepare all required actions 2025-12-04T09:13:34.0514412Z Getting action download info 2025-12-04T09:13:34.4782006Z Download action repository 'pytorch/test-infra@main' (SHA:39aa74d619174326f4e2fb0e216151c2f29d9ffd) 2025-12-04T09:13:35.9860139Z Download action repository 'pytorch/pytorch@main' (SHA:7716da9fb23f27a65b41f9f016a2afadf281c18f) 2025-12-04T09:13:50.5229885Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-12-04T09:13:50.9144611Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-12-04T09:13:51.1853585Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-12-04T09:13:51.3835985Z Download action repository 'seemethere/download-artifact-s3@1da556a7aa0a088e3153970611f6c432d58e80e6' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-12-04T09:13:51.6349671Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-12-04T09:13:51.9360890Z Getting action download info 2025-12-04T09:13:52.0832777Z Download action repository 'actions/checkout@v4' (SHA:34e114876b0b11c390a56381ad16ebd13914f8d5) 2025-12-04T09:13:52.4020215Z Getting action download info 2025-12-04T09:13:52.5247343Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-12-04T09:13:52.7924268Z Getting action download info 2025-12-04T09:13:52.9636552Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-12-04T09:13:53.2259747Z Getting action download info 2025-12-04T09:13:53.3877400Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32) 2025-12-04T09:13:53.3881568Z ##[group] Inputs 2025-12-04T09:13:53.3881970Z build-environment: linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:13:53.3887980Z test-matrix: {"include": [{"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests"}]} 2025-12-04T09:13:53.3894454Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:13:53.3895393Z sync-tag: 2025-12-04T09:13:53.3896264Z timeout-minutes: 240 2025-12-04T09:13:53.3896543Z use-gha: 2025-12-04T09:13:53.3896774Z dashboard-tag: 2025-12-04T09:13:53.3897016Z s3-bucket: gha-artifacts 2025-12-04T09:13:53.3897304Z aws-role-to-assume: 2025-12-04T09:13:53.3897912Z disable-monitor: false 2025-12-04T09:13:53.3898221Z monitor-log-interval: 5 2025-12-04T09:13:53.3898549Z monitor-data-collect-interval: 1 2025-12-04T09:13:53.3898885Z ##[endgroup] 2025-12-04T09:13:53.3899465Z Complete job name: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:13:53.4440886Z A job started hook has been configured by the self-hosted runner administrator 2025-12-04T09:13:53.4546673Z ##[group]Run '/home/ec2-user/runner-scripts/before_job.sh' 2025-12-04T09:13:53.4556209Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:13:53.4556898Z ##[endgroup] 2025-12-04T09:13:54.9117238Z Runner Type: linux.4xlarge 2025-12-04T09:13:54.9117770Z Instance Type: c5.4xlarge 2025-12-04T09:13:54.9118051Z AMI Name: unknown 2025-12-04T09:13:54.9149558Z AMI ID: ami-08982f1c5bf93d976 2025-12-04T09:14:00.4157839Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-12-04T09:14:00.4158324Z with: 2025-12-04T09:14:00.4158927Z github-secret: *** 2025-12-04T09:14:00.4159708Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-12-04T09:14:00.4160568Z activate-with-label: false 2025-12-04T09:14:00.4160867Z label: with-ssh 2025-12-04T09:14:00.4161135Z remove-existing-keys: true 2025-12-04T09:14:00.4161439Z fail-silently: true 2025-12-04T09:14:00.4161698Z env: 2025-12-04T09:14:00.4161914Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:14:00.4162201Z ##[endgroup] 2025-12-04T09:14:00.5358191Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-12-04T09:14:00.5359816Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-12-04T09:14:00.5518304Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-12-04T09:14:00.5518783Z with: 2025-12-04T09:14:00.5519004Z no-sudo: true 2025-12-04T09:14:00.5519250Z submodules: recursive 2025-12-04T09:14:00.5519525Z fetch-depth: 0 2025-12-04T09:14:00.5519753Z env: 2025-12-04T09:14:00.5519975Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:14:00.5520248Z ##[endgroup] 2025-12-04T09:14:00.5596525Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:14:00.5597593Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:14:00.5606301Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:14:00.5606717Z env: 2025-12-04T09:14:00.5606963Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:14:00.5607284Z ##[endgroup] 2025-12-04T09:14:00.5715986Z ##[group]Run # Use all available CPUs for fetching 2025-12-04T09:14:00.5716437Z # Use all available CPUs for fetching 2025-12-04T09:14:00.5716843Z cd "${GITHUB_WORKSPACE}" 2025-12-04T09:14:00.5717229Z git config --global fetch.parallel 0 2025-12-04T09:14:00.5717668Z git config --global submodule.fetchJobs 0 2025-12-04T09:14:00.5718021Z  2025-12-04T09:14:00.5718406Z # Clean workspace. The default checkout action should also do this, but 2025-12-04T09:14:00.5718918Z # do it here as well just in case 2025-12-04T09:14:00.5719413Z if [[ -d .git ]]; then 2025-12-04T09:14:00.5719725Z  if [ -z "${NO_SUDO}" ]; then 2025-12-04T09:14:00.5720058Z  sudo git clean -ffdx 2025-12-04T09:14:00.5720345Z  else 2025-12-04T09:14:00.5720594Z  git clean -ffdx 2025-12-04T09:14:00.5720872Z  fi 2025-12-04T09:14:00.5721101Z fi 2025-12-04T09:14:00.5727206Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:14:00.5727613Z env: 2025-12-04T09:14:00.5727910Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:14:00.5728196Z NO_SUDO: true 2025-12-04T09:14:00.5728430Z ##[endgroup] 2025-12-04T09:14:00.5847237Z ##[group]Run actions/checkout@v4 2025-12-04T09:14:00.5847554Z with: 2025-12-04T09:14:00.5847818Z ref: ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:14:00.5848169Z fetch-depth: 0 2025-12-04T09:14:00.5848421Z submodules: recursive 2025-12-04T09:14:00.5848696Z show-progress: false 2025-12-04T09:14:00.5848981Z repository: pytorch/pytorch 2025-12-04T09:14:00.5849423Z token: *** 2025-12-04T09:14:00.5849642Z ssh-strict: true 2025-12-04T09:14:00.5849885Z ssh-user: git 2025-12-04T09:14:00.5850133Z persist-credentials: true 2025-12-04T09:14:00.5850399Z clean: true 2025-12-04T09:14:00.5850648Z sparse-checkout-cone-mode: true 2025-12-04T09:14:00.5850958Z fetch-tags: false 2025-12-04T09:14:00.5851182Z lfs: false 2025-12-04T09:14:00.5851407Z set-safe-directory: true 2025-12-04T09:14:00.5851679Z env: 2025-12-04T09:14:00.5851883Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:14:00.5852148Z ##[endgroup] 2025-12-04T09:14:00.6991071Z Syncing repository: pytorch/pytorch 2025-12-04T09:14:00.6992545Z ##[group]Getting Git version info 2025-12-04T09:14:00.6993072Z Working directory is '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-12-04T09:14:00.6993784Z [command]/usr/bin/git version 2025-12-04T09:14:00.6994089Z git version 2.50.1 2025-12-04T09:14:00.7005498Z ##[endgroup] 2025-12-04T09:14:00.7014769Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/d97a26eb-c763-401c-a71b-86346972fb1f/.gitconfig' 2025-12-04T09:14:00.7034475Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/d97a26eb-c763-401c-a71b-86346972fb1f' before making global git config changes 2025-12-04T09:14:00.7035572Z Adding repository directory to the temporary git global config as a safe directory 2025-12-04T09:14:00.7039560Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-12-04T09:14:00.7084615Z Deleting the contents of '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-12-04T09:14:00.7087568Z ##[group]Initializing the repository 2025-12-04T09:14:00.7091743Z [command]/usr/bin/git init /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-12-04T09:14:00.7124495Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-12-04T09:14:00.7125172Z hint: is subject to change. To configure the initial branch name to use in all 2025-12-04T09:14:00.7125811Z hint: of your new repositories, which will suppress this warning, call: 2025-12-04T09:14:00.7126254Z hint: 2025-12-04T09:14:00.7126575Z hint: git config --global init.defaultBranch 2025-12-04T09:14:00.7126948Z hint: 2025-12-04T09:14:00.7127290Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-12-04T09:14:00.7127919Z hint: 'development'. The just-created branch can be renamed via this command: 2025-12-04T09:14:00.7128391Z hint: 2025-12-04T09:14:00.7128620Z hint: git branch -m 2025-12-04T09:14:00.7128882Z hint: 2025-12-04T09:14:00.7129278Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-12-04T09:14:00.7130049Z Initialized empty Git repository in /home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/ 2025-12-04T09:14:00.7134657Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-12-04T09:14:00.7161759Z ##[endgroup] 2025-12-04T09:14:00.7162425Z ##[group]Disabling automatic garbage collection 2025-12-04T09:14:00.7166004Z [command]/usr/bin/git config --local gc.auto 0 2025-12-04T09:14:00.7191724Z ##[endgroup] 2025-12-04T09:14:00.7192136Z ##[group]Setting up auth 2025-12-04T09:14:00.7198101Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-12-04T09:14:00.7226013Z [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' || :" 2025-12-04T09:14:00.7542553Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-12-04T09:14:00.7570584Z [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' || :" 2025-12-04T09:14:00.7860684Z [command]/usr/bin/git config --local --name-only --get-regexp ^includeIf\.gitdir: 2025-12-04T09:14:00.7888159Z [command]/usr/bin/git submodule foreach --recursive git config --local --show-origin --name-only --get-regexp remote.origin.url 2025-12-04T09:14:00.8184576Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-12-04T09:14:00.8248958Z ##[endgroup] 2025-12-04T09:14:00.8249428Z ##[group]Fetching the repository 2025-12-04T09:14:00.8261878Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-12-04T09:14:55.1278790Z From https://github.com/pytorch/pytorch 2025-12-04T09:14:55.1279603Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-12-04T09:14:55.1280475Z * [new branch] 2.9.1 -> origin/2.9.1 2025-12-04T09:14:55.1281137Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-12-04T09:14:55.1282026Z * [new branch] Flamefire-patch-1 -> origin/Flamefire-patch-1 2025-12-04T09:14:55.1282771Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-12-04T09:14:55.1283687Z * [new branch] HOPrintFunc -> origin/HOPrintFunc 2025-12-04T09:14:55.1285626Z * [new branch] IvanKobzarev/stack/1 -> origin/IvanKobzarev/stack/1 2025-12-04T09:14:55.1287828Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-12-04T09:14:55.1288713Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-12-04T09:14:55.1290051Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-12-04T09:14:55.1291345Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-12-04T09:14:55.1292447Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-12-04T09:14:55.1293623Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-12-04T09:14:55.1294892Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-12-04T09:14:55.1296045Z * [new branch] VLA_exp -> origin/VLA_exp 2025-12-04T09:14:55.1297784Z * [new branch] activation_bench -> origin/activation_bench 2025-12-04T09:14:55.1299755Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-12-04T09:14:55.1301418Z * [new branch] adi/onednn_aarch64 -> origin/adi/onednn_aarch64 2025-12-04T09:14:55.1302569Z * [new branch] adi/test -> origin/adi/test 2025-12-04T09:14:55.1303786Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-12-04T09:14:55.1305008Z * [new branch] adi/test_m8g -> origin/adi/test_m8g 2025-12-04T09:14:55.1306222Z * [new branch] adi/test_onednn -> origin/adi/test_onednn 2025-12-04T09:14:55.1307416Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-12-04T09:14:55.1308655Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-12-04T09:14:55.1309814Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-12-04T09:14:55.1311508Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-12-04T09:14:55.1313690Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-12-04T09:14:55.1314739Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-12-04T09:14:55.1316272Z * [new branch] albanD-patch-1 -> origin/albanD-patch-1 2025-12-04T09:14:55.1317306Z * [new branch] also-surround-shimh -> origin/also-surround-shimh 2025-12-04T09:14:55.1319313Z * [new branch] angelayi/aot_compile -> origin/angelayi/aot_compile 2025-12-04T09:14:55.1320441Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-12-04T09:14:55.1321602Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-12-04T09:14:55.1322974Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-12-04T09:14:55.1324086Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-12-04T09:14:55.1325486Z * [new branch] angelayi/inductor_const -> origin/angelayi/inductor_const 2025-12-04T09:14:55.1326588Z * [new branch] angelayi/lstm -> origin/angelayi/lstm 2025-12-04T09:14:55.1328403Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-12-04T09:14:55.1329783Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-12-04T09:14:55.1331048Z * [new branch] angelayi/side_eff -> origin/angelayi/side_eff 2025-12-04T09:14:55.1332353Z * [new branch] angelayi/state_dict -> origin/angelayi/state_dict 2025-12-04T09:14:55.1333663Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-12-04T09:14:55.1334991Z * [new branch] angelayi/symm_mem -> origin/angelayi/symm_mem 2025-12-04T09:14:55.1336126Z * [new branch] angelayi/test_cpp -> origin/angelayi/test_cpp 2025-12-04T09:14:55.1337400Z * [new branch] angelayi/torch_size -> origin/angelayi/torch_size 2025-12-04T09:14:55.1338639Z * [new branch] annotate_assert -> origin/annotate_assert 2025-12-04T09:14:55.1339895Z * [new branch] annotate_fallback_kernel -> origin/annotate_fallback_kernel 2025-12-04T09:14:55.1341103Z * [new branch] annotation_deepcopy -> origin/annotation_deepcopy 2025-12-04T09:14:55.1342654Z * [new branch] annotation_dynamo -> origin/annotation_dynamo 2025-12-04T09:14:55.1344298Z * [new branch] aot_eager_stack_trace -> origin/aot_eager_stack_trace 2025-12-04T09:14:55.1345295Z * [new 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zhxchen17/dynamo/unsafe_drop_all_guards -> origin/zhxchen17/dynamo/unsafe_drop_all_guards 2025-12-04T09:14:55.8034467Z * [new branch] zhxchen17/export/call_override -> origin/zhxchen17/export/call_override 2025-12-04T09:14:55.8035616Z * [new branch] zhxchen17/export/codemod1 -> origin/zhxchen17/export/codemod1 2025-12-04T09:14:55.8036869Z * [new branch] zhxchen17/export/ctx_return -> origin/zhxchen17/export/ctx_return 2025-12-04T09:14:55.8038186Z * [new branch] zhxchen17/export/disable_side_effect_warn -> origin/zhxchen17/export/disable_side_effect_warn 2025-12-04T09:14:55.8039207Z * [new branch] zhxchen17/export/pytree_check -> origin/zhxchen17/export/pytree_check 2025-12-04T09:14:55.8041253Z * [new branch] zhxchen17/precompile/aoti -> origin/zhxchen17/precompile/aoti 2025-12-04T09:14:55.8042710Z * [new branch] zhxchen17/precompile/globals -> origin/zhxchen17/precompile/globals 2025-12-04T09:14:55.8047984Z * [new branch] zhxchen17/precompile/inductor_guards -> origin/zhxchen17/precompile/inductor_guards 2025-12-04T09:14:55.8049459Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-12-04T09:14:55.8050816Z * [new branch] zhxchen17/torch_export_api_update -> origin/zhxchen17/torch_export_api_update 2025-12-04T09:14:55.8052485Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-12-04T09:14:55.8054156Z * [new branch] zxiiro/build-times -> origin/zxiiro/build-times 2025-12-04T09:14:55.8055445Z * [new branch] zxiiro/c7i.2xlarge -> origin/zxiiro/c7i.2xlarge 2025-12-04T09:14:55.8056688Z * [new branch] zxiiro/c7i.2xlarge.h100 -> origin/zxiiro/c7i.2xlarge.h100 2025-12-04T09:14:55.8057867Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-12-04T09:14:55.8059077Z * [new branch] zxiiro/risc64 -> origin/zxiiro/risc64 2025-12-04T09:14:55.8060349Z * [new branch] zxiiro/test-multicloud-arc -> origin/zxiiro/test-multicloud-arc 2025-12-04T09:14:55.8061510Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-12-04T09:14:55.8062339Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-12-04T09:14:55.8063533Z * [new tag] ciflow/b200/115316 -> ciflow/b200/115316 2025-12-04T09:14:55.8064174Z * [new tag] ciflow/b200/160685 -> ciflow/b200/160685 2025-12-04T09:14:55.8065151Z * [new tag] ciflow/b200/161607 -> ciflow/b200/161607 2025-12-04T09:14:55.8065747Z * [new tag] ciflow/b200/161938 -> ciflow/b200/161938 2025-12-04T09:14:55.8066879Z * [new tag] ciflow/b200/167207 -> ciflow/b200/167207 2025-12-04T09:14:55.8067479Z * [new tag] ciflow/b200/167989 -> ciflow/b200/167989 2025-12-04T09:14:55.8068587Z * [new tag] ciflow/b200/168096 -> ciflow/b200/168096 2025-12-04T09:14:55.8069304Z * [new tag] ciflow/b200/168175 -> ciflow/b200/168175 2025-12-04T09:14:55.8070496Z * [new tag] ciflow/b200/168195 -> ciflow/b200/168195 2025-12-04T09:14:55.8071124Z * [new tag] ciflow/b200/169200 -> ciflow/b200/169200 2025-12-04T09:14:55.8072223Z * [new tag] ciflow/b200/169216 -> ciflow/b200/169216 2025-12-04T09:14:55.8073437Z * [new tag] ciflow/b200/169380 -> ciflow/b200/169380 2025-12-04T09:14:55.8074653Z * [new tag] ciflow/b200/169412 -> ciflow/b200/169412 2025-12-04T09:14:55.8075702Z * [new tag] ciflow/b200/169470 -> ciflow/b200/169470 2025-12-04T09:14:55.8076334Z * [new tag] ciflow/b200/169471 -> ciflow/b200/169471 2025-12-04T09:14:55.8077386Z * [new tag] ciflow/b200/169472 -> ciflow/b200/169472 2025-12-04T09:14:55.8078502Z * [new tag] ciflow/b200/169514 -> ciflow/b200/169514 2025-12-04T09:14:55.8079136Z * [new tag] ciflow/b200/169517 -> ciflow/b200/169517 2025-12-04T09:14:55.8080440Z * [new tag] ciflow/binaries/165922 -> ciflow/binaries/165922 2025-12-04T09:14:55.8081056Z * [new tag] ciflow/binaries/169510 -> ciflow/binaries/169510 2025-12-04T09:14:55.8082379Z * [new tag] ciflow/binaries_wheel/157994 -> ciflow/binaries_wheel/157994 2025-12-04T09:14:55.8083085Z * [new tag] ciflow/binaries_wheel/166829 -> ciflow/binaries_wheel/166829 2025-12-04T09:14:55.8083957Z * [new tag] ciflow/binaries_wheel/167972 -> ciflow/binaries_wheel/167972 2025-12-04T09:14:55.8085138Z * [new tag] ciflow/binaries_wheel/167981 -> ciflow/binaries_wheel/167981 2025-12-04T09:14:55.8085907Z * [new tag] ciflow/dynamo/167695 -> ciflow/dynamo/167695 2025-12-04T09:14:55.8086648Z * [new tag] ciflow/dynamo/168096 -> ciflow/dynamo/168096 2025-12-04T09:14:55.8087737Z * [new tag] ciflow/dynamo/169525 -> ciflow/dynamo/169525 2025-12-04T09:14:55.8088680Z * [new tag] ciflow/h100-cutlass-backend/161938 -> ciflow/h100-cutlass-backend/161938 2025-12-04T09:14:55.8089476Z * [new tag] ciflow/h100-cutlass-backend/161940 -> ciflow/h100-cutlass-backend/161940 2025-12-04T09:14:55.8090654Z * [new tag] ciflow/h100-distributed/168923 -> ciflow/h100-distributed/168923 2025-12-04T09:14:55.8091325Z * [new tag] ciflow/h100-symm-mem/167552 -> ciflow/h100-symm-mem/167552 2025-12-04T09:14:55.8092176Z * [new tag] ciflow/h100-symm-mem/168129 -> ciflow/h100-symm-mem/168129 2025-12-04T09:14:55.8093118Z * [new tag] ciflow/h100-symm-mem/168917 -> ciflow/h100-symm-mem/168917 2025-12-04T09:14:55.8094206Z * [new tag] ciflow/h100-symm-mem/169156 -> ciflow/h100-symm-mem/169156 2025-12-04T09:14:55.8095041Z * [new tag] ciflow/h100-symm-mem/169200 -> ciflow/h100-symm-mem/169200 2025-12-04T09:14:55.8095857Z * [new tag] ciflow/h100-symm-mem/169216 -> ciflow/h100-symm-mem/169216 2025-12-04T09:14:55.8096648Z * [new tag] ciflow/h100-symm-mem/169338 -> ciflow/h100-symm-mem/169338 2025-12-04T09:14:55.8097535Z * [new tag] ciflow/h100-symm-mem/169355 -> ciflow/h100-symm-mem/169355 2025-12-04T09:14:55.8098349Z * [new tag] ciflow/h100-symm-mem/169543 -> ciflow/h100-symm-mem/169543 2025-12-04T09:14:55.8099231Z * [new tag] ciflow/h100/115316 -> ciflow/h100/115316 2025-12-04T09:14:55.8100058Z * [new tag] ciflow/h100/160685 -> ciflow/h100/160685 2025-12-04T09:14:55.8100812Z * [new tag] ciflow/h100/160729 -> ciflow/h100/160729 2025-12-04T09:14:55.8101593Z * [new tag] ciflow/h100/161607 -> ciflow/h100/161607 2025-12-04T09:14:55.8102406Z * [new tag] ciflow/h100/161938 -> ciflow/h100/161938 2025-12-04T09:14:55.8103271Z * [new tag] ciflow/h100/167207 -> ciflow/h100/167207 2025-12-04T09:14:55.8103960Z * [new tag] ciflow/h100/167989 -> ciflow/h100/167989 2025-12-04T09:14:55.8104711Z * [new tag] ciflow/h100/168096 -> ciflow/h100/168096 2025-12-04T09:14:55.8105448Z * [new tag] ciflow/h100/168175 -> ciflow/h100/168175 2025-12-04T09:14:55.8106253Z * [new tag] ciflow/h100/168195 -> ciflow/h100/168195 2025-12-04T09:14:55.8107009Z * [new tag] ciflow/h100/168980 -> ciflow/h100/168980 2025-12-04T09:14:55.8108162Z * [new tag] ciflow/h100/169200 -> ciflow/h100/169200 2025-12-04T09:14:55.8109085Z * [new tag] ciflow/h100/169216 -> ciflow/h100/169216 2025-12-04T09:14:55.8110079Z * [new tag] ciflow/h100/169380 -> ciflow/h100/169380 2025-12-04T09:14:55.8110907Z * [new tag] ciflow/h100/169412 -> ciflow/h100/169412 2025-12-04T09:14:55.8112185Z * [new tag] ciflow/h100/169470 -> ciflow/h100/169470 2025-12-04T09:14:55.8112915Z * [new tag] ciflow/h100/169471 -> ciflow/h100/169471 2025-12-04T09:14:55.8113779Z * [new tag] ciflow/h100/169472 -> ciflow/h100/169472 2025-12-04T09:14:55.8114594Z * [new tag] ciflow/h100/169514 -> ciflow/h100/169514 2025-12-04T09:14:55.8115604Z * [new tag] ciflow/inductor-cu126/168096 -> ciflow/inductor-cu126/168096 2025-12-04T09:14:55.8116939Z * [new tag] ciflow/inductor-micro-benchmark-cpu-x86/168096 -> ciflow/inductor-micro-benchmark-cpu-x86/168096 2025-12-04T09:14:55.8117787Z * [new tag] ciflow/inductor-micro-benchmark/166165 -> ciflow/inductor-micro-benchmark/166165 2025-12-04T09:14:55.8118618Z * [new tag] ciflow/inductor-micro-benchmark/168096 -> ciflow/inductor-micro-benchmark/168096 2025-12-04T09:14:55.8119644Z * [new tag] ciflow/inductor-perf-compare/168096 -> ciflow/inductor-perf-compare/168096 2025-12-04T09:14:55.8121295Z * [new tag] ciflow/inductor-perf-test-nightly-rocm-mi300/168073 -> ciflow/inductor-perf-test-nightly-rocm-mi300/168073 2025-12-04T09:14:55.8121882Z * [new tag] ciflow/inductor-perf-test-nightly-rocm-mi300/168096 -> ciflow/inductor-perf-test-nightly-rocm-mi300/168096 2025-12-04T09:14:55.8122681Z * [new tag] ciflow/inductor-perf-test-nightly-rocm-mi300/169024 -> ciflow/inductor-perf-test-nightly-rocm-mi300/169024 2025-12-04T09:14:55.8123729Z * [new tag] ciflow/inductor-perf-test-nightly-rocm-mi355/169024 -> ciflow/inductor-perf-test-nightly-rocm-mi355/169024 2025-12-04T09:14:55.8124492Z * [new tag] ciflow/inductor-perf-test-nightly/168096 -> ciflow/inductor-perf-test-nightly/168096 2025-12-04T09:14:55.8125462Z * [new tag] ciflow/inductor-periodic/168096 -> ciflow/inductor-periodic/168096 2025-12-04T09:14:55.8126218Z * [new tag] ciflow/inductor-periodic/169024 -> ciflow/inductor-periodic/169024 2025-12-04T09:14:55.8127158Z * [new tag] ciflow/inductor-periodic/169425 -> ciflow/inductor-periodic/169425 2025-12-04T09:14:55.8128286Z * [new tag] ciflow/inductor-rocm-mi200/165545 -> ciflow/inductor-rocm-mi200/165545 2025-12-04T09:14:55.8129142Z * [new tag] ciflow/inductor-rocm-mi200/165997 -> ciflow/inductor-rocm-mi200/165997 2025-12-04T09:14:55.8129923Z * [new tag] ciflow/inductor-rocm-mi200/168096 -> ciflow/inductor-rocm-mi200/168096 2025-12-04T09:14:55.8130916Z * [new tag] ciflow/inductor-rocm-mi200/169063 -> ciflow/inductor-rocm-mi200/169063 2025-12-04T09:14:55.8131737Z * [new tag] ciflow/inductor-rocm-mi200/169425 -> ciflow/inductor-rocm-mi200/169425 2025-12-04T09:14:55.8132812Z * [new tag] ciflow/inductor-rocm-mi300/165545 -> ciflow/inductor-rocm-mi300/165545 2025-12-04T09:14:55.8133455Z * [new tag] ciflow/inductor-rocm-mi300/168096 -> ciflow/inductor-rocm-mi300/168096 2025-12-04T09:14:55.8134206Z * [new tag] ciflow/inductor-rocm-mi300/169063 -> ciflow/inductor-rocm-mi300/169063 2025-12-04T09:14:55.8135026Z * [new tag] ciflow/inductor-rocm-mi300/169425 -> ciflow/inductor-rocm-mi300/169425 2025-12-04T09:14:55.8136043Z * [new tag] ciflow/inductor-rocm/162052 -> ciflow/inductor-rocm/162052 2025-12-04T09:14:55.8136829Z * [new tag] ciflow/inductor-rocm/168971 -> ciflow/inductor-rocm/168971 2025-12-04T09:14:55.8137808Z * [new tag] ciflow/inductor-windows/168096 -> ciflow/inductor-windows/168096 2025-12-04T09:14:55.8138682Z * [new tag] ciflow/inductor/144542 -> ciflow/inductor/144542 2025-12-04T09:14:55.8139562Z * [new tag] ciflow/inductor/146506 -> ciflow/inductor/146506 2025-12-04T09:14:55.8140346Z * [new tag] ciflow/inductor/147990 -> ciflow/inductor/147990 2025-12-04T09:14:55.8141215Z * [new tag] ciflow/inductor/148294 -> ciflow/inductor/148294 2025-12-04T09:14:55.8142035Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-12-04T09:14:55.8143030Z * [new tag] ciflow/inductor/157149 -> ciflow/inductor/157149 2025-12-04T09:14:55.8143839Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-12-04T09:14:55.8144620Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-12-04T09:14:55.8145382Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-12-04T09:14:55.8146149Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-12-04T09:14:55.8146928Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-12-04T09:14:55.8148106Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-12-04T09:14:55.8149477Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-12-04T09:14:55.8150449Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-12-04T09:14:55.8151137Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-12-04T09:14:55.8152104Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-12-04T09:14:55.8152772Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-12-04T09:14:55.8153731Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-12-04T09:14:55.8154412Z * [new tag] ciflow/inductor/162795 -> ciflow/inductor/162795 2025-12-04T09:14:55.8155540Z * [new tag] ciflow/inductor/163245 -> ciflow/inductor/163245 2025-12-04T09:14:55.8156250Z * [new tag] ciflow/inductor/163335 -> ciflow/inductor/163335 2025-12-04T09:14:55.8157211Z * [new tag] ciflow/inductor/163503 -> ciflow/inductor/163503 2025-12-04T09:14:55.8157892Z * [new tag] ciflow/inductor/163942 -> ciflow/inductor/163942 2025-12-04T09:14:55.8159010Z * [new tag] ciflow/inductor/165270 -> ciflow/inductor/165270 2025-12-04T09:14:55.8159708Z * [new tag] ciflow/inductor/165274 -> ciflow/inductor/165274 2025-12-04T09:14:55.8160685Z * [new tag] ciflow/inductor/165322 -> ciflow/inductor/165322 2025-12-04T09:14:55.8161338Z * [new tag] ciflow/inductor/165597 -> ciflow/inductor/165597 2025-12-04T09:14:55.8162306Z * [new tag] ciflow/inductor/166063 -> ciflow/inductor/166063 2025-12-04T09:14:55.8162958Z * [new tag] ciflow/inductor/166075 -> ciflow/inductor/166075 2025-12-04T09:14:55.8164052Z * [new tag] ciflow/inductor/166165 -> ciflow/inductor/166165 2025-12-04T09:14:55.8165091Z * [new tag] ciflow/inductor/166254 -> ciflow/inductor/166254 2025-12-04T09:14:55.8165890Z * [new tag] ciflow/inductor/166483 -> ciflow/inductor/166483 2025-12-04T09:14:55.8166703Z * [new tag] ciflow/inductor/166494 -> ciflow/inductor/166494 2025-12-04T09:14:55.8167622Z * [new tag] ciflow/inductor/166545 -> ciflow/inductor/166545 2025-12-04T09:14:55.8168429Z * [new tag] ciflow/inductor/166788 -> ciflow/inductor/166788 2025-12-04T09:14:55.8169382Z * [new tag] ciflow/inductor/166846 -> ciflow/inductor/166846 2025-12-04T09:14:55.8170225Z * [new tag] ciflow/inductor/167300 -> ciflow/inductor/167300 2025-12-04T09:14:55.8171042Z * [new tag] ciflow/inductor/167407 -> ciflow/inductor/167407 2025-12-04T09:14:55.8171981Z * [new tag] ciflow/inductor/167536 -> ciflow/inductor/167536 2025-12-04T09:14:55.8172811Z * [new tag] ciflow/inductor/167552 -> ciflow/inductor/167552 2025-12-04T09:14:55.8173613Z * [new tag] ciflow/inductor/167555 -> ciflow/inductor/167555 2025-12-04T09:14:55.8174551Z * [new tag] ciflow/inductor/167583 -> ciflow/inductor/167583 2025-12-04T09:14:55.8175358Z * [new tag] ciflow/inductor/167599 -> ciflow/inductor/167599 2025-12-04T09:14:55.8176242Z * [new tag] ciflow/inductor/167647 -> ciflow/inductor/167647 2025-12-04T09:14:55.8176979Z * [new tag] ciflow/inductor/167677 -> ciflow/inductor/167677 2025-12-04T09:14:55.8177834Z * [new tag] ciflow/inductor/167680 -> ciflow/inductor/167680 2025-12-04T09:14:55.8178643Z * [new tag] ciflow/inductor/167695 -> ciflow/inductor/167695 2025-12-04T09:14:55.8179522Z * [new tag] ciflow/inductor/167742 -> ciflow/inductor/167742 2025-12-04T09:14:55.8180313Z * [new tag] ciflow/inductor/167768 -> ciflow/inductor/167768 2025-12-04T09:14:55.8181468Z * [new tag] ciflow/inductor/167773 -> ciflow/inductor/167773 2025-12-04T09:14:55.8182326Z * [new tag] ciflow/inductor/167781 -> ciflow/inductor/167781 2025-12-04T09:14:55.8183162Z * [new tag] ciflow/inductor/167880 -> ciflow/inductor/167880 2025-12-04T09:14:55.8183964Z * [new tag] ciflow/inductor/167887 -> ciflow/inductor/167887 2025-12-04T09:14:55.8184756Z * [new tag] ciflow/inductor/167972 -> ciflow/inductor/167972 2025-12-04T09:14:55.8185579Z * [new tag] ciflow/inductor/167989 -> ciflow/inductor/167989 2025-12-04T09:14:55.8186411Z * [new tag] ciflow/inductor/168002 -> ciflow/inductor/168002 2025-12-04T09:14:55.8187208Z * [new tag] ciflow/inductor/168050 -> ciflow/inductor/168050 2025-12-04T09:14:55.8188035Z * [new tag] ciflow/inductor/168051 -> ciflow/inductor/168051 2025-12-04T09:14:55.8188840Z * [new tag] ciflow/inductor/168052 -> ciflow/inductor/168052 2025-12-04T09:14:55.8189734Z * [new tag] ciflow/inductor/168073 -> ciflow/inductor/168073 2025-12-04T09:14:55.8190430Z * [new tag] ciflow/inductor/168096 -> ciflow/inductor/168096 2025-12-04T09:14:55.8191249Z * [new tag] ciflow/inductor/168114 -> ciflow/inductor/168114 2025-12-04T09:14:55.8192010Z * [new tag] ciflow/inductor/168115 -> ciflow/inductor/168115 2025-12-04T09:14:55.8193062Z * [new tag] ciflow/inductor/168127 -> ciflow/inductor/168127 2025-12-04T09:14:55.8193610Z * [new tag] ciflow/inductor/168129 -> ciflow/inductor/168129 2025-12-04T09:14:55.8194750Z * [new tag] ciflow/inductor/168157 -> ciflow/inductor/168157 2025-12-04T09:14:55.8195536Z * [new tag] ciflow/inductor/168175 -> ciflow/inductor/168175 2025-12-04T09:14:55.8196310Z * [new tag] ciflow/inductor/168185 -> ciflow/inductor/168185 2025-12-04T09:14:55.8197100Z * [new tag] ciflow/inductor/168195 -> ciflow/inductor/168195 2025-12-04T09:14:55.8197902Z * [new tag] ciflow/inductor/168209 -> ciflow/inductor/168209 2025-12-04T09:14:55.8198717Z * [new tag] ciflow/inductor/168266 -> ciflow/inductor/168266 2025-12-04T09:14:55.8199550Z * [new tag] ciflow/inductor/168316 -> ciflow/inductor/168316 2025-12-04T09:14:55.8200513Z * [new tag] ciflow/inductor/168326 -> ciflow/inductor/168326 2025-12-04T09:14:55.8201333Z * [new tag] ciflow/inductor/168368 -> ciflow/inductor/168368 2025-12-04T09:14:55.8202159Z * [new tag] ciflow/inductor/168894 -> ciflow/inductor/168894 2025-12-04T09:14:55.8203001Z * [new tag] ciflow/inductor/168934 -> ciflow/inductor/168934 2025-12-04T09:14:55.8204374Z * [new tag] ciflow/inductor/168939 -> ciflow/inductor/168939 2025-12-04T09:14:55.8205191Z * [new tag] ciflow/inductor/168946 -> ciflow/inductor/168946 2025-12-04T09:14:55.8205963Z * [new tag] ciflow/inductor/168950 -> ciflow/inductor/168950 2025-12-04T09:14:55.8206818Z * [new tag] ciflow/inductor/168951 -> ciflow/inductor/168951 2025-12-04T09:14:55.8207653Z * [new tag] ciflow/inductor/168952 -> ciflow/inductor/168952 2025-12-04T09:14:55.8208455Z * [new tag] ciflow/inductor/168955 -> ciflow/inductor/168955 2025-12-04T09:14:55.8209246Z * [new tag] ciflow/inductor/168971 -> ciflow/inductor/168971 2025-12-04T09:14:55.8210071Z * [new tag] ciflow/inductor/168979 -> ciflow/inductor/168979 2025-12-04T09:14:55.8210915Z * [new tag] ciflow/inductor/168980 -> ciflow/inductor/168980 2025-12-04T09:14:55.8211857Z * [new tag] ciflow/inductor/168983 -> ciflow/inductor/168983 2025-12-04T09:14:55.8212676Z * [new tag] ciflow/inductor/169006 -> ciflow/inductor/169006 2025-12-04T09:14:55.8213570Z * [new tag] ciflow/inductor/169023 -> ciflow/inductor/169023 2025-12-04T09:14:55.8214387Z * [new tag] ciflow/inductor/169024 -> ciflow/inductor/169024 2025-12-04T09:14:55.8215238Z * [new tag] ciflow/inductor/169025 -> ciflow/inductor/169025 2025-12-04T09:14:55.8216004Z * [new tag] ciflow/inductor/169066 -> ciflow/inductor/169066 2025-12-04T09:14:55.8216852Z * [new tag] ciflow/inductor/169091 -> ciflow/inductor/169091 2025-12-04T09:14:55.8217649Z * [new tag] ciflow/inductor/169102 -> ciflow/inductor/169102 2025-12-04T09:14:55.8218476Z * [new tag] ciflow/inductor/169103 -> ciflow/inductor/169103 2025-12-04T09:14:55.8219483Z * [new tag] ciflow/inductor/169121 -> ciflow/inductor/169121 2025-12-04T09:14:55.8220336Z * [new tag] ciflow/inductor/169134 -> ciflow/inductor/169134 2025-12-04T09:14:55.8221165Z * [new tag] ciflow/inductor/169135 -> ciflow/inductor/169135 2025-12-04T09:14:55.8222076Z * [new tag] ciflow/inductor/169141 -> ciflow/inductor/169141 2025-12-04T09:14:55.8222929Z * [new tag] ciflow/inductor/169151 -> ciflow/inductor/169151 2025-12-04T09:14:55.8223863Z * [new tag] ciflow/inductor/169161 -> ciflow/inductor/169161 2025-12-04T09:14:55.8224686Z * [new tag] ciflow/inductor/169167 -> ciflow/inductor/169167 2025-12-04T09:14:55.8225695Z * [new tag] ciflow/inductor/169177 -> ciflow/inductor/169177 2025-12-04T09:14:55.8226704Z * [new tag] ciflow/inductor/169185 -> ciflow/inductor/169185 2025-12-04T09:14:55.8227515Z * [new tag] ciflow/inductor/169196 -> ciflow/inductor/169196 2025-12-04T09:14:55.8228301Z * [new tag] ciflow/inductor/169200 -> ciflow/inductor/169200 2025-12-04T09:14:55.8229136Z * [new tag] ciflow/inductor/169204 -> ciflow/inductor/169204 2025-12-04T09:14:55.8230038Z * [new tag] ciflow/inductor/169216 -> ciflow/inductor/169216 2025-12-04T09:14:55.8230766Z * [new tag] ciflow/inductor/169219 -> ciflow/inductor/169219 2025-12-04T09:14:55.8231551Z * [new tag] ciflow/inductor/169220 -> ciflow/inductor/169220 2025-12-04T09:14:55.8232753Z * [new tag] ciflow/inductor/169230 -> ciflow/inductor/169230 2025-12-04T09:14:55.8233401Z * [new tag] ciflow/inductor/169242 -> ciflow/inductor/169242 2025-12-04T09:14:55.8234541Z * [new tag] ciflow/inductor/169245 -> ciflow/inductor/169245 2025-12-04T09:14:55.8235158Z * [new tag] ciflow/inductor/169260 -> ciflow/inductor/169260 2025-12-04T09:14:55.8236234Z * [new tag] ciflow/inductor/169282 -> ciflow/inductor/169282 2025-12-04T09:14:55.8236980Z * [new tag] ciflow/inductor/169286 -> ciflow/inductor/169286 2025-12-04T09:14:55.8237801Z * [new tag] ciflow/inductor/169299 -> ciflow/inductor/169299 2025-12-04T09:14:55.8238739Z * [new tag] ciflow/inductor/169304 -> ciflow/inductor/169304 2025-12-04T09:14:55.8240186Z * [new tag] ciflow/inductor/169305 -> ciflow/inductor/169305 2025-12-04T09:14:55.8241018Z * [new tag] ciflow/inductor/169308 -> ciflow/inductor/169308 2025-12-04T09:14:55.8241720Z * [new tag] ciflow/inductor/169319 -> ciflow/inductor/169319 2025-12-04T09:14:55.8242698Z * [new tag] ciflow/inductor/169326 -> ciflow/inductor/169326 2025-12-04T09:14:55.8243898Z * [new tag] ciflow/inductor/169332 -> ciflow/inductor/169332 2025-12-04T09:14:55.8244570Z * [new tag] ciflow/inductor/169333 -> ciflow/inductor/169333 2025-12-04T09:14:55.8245832Z * [new tag] ciflow/inductor/169336 -> ciflow/inductor/169336 2025-12-04T09:14:55.8246438Z * [new tag] ciflow/inductor/169340 -> ciflow/inductor/169340 2025-12-04T09:14:55.8247559Z * [new tag] ciflow/inductor/169341 -> ciflow/inductor/169341 2025-12-04T09:14:55.8248198Z * [new tag] ciflow/inductor/169343 -> ciflow/inductor/169343 2025-12-04T09:14:55.8249230Z * [new tag] ciflow/inductor/169346 -> ciflow/inductor/169346 2025-12-04T09:14:55.8250331Z * [new tag] ciflow/inductor/169348 -> ciflow/inductor/169348 2025-12-04T09:14:55.8251167Z * [new tag] ciflow/inductor/169350 -> ciflow/inductor/169350 2025-12-04T09:14:55.8252024Z * [new tag] ciflow/inductor/169355 -> ciflow/inductor/169355 2025-12-04T09:14:55.8252850Z * [new tag] ciflow/inductor/169370 -> ciflow/inductor/169370 2025-12-04T09:14:55.8254126Z * [new tag] ciflow/inductor/169375 -> ciflow/inductor/169375 2025-12-04T09:14:55.8254749Z * [new tag] ciflow/inductor/169389 -> ciflow/inductor/169389 2025-12-04T09:14:55.8255780Z * [new tag] ciflow/inductor/169391 -> ciflow/inductor/169391 2025-12-04T09:14:55.8256555Z * [new tag] ciflow/inductor/169393 -> ciflow/inductor/169393 2025-12-04T09:14:55.8257352Z * [new tag] ciflow/inductor/169399 -> ciflow/inductor/169399 2025-12-04T09:14:55.8258326Z * [new tag] ciflow/inductor/169400 -> ciflow/inductor/169400 2025-12-04T09:14:55.8259210Z * [new tag] ciflow/inductor/169415 -> ciflow/inductor/169415 2025-12-04T09:14:55.8260170Z * [new tag] ciflow/inductor/169417 -> ciflow/inductor/169417 2025-12-04T09:14:55.8261374Z * [new tag] ciflow/inductor/169418 -> ciflow/inductor/169418 2025-12-04T09:14:55.8262333Z * [new tag] ciflow/inductor/169430 -> ciflow/inductor/169430 2025-12-04T09:14:55.8263208Z * [new tag] ciflow/inductor/169432 -> ciflow/inductor/169432 2025-12-04T09:14:55.8264030Z * [new tag] ciflow/inductor/169436 -> ciflow/inductor/169436 2025-12-04T09:14:55.8265000Z * [new tag] ciflow/inductor/169437 -> ciflow/inductor/169437 2025-12-04T09:14:55.8265842Z * [new tag] ciflow/inductor/169438 -> ciflow/inductor/169438 2025-12-04T09:14:55.8266643Z * [new tag] ciflow/inductor/169441 -> ciflow/inductor/169441 2025-12-04T09:14:55.8267488Z * [new tag] ciflow/inductor/169446 -> ciflow/inductor/169446 2025-12-04T09:14:55.8268453Z * [new tag] ciflow/inductor/169447 -> ciflow/inductor/169447 2025-12-04T09:14:55.8269286Z * [new tag] ciflow/inductor/169452 -> ciflow/inductor/169452 2025-12-04T09:14:55.8270289Z * [new tag] ciflow/inductor/169455 -> ciflow/inductor/169455 2025-12-04T09:14:55.8271123Z * [new tag] ciflow/inductor/169459 -> ciflow/inductor/169459 2025-12-04T09:14:55.8272084Z * [new tag] ciflow/inductor/169463 -> ciflow/inductor/169463 2025-12-04T09:14:55.8273031Z * [new tag] ciflow/inductor/169476 -> ciflow/inductor/169476 2025-12-04T09:14:55.8273893Z * [new tag] ciflow/inductor/169485 -> ciflow/inductor/169485 2025-12-04T09:14:55.8274704Z * [new tag] ciflow/inductor/169493 -> ciflow/inductor/169493 2025-12-04T09:14:55.8275524Z * [new tag] ciflow/inductor/169496 -> ciflow/inductor/169496 2025-12-04T09:14:55.8276374Z * [new tag] ciflow/inductor/169497 -> ciflow/inductor/169497 2025-12-04T09:14:55.8277214Z * [new tag] ciflow/inductor/169503 -> ciflow/inductor/169503 2025-12-04T09:14:55.8278058Z * [new tag] ciflow/inductor/169504 -> ciflow/inductor/169504 2025-12-04T09:14:55.8279237Z * [new tag] ciflow/inductor/169505 -> ciflow/inductor/169505 2025-12-04T09:14:55.8280606Z * [new tag] ciflow/inductor/169508 -> ciflow/inductor/169508 2025-12-04T09:14:55.8281389Z * [new tag] ciflow/inductor/169509 -> ciflow/inductor/169509 2025-12-04T09:14:55.8282248Z * [new tag] ciflow/inductor/169513 -> ciflow/inductor/169513 2025-12-04T09:14:55.8283092Z * [new tag] ciflow/inductor/169514 -> ciflow/inductor/169514 2025-12-04T09:14:55.8283879Z * [new tag] ciflow/inductor/169515 -> ciflow/inductor/169515 2025-12-04T09:14:55.8284821Z * [new tag] ciflow/inductor/169517 -> ciflow/inductor/169517 2025-12-04T09:14:55.8285667Z * [new tag] ciflow/inductor/169519 -> ciflow/inductor/169519 2025-12-04T09:14:55.8286573Z * [new tag] ciflow/inductor/169520 -> ciflow/inductor/169520 2025-12-04T09:14:55.8287455Z * [new tag] ciflow/inductor/169521 -> ciflow/inductor/169521 2025-12-04T09:14:55.8288264Z * [new tag] ciflow/inductor/169524 -> ciflow/inductor/169524 2025-12-04T09:14:55.8289115Z * [new tag] ciflow/inductor/169527 -> ciflow/inductor/169527 2025-12-04T09:14:55.8289937Z * [new tag] ciflow/inductor/169528 -> ciflow/inductor/169528 2025-12-04T09:14:55.8290932Z * [new tag] ciflow/inductor/169532 -> ciflow/inductor/169532 2025-12-04T09:14:55.8291715Z * [new tag] ciflow/inductor/169535 -> ciflow/inductor/169535 2025-12-04T09:14:55.8292530Z * [new tag] ciflow/inductor/169536 -> ciflow/inductor/169536 2025-12-04T09:14:55.8293449Z * [new tag] ciflow/inductor/169547 -> ciflow/inductor/169547 2025-12-04T09:14:55.8294292Z * [new tag] ciflow/inductor/169548 -> ciflow/inductor/169548 2025-12-04T09:14:55.8294995Z * [new tag] ciflow/inductor/169549 -> ciflow/inductor/169549 2025-12-04T09:14:55.8295801Z * [new tag] ciflow/inductor/169551 -> ciflow/inductor/169551 2025-12-04T09:14:55.8296874Z * [new tag] ciflow/inductor/169552 -> ciflow/inductor/169552 2025-12-04T09:14:55.8297458Z * [new tag] ciflow/inductor/169553 -> ciflow/inductor/169553 2025-12-04T09:14:55.8298591Z * [new tag] ciflow/inductor/169557 -> ciflow/inductor/169557 2025-12-04T09:14:55.8299384Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-12-04T09:14:55.8300558Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-12-04T09:14:55.8301661Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-12-04T09:14:55.8302372Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-12-04T09:14:55.8303207Z * [new tag] ciflow/linux-aarch64/166075 -> ciflow/linux-aarch64/166075 2025-12-04T09:14:55.8303941Z * [new tag] ciflow/linux-aarch64/166876 -> ciflow/linux-aarch64/166876 2025-12-04T09:14:55.8305025Z * [new tag] ciflow/linux-aarch64/167981 -> ciflow/linux-aarch64/167981 2025-12-04T09:14:55.8305669Z * [new tag] ciflow/mps/166254 -> ciflow/mps/166254 2025-12-04T09:14:55.8306793Z * [new tag] ciflow/mps/169017 -> ciflow/mps/169017 2025-12-04T09:14:55.8307593Z * [new tag] ciflow/mps/169372 -> ciflow/mps/169372 2025-12-04T09:14:55.8308372Z * [new tag] ciflow/mps/169478 -> ciflow/mps/169478 2025-12-04T09:14:55.8309387Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-12-04T09:14:55.8310099Z * [new tag] ciflow/op-benchmark/166075 -> ciflow/op-benchmark/166075 2025-12-04T09:14:55.8310874Z * [new tag] ciflow/op-benchmark/169544 -> ciflow/op-benchmark/169544 2025-12-04T09:14:55.8311937Z * [new tag] ciflow/periodic-rocm-mi200/165997 -> ciflow/periodic-rocm-mi200/165997 2025-12-04T09:14:55.8312827Z * [new tag] ciflow/periodic-rocm-mi200/166517 -> ciflow/periodic-rocm-mi200/166517 2025-12-04T09:14:55.8313630Z * [new tag] ciflow/periodic-rocm-mi200/169063 -> ciflow/periodic-rocm-mi200/169063 2025-12-04T09:14:55.8314447Z * [new tag] ciflow/periodic-rocm-mi200/169425 -> ciflow/periodic-rocm-mi200/169425 2025-12-04T09:14:55.8315400Z * [new tag] ciflow/periodic-rocm-mi300/166517 -> ciflow/periodic-rocm-mi300/166517 2025-12-04T09:14:55.8316126Z * [new tag] ciflow/periodic-rocm-mi300/169063 -> ciflow/periodic-rocm-mi300/169063 2025-12-04T09:14:55.8316880Z * [new tag] ciflow/periodic-rocm-mi300/169425 -> ciflow/periodic-rocm-mi300/169425 2025-12-04T09:14:55.8318172Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-12-04T09:14:55.8318697Z * [new tag] ciflow/periodic/167207 -> ciflow/periodic/167207 2025-12-04T09:14:55.8319819Z * [new tag] ciflow/periodic/167978 -> ciflow/periodic/167978 2025-12-04T09:14:55.8320363Z * [new tag] ciflow/periodic/168096 -> ciflow/periodic/168096 2025-12-04T09:14:55.8321413Z * [new tag] ciflow/periodic/169286 -> ciflow/periodic/169286 2025-12-04T09:14:55.8322098Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-12-04T09:14:55.8323293Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-12-04T09:14:55.8324197Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-12-04T09:14:55.8325381Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-12-04T09:14:55.8326924Z * [new tag] ciflow/periodic/7c648509a7470ace9fb2bae960dd4790f7e943e9 -> ciflow/periodic/7c648509a7470ace9fb2bae960dd4790f7e943e9 2025-12-04T09:14:55.8327775Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-12-04T09:14:55.8329184Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-12-04T09:14:55.8330070Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-12-04T09:14:55.8331156Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-12-04T09:14:55.8332342Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-12-04T09:14:55.8333578Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-12-04T09:14:55.8334632Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-12-04T09:14:55.8335622Z * [new tag] ciflow/pull/167207 -> ciflow/pull/167207 2025-12-04T09:14:55.8336778Z * [new tag] ciflow/quantization-periodic/169207 -> ciflow/quantization-periodic/169207 2025-12-04T09:14:55.8337583Z * [new tag] ciflow/rocm-mi200/165545 -> ciflow/rocm-mi200/165545 2025-12-04T09:14:55.8338385Z * [new tag] ciflow/rocm-mi200/165997 -> ciflow/rocm-mi200/165997 2025-12-04T09:14:55.8339221Z * [new tag] ciflow/rocm-mi200/168096 -> ciflow/rocm-mi200/168096 2025-12-04T09:14:55.8340179Z * [new tag] ciflow/rocm-mi200/168275 -> ciflow/rocm-mi200/168275 2025-12-04T09:14:55.8340985Z * [new tag] ciflow/rocm-mi200/169063 -> ciflow/rocm-mi200/169063 2025-12-04T09:14:55.8341932Z * [new tag] ciflow/rocm-mi200/169356 -> ciflow/rocm-mi200/169356 2025-12-04T09:14:55.8342839Z * [new tag] ciflow/rocm-mi200/169425 -> ciflow/rocm-mi200/169425 2025-12-04T09:14:55.8344030Z * [new tag] ciflow/rocm-mi300/165545 -> ciflow/rocm-mi300/165545 2025-12-04T09:14:55.8344741Z * [new tag] ciflow/rocm-mi300/167157 -> ciflow/rocm-mi300/167157 2025-12-04T09:14:55.8345796Z * [new tag] ciflow/rocm-mi300/168096 -> ciflow/rocm-mi300/168096 2025-12-04T09:14:55.8346317Z * [new tag] ciflow/rocm-mi300/169063 -> ciflow/rocm-mi300/169063 2025-12-04T09:14:55.8347370Z * [new tag] ciflow/rocm-mi300/169425 -> ciflow/rocm-mi300/169425 2025-12-04T09:14:55.8348051Z * [new tag] ciflow/rocm-mi355/167157 -> ciflow/rocm-mi355/167157 2025-12-04T09:14:55.8349141Z * [new tag] ciflow/rocm-mi355/168275 -> ciflow/rocm-mi355/168275 2025-12-04T09:14:55.8349670Z * [new tag] ciflow/rocm-mi355/169425 -> ciflow/rocm-mi355/169425 2025-12-04T09:14:55.8350852Z * [new tag] ciflow/rocm-navi31/168275 -> ciflow/rocm-navi31/168275 2025-12-04T09:14:55.8351380Z * [new tag] ciflow/rocm-navi31/169425 -> ciflow/rocm-navi31/169425 2025-12-04T09:14:55.8352518Z * [new tag] ciflow/rocm/115316 -> ciflow/rocm/115316 2025-12-04T09:14:55.8353061Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-12-04T09:14:55.8354512Z * [new tag] ciflow/rocm/160685 -> ciflow/rocm/160685 2025-12-04T09:14:55.8355306Z * [new tag] ciflow/rocm/161607 -> ciflow/rocm/161607 2025-12-04T09:14:55.8356094Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-12-04T09:14:55.8356803Z * [new tag] ciflow/rocm/165997 -> ciflow/rocm/165997 2025-12-04T09:14:55.8357839Z * [new tag] ciflow/rocm/166165 -> ciflow/rocm/166165 2025-12-04T09:14:55.8358420Z * [new tag] ciflow/rocm/166517 -> ciflow/rocm/166517 2025-12-04T09:14:55.8359176Z * [new tag] ciflow/rocm/167207 -> ciflow/rocm/167207 2025-12-04T09:14:55.8360011Z * [new tag] ciflow/rocm/167536 -> ciflow/rocm/167536 2025-12-04T09:14:55.8360739Z * [new tag] ciflow/rocm/167781 -> ciflow/rocm/167781 2025-12-04T09:14:55.8361991Z * [new tag] ciflow/rocm/167989 -> ciflow/rocm/167989 2025-12-04T09:14:55.8362873Z * [new tag] ciflow/rocm/168073 -> ciflow/rocm/168073 2025-12-04T09:14:55.8363912Z * [new tag] ciflow/rocm/168195 -> ciflow/rocm/168195 2025-12-04T09:14:55.8364709Z * [new tag] ciflow/rocm/168939 -> ciflow/rocm/168939 2025-12-04T09:14:55.8365608Z * [new tag] ciflow/rocm/168971 -> ciflow/rocm/168971 2025-12-04T09:14:55.8366450Z * [new tag] ciflow/rocm/169024 -> ciflow/rocm/169024 2025-12-04T09:14:55.8367251Z * [new tag] ciflow/rocm/169200 -> ciflow/rocm/169200 2025-12-04T09:14:55.8368073Z * [new tag] ciflow/rocm/169216 -> ciflow/rocm/169216 2025-12-04T09:14:55.8368887Z * [new tag] ciflow/rocm/169312 -> ciflow/rocm/169312 2025-12-04T09:14:55.8369730Z * [new tag] ciflow/rocm/169380 -> ciflow/rocm/169380 2025-12-04T09:14:55.8370575Z * [new tag] ciflow/rocm/169427 -> ciflow/rocm/169427 2025-12-04T09:14:55.8371377Z * [new tag] ciflow/rocm/169455 -> ciflow/rocm/169455 2025-12-04T09:14:55.8372198Z * [new tag] ciflow/rocm/169470 -> ciflow/rocm/169470 2025-12-04T09:14:55.8372990Z * [new tag] ciflow/rocm/169471 -> ciflow/rocm/169471 2025-12-04T09:14:55.8373845Z * [new tag] ciflow/rocm/169472 -> ciflow/rocm/169472 2025-12-04T09:14:55.8374649Z * [new tag] ciflow/rocm/169514 -> ciflow/rocm/169514 2025-12-04T09:14:55.8375942Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-12-04T09:14:55.8376758Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-12-04T09:14:55.8378364Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-12-04T09:14:55.8378738Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-12-04T09:14:55.8379537Z * [new tag] ciflow/slow/167207 -> ciflow/slow/167207 2025-12-04T09:14:55.8380270Z * [new tag] ciflow/slow/168050 -> ciflow/slow/168050 2025-12-04T09:14:55.8381434Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-12-04T09:14:55.8382618Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-12-04T09:14:55.8383864Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-12-04T09:14:55.8385020Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-12-04T09:14:55.8386275Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-12-04T09:14:55.8387084Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-12-04T09:14:55.8388262Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-12-04T09:14:55.8389052Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-12-04T09:14:55.8390670Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-12-04T09:14:55.8391150Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-12-04T09:14:55.8392390Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-12-04T09:14:55.8393150Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-12-04T09:14:55.8394331Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-12-04T09:14:55.8395231Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-12-04T09:14:55.8396913Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-12-04T09:14:55.8397861Z * [new tag] ciflow/torchbench/168175 -> ciflow/torchbench/168175 2025-12-04T09:14:55.8398780Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-12-04T09:14:55.8399564Z * [new tag] ciflow/trunk/157149 -> ciflow/trunk/157149 2025-12-04T09:14:55.8400332Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-12-04T09:14:55.8401136Z * [new tag] ciflow/trunk/159718 -> ciflow/trunk/159718 2025-12-04T09:14:55.8401909Z * [new tag] ciflow/trunk/160685 -> ciflow/trunk/160685 2025-12-04T09:14:55.8402658Z * [new tag] ciflow/trunk/160729 -> ciflow/trunk/160729 2025-12-04T09:14:55.8403488Z * [new tag] ciflow/trunk/162275 -> ciflow/trunk/162275 2025-12-04T09:14:55.8404296Z * [new tag] ciflow/trunk/162795 -> ciflow/trunk/162795 2025-12-04T09:14:55.8405162Z * [new tag] ciflow/trunk/163245 -> ciflow/trunk/163245 2025-12-04T09:14:55.8405844Z * [new tag] ciflow/trunk/163942 -> ciflow/trunk/163942 2025-12-04T09:14:55.8406693Z * [new tag] ciflow/trunk/165274 -> ciflow/trunk/165274 2025-12-04T09:14:55.8408017Z * [new tag] ciflow/trunk/165483 -> ciflow/trunk/165483 2025-12-04T09:14:55.8408943Z * [new tag] ciflow/trunk/165728 -> ciflow/trunk/165728 2025-12-04T09:14:55.8409912Z * [new tag] ciflow/trunk/165922 -> ciflow/trunk/165922 2025-12-04T09:14:55.8410724Z * [new tag] ciflow/trunk/166075 -> ciflow/trunk/166075 2025-12-04T09:14:55.8411661Z * [new tag] ciflow/trunk/166165 -> ciflow/trunk/166165 2025-12-04T09:14:55.8412461Z * [new tag] ciflow/trunk/166829 -> ciflow/trunk/166829 2025-12-04T09:14:55.8413413Z * [new tag] ciflow/trunk/166843 -> ciflow/trunk/166843 2025-12-04T09:14:55.8414325Z * [new tag] ciflow/trunk/166876 -> ciflow/trunk/166876 2025-12-04T09:14:55.8415132Z * [new tag] ciflow/trunk/167207 -> ciflow/trunk/167207 2025-12-04T09:14:55.8415980Z * [new tag] ciflow/trunk/167536 -> ciflow/trunk/167536 2025-12-04T09:14:55.8416790Z * [new tag] ciflow/trunk/167552 -> ciflow/trunk/167552 2025-12-04T09:14:55.8417644Z * [new tag] ciflow/trunk/167555 -> ciflow/trunk/167555 2025-12-04T09:14:55.8418489Z * [new tag] ciflow/trunk/167599 -> ciflow/trunk/167599 2025-12-04T09:14:55.8419315Z * [new tag] ciflow/trunk/167659 -> ciflow/trunk/167659 2025-12-04T09:14:55.8420267Z * [new tag] ciflow/trunk/167672 -> ciflow/trunk/167672 2025-12-04T09:14:55.8421085Z * [new tag] ciflow/trunk/167742 -> ciflow/trunk/167742 2025-12-04T09:14:55.8421923Z * [new tag] ciflow/trunk/167781 -> ciflow/trunk/167781 2025-12-04T09:14:55.8423103Z * [new tag] ciflow/trunk/167837 -> ciflow/trunk/167837 2025-12-04T09:14:55.8423758Z * [new tag] ciflow/trunk/167887 -> ciflow/trunk/167887 2025-12-04T09:14:55.8424633Z * [new tag] ciflow/trunk/167978 -> ciflow/trunk/167978 2025-12-04T09:14:55.8425528Z * [new tag] ciflow/trunk/168050 -> ciflow/trunk/168050 2025-12-04T09:14:55.8426332Z * [new tag] ciflow/trunk/168051 -> ciflow/trunk/168051 2025-12-04T09:14:55.8427122Z * [new tag] ciflow/trunk/168096 -> ciflow/trunk/168096 2025-12-04T09:14:55.8427963Z * [new tag] ciflow/trunk/168127 -> ciflow/trunk/168127 2025-12-04T09:14:55.8428789Z * [new tag] ciflow/trunk/168157 -> ciflow/trunk/168157 2025-12-04T09:14:55.8429610Z * [new tag] ciflow/trunk/168175 -> ciflow/trunk/168175 2025-12-04T09:14:55.8430430Z * [new tag] ciflow/trunk/168209 -> ciflow/trunk/168209 2025-12-04T09:14:55.8431975Z * [new tag] ciflow/trunk/168213 -> ciflow/trunk/168213 2025-12-04T09:14:55.8432817Z * [new tag] ciflow/trunk/168226 -> ciflow/trunk/168226 2025-12-04T09:14:55.8433653Z * [new tag] ciflow/trunk/168262 -> ciflow/trunk/168262 2025-12-04T09:14:55.8434494Z * [new tag] ciflow/trunk/168275 -> ciflow/trunk/168275 2025-12-04T09:14:55.8435426Z * [new tag] ciflow/trunk/168328 -> ciflow/trunk/168328 2025-12-04T09:14:55.8436252Z * [new tag] ciflow/trunk/168368 -> ciflow/trunk/168368 2025-12-04T09:14:55.8437087Z * [new tag] ciflow/trunk/168917 -> ciflow/trunk/168917 2025-12-04T09:14:55.8437893Z * [new tag] ciflow/trunk/168933 -> ciflow/trunk/168933 2025-12-04T09:14:55.8438870Z * [new tag] ciflow/trunk/168941 -> ciflow/trunk/168941 2025-12-04T09:14:55.8439799Z * [new tag] ciflow/trunk/168955 -> ciflow/trunk/168955 2025-12-04T09:14:55.8440637Z * [new tag] ciflow/trunk/168980 -> ciflow/trunk/168980 2025-12-04T09:14:55.8441683Z * [new tag] ciflow/trunk/169004 -> ciflow/trunk/169004 2025-12-04T09:14:55.8442719Z * [new tag] ciflow/trunk/169006 -> ciflow/trunk/169006 2025-12-04T09:14:55.8443600Z * [new tag] ciflow/trunk/169023 -> ciflow/trunk/169023 2025-12-04T09:14:55.8444478Z * [new tag] ciflow/trunk/169025 -> ciflow/trunk/169025 2025-12-04T09:14:55.8445381Z * [new tag] ciflow/trunk/169048 -> ciflow/trunk/169048 2025-12-04T09:14:55.8446257Z * [new tag] ciflow/trunk/169066 -> ciflow/trunk/169066 2025-12-04T09:14:55.8447095Z * [new tag] ciflow/trunk/169091 -> ciflow/trunk/169091 2025-12-04T09:14:55.8447913Z * [new tag] ciflow/trunk/169102 -> ciflow/trunk/169102 2025-12-04T09:14:55.8448727Z * [new tag] ciflow/trunk/169103 -> ciflow/trunk/169103 2025-12-04T09:14:55.8449681Z * [new tag] ciflow/trunk/169125 -> ciflow/trunk/169125 2025-12-04T09:14:55.8450625Z * [new tag] ciflow/trunk/169139 -> ciflow/trunk/169139 2025-12-04T09:14:55.8451574Z * [new tag] ciflow/trunk/169148 -> ciflow/trunk/169148 2025-12-04T09:14:55.8452409Z * [new tag] ciflow/trunk/169151 -> ciflow/trunk/169151 2025-12-04T09:14:55.8453295Z * [new tag] ciflow/trunk/169156 -> ciflow/trunk/169156 2025-12-04T09:14:55.8454243Z * [new tag] ciflow/trunk/169176 -> ciflow/trunk/169176 2025-12-04T09:14:55.8455083Z * [new tag] ciflow/trunk/169204 -> ciflow/trunk/169204 2025-12-04T09:14:55.8455934Z * [new tag] ciflow/trunk/169207 -> ciflow/trunk/169207 2025-12-04T09:14:55.8456757Z * [new tag] ciflow/trunk/169211 -> ciflow/trunk/169211 2025-12-04T09:14:55.8458030Z * [new tag] ciflow/trunk/169231 -> ciflow/trunk/169231 2025-12-04T09:14:55.8458765Z * [new tag] ciflow/trunk/169260 -> ciflow/trunk/169260 2025-12-04T09:14:55.8459906Z * [new tag] ciflow/trunk/169271 -> ciflow/trunk/169271 2025-12-04T09:14:55.8460482Z * [new tag] ciflow/trunk/169280 -> ciflow/trunk/169280 2025-12-04T09:14:55.8461580Z * [new tag] ciflow/trunk/169281 -> ciflow/trunk/169281 2025-12-04T09:14:55.8462149Z * [new tag] ciflow/trunk/169286 -> ciflow/trunk/169286 2025-12-04T09:14:55.8463388Z * [new tag] ciflow/trunk/169293 -> ciflow/trunk/169293 2025-12-04T09:14:55.8464077Z * [new tag] ciflow/trunk/169296 -> ciflow/trunk/169296 2025-12-04T09:14:55.8464938Z * [new tag] ciflow/trunk/169304 -> ciflow/trunk/169304 2025-12-04T09:14:55.8465769Z * [new tag] ciflow/trunk/169305 -> ciflow/trunk/169305 2025-12-04T09:14:55.8466568Z * [new tag] ciflow/trunk/169312 -> ciflow/trunk/169312 2025-12-04T09:14:55.8467885Z * [new tag] ciflow/trunk/169328 -> ciflow/trunk/169328 2025-12-04T09:14:55.8468660Z * [new tag] ciflow/trunk/169343 -> ciflow/trunk/169343 2025-12-04T09:14:55.8469520Z * [new tag] ciflow/trunk/169355 -> ciflow/trunk/169355 2025-12-04T09:14:55.8470399Z * [new tag] ciflow/trunk/169370 -> ciflow/trunk/169370 2025-12-04T09:14:55.8471555Z * [new tag] ciflow/trunk/169379 -> ciflow/trunk/169379 2025-12-04T09:14:55.8472179Z * [new tag] ciflow/trunk/169380 -> ciflow/trunk/169380 2025-12-04T09:14:55.8473258Z * [new tag] ciflow/trunk/169385 -> ciflow/trunk/169385 2025-12-04T09:14:55.8473765Z * [new tag] ciflow/trunk/169387 -> ciflow/trunk/169387 2025-12-04T09:14:55.8474961Z * [new tag] ciflow/trunk/169410 -> ciflow/trunk/169410 2025-12-04T09:14:55.8475563Z * [new tag] ciflow/trunk/169412 -> ciflow/trunk/169412 2025-12-04T09:14:55.8476639Z * [new tag] ciflow/trunk/169418 -> ciflow/trunk/169418 2025-12-04T09:14:55.8477259Z * [new tag] ciflow/trunk/169423 -> ciflow/trunk/169423 2025-12-04T09:14:55.8478279Z * [new tag] ciflow/trunk/169427 -> ciflow/trunk/169427 2025-12-04T09:14:55.8478879Z * [new tag] ciflow/trunk/169430 -> ciflow/trunk/169430 2025-12-04T09:14:55.8479969Z * [new tag] ciflow/trunk/169437 -> ciflow/trunk/169437 2025-12-04T09:14:55.8480576Z * [new tag] ciflow/trunk/169442 -> ciflow/trunk/169442 2025-12-04T09:14:55.8481667Z * [new tag] ciflow/trunk/169452 -> ciflow/trunk/169452 2025-12-04T09:14:55.8482342Z * [new tag] ciflow/trunk/169454 -> ciflow/trunk/169454 2025-12-04T09:14:55.8483154Z * [new tag] ciflow/trunk/169459 -> ciflow/trunk/169459 2025-12-04T09:14:55.8484288Z * [new tag] ciflow/trunk/169474 -> ciflow/trunk/169474 2025-12-04T09:14:55.8485007Z * [new tag] ciflow/trunk/169475 -> ciflow/trunk/169475 2025-12-04T09:14:55.8485865Z * [new tag] ciflow/trunk/169476 -> ciflow/trunk/169476 2025-12-04T09:14:55.8486880Z * [new tag] ciflow/trunk/169487 -> ciflow/trunk/169487 2025-12-04T09:14:55.8487731Z * [new tag] ciflow/trunk/169497 -> ciflow/trunk/169497 2025-12-04T09:14:55.8489109Z * [new tag] ciflow/trunk/169503 -> ciflow/trunk/169503 2025-12-04T09:14:55.8489728Z * [new tag] ciflow/trunk/169505 -> ciflow/trunk/169505 2025-12-04T09:14:55.8490644Z * [new tag] ciflow/trunk/169507 -> ciflow/trunk/169507 2025-12-04T09:14:55.8491479Z * [new tag] ciflow/trunk/169514 -> ciflow/trunk/169514 2025-12-04T09:14:55.8492385Z * [new tag] ciflow/trunk/169517 -> ciflow/trunk/169517 2025-12-04T09:14:55.8493355Z * [new tag] ciflow/trunk/169519 -> ciflow/trunk/169519 2025-12-04T09:14:55.8494162Z * [new tag] ciflow/trunk/169528 -> ciflow/trunk/169528 2025-12-04T09:14:55.8495043Z * [new tag] ciflow/trunk/169541 -> ciflow/trunk/169541 2025-12-04T09:14:55.8495950Z * [new tag] ciflow/trunk/169555 -> ciflow/trunk/169555 2025-12-04T09:14:55.8497462Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-12-04T09:14:55.8498337Z * [new tag] ciflow/vllm/165270 -> ciflow/vllm/165270 2025-12-04T09:14:55.8499163Z * [new tag] ciflow/vllm/165274 -> ciflow/vllm/165274 2025-12-04T09:14:55.8499915Z * [new tag] ciflow/vllm/166494 -> ciflow/vllm/166494 2025-12-04T09:14:55.8500732Z * [new tag] ciflow/vllm/169219 -> ciflow/vllm/169219 2025-12-04T09:14:55.8501521Z * [new tag] ciflow/vllm/169220 -> ciflow/vllm/169220 2025-12-04T09:14:55.8502559Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-12-04T09:14:55.8503193Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-12-04T09:14:55.8504010Z * [new tag] ciflow/xpu/161940 -> ciflow/xpu/161940 2025-12-04T09:14:55.8504915Z * [new tag] ciflow/xpu/163251 -> ciflow/xpu/163251 2025-12-04T09:14:55.8505748Z * [new tag] ciflow/xpu/166829 -> ciflow/xpu/166829 2025-12-04T09:14:55.8506533Z * [new tag] ciflow/xpu/166843 -> ciflow/xpu/166843 2025-12-04T09:14:55.8507282Z * [new tag] ciflow/xpu/167972 -> ciflow/xpu/167972 2025-12-04T09:14:55.8508070Z * [new tag] ciflow/xpu/167981 -> ciflow/xpu/167981 2025-12-04T09:14:55.8508892Z * [new tag] ciflow/xpu/168213 -> ciflow/xpu/168213 2025-12-04T09:14:55.8509629Z * [new tag] ciflow/xpu/168262 -> ciflow/xpu/168262 2025-12-04T09:14:55.8510442Z * [new tag] ciflow/xpu/168328 -> ciflow/xpu/168328 2025-12-04T09:14:55.8511699Z * [new tag] ciflow/xpu/168950 -> ciflow/xpu/168950 2025-12-04T09:14:55.8512927Z * [new tag] ciflow/xpu/169039 -> ciflow/xpu/169039 2025-12-04T09:14:55.8513747Z * [new tag] ciflow/xpu/169200 -> ciflow/xpu/169200 2025-12-04T09:14:55.8514585Z * [new tag] ciflow/xpu/169203 -> ciflow/xpu/169203 2025-12-04T09:14:55.8515419Z * [new tag] ciflow/xpu/169230 -> ciflow/xpu/169230 2025-12-04T09:14:55.8516267Z * [new tag] ciflow/xpu/169231 -> ciflow/xpu/169231 2025-12-04T09:14:55.8517207Z * [new tag] ciflow/xpu/169241 -> ciflow/xpu/169241 2025-12-04T09:14:55.8518043Z * [new tag] ciflow/xpu/169280 -> ciflow/xpu/169280 2025-12-04T09:14:55.8518866Z * [new tag] ciflow/xpu/169296 -> ciflow/xpu/169296 2025-12-04T09:14:55.8519996Z * [new tag] ciflow/xpu/169353 -> ciflow/xpu/169353 2025-12-04T09:14:55.8520567Z * [new tag] ciflow/xpu/169410 -> ciflow/xpu/169410 2025-12-04T09:14:55.8521633Z * [new tag] ciflow/xpu/169442 -> ciflow/xpu/169442 2025-12-04T09:14:55.8522341Z * [new tag] ciflow/xpu/169555 -> ciflow/xpu/169555 2025-12-04T09:14:55.8523536Z * [new tag] cslpull75 -> cslpull75 2025-12-04T09:14:55.8524338Z * [new tag] cslpull76 -> cslpull76 2025-12-04T09:14:55.8525280Z * [new tag] cslpull77 -> cslpull77 2025-12-04T09:14:55.8526252Z * [new tag] cslpull78 -> cslpull78 2025-12-04T09:14:55.8527506Z * [new tag] cslpull79 -> cslpull79 2025-12-04T09:14:55.8528652Z * [new tag] cslpull80 -> cslpull80 2025-12-04T09:14:55.8529469Z * [new tag] cslpull81 -> cslpull81 2025-12-04T09:14:55.8530614Z * [new tag] cslpull82 -> cslpull82 2025-12-04T09:14:55.8531431Z * [new tag] cslpull83 -> cslpull83 2025-12-04T09:14:55.8532358Z * [new tag] cslpull84 -> cslpull84 2025-12-04T09:14:55.8533233Z * [new tag] cslpull85 -> cslpull85 2025-12-04T09:14:55.8534430Z * [new tag] cslpull86 -> cslpull86 2025-12-04T09:14:55.8535147Z * [new tag] cslpull87 -> cslpull87 2025-12-04T09:14:55.8536227Z * [new tag] cslpull88 -> cslpull88 2025-12-04T09:14:55.8537059Z * [new tag] cslpull89 -> cslpull89 2025-12-04T09:14:55.8537831Z * [new tag] cslpull90 -> cslpull90 2025-12-04T09:14:55.8539356Z * [new tag] cslpull91 -> cslpull91 2025-12-04T09:14:55.8540133Z * [new tag] cslpull92 -> cslpull92 2025-12-04T09:14:55.8541286Z * [new tag] flight_5 -> flight_5 2025-12-04T09:14:55.8542545Z * [new tag] flight_5.1 -> flight_5.1 2025-12-04T09:14:55.8546741Z * [new tag] flight_5.2 -> flight_5.2 2025-12-04T09:14:55.8547889Z * [new tag] flight_5.3 -> flight_5.3 2025-12-04T09:14:55.8548686Z * [new tag] forpull1 -> forpull1 2025-12-04T09:14:55.8550111Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-12-04T09:14:55.8550930Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-12-04T09:14:55.8551982Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-12-04T09:14:55.8552904Z * [new tag] nightly-binary -> nightly-binary 2025-12-04T09:14:55.8554097Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-12-04T09:14:55.8555133Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-12-04T09:14:55.8556567Z * [new tag] trunk/02d8bd6974cf84b721680d773dbdb1b6f40ce272 -> trunk/02d8bd6974cf84b721680d773dbdb1b6f40ce272 2025-12-04T09:14:55.8557271Z * [new tag] trunk/066997fb38ade71e00d78e9d572e380b5f02bd3e -> trunk/066997fb38ade71e00d78e9d572e380b5f02bd3e 2025-12-04T09:14:55.8558831Z * [new tag] trunk/076e7b19fa1d481ad778d06d2b49ba57d3ce8c88 -> trunk/076e7b19fa1d481ad778d06d2b49ba57d3ce8c88 2025-12-04T09:14:55.8559807Z * [new tag] trunk/07dcc0b83db3211653a38565a24e15acdba75654 -> trunk/07dcc0b83db3211653a38565a24e15acdba75654 2025-12-04T09:14:55.8560813Z * [new tag] trunk/082e96b68dfcd16cab7cfafc4d3d055767dab3eb -> trunk/082e96b68dfcd16cab7cfafc4d3d055767dab3eb 2025-12-04T09:14:55.8561763Z * [new tag] trunk/088048f2fea28ff7d450f65c72419ca45780d30b -> trunk/088048f2fea28ff7d450f65c72419ca45780d30b 2025-12-04T09:14:55.8562748Z * [new tag] trunk/09076941a95c76f4d9ad189d064dfd8baa39e672 -> trunk/09076941a95c76f4d9ad189d064dfd8baa39e672 2025-12-04T09:14:55.8563672Z * [new tag] trunk/0b80a4c62b94402844bf221791c096b0035c6d75 -> trunk/0b80a4c62b94402844bf221791c096b0035c6d75 2025-12-04T09:14:55.8565065Z * [new tag] trunk/0bbbdf1750567a980634ad907a325357ba8ba8f2 -> trunk/0bbbdf1750567a980634ad907a325357ba8ba8f2 2025-12-04T09:14:55.8565984Z * [new tag] trunk/0c281dd78773b2bc17c58ead0e4cd4ac46e775c5 -> trunk/0c281dd78773b2bc17c58ead0e4cd4ac46e775c5 2025-12-04T09:14:55.8566929Z * [new tag] trunk/135f3753c418a6879b1954904184937b67e61688 -> trunk/135f3753c418a6879b1954904184937b67e61688 2025-12-04T09:14:55.8567912Z * [new tag] trunk/15da21026cb13cd20257dc9e96830db108743c10 -> trunk/15da21026cb13cd20257dc9e96830db108743c10 2025-12-04T09:14:55.8568890Z * [new tag] trunk/166efdad2ac827f30fb02504c6017520257f88ec -> trunk/166efdad2ac827f30fb02504c6017520257f88ec 2025-12-04T09:14:55.8569848Z * [new tag] trunk/174272c15fae553d8488140af931f7d8050a313f -> trunk/174272c15fae553d8488140af931f7d8050a313f 2025-12-04T09:14:55.8571232Z * [new tag] trunk/18f3ca08f13b8de61307f5e8cd7d4cccb67e9d11 -> trunk/18f3ca08f13b8de61307f5e8cd7d4cccb67e9d11 2025-12-04T09:14:55.8571959Z * [new tag] trunk/1902eddfe655a15ebcf2c72bd81ade110fdeef63 -> trunk/1902eddfe655a15ebcf2c72bd81ade110fdeef63 2025-12-04T09:14:55.8572982Z * [new tag] trunk/195f92e98d3d66738577f11f22c4b5c8a1c76dd5 -> trunk/195f92e98d3d66738577f11f22c4b5c8a1c76dd5 2025-12-04T09:14:55.8573962Z * [new tag] trunk/1aa13e17de39e3c768ea7aebaad166ce72a06676 -> trunk/1aa13e17de39e3c768ea7aebaad166ce72a06676 2025-12-04T09:14:55.8574901Z * [new tag] trunk/1afe2832f58e24e54a5bfda5a5afa9b96fdea40e -> trunk/1afe2832f58e24e54a5bfda5a5afa9b96fdea40e 2025-12-04T09:14:55.8575857Z * [new tag] trunk/1c87554d74140eaee964ca8b1832cede67f5f520 -> trunk/1c87554d74140eaee964ca8b1832cede67f5f520 2025-12-04T09:14:55.8576863Z * [new tag] trunk/1ccb743b7b5be955f49736c162c4f5004b8a0dd8 -> trunk/1ccb743b7b5be955f49736c162c4f5004b8a0dd8 2025-12-04T09:14:55.8577913Z * [new tag] trunk/1cee47d6ce0a02227185b566593f002dd639ca0c -> trunk/1cee47d6ce0a02227185b566593f002dd639ca0c 2025-12-04T09:14:55.8578658Z * [new tag] trunk/1d21b4df2babe322e5d085ceb6de884eb260a62d -> trunk/1d21b4df2babe322e5d085ceb6de884eb260a62d 2025-12-04T09:14:55.8579722Z * [new tag] trunk/1e34fb2550e4aa650314f7a6d9f6daf4da7478a8 -> trunk/1e34fb2550e4aa650314f7a6d9f6daf4da7478a8 2025-12-04T09:14:55.8580770Z * [new tag] trunk/1e526fb5b1d93bfc70691c5c3955fdffc1b7b7de -> trunk/1e526fb5b1d93bfc70691c5c3955fdffc1b7b7de 2025-12-04T09:14:55.8581762Z * [new tag] trunk/1ee32a8b1f554a312d79bad01ded24f38cd95543 -> trunk/1ee32a8b1f554a312d79bad01ded24f38cd95543 2025-12-04T09:14:55.8582752Z * [new tag] trunk/201e2c4117eb9744594dad6a5c18213d7b4705d7 -> trunk/201e2c4117eb9744594dad6a5c18213d7b4705d7 2025-12-04T09:14:55.8583693Z * [new tag] trunk/2353a0f60eb4b4cb6675907a7fa9fbedc1c02e7f -> trunk/2353a0f60eb4b4cb6675907a7fa9fbedc1c02e7f 2025-12-04T09:14:55.8585022Z * [new tag] trunk/285779b1621cf9f073a062b0889a642d200308d9 -> trunk/285779b1621cf9f073a062b0889a642d200308d9 2025-12-04T09:14:55.8585737Z * [new tag] trunk/2887faaec6295d081580d09fce161201826c6d87 -> trunk/2887faaec6295d081580d09fce161201826c6d87 2025-12-04T09:14:55.8586716Z * [new tag] trunk/296e67c92635443c67b11c0ae1bd045f03ebb7bc -> trunk/296e67c92635443c67b11c0ae1bd045f03ebb7bc 2025-12-04T09:14:55.8587646Z * [new tag] trunk/29856679769b3dede478767e2fe6cfb51197cb25 -> trunk/29856679769b3dede478767e2fe6cfb51197cb25 2025-12-04T09:14:55.8588823Z * [new tag] trunk/29e5455a4740c326ab187c7aa7b5ef98034ea563 -> trunk/29e5455a4740c326ab187c7aa7b5ef98034ea563 2025-12-04T09:14:55.8589774Z * [new tag] trunk/2ac3ef882afb23136adc188975f0a8802fc68adf -> trunk/2ac3ef882afb23136adc188975f0a8802fc68adf 2025-12-04T09:14:55.8590625Z * [new tag] trunk/2bec68e73b64715354af076ad309335f943e36cd -> trunk/2bec68e73b64715354af076ad309335f943e36cd 2025-12-04T09:14:55.8591568Z * [new tag] trunk/2c87367e6f88662cd5cedbd1537748b7948c38e1 -> trunk/2c87367e6f88662cd5cedbd1537748b7948c38e1 2025-12-04T09:14:55.8592625Z * [new tag] trunk/2d1f78fe3ec13820f136a2e0336da12a25f41708 -> trunk/2d1f78fe3ec13820f136a2e0336da12a25f41708 2025-12-04T09:14:55.8593614Z * [new tag] trunk/2df6058f116a65722a0e03073402feb242572d35 -> trunk/2df6058f116a65722a0e03073402feb242572d35 2025-12-04T09:14:55.8594612Z * [new tag] trunk/2e0c2e170fe658c440775c8e5c44228aafcc47ec -> trunk/2e0c2e170fe658c440775c8e5c44228aafcc47ec 2025-12-04T09:14:55.8595658Z * [new tag] trunk/2f9b7dad7b5419b063bd0f2e204de192720ebb94 -> trunk/2f9b7dad7b5419b063bd0f2e204de192720ebb94 2025-12-04T09:14:55.8596629Z * [new tag] trunk/305168768a95d69c444df5cd334bb774edfe06f1 -> trunk/305168768a95d69c444df5cd334bb774edfe06f1 2025-12-04T09:14:55.8597575Z * [new tag] trunk/31fc12773026e8e00f054dd79ad9b2491e693b48 -> trunk/31fc12773026e8e00f054dd79ad9b2491e693b48 2025-12-04T09:14:55.8598516Z * [new tag] trunk/320de0c6b0a3e7c6d2693ea5c28d5d0156ba7991 -> trunk/320de0c6b0a3e7c6d2693ea5c28d5d0156ba7991 2025-12-04T09:14:55.8599483Z * [new tag] trunk/3418bd29475dff06695045fcdf93e7d0dac67da8 -> trunk/3418bd29475dff06695045fcdf93e7d0dac67da8 2025-12-04T09:14:55.8600453Z * [new tag] trunk/34a98608afa0cb5b48f0d6d30432fdd0a2614ddf -> trunk/34a98608afa0cb5b48f0d6d30432fdd0a2614ddf 2025-12-04T09:14:55.8601503Z * [new tag] trunk/35b7a9a26c5923d98aebaa41a031dae21788a9ee -> trunk/35b7a9a26c5923d98aebaa41a031dae21788a9ee 2025-12-04T09:14:55.8602539Z * [new tag] trunk/39d07dbf03a911bdd45d1af78d8638dc92074938 -> trunk/39d07dbf03a911bdd45d1af78d8638dc92074938 2025-12-04T09:14:55.8603394Z * [new tag] trunk/3cd98b4205ada151042cc7ff097a82d4a4b18725 -> trunk/3cd98b4205ada151042cc7ff097a82d4a4b18725 2025-12-04T09:14:55.8604433Z * [new tag] trunk/3d35fd20a78ff4d016fa80f4e5fad37191d7bcae -> trunk/3d35fd20a78ff4d016fa80f4e5fad37191d7bcae 2025-12-04T09:14:55.8605482Z * [new tag] trunk/409a5fee945c46a3edaf5df162812f201bfd7b2f -> trunk/409a5fee945c46a3edaf5df162812f201bfd7b2f 2025-12-04T09:14:55.8606404Z * [new tag] trunk/42e9005cda22da3f1c559c3649218cebd671027c -> trunk/42e9005cda22da3f1c559c3649218cebd671027c 2025-12-04T09:14:55.8607375Z * [new tag] trunk/43b94713bbf340d3c124fde02d0f73add4021247 -> trunk/43b94713bbf340d3c124fde02d0f73add4021247 2025-12-04T09:14:55.8608389Z * [new tag] trunk/44ac69388a4a5eb463dbd2a13f00d1e3b924566c -> trunk/44ac69388a4a5eb463dbd2a13f00d1e3b924566c 2025-12-04T09:14:55.8611200Z * [new tag] trunk/45d14e2497292be06ad36eaa1aaaf7c630a2586a -> trunk/45d14e2497292be06ad36eaa1aaaf7c630a2586a 2025-12-04T09:14:55.8611667Z * [new tag] trunk/45d310ad84854dff730c0b12e577d7998d978686 -> trunk/45d310ad84854dff730c0b12e577d7998d978686 2025-12-04T09:14:55.8612387Z * [new tag] trunk/47b28ddf7bd74b50fa93b307a7d3b183a6d77f54 -> trunk/47b28ddf7bd74b50fa93b307a7d3b183a6d77f54 2025-12-04T09:14:55.8613008Z * [new tag] trunk/481e5ab336275bd3acd5fa8a611b05b4469012af -> trunk/481e5ab336275bd3acd5fa8a611b05b4469012af 2025-12-04T09:14:55.8613511Z * [new tag] trunk/491731647f6b8a9345dcfb3bc9416aea254a7d96 -> trunk/491731647f6b8a9345dcfb3bc9416aea254a7d96 2025-12-04T09:14:55.8613986Z * [new tag] trunk/49a04d26088acc17d948ddd66920f3e16371e873 -> trunk/49a04d26088acc17d948ddd66920f3e16371e873 2025-12-04T09:14:55.8615577Z * [new tag] trunk/4bebc827c47d2f1f0fa1a417a5201a97aef3d985 -> trunk/4bebc827c47d2f1f0fa1a417a5201a97aef3d985 2025-12-04T09:14:55.8616237Z * [new tag] trunk/4c246677784c6a14bc2dbb9ff8773ef0a3a3222f -> trunk/4c246677784c6a14bc2dbb9ff8773ef0a3a3222f 2025-12-04T09:14:55.8617442Z * [new tag] trunk/4cfb47ff548b6d996641058cf04a70e311a4c3aa -> trunk/4cfb47ff548b6d996641058cf04a70e311a4c3aa 2025-12-04T09:14:55.8618485Z * [new tag] trunk/4e0061c1aa52f606dda8cfab0bd7591e588faf2c -> trunk/4e0061c1aa52f606dda8cfab0bd7591e588faf2c 2025-12-04T09:14:55.8620029Z * [new tag] trunk/4fefb8e7e942386ffac764a41b232241f82bea3a -> trunk/4fefb8e7e942386ffac764a41b232241f82bea3a 2025-12-04T09:14:55.8620997Z * [new tag] trunk/503b2640023521f5a35cd9a52fc8033d73a95d0d -> trunk/503b2640023521f5a35cd9a52fc8033d73a95d0d 2025-12-04T09:14:55.8621977Z * [new tag] trunk/518c2b1b3dab9a2ef2849e04b3bc2f20c1c41db9 -> trunk/518c2b1b3dab9a2ef2849e04b3bc2f20c1c41db9 2025-12-04T09:14:55.8622967Z * [new tag] trunk/5191b2fa68ba19960912bfd7fd721c79d76bb1f3 -> trunk/5191b2fa68ba19960912bfd7fd721c79d76bb1f3 2025-12-04T09:14:55.8623992Z * [new tag] trunk/52ac0f0dc4acacd219f1317fbc28ec631c01e07a -> trunk/52ac0f0dc4acacd219f1317fbc28ec631c01e07a 2025-12-04T09:14:55.8625071Z * [new tag] trunk/539ba711b029de9f191070f4f0d12f18f5b7f292 -> trunk/539ba711b029de9f191070f4f0d12f18f5b7f292 2025-12-04T09:14:55.8626031Z * [new tag] trunk/556375b55deebebbc56cb7aef81f4d52f031ba28 -> trunk/556375b55deebebbc56cb7aef81f4d52f031ba28 2025-12-04T09:14:55.8627042Z * [new tag] trunk/55c4ab554845481d0a69a3811937575fe8bb1a66 -> trunk/55c4ab554845481d0a69a3811937575fe8bb1a66 2025-12-04T09:14:55.8628015Z * [new tag] trunk/5634469fda9e5d98869c82c7d03bb08914245f96 -> trunk/5634469fda9e5d98869c82c7d03bb08914245f96 2025-12-04T09:14:55.8628861Z * [new tag] trunk/5778f6ff894686a975a9a23645178ae4c87ad5dc -> trunk/5778f6ff894686a975a9a23645178ae4c87ad5dc 2025-12-04T09:14:55.8629883Z * [new tag] trunk/587d63a3e07de5dc91065f9ef70bcacda9989068 -> trunk/587d63a3e07de5dc91065f9ef70bcacda9989068 2025-12-04T09:14:55.8630920Z * [new tag] trunk/597930f6b568852356ca9795dac76f9e4653adbd -> trunk/597930f6b568852356ca9795dac76f9e4653adbd 2025-12-04T09:14:55.8631691Z * [new tag] trunk/597df3a4e2a67b9fdbe1a89b2f4d74f822274db6 -> trunk/597df3a4e2a67b9fdbe1a89b2f4d74f822274db6 2025-12-04T09:14:55.8632858Z * [new tag] trunk/59abd50e931f4efb21b053f7a2911f5d8a49d883 -> trunk/59abd50e931f4efb21b053f7a2911f5d8a49d883 2025-12-04T09:14:55.8633824Z * [new tag] trunk/5a607febc04c3a2b5824c75f3f60307867439a2c -> trunk/5a607febc04c3a2b5824c75f3f60307867439a2c 2025-12-04T09:14:55.8634831Z * [new tag] trunk/5bf1cdf4755c54ef462b44cb8041b0a57311556b -> trunk/5bf1cdf4755c54ef462b44cb8041b0a57311556b 2025-12-04T09:14:55.8635608Z * [new tag] trunk/5f0030ba63d334d7e8c93a09e41403b89e4c573c -> trunk/5f0030ba63d334d7e8c93a09e41403b89e4c573c 2025-12-04T09:14:55.8636642Z * [new tag] trunk/5f21d27e71268464d362a96c9ac09ea475f7f202 -> trunk/5f21d27e71268464d362a96c9ac09ea475f7f202 2025-12-04T09:14:55.8637658Z * [new tag] trunk/5fafc13038c9988d9ac21fa793fbd5890604b447 -> trunk/5fafc13038c9988d9ac21fa793fbd5890604b447 2025-12-04T09:14:55.8638736Z * [new tag] trunk/61be54a31dc09b59d99b62176fb935aee0b924ef -> trunk/61be54a31dc09b59d99b62176fb935aee0b924ef 2025-12-04T09:14:55.8639613Z * [new tag] trunk/62d3ccd71484ed6a760d909b41487101bbc65719 -> trunk/62d3ccd71484ed6a760d909b41487101bbc65719 2025-12-04T09:14:55.8640645Z * [new tag] trunk/641cdb68ae27668eb441d0e49c87a0602c120c2b -> trunk/641cdb68ae27668eb441d0e49c87a0602c120c2b 2025-12-04T09:14:55.8641632Z * [new tag] trunk/65c4620d6bb0c6029f69762c22b91dda2294da9a -> trunk/65c4620d6bb0c6029f69762c22b91dda2294da9a 2025-12-04T09:14:55.8642889Z * [new tag] trunk/66004b993744b4106bf8afaba71f3c228a804206 -> trunk/66004b993744b4106bf8afaba71f3c228a804206 2025-12-04T09:14:55.8643905Z * [new tag] trunk/6658a04c7ca67acb64512341342e7b3ee13ee386 -> trunk/6658a04c7ca67acb64512341342e7b3ee13ee386 2025-12-04T09:14:55.8644896Z * [new tag] trunk/6864e309092a71f8ab0ca6a4dc7f8a4073fd31c4 -> trunk/6864e309092a71f8ab0ca6a4dc7f8a4073fd31c4 2025-12-04T09:14:55.8646005Z * [new tag] trunk/6c261c6cb07892c90ca19ed51c9705b1659a3f7d -> trunk/6c261c6cb07892c90ca19ed51c9705b1659a3f7d 2025-12-04T09:14:55.8646903Z * [new tag] trunk/6c8b6a043f1628188b6396b3a2a6e000ca68362b -> trunk/6c8b6a043f1628188b6396b3a2a6e000ca68362b 2025-12-04T09:14:55.8647988Z * [new tag] trunk/6ceb4a32f92ae67ce5d7d97931d17401ebf5ffa5 -> trunk/6ceb4a32f92ae67ce5d7d97931d17401ebf5ffa5 2025-12-04T09:14:55.8648907Z * [new tag] trunk/6e404e9b7d6f5fb0de86aa73888c3038248c17f8 -> trunk/6e404e9b7d6f5fb0de86aa73888c3038248c17f8 2025-12-04T09:14:55.8649917Z * [new tag] trunk/6ec30b490aee1db6bcdc7340abddef25784f08ec -> trunk/6ec30b490aee1db6bcdc7340abddef25784f08ec 2025-12-04T09:14:55.8650896Z * [new tag] trunk/6f2783a6c08e1db34275ff25176ffe9aebc30a71 -> trunk/6f2783a6c08e1db34275ff25176ffe9aebc30a71 2025-12-04T09:14:55.8651916Z * [new tag] trunk/6f53fefeb90ad3281119b5cfc4aa9ffd8a066e3d -> trunk/6f53fefeb90ad3281119b5cfc4aa9ffd8a066e3d 2025-12-04T09:14:55.8652999Z * [new tag] trunk/6f7dcf51e46d0c880db1a2f5c70de57adb576f4a -> trunk/6f7dcf51e46d0c880db1a2f5c70de57adb576f4a 2025-12-04T09:14:55.8654081Z * [new tag] trunk/6ff831180d2fa436c7f1c1af3adac641fce9d60e -> trunk/6ff831180d2fa436c7f1c1af3adac641fce9d60e 2025-12-04T09:14:55.8655014Z * [new tag] trunk/70076464a63ab218a7ceefb0e76ccd7131deb8f8 -> trunk/70076464a63ab218a7ceefb0e76ccd7131deb8f8 2025-12-04T09:14:55.8655985Z * [new tag] trunk/70d797a5fc109b20a517646fcaa819477cd0d485 -> trunk/70d797a5fc109b20a517646fcaa819477cd0d485 2025-12-04T09:14:55.8656955Z * [new tag] trunk/7348cb355ff0a6f79cd4871215aea72185748734 -> trunk/7348cb355ff0a6f79cd4871215aea72185748734 2025-12-04T09:14:55.8657956Z * [new tag] trunk/74fe26a1ebe32931783569f2e762e3c2c974901f -> trunk/74fe26a1ebe32931783569f2e762e3c2c974901f 2025-12-04T09:14:55.8658986Z * [new tag] trunk/76aeb8c7e0f795b3fddca134cbea9a69da3ee696 -> trunk/76aeb8c7e0f795b3fddca134cbea9a69da3ee696 2025-12-04T09:14:55.8659743Z * [new tag] trunk/7716da9fb23f27a65b41f9f016a2afadf281c18f -> trunk/7716da9fb23f27a65b41f9f016a2afadf281c18f 2025-12-04T09:14:55.8660835Z * [new tag] trunk/7741edd4ed665f3988052e260863efb508d61a03 -> trunk/7741edd4ed665f3988052e260863efb508d61a03 2025-12-04T09:14:55.8661907Z * [new tag] trunk/78adb3b3df41b45d2368b67226d2f864b78939a6 -> trunk/78adb3b3df41b45d2368b67226d2f864b78939a6 2025-12-04T09:14:55.8662930Z * [new tag] trunk/79d7b178225e5ed24d4e1db74e5abbff848f5fb7 -> trunk/79d7b178225e5ed24d4e1db74e5abbff848f5fb7 2025-12-04T09:14:55.8663631Z * [new tag] trunk/7a1e316115fc6996b3f2336822ba5d5f6179f0c3 -> trunk/7a1e316115fc6996b3f2336822ba5d5f6179f0c3 2025-12-04T09:14:55.8664642Z * [new tag] trunk/7a41b66367c38d0af3e8a90f7be48d6b281e7bca -> trunk/7a41b66367c38d0af3e8a90f7be48d6b281e7bca 2025-12-04T09:14:55.8665648Z * [new tag] trunk/7b7af390ea8541c611d1ce2018a6934188fc197b -> trunk/7b7af390ea8541c611d1ce2018a6934188fc197b 2025-12-04T09:14:55.8666765Z * [new tag] trunk/7ba4680f3755a560af81aa0f688791e367aa3609 -> trunk/7ba4680f3755a560af81aa0f688791e367aa3609 2025-12-04T09:14:55.8667701Z * [new tag] trunk/7bc2a66ded06a0b2549aa51d807edc5dc3e73d1b -> trunk/7bc2a66ded06a0b2549aa51d807edc5dc3e73d1b 2025-12-04T09:14:55.8668480Z * [new tag] trunk/7c648509a7470ace9fb2bae960dd4790f7e943e9 -> trunk/7c648509a7470ace9fb2bae960dd4790f7e943e9 2025-12-04T09:14:55.8669448Z * [new tag] trunk/7cbc2d034cecd21ab5c9707d0a9c525c17143fb8 -> trunk/7cbc2d034cecd21ab5c9707d0a9c525c17143fb8 2025-12-04T09:14:55.8670432Z * [new tag] trunk/7d1bbaf4ba301ea3fba6f3c7bc02d58f6417aaed -> trunk/7d1bbaf4ba301ea3fba6f3c7bc02d58f6417aaed 2025-12-04T09:14:55.8671467Z * [new tag] trunk/7d2a33e4ebf60b217a3cd77feae19231eb996fc8 -> trunk/7d2a33e4ebf60b217a3cd77feae19231eb996fc8 2025-12-04T09:14:55.8672412Z * [new tag] trunk/7eb625920054b1126a7d2d99818aaa188c6ba95e -> trunk/7eb625920054b1126a7d2d99818aaa188c6ba95e 2025-12-04T09:14:55.8673201Z * [new tag] trunk/7f55ba19c456a3d6cc443dd9edb6bb7cca677ead -> trunk/7f55ba19c456a3d6cc443dd9edb6bb7cca677ead 2025-12-04T09:14:55.8674265Z * [new tag] trunk/81af382128efa094d8702e18f2c133760904c718 -> trunk/81af382128efa094d8702e18f2c133760904c718 2025-12-04T09:14:55.8675694Z * [new tag] trunk/84149583d483e9c973c9a0feda70e4f3964947b0 -> trunk/84149583d483e9c973c9a0feda70e4f3964947b0 2025-12-04T09:14:55.8676814Z * [new tag] trunk/85a315917efe82c24306be805c584ec044951c75 -> trunk/85a315917efe82c24306be805c584ec044951c75 2025-12-04T09:14:55.8677789Z * [new tag] trunk/87329491c82a5f8c1cc4ec11d8f55a5de2551ece -> trunk/87329491c82a5f8c1cc4ec11d8f55a5de2551ece 2025-12-04T09:14:55.8678584Z * [new tag] trunk/892640e25aeefa8007c5af837214b4502b6b62a6 -> trunk/892640e25aeefa8007c5af837214b4502b6b62a6 2025-12-04T09:14:55.8680355Z * [new tag] trunk/89e3bbcb5b5321dc8b9520b4d5a8ee60cea1d0b4 -> trunk/89e3bbcb5b5321dc8b9520b4d5a8ee60cea1d0b4 2025-12-04T09:14:55.8681153Z * [new tag] trunk/8c73bbbb02159223c0c97d268a0a74cb78158a1c -> trunk/8c73bbbb02159223c0c97d268a0a74cb78158a1c 2025-12-04T09:14:55.8682245Z * [new tag] trunk/8d56e98c8db988a22cb2dfaeefb30bc7d2a3cc43 -> trunk/8d56e98c8db988a22cb2dfaeefb30bc7d2a3cc43 2025-12-04T09:14:55.8683310Z * [new tag] trunk/8d9dd9603e5ee26c01007f0cd4f018e584840922 -> trunk/8d9dd9603e5ee26c01007f0cd4f018e584840922 2025-12-04T09:14:55.8684377Z * [new tag] trunk/8ef0c0b02b062d75e7c9be2594914a3e784d23ca -> trunk/8ef0c0b02b062d75e7c9be2594914a3e784d23ca 2025-12-04T09:14:55.8685549Z * [new tag] trunk/90b27e7e8352cde97d32ddad24740ef819633f38 -> trunk/90b27e7e8352cde97d32ddad24740ef819633f38 2025-12-04T09:14:55.8686823Z * [new tag] trunk/90f0139e64b2951815d524b6a373bed20c4fbf90 -> trunk/90f0139e64b2951815d524b6a373bed20c4fbf90 2025-12-04T09:14:55.8687544Z * [new tag] trunk/93d0d6838c56af59b0dba794e6aa08f0c1c7799c -> trunk/93d0d6838c56af59b0dba794e6aa08f0c1c7799c 2025-12-04T09:14:55.8688356Z * [new tag] trunk/94ca8d5f1e81fea3ae488650a0fb6795049a9f87 -> trunk/94ca8d5f1e81fea3ae488650a0fb6795049a9f87 2025-12-04T09:14:55.8689417Z * [new tag] trunk/9844fbeadd5cebdf1281d6fbf79164139c352693 -> trunk/9844fbeadd5cebdf1281d6fbf79164139c352693 2025-12-04T09:14:55.8690405Z * [new tag] trunk/99024dec888ec1e50b546822a32b6fb2f35e5eaa -> trunk/99024dec888ec1e50b546822a32b6fb2f35e5eaa 2025-12-04T09:14:55.8691372Z * [new tag] trunk/9a296e640fc88aa44d275b48cd9cc30c573b169d -> trunk/9a296e640fc88aa44d275b48cd9cc30c573b169d 2025-12-04T09:14:55.8692412Z * [new tag] trunk/9b3e34d8589b29f7b4e7fab6f78711b7ca6e4639 -> trunk/9b3e34d8589b29f7b4e7fab6f78711b7ca6e4639 2025-12-04T09:14:55.8693419Z * [new tag] trunk/9cd055e547e9b67a5f9827f8999c38d7eda1bcb8 -> trunk/9cd055e547e9b67a5f9827f8999c38d7eda1bcb8 2025-12-04T09:14:55.8694388Z * [new tag] trunk/9f0df5686cb4ada94f94620acba2e3c3f363b11d -> trunk/9f0df5686cb4ada94f94620acba2e3c3f363b11d 2025-12-04T09:14:55.8695388Z * [new tag] trunk/9f7fceb887d0cfa0326a59b887821c63ff11340a -> trunk/9f7fceb887d0cfa0326a59b887821c63ff11340a 2025-12-04T09:14:55.8696377Z * [new tag] trunk/9f8ef8855d3078d70f7b782540ff2aaf158d6742 -> trunk/9f8ef8855d3078d70f7b782540ff2aaf158d6742 2025-12-04T09:14:55.8697481Z * [new tag] trunk/9fb52efc797b47a1f425a03aa5e47b866d8b1098 -> trunk/9fb52efc797b47a1f425a03aa5e47b866d8b1098 2025-12-04T09:14:55.8698523Z * [new tag] trunk/9ff4a2ebc5762d46c73e46b1b523d7ff349fedfa -> trunk/9ff4a2ebc5762d46c73e46b1b523d7ff349fedfa 2025-12-04T09:14:55.8699840Z * [new tag] trunk/a0f3937b94422354538ebbd47202d5b0e8a3fd0d -> trunk/a0f3937b94422354538ebbd47202d5b0e8a3fd0d 2025-12-04T09:14:55.8700851Z * [new tag] trunk/a15066c28b3145e6edbfc88359d0411d14cfc70c -> trunk/a15066c28b3145e6edbfc88359d0411d14cfc70c 2025-12-04T09:14:55.8701834Z * [new tag] trunk/a20f775e82564d2a9979221ed7f3b8d7cf54ce90 -> trunk/a20f775e82564d2a9979221ed7f3b8d7cf54ce90 2025-12-04T09:14:55.8702904Z * [new tag] trunk/a2973fb00ec002dd4b6bbf07385f066efb259b8c -> trunk/a2973fb00ec002dd4b6bbf07385f066efb259b8c 2025-12-04T09:14:55.8703602Z * [new tag] trunk/a7dc6dab9ad911259d4801c502907e531594db45 -> trunk/a7dc6dab9ad911259d4801c502907e531594db45 2025-12-04T09:14:55.8704735Z * [new tag] trunk/a951a9cee65c01660bbc6e6fded90ecb10fa6109 -> trunk/a951a9cee65c01660bbc6e6fded90ecb10fa6109 2025-12-04T09:14:55.8705776Z * [new tag] trunk/abfa1a6d65c7c159e35c72c25979b9da4971689e -> trunk/abfa1a6d65c7c159e35c72c25979b9da4971689e 2025-12-04T09:14:55.8706794Z * [new tag] trunk/ae3a2395bf66151078e2d201716f7d63ce1c6f3e -> trunk/ae3a2395bf66151078e2d201716f7d63ce1c6f3e 2025-12-04T09:14:55.8707542Z * [new tag] trunk/afdff7f0325080dedac44d080cb5a3b0e65e6c5e -> trunk/afdff7f0325080dedac44d080cb5a3b0e65e6c5e 2025-12-04T09:14:55.8708418Z * [new tag] trunk/b1aed4e7a72c03a38f44543aaea0dae2e9b76d48 -> trunk/b1aed4e7a72c03a38f44543aaea0dae2e9b76d48 2025-12-04T09:14:55.8709456Z * [new tag] trunk/b1decff555cd50e2123c8c6e25cc0d447c411f62 -> trunk/b1decff555cd50e2123c8c6e25cc0d447c411f62 2025-12-04T09:14:55.8710528Z * [new tag] trunk/b2b6b034c9fd08672c40e63ef243556ad4c49bd2 -> trunk/b2b6b034c9fd08672c40e63ef243556ad4c49bd2 2025-12-04T09:14:55.8711489Z * [new tag] trunk/b39813b4a04931682b0491adba2138d01d716d99 -> trunk/b39813b4a04931682b0491adba2138d01d716d99 2025-12-04T09:14:55.8712597Z * [new tag] trunk/b3a7edb2311367974cc7cd764cfb11a5d6758b24 -> trunk/b3a7edb2311367974cc7cd764cfb11a5d6758b24 2025-12-04T09:14:55.8713585Z * [new tag] trunk/b4cc1329c86acaef6d42c1fac7169b8d870ab0d7 -> trunk/b4cc1329c86acaef6d42c1fac7169b8d870ab0d7 2025-12-04T09:14:55.8714641Z * [new tag] trunk/b555c39217f765759954a4f9f9bd1e9b87bed11a -> trunk/b555c39217f765759954a4f9f9bd1e9b87bed11a 2025-12-04T09:14:55.8715637Z * [new tag] trunk/b6b6c80379388b7f9932c3e6a0f9907bf430e417 -> trunk/b6b6c80379388b7f9932c3e6a0f9907bf430e417 2025-12-04T09:14:55.8716637Z * [new tag] trunk/b6b6d912df0b6f4082f8e50b18bd1de1dd7325f4 -> trunk/b6b6d912df0b6f4082f8e50b18bd1de1dd7325f4 2025-12-04T09:14:55.8717764Z * [new tag] trunk/b7d60685f8cbc939b68a20871e90db67e729329b -> trunk/b7d60685f8cbc939b68a20871e90db67e729329b 2025-12-04T09:14:55.8718933Z * [new tag] trunk/b7f6b9a4fc6259f7af068f31868b3119bb1bac3e -> trunk/b7f6b9a4fc6259f7af068f31868b3119bb1bac3e 2025-12-04T09:14:55.8720033Z * [new tag] trunk/b8c4ba3593761e7b2a3ebd86f040fb07b47c02cf -> trunk/b8c4ba3593761e7b2a3ebd86f040fb07b47c02cf 2025-12-04T09:14:55.8720969Z * [new tag] trunk/b9c8f3a4884befb965ff42620ce44a71b04887f5 -> trunk/b9c8f3a4884befb965ff42620ce44a71b04887f5 2025-12-04T09:14:55.8722035Z * [new tag] trunk/ba1412546f3082c0958c077acc2025e4dbc33f1f -> trunk/ba1412546f3082c0958c077acc2025e4dbc33f1f 2025-12-04T09:14:55.8723058Z * [new tag] trunk/bac403c0b38c63bdbcc0c31f1c2b0bc0260f610f -> trunk/bac403c0b38c63bdbcc0c31f1c2b0bc0260f610f 2025-12-04T09:14:55.8724027Z * [new tag] trunk/bb3034198b459401fabeab254e1b99f0115046e2 -> trunk/bb3034198b459401fabeab254e1b99f0115046e2 2025-12-04T09:14:55.8725254Z * [new tag] trunk/bc39b2b3bc7a6e19a42e62bd576974035086fe55 -> trunk/bc39b2b3bc7a6e19a42e62bd576974035086fe55 2025-12-04T09:14:55.8726318Z * [new tag] trunk/bc43d5b297f207a11d83d77ddf0152bdaabe15a8 -> trunk/bc43d5b297f207a11d83d77ddf0152bdaabe15a8 2025-12-04T09:14:55.8727344Z * [new tag] trunk/bc6a4863c7246a6493d16d4ea6eee71ec07c6a09 -> trunk/bc6a4863c7246a6493d16d4ea6eee71ec07c6a09 2025-12-04T09:14:55.8728306Z * [new tag] trunk/bea4912944defdbcb8b061800caab6cbbbd01df5 -> trunk/bea4912944defdbcb8b061800caab6cbbbd01df5 2025-12-04T09:14:55.8729748Z * [new tag] trunk/c04e2c656f48d82d1521b867bbbf03967b9b7564 -> trunk/c04e2c656f48d82d1521b867bbbf03967b9b7564 2025-12-04T09:14:55.8730548Z * [new tag] trunk/c0660bcee27e7d7731634e274576a7081882bede -> trunk/c0660bcee27e7d7731634e274576a7081882bede 2025-12-04T09:14:55.8731686Z * [new tag] trunk/c178ed43d3d99cbefe84fbfb21d6f282b20d62ac -> trunk/c178ed43d3d99cbefe84fbfb21d6f282b20d62ac 2025-12-04T09:14:55.8732672Z * [new tag] trunk/c55b1e8f61d041ee436d697449eb028931d574fb -> trunk/c55b1e8f61d041ee436d697449eb028931d574fb 2025-12-04T09:14:55.8733758Z * [new tag] trunk/c6ae7579fe12fe75f1a8f7043a494c90567273f1 -> trunk/c6ae7579fe12fe75f1a8f7043a494c90567273f1 2025-12-04T09:14:55.8734847Z * [new tag] trunk/c8210e7d94bad5ae21ac389fa4ba8a463c76c4d0 -> trunk/c8210e7d94bad5ae21ac389fa4ba8a463c76c4d0 2025-12-04T09:14:55.8735914Z * [new tag] trunk/cc0853af42122f8185321f542616f4474e717f09 -> trunk/cc0853af42122f8185321f542616f4474e717f09 2025-12-04T09:14:55.8736776Z * [new tag] trunk/cddec6562eabfa390d014fa3741a5659cf9c94c9 -> trunk/cddec6562eabfa390d014fa3741a5659cf9c94c9 2025-12-04T09:14:55.8737865Z * [new tag] trunk/ce5e7e3bf1f4b69a4f4f93d288ba75b906df492a -> trunk/ce5e7e3bf1f4b69a4f4f93d288ba75b906df492a 2025-12-04T09:14:55.8738949Z * [new tag] trunk/d038b0130ec7c20ebcac219301292fd8e98a1ace -> trunk/d038b0130ec7c20ebcac219301292fd8e98a1ace 2025-12-04T09:14:55.8739812Z * [new tag] trunk/d16447dacaf2420ea175f0c275c75da951f57d39 -> trunk/d16447dacaf2420ea175f0c275c75da951f57d39 2025-12-04T09:14:55.8740910Z * [new tag] trunk/d19f1e8cab6810bb2e99141f9976665954c67a50 -> trunk/d19f1e8cab6810bb2e99141f9976665954c67a50 2025-12-04T09:14:55.8741890Z * [new tag] trunk/d1c9f03b2a5af4104721712f8cdffe9b4f340c01 -> trunk/d1c9f03b2a5af4104721712f8cdffe9b4f340c01 2025-12-04T09:14:55.8743158Z * [new tag] trunk/d40f4950f2b7f7aa380a22fe0f6166e71680fbcf -> trunk/d40f4950f2b7f7aa380a22fe0f6166e71680fbcf 2025-12-04T09:14:55.8744252Z * [new tag] trunk/d5038950bacfe36bbf24a47a455fe76901deb8e8 -> trunk/d5038950bacfe36bbf24a47a455fe76901deb8e8 2025-12-04T09:14:55.8745137Z * [new tag] trunk/d54ff42903c2ae0533931ff11d23b35f875bdb3d -> trunk/d54ff42903c2ae0533931ff11d23b35f875bdb3d 2025-12-04T09:14:55.8746765Z * [new tag] trunk/d76697633a2d2b9cced1ae21161849b33bfe7e47 -> trunk/d76697633a2d2b9cced1ae21161849b33bfe7e47 2025-12-04T09:14:55.8747662Z * [new tag] trunk/d78f52b199c547106d4cd9d2856dd0805c118bf1 -> trunk/d78f52b199c547106d4cd9d2856dd0805c118bf1 2025-12-04T09:14:55.8748667Z * [new tag] trunk/d8fd5c6eed28e5004150691d048a3f6785e19a8e -> trunk/d8fd5c6eed28e5004150691d048a3f6785e19a8e 2025-12-04T09:14:55.8749655Z * [new tag] trunk/d900f5e86745dec76713f4b0ef07005ef36b2f5a -> trunk/d900f5e86745dec76713f4b0ef07005ef36b2f5a 2025-12-04T09:14:55.8750660Z * [new tag] trunk/d973dc6b87d763859fe1c5bd1287e3b6b1c49d1b -> trunk/d973dc6b87d763859fe1c5bd1287e3b6b1c49d1b 2025-12-04T09:14:55.8751804Z * [new tag] trunk/d998c03304cb6ede76e1ed535b4ddeb6c2bf40ec -> trunk/d998c03304cb6ede76e1ed535b4ddeb6c2bf40ec 2025-12-04T09:14:55.8752844Z * [new tag] trunk/d9cb8a70833101dbbe16b99520cfbdd70d0a87bf -> trunk/d9cb8a70833101dbbe16b99520cfbdd70d0a87bf 2025-12-04T09:14:55.8753892Z * [new tag] trunk/d9d5e91b43f70eb8637af55db6856d49be391ffd -> trunk/d9d5e91b43f70eb8637af55db6856d49be391ffd 2025-12-04T09:14:55.8754854Z * [new tag] trunk/dd18a75336a4fbd7497955cc5665904724fce889 -> trunk/dd18a75336a4fbd7497955cc5665904724fce889 2025-12-04T09:14:55.8755926Z * [new tag] trunk/ded9bcd61a059bf723e6e84689552962b480ea77 -> trunk/ded9bcd61a059bf723e6e84689552962b480ea77 2025-12-04T09:14:55.8757427Z * [new tag] trunk/dfbd3714d15c37a7b83b322a6b60f997fc00f50c -> trunk/dfbd3714d15c37a7b83b322a6b60f997fc00f50c 2025-12-04T09:14:55.8758354Z * [new tag] trunk/e115f9f4e4b039f8e9a642aaa2bd8254a920541b -> trunk/e115f9f4e4b039f8e9a642aaa2bd8254a920541b 2025-12-04T09:14:55.8759189Z * [new tag] trunk/e3f24fd73ad74c6e7176687986436956c7c18235 -> trunk/e3f24fd73ad74c6e7176687986436956c7c18235 2025-12-04T09:14:55.8760301Z * [new tag] trunk/e7d24d3ff93d1503ba63860b7057438ad93f918e -> trunk/e7d24d3ff93d1503ba63860b7057438ad93f918e 2025-12-04T09:14:55.8761389Z * [new tag] trunk/ea7035f462a0d2830865ee86c832bd101e1427fc -> trunk/ea7035f462a0d2830865ee86c832bd101e1427fc 2025-12-04T09:14:55.8762406Z * [new tag] trunk/eabb7ad2128580ef674446027b95bcf4e21e8df3 -> trunk/eabb7ad2128580ef674446027b95bcf4e21e8df3 2025-12-04T09:14:55.8763486Z * [new tag] trunk/eb5c63652a33da42e7018c23df5f20a3eb4c6ccf -> trunk/eb5c63652a33da42e7018c23df5f20a3eb4c6ccf 2025-12-04T09:14:55.8764548Z * [new tag] trunk/ec2c71f5c85021b8938cdafadce24c15a36fd93e -> trunk/ec2c71f5c85021b8938cdafadce24c15a36fd93e 2025-12-04T09:14:55.8765610Z * [new tag] trunk/ecbcc3f6bf327856b435b259ac63cc2f328c4b4e -> trunk/ecbcc3f6bf327856b435b259ac63cc2f328c4b4e 2025-12-04T09:14:55.8767148Z * [new tag] trunk/ee87bbe876c42575e961b32a0827d76bc9782ca2 -> trunk/ee87bbe876c42575e961b32a0827d76bc9782ca2 2025-12-04T09:14:55.8768027Z * [new tag] trunk/ef019d1d431c4c5a95b594cb90d40a50cd00f5e4 -> trunk/ef019d1d431c4c5a95b594cb90d40a50cd00f5e4 2025-12-04T09:14:55.8769014Z * [new tag] trunk/ef8ecc13830a86c4b231f1aad9aba7851db61b53 -> trunk/ef8ecc13830a86c4b231f1aad9aba7851db61b53 2025-12-04T09:14:55.8770052Z * [new tag] trunk/f1076f5510920044912247b1abb8760cb820f598 -> trunk/f1076f5510920044912247b1abb8760cb820f598 2025-12-04T09:14:55.8771054Z * [new tag] trunk/f2d6a75a00a1d648ca9a0abc6a33e14c3dea6c40 -> trunk/f2d6a75a00a1d648ca9a0abc6a33e14c3dea6c40 2025-12-04T09:14:55.8776904Z * [new tag] trunk/f47dd0ddef1359e5b43e4b962412f67b30ecde56 -> trunk/f47dd0ddef1359e5b43e4b962412f67b30ecde56 2025-12-04T09:14:55.8777714Z * [new tag] trunk/f49d32dfa4730dcfb1b60eeeb369b5889da983c8 -> trunk/f49d32dfa4730dcfb1b60eeeb369b5889da983c8 2025-12-04T09:14:55.8778162Z * [new tag] trunk/f4dedf78fc30fd4b93975787ca6074ee89db9467 -> trunk/f4dedf78fc30fd4b93975787ca6074ee89db9467 2025-12-04T09:14:55.8778856Z * [new tag] trunk/f7c0d03819ebed05c4038f095d66d1b8c54aca17 -> trunk/f7c0d03819ebed05c4038f095d66d1b8c54aca17 2025-12-04T09:14:55.8779272Z * [new tag] trunk/f7e1bd80a063e17453c361837ba6ea2570920a73 -> trunk/f7e1bd80a063e17453c361837ba6ea2570920a73 2025-12-04T09:14:55.8779689Z * [new tag] trunk/f9bd6c53624c7c0ea3772de78498326e84c2f0e7 -> trunk/f9bd6c53624c7c0ea3772de78498326e84c2f0e7 2025-12-04T09:14:55.8780272Z * [new tag] trunk/fb5be221a46b51bfc9509013b0d85bc5a9d4f15b -> trunk/fb5be221a46b51bfc9509013b0d85bc5a9d4f15b 2025-12-04T09:14:55.8780710Z * [new tag] trunk/fdf863d5e1de3b2688c9511e96876e34581dbfd7 -> trunk/fdf863d5e1de3b2688c9511e96876e34581dbfd7 2025-12-04T09:14:55.8781376Z * [new tag] trunk/fe0e65adfc0e7ca6e5f57e6ea8b16bd5cc967307 -> trunk/fe0e65adfc0e7ca6e5f57e6ea8b16bd5cc967307 2025-12-04T09:14:55.8781791Z * [new tag] trunk/fec710bf89173f5355468a7ce1afe9157c3d9009 -> trunk/fec710bf89173f5355468a7ce1afe9157c3d9009 2025-12-04T09:14:55.8782743Z * [new tag] trunk/ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 -> trunk/ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:14:55.8783853Z * [new tag] v0.1.1 -> v0.1.1 2025-12-04T09:14:55.8784742Z * [new tag] v0.1.10 -> v0.1.10 2025-12-04T09:14:55.8785875Z * [new tag] v0.1.11 -> v0.1.11 2025-12-04T09:14:55.8786723Z * [new tag] v0.1.12 -> v0.1.12 2025-12-04T09:14:55.8787588Z * [new tag] v0.1.2 -> v0.1.2 2025-12-04T09:14:55.8788485Z * [new tag] v0.1.3 -> v0.1.3 2025-12-04T09:14:55.8789539Z * [new tag] v0.1.4 -> v0.1.4 2025-12-04T09:14:55.8790269Z * [new tag] v0.1.5 -> v0.1.5 2025-12-04T09:14:55.8791339Z * [new tag] v0.1.6 -> v0.1.6 2025-12-04T09:14:55.8792145Z * [new tag] v0.1.7 -> v0.1.7 2025-12-04T09:14:55.8793102Z * [new tag] v0.1.8 -> v0.1.8 2025-12-04T09:14:55.8793984Z * [new tag] v0.1.9 -> v0.1.9 2025-12-04T09:14:55.8795078Z * [new tag] v0.2.0 -> v0.2.0 2025-12-04T09:14:55.8795933Z * [new tag] v0.3.0 -> v0.3.0 2025-12-04T09:14:55.8797057Z * [new tag] v0.3.1 -> v0.3.1 2025-12-04T09:14:55.8797858Z * [new tag] v0.4.0 -> v0.4.0 2025-12-04T09:14:55.8799079Z * [new tag] v0.4.1 -> v0.4.1 2025-12-04T09:14:55.8799924Z * [new tag] v1.0.0 -> v1.0.0 2025-12-04T09:14:55.8801000Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-12-04T09:14:55.8801818Z * [new tag] v1.0.1 -> v1.0.1 2025-12-04T09:14:55.8802928Z * [new tag] v1.0rc0 -> v1.0rc0 2025-12-04T09:14:55.8803601Z * [new tag] v1.0rc1 -> v1.0rc1 2025-12-04T09:14:55.8804822Z * [new tag] v1.1.0 -> v1.1.0 2025-12-04T09:14:55.8805857Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-12-04T09:14:55.8806974Z * [new tag] v1.10.0 -> v1.10.0 2025-12-04T09:14:55.8808040Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-12-04T09:14:55.8808841Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-12-04T09:14:55.8809524Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-12-04T09:14:55.8810753Z * [new tag] v1.10.1 -> v1.10.1 2025-12-04T09:14:55.8811313Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-12-04T09:14:55.8812340Z * [new tag] v1.10.2 -> v1.10.2 2025-12-04T09:14:55.8812973Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-12-04T09:14:55.8814148Z * [new tag] v1.11.0 -> v1.11.0 2025-12-04T09:14:55.8815094Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-12-04T09:14:55.8816331Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-12-04T09:14:55.8817280Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-12-04T09:14:55.8818398Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-12-04T09:14:55.8819296Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-12-04T09:14:55.8820120Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-12-04T09:14:55.8820835Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-12-04T09:14:55.8822081Z * [new tag] v1.12.0 -> v1.12.0 2025-12-04T09:14:55.8822887Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-12-04T09:14:55.8823971Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-12-04T09:14:55.8824857Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-12-04T09:14:55.8825940Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-12-04T09:14:55.8826842Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-12-04T09:14:55.8828037Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-12-04T09:14:55.8828618Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-12-04T09:14:55.8829397Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-12-04T09:14:55.8830099Z * [new tag] v1.12.1 -> v1.12.1 2025-12-04T09:14:55.8831449Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-12-04T09:14:55.8832196Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-12-04T09:14:55.8833423Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-12-04T09:14:55.8834411Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-12-04T09:14:55.8835010Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-12-04T09:14:55.8836231Z * [new tag] v1.13.0 -> v1.13.0 2025-12-04T09:14:55.8837056Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-12-04T09:14:55.8837976Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-12-04T09:14:55.8839098Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-12-04T09:14:55.8840138Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-12-04T09:14:55.8840705Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-12-04T09:14:55.8841735Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-12-04T09:14:55.8843009Z * [new tag] v1.13.1 -> v1.13.1 2025-12-04T09:14:55.8843580Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-12-04T09:14:55.8845279Z * [new tag] v1.2.0 -> v1.2.0 2025-12-04T09:14:55.8846026Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-12-04T09:14:55.8847333Z * [new tag] v1.3.0 -> v1.3.0 2025-12-04T09:14:55.8848042Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-12-04T09:14:55.8849068Z * [new tag] v1.3.1 -> v1.3.1 2025-12-04T09:14:55.8849760Z * [new tag] v1.4.0 -> v1.4.0 2025-12-04T09:14:55.8851005Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-12-04T09:14:55.8851702Z * [new tag] v1.4.1 -> v1.4.1 2025-12-04T09:14:55.8852852Z * [new tag] v1.5.0 -> v1.5.0 2025-12-04T09:14:55.8853937Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-12-04T09:14:55.8855081Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-12-04T09:14:55.8855858Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-12-04T09:14:55.8856961Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-12-04T09:14:55.8857595Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-12-04T09:14:55.8858780Z * [new tag] v1.5.1 -> v1.5.1 2025-12-04T09:14:55.8859393Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-12-04T09:14:55.8860205Z * [new tag] v1.6.0 -> v1.6.0 2025-12-04T09:14:55.8861336Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-12-04T09:14:55.8862419Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-12-04T09:14:55.8863288Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-12-04T09:14:55.8864363Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-12-04T09:14:55.8865267Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-12-04T09:14:55.8866333Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-12-04T09:14:55.8866933Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-12-04T09:14:55.8868117Z * [new tag] v1.7.0 -> v1.7.0 2025-12-04T09:14:55.8869146Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-12-04T09:14:55.8870214Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-12-04T09:14:55.8871070Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-12-04T09:14:55.8871848Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-12-04T09:14:55.8872939Z * [new tag] v1.7.1 -> v1.7.1 2025-12-04T09:14:55.8874075Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-12-04T09:14:55.8874964Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-12-04T09:14:55.8875776Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-12-04T09:14:55.8876883Z * [new tag] v1.8.0 -> v1.8.0 2025-12-04T09:14:55.8877702Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-12-04T09:14:55.8878780Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-12-04T09:14:55.8879673Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-12-04T09:14:55.8880612Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-12-04T09:14:55.8881389Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-12-04T09:14:55.8882126Z * [new tag] v1.8.1 -> v1.8.1 2025-12-04T09:14:55.8883267Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-12-04T09:14:55.8883916Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-12-04T09:14:55.8884744Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-12-04T09:14:55.8886456Z * [new tag] v1.8.2 -> v1.8.2 2025-12-04T09:14:55.8886958Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-12-04T09:14:55.8888250Z * [new tag] v1.9.0 -> v1.9.0 2025-12-04T09:14:55.8889043Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-12-04T09:14:55.8890321Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-12-04T09:14:55.8891443Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-12-04T09:14:55.8891837Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-12-04T09:14:55.8893114Z * [new tag] v1.9.1 -> v1.9.1 2025-12-04T09:14:55.8894303Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-12-04T09:14:55.8894840Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-12-04T09:14:55.8896091Z * [new tag] v2.0.0 -> v2.0.0 2025-12-04T09:14:55.8897351Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-12-04T09:14:55.8897982Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-12-04T09:14:55.8899124Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-12-04T09:14:55.8899989Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-12-04T09:14:55.8901116Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-12-04T09:14:55.8901849Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-12-04T09:14:55.8903022Z * [new tag] v2.0.1 -> v2.0.1 2025-12-04T09:14:55.8904027Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-12-04T09:14:55.8904589Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-12-04T09:14:55.8905798Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-12-04T09:14:55.8906987Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-12-04T09:14:55.8908509Z * [new tag] v2.1.0 -> v2.1.0 2025-12-04T09:14:55.8909583Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-12-04T09:14:55.8910663Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-12-04T09:14:55.8911728Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-12-04T09:14:55.8912967Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-12-04T09:14:55.8913592Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-12-04T09:14:55.8914390Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-12-04T09:14:55.8915613Z * [new tag] v2.1.1 -> v2.1.1 2025-12-04T09:14:55.8916692Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-12-04T09:14:55.8917573Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-12-04T09:14:55.8918762Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-12-04T09:14:55.8919698Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-12-04T09:14:55.8920692Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-12-04T09:14:55.8921490Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-12-04T09:14:55.8922364Z * [new tag] v2.1.2 -> v2.1.2 2025-12-04T09:14:55.8923527Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-12-04T09:14:55.8924518Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-12-04T09:14:55.8925362Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-12-04T09:14:55.8926499Z * [new tag] v2.2.0 -> v2.2.0 2025-12-04T09:14:55.8927353Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-12-04T09:14:55.8928422Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-12-04T09:14:55.8929258Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-12-04T09:14:55.8930316Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-12-04T09:14:55.8931168Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-12-04T09:14:55.8932284Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-12-04T09:14:55.8932947Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-12-04T09:14:55.8933720Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-12-04T09:14:55.8934908Z * [new tag] v2.2.1 -> v2.2.1 2025-12-04T09:14:55.8935970Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-12-04T09:14:55.8936611Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-12-04T09:14:55.8937399Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-12-04T09:14:55.8938174Z * [new tag] v2.2.2 -> v2.2.2 2025-12-04T09:14:55.8939413Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-12-04T09:14:55.8940207Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-12-04T09:14:55.8940995Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-12-04T09:14:55.8942182Z * [new tag] v2.3.0 -> v2.3.0 2025-12-04T09:14:55.8943215Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-12-04T09:14:55.8944434Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-12-04T09:14:55.8945460Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-12-04T09:14:55.8946145Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-12-04T09:14:55.8947352Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-12-04T09:14:55.8948614Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-12-04T09:14:55.8949118Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-12-04T09:14:55.8950466Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-12-04T09:14:55.8951019Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-12-04T09:14:55.8952267Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-12-04T09:14:55.8953046Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-12-04T09:14:55.8953831Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-12-04T09:14:55.8954622Z * [new tag] v2.3.1 -> v2.3.1 2025-12-04T09:14:55.8955877Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-12-04T09:14:55.8956882Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-12-04T09:14:55.8957773Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-12-04T09:14:55.8958960Z * [new tag] v2.4.0 -> v2.4.0 2025-12-04T09:14:55.8960058Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-12-04T09:14:55.8960812Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-12-04T09:14:55.8961814Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-12-04T09:14:55.8962882Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-12-04T09:14:55.8963801Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-12-04T09:14:55.8964997Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-12-04T09:14:55.8966063Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-12-04T09:14:55.8966971Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-12-04T09:14:55.8968182Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-12-04T09:14:55.8968801Z * [new tag] v2.4.1 -> v2.4.1 2025-12-04T09:14:55.8970424Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-12-04T09:14:55.8971486Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-12-04T09:14:55.8972610Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-12-04T09:14:55.8973616Z * [new tag] v2.5.0 -> v2.5.0 2025-12-04T09:14:55.8974546Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-12-04T09:14:55.8975335Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-12-04T09:14:55.8976417Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-12-04T09:14:55.8977309Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-12-04T09:14:55.8978493Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-12-04T09:14:55.8979359Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-12-04T09:14:55.8980572Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-12-04T09:14:55.8981449Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-12-04T09:14:55.8982565Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-12-04T09:14:55.8983628Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-12-04T09:14:55.8984296Z * [new tag] v2.5.1 -> v2.5.1 2025-12-04T09:14:55.8985028Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-12-04T09:14:55.8985834Z * [new tag] v2.6.0 -> v2.6.0 2025-12-04T09:14:55.8987020Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-12-04T09:14:55.8988102Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-12-04T09:14:55.8989183Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-12-04T09:14:55.8990047Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-12-04T09:14:55.8991371Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-12-04T09:14:55.8992549Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-12-04T09:14:55.8993448Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-12-04T09:14:55.8994711Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-12-04T09:14:55.8995778Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-12-04T09:14:55.8996985Z * [new tag] v2.7.0 -> v2.7.0 2025-12-04T09:14:55.8997880Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-12-04T09:14:55.8998683Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-12-04T09:14:55.8999937Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-12-04T09:14:55.9000964Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-12-04T09:14:55.9001889Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-12-04T09:14:55.9002952Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-12-04T09:14:55.9003846Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-12-04T09:14:55.9005185Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-12-04T09:14:55.9006264Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-12-04T09:14:55.9007330Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-12-04T09:14:55.9008011Z * [new tag] v2.7.1 -> v2.7.1 2025-12-04T09:14:55.9009262Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-12-04T09:14:55.9010366Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-12-04T09:14:55.9011476Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-12-04T09:14:55.9012535Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-12-04T09:14:55.9013511Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-12-04T09:14:55.9014268Z * [new tag] v2.8.0 -> v2.8.0 2025-12-04T09:14:55.9015376Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-12-04T09:14:55.9016285Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-12-04T09:14:55.9017588Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-12-04T09:14:55.9018660Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-12-04T09:14:55.9019784Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-12-04T09:14:55.9020761Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-12-04T09:14:55.9021839Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-12-04T09:14:55.9022898Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-12-04T09:14:55.9023955Z * [new tag] v2.9.0 -> v2.9.0 2025-12-04T09:14:55.9025036Z * [new tag] v2.9.0-rc1 -> v2.9.0-rc1 2025-12-04T09:14:55.9026180Z * [new tag] v2.9.0-rc10 -> v2.9.0-rc10 2025-12-04T09:14:55.9026989Z * [new tag] v2.9.0-rc11 -> v2.9.0-rc11 2025-12-04T09:14:55.9028443Z * [new tag] v2.9.0-rc2 -> v2.9.0-rc2 2025-12-04T09:14:55.9029532Z * [new tag] v2.9.0-rc3 -> v2.9.0-rc3 2025-12-04T09:14:55.9030552Z * [new tag] v2.9.0-rc4 -> v2.9.0-rc4 2025-12-04T09:14:55.9031652Z * [new tag] v2.9.0-rc5 -> v2.9.0-rc5 2025-12-04T09:14:55.9032930Z * [new tag] v2.9.0-rc6 -> v2.9.0-rc6 2025-12-04T09:14:55.9034018Z * [new tag] v2.9.0-rc7 -> v2.9.0-rc7 2025-12-04T09:14:55.9035289Z * [new tag] v2.9.0-rc8 -> v2.9.0-rc8 2025-12-04T09:14:55.9036005Z * [new tag] v2.9.0-rc9 -> v2.9.0-rc9 2025-12-04T09:14:55.9037294Z * [new tag] v2.9.1 -> v2.9.1 2025-12-04T09:14:55.9038412Z * [new tag] v2.9.1-rc1 -> v2.9.1-rc1 2025-12-04T09:14:55.9039622Z * [new tag] v2.9.1-rc2 -> v2.9.1-rc2 2025-12-04T09:14:55.9041408Z * [new tag] viable/strict/1759343184 -> viable/strict/1759343184 2025-12-04T09:14:55.9042594Z * [new tag] viable/strict/1759346540 -> viable/strict/1759346540 2025-12-04T09:14:55.9046452Z * [new tag] viable/strict/1759348181 -> viable/strict/1759348181 2025-12-04T09:14:55.9047407Z * [new tag] viable/strict/1759350324 -> viable/strict/1759350324 2025-12-04T09:14:55.9048354Z * [new tag] viable/strict/1759351793 -> viable/strict/1759351793 2025-12-04T09:14:55.9049327Z * [new tag] viable/strict/1759353844 -> viable/strict/1759353844 2025-12-04T09:14:55.9050266Z * [new tag] viable/strict/1759355374 -> viable/strict/1759355374 2025-12-04T09:14:55.9051251Z * [new tag] viable/strict/1759357472 -> viable/strict/1759357472 2025-12-04T09:14:55.9052169Z * [new tag] viable/strict/1759361002 -> viable/strict/1759361002 2025-12-04T09:14:55.9053485Z * [new tag] viable/strict/1759362585 -> viable/strict/1759362585 2025-12-04T09:14:55.9054619Z * [new tag] viable/strict/1759365359 -> viable/strict/1759365359 2025-12-04T09:14:55.9055555Z * [new tag] viable/strict/1759370089 -> viable/strict/1759370089 2025-12-04T09:14:55.9056625Z * [new tag] viable/strict/1759377554 -> viable/strict/1759377554 2025-12-04T09:14:55.9057598Z * [new tag] viable/strict/1759379133 -> viable/strict/1759379133 2025-12-04T09:14:55.9058572Z * [new tag] viable/strict/1759389871 -> viable/strict/1759389871 2025-12-04T09:14:55.9059678Z * [new tag] viable/strict/1759393562 -> viable/strict/1759393562 2025-12-04T09:14:55.9060581Z * [new tag] viable/strict/1759395076 -> viable/strict/1759395076 2025-12-04T09:14:55.9061758Z * [new tag] viable/strict/1759398579 -> viable/strict/1759398579 2025-12-04T09:14:55.9062639Z * [new tag] viable/strict/1759404142 -> viable/strict/1759404142 2025-12-04T09:14:55.9063852Z * [new tag] viable/strict/1759405773 -> viable/strict/1759405773 2025-12-04T09:14:55.9064490Z * [new tag] viable/strict/1759408041 -> viable/strict/1759408041 2025-12-04T09:14:55.9065687Z * [new tag] viable/strict/1759411593 -> viable/strict/1759411593 2025-12-04T09:14:55.9066508Z * [new tag] viable/strict/1759427395 -> viable/strict/1759427395 2025-12-04T09:14:55.9067674Z * [new tag] viable/strict/1759434582 -> viable/strict/1759434582 2025-12-04T09:14:55.9068877Z * [new tag] viable/strict/1759436720 -> viable/strict/1759436720 2025-12-04T09:14:55.9069589Z * [new tag] viable/strict/1759440219 -> viable/strict/1759440219 2025-12-04T09:14:55.9070517Z * [new tag] viable/strict/1759441948 -> viable/strict/1759441948 2025-12-04T09:14:55.9072018Z * [new tag] viable/strict/1759443860 -> viable/strict/1759443860 2025-12-04T09:14:55.9072916Z * [new tag] viable/strict/1759445377 -> viable/strict/1759445377 2025-12-04T09:14:55.9074131Z * [new tag] viable/strict/1759447415 -> viable/strict/1759447415 2025-12-04T09:14:55.9075051Z * [new tag] viable/strict/1759451750 -> viable/strict/1759451750 2025-12-04T09:14:55.9076108Z * [new tag] viable/strict/1759453910 -> viable/strict/1759453910 2025-12-04T09:14:55.9077075Z * [new tag] viable/strict/1759456483 -> viable/strict/1759456483 2025-12-04T09:14:55.9078190Z * [new tag] viable/strict/1759459279 -> viable/strict/1759459279 2025-12-04T09:14:55.9079118Z * [new tag] viable/strict/1759460742 -> viable/strict/1759460742 2025-12-04T09:14:55.9080059Z * [new tag] viable/strict/1759462025 -> viable/strict/1759462025 2025-12-04T09:14:55.9081240Z * [new tag] viable/strict/1759469086 -> viable/strict/1759469086 2025-12-04T09:14:55.9082129Z * [new tag] viable/strict/1759470581 -> viable/strict/1759470581 2025-12-04T09:14:55.9083207Z * [new tag] viable/strict/1759472786 -> viable/strict/1759472786 2025-12-04T09:14:55.9084121Z * [new tag] viable/strict/1759476294 -> viable/strict/1759476294 2025-12-04T09:14:55.9085289Z * [new tag] viable/strict/1759479963 -> viable/strict/1759479963 2025-12-04T09:14:55.9086198Z * [new tag] viable/strict/1759492177 -> viable/strict/1759492177 2025-12-04T09:14:55.9087313Z * [new tag] viable/strict/1759519278 -> viable/strict/1759519278 2025-12-04T09:14:55.9088185Z * [new tag] viable/strict/1759524580 -> viable/strict/1759524580 2025-12-04T09:14:55.9089232Z * [new tag] viable/strict/1759528193 -> viable/strict/1759528193 2025-12-04T09:14:55.9090467Z * [new tag] viable/strict/1759533797 -> viable/strict/1759533797 2025-12-04T09:14:55.9091435Z * [new tag] viable/strict/1759542780 -> viable/strict/1759542780 2025-12-04T09:14:55.9092630Z * [new tag] viable/strict/1759549779 -> viable/strict/1759549779 2025-12-04T09:14:55.9093366Z * [new tag] viable/strict/1759555455 -> viable/strict/1759555455 2025-12-04T09:14:55.9094527Z * [new tag] viable/strict/1759559176 -> viable/strict/1759559176 2025-12-04T09:14:55.9095350Z * [new tag] viable/strict/1759560629 -> viable/strict/1759560629 2025-12-04T09:14:55.9096515Z * [new tag] viable/strict/1759569848 -> viable/strict/1759569848 2025-12-04T09:14:55.9097797Z * [new tag] viable/strict/1759571382 -> viable/strict/1759571382 2025-12-04T09:14:55.9098492Z * [new tag] viable/strict/1759573474 -> viable/strict/1759573474 2025-12-04T09:14:55.9099727Z * [new tag] viable/strict/1759618187 -> viable/strict/1759618187 2025-12-04T09:14:55.9100760Z * [new tag] viable/strict/1759626742 -> viable/strict/1759626742 2025-12-04T09:14:55.9101842Z * [new tag] viable/strict/1759632427 -> viable/strict/1759632427 2025-12-04T09:14:55.9102654Z * [new tag] viable/strict/1759634971 -> viable/strict/1759634971 2025-12-04T09:14:55.9103898Z * [new tag] viable/strict/1759661382 -> viable/strict/1759661382 2025-12-04T09:14:55.9104955Z * [new tag] viable/strict/1759663294 -> viable/strict/1759663294 2025-12-04T09:14:55.9105995Z * [new tag] viable/strict/1759708178 -> viable/strict/1759708178 2025-12-04T09:14:55.9107271Z * [new tag] viable/strict/1759715695 -> viable/strict/1759715695 2025-12-04T09:14:55.9107985Z * [new tag] viable/strict/1759728293 -> viable/strict/1759728293 2025-12-04T09:14:55.9109192Z * [new tag] viable/strict/1759735513 -> viable/strict/1759735513 2025-12-04T09:14:55.9110025Z * [new tag] viable/strict/1759739177 -> viable/strict/1759739177 2025-12-04T09:14:55.9111226Z * [new tag] viable/strict/1759758635 -> viable/strict/1759758635 2025-12-04T09:14:55.9112031Z * [new tag] viable/strict/1759765784 -> viable/strict/1759765784 2025-12-04T09:14:55.9113185Z * [new tag] viable/strict/1759767948 -> viable/strict/1759767948 2025-12-04T09:14:55.9114031Z * [new tag] viable/strict/1759771461 -> viable/strict/1759771461 2025-12-04T09:14:55.9115073Z * [new tag] viable/strict/1759776706 -> viable/strict/1759776706 2025-12-04T09:14:55.9115916Z * [new tag] viable/strict/1759782317 -> viable/strict/1759782317 2025-12-04T09:14:55.9117159Z * [new tag] viable/strict/1759783777 -> viable/strict/1759783777 2025-12-04T09:14:55.9117976Z * [new tag] viable/strict/1759785815 -> viable/strict/1759785815 2025-12-04T09:14:55.9119235Z * [new tag] viable/strict/1759789459 -> viable/strict/1759789459 2025-12-04T09:14:55.9120040Z * [new tag] viable/strict/1759790974 -> viable/strict/1759790974 2025-12-04T09:14:55.9120915Z * [new tag] viable/strict/1759794583 -> viable/strict/1759794583 2025-12-04T09:14:55.9122055Z * [new tag] viable/strict/1759797408 -> viable/strict/1759797408 2025-12-04T09:14:55.9123095Z * [new tag] viable/strict/1759799518 -> viable/strict/1759799518 2025-12-04T09:14:55.9123909Z * [new tag] viable/strict/1759804909 -> viable/strict/1759804909 2025-12-04T09:14:55.9125170Z * [new tag] viable/strict/1759807643 -> viable/strict/1759807643 2025-12-04T09:14:55.9126022Z * [new tag] viable/strict/1759809089 -> viable/strict/1759809089 2025-12-04T09:14:55.9127184Z * [new tag] viable/strict/1759811145 -> viable/strict/1759811145 2025-12-04T09:14:55.9128047Z * [new tag] viable/strict/1759812581 -> viable/strict/1759812581 2025-12-04T09:14:55.9129038Z * [new tag] viable/strict/1759814683 -> viable/strict/1759814683 2025-12-04T09:14:55.9130031Z * [new tag] viable/strict/1759821889 -> viable/strict/1759821889 2025-12-04T09:14:55.9131152Z * [new tag] viable/strict/1759823376 -> viable/strict/1759823376 2025-12-04T09:14:55.9132108Z * [new tag] viable/strict/1759827107 -> viable/strict/1759827107 2025-12-04T09:14:55.9133058Z * [new tag] viable/strict/1759830577 -> viable/strict/1759830577 2025-12-04T09:14:55.9134247Z * [new tag] viable/strict/1759832720 -> viable/strict/1759832720 2025-12-04T09:14:55.9135100Z * [new tag] viable/strict/1759842063 -> viable/strict/1759842063 2025-12-04T09:14:55.9136068Z * [new tag] viable/strict/1759847121 -> viable/strict/1759847121 2025-12-04T09:14:55.9137883Z * [new tag] viable/strict/1759850721 -> viable/strict/1759850721 2025-12-04T09:14:55.9138736Z * [new tag] viable/strict/1759857870 -> viable/strict/1759857870 2025-12-04T09:14:55.9140027Z * [new tag] viable/strict/1759863143 -> viable/strict/1759863143 2025-12-04T09:14:55.9140921Z * [new tag] viable/strict/1759875874 -> viable/strict/1759875874 2025-12-04T09:14:55.9141770Z * [new tag] viable/strict/1759877385 -> viable/strict/1759877385 2025-12-04T09:14:55.9143073Z * [new tag] viable/strict/1759883801 -> viable/strict/1759883801 2025-12-04T09:14:55.9144383Z * [new tag] viable/strict/1759885922 -> viable/strict/1759885922 2025-12-04T09:14:55.9145151Z * [new tag] viable/strict/1759888488 -> viable/strict/1759888488 2025-12-04T09:14:55.9146085Z * [new tag] viable/strict/1759895471 -> viable/strict/1759895471 2025-12-04T09:14:55.9147193Z * [new tag] viable/strict/1759904803 -> viable/strict/1759904803 2025-12-04T09:14:55.9148389Z * [new tag] viable/strict/1759908300 -> viable/strict/1759908300 2025-12-04T09:14:55.9149520Z * [new tag] viable/strict/1759915520 -> viable/strict/1759915520 2025-12-04T09:14:55.9150438Z * [new tag] viable/strict/1759916978 -> viable/strict/1759916978 2025-12-04T09:14:55.9151277Z * [new tag] viable/strict/1759930024 -> viable/strict/1759930024 2025-12-04T09:14:55.9152392Z * [new tag] viable/strict/1759948122 -> viable/strict/1759948122 2025-12-04T09:14:55.9153312Z * [new tag] viable/strict/1759952983 -> viable/strict/1759952983 2025-12-04T09:14:55.9154499Z * [new tag] viable/strict/1759955121 -> viable/strict/1759955121 2025-12-04T09:14:55.9155355Z * [new tag] viable/strict/1759962298 -> viable/strict/1759962298 2025-12-04T09:14:55.9156451Z * [new tag] viable/strict/1759965837 -> viable/strict/1759965837 2025-12-04T09:14:55.9157525Z * [new tag] viable/strict/1759970213 -> viable/strict/1759970213 2025-12-04T09:14:55.9158417Z * [new tag] viable/strict/1759974894 -> viable/strict/1759974894 2025-12-04T09:14:55.9159386Z * [new tag] viable/strict/1759977763 -> viable/strict/1759977763 2025-12-04T09:14:55.9160550Z * [new tag] viable/strict/1759979241 -> viable/strict/1759979241 2025-12-04T09:14:55.9161459Z * [new tag] viable/strict/1759985417 -> viable/strict/1759985417 2025-12-04T09:14:55.9162510Z * [new tag] viable/strict/1759987490 -> viable/strict/1759987490 2025-12-04T09:14:55.9163454Z * [new tag] viable/strict/1759996180 -> viable/strict/1759996180 2025-12-04T09:14:55.9164663Z * [new tag] viable/strict/1760065682 -> viable/strict/1760065682 2025-12-04T09:14:55.9165807Z * [new tag] viable/strict/1760066894 -> viable/strict/1760066894 2025-12-04T09:14:55.9166905Z * [new tag] viable/strict/1760070345 -> viable/strict/1760070345 2025-12-04T09:14:55.9167603Z * [new tag] viable/strict/1760089782 -> viable/strict/1760089782 2025-12-04T09:14:55.9168810Z * [new tag] viable/strict/1760091921 -> viable/strict/1760091921 2025-12-04T09:14:55.9169873Z * [new tag] viable/strict/1760127924 -> viable/strict/1760127924 2025-12-04T09:14:55.9170666Z * [new tag] viable/strict/1760129489 -> viable/strict/1760129489 2025-12-04T09:14:55.9171946Z * [new tag] viable/strict/1760132980 -> viable/strict/1760132980 2025-12-04T09:14:55.9173046Z * [new tag] viable/strict/1760135060 -> viable/strict/1760135060 2025-12-04T09:14:55.9173881Z * [new tag] viable/strict/1760215782 -> viable/strict/1760215782 2025-12-04T09:14:55.9175124Z * [new tag] viable/strict/1760273849 -> viable/strict/1760273849 2025-12-04T09:14:55.9175909Z * [new tag] viable/strict/1760275517 -> viable/strict/1760275517 2025-12-04T09:14:55.9177053Z * [new tag] viable/strict/1760276979 -> viable/strict/1760276979 2025-12-04T09:14:55.9178145Z * [new tag] viable/strict/1760279007 -> viable/strict/1760279007 2025-12-04T09:14:55.9178838Z * [new tag] viable/strict/1760286328 -> viable/strict/1760286328 2025-12-04T09:14:55.9179773Z * [new tag] viable/strict/1760493304 -> viable/strict/1760493304 2025-12-04T09:14:55.9180809Z * [new tag] viable/strict/1760496298 -> viable/strict/1760496298 2025-12-04T09:14:55.9181678Z * [new tag] viable/strict/1760518396 -> viable/strict/1760518396 2025-12-04T09:14:55.9182749Z * [new tag] viable/strict/1760534864 -> viable/strict/1760534864 2025-12-04T09:14:55.9183703Z * [new tag] viable/strict/1760549062 -> viable/strict/1760549062 2025-12-04T09:14:55.9184825Z * [new tag] viable/strict/1760552799 -> viable/strict/1760552799 2025-12-04T09:14:55.9185813Z * [new tag] viable/strict/1760554355 -> viable/strict/1760554355 2025-12-04T09:14:55.9186914Z * [new tag] viable/strict/1760556275 -> viable/strict/1760556275 2025-12-04T09:14:55.9187862Z * [new tag] viable/strict/1760564979 -> viable/strict/1760564979 2025-12-04T09:14:55.9188965Z * [new tag] viable/strict/1760567049 -> viable/strict/1760567049 2025-12-04T09:14:55.9190396Z * [new tag] viable/strict/1760568585 -> viable/strict/1760568585 2025-12-04T09:14:55.9191296Z * [new tag] viable/strict/1760570630 -> viable/strict/1760570630 2025-12-04T09:14:55.9192270Z * [new tag] viable/strict/1760572180 -> viable/strict/1760572180 2025-12-04T09:14:55.9193277Z * [new tag] viable/strict/1760575094 -> viable/strict/1760575094 2025-12-04T09:14:55.9194532Z * [new tag] viable/strict/1760579709 -> viable/strict/1760579709 2025-12-04T09:14:55.9196016Z * [new tag] viable/strict/1760582614 -> viable/strict/1760582614 2025-12-04T09:14:55.9196909Z * [new tag] viable/strict/1760586815 -> viable/strict/1760586815 2025-12-04T09:14:55.9197837Z * [new tag] viable/strict/1760588829 -> viable/strict/1760588829 2025-12-04T09:14:55.9198883Z * [new tag] viable/strict/1760590200 -> viable/strict/1760590200 2025-12-04T09:14:55.9199966Z * [new tag] viable/strict/1760592311 -> viable/strict/1760592311 2025-12-04T09:14:55.9200898Z * [new tag] viable/strict/1760619733 -> viable/strict/1760619733 2025-12-04T09:14:55.9201734Z * [new tag] viable/strict/1760628335 -> viable/strict/1760628335 2025-12-04T09:14:55.9202850Z * [new tag] viable/strict/1760635490 -> viable/strict/1760635490 2025-12-04T09:14:55.9204232Z * [new tag] viable/strict/1760640743 -> viable/strict/1760640743 2025-12-04T09:14:55.9205212Z * [new tag] viable/strict/1760642528 -> viable/strict/1760642528 2025-12-04T09:14:55.9206374Z * [new tag] viable/strict/1760646330 -> viable/strict/1760646330 2025-12-04T09:14:55.9207266Z * [new tag] viable/strict/1760666101 -> viable/strict/1760666101 2025-12-04T09:14:55.9208337Z * [new tag] viable/strict/1760668990 -> viable/strict/1760668990 2025-12-04T09:14:55.9209405Z * [new tag] viable/strict/1760670600 -> viable/strict/1760670600 2025-12-04T09:14:55.9210365Z * [new tag] viable/strict/1760671704 -> viable/strict/1760671704 2025-12-04T09:14:55.9211326Z * [new tag] viable/strict/1760673121 -> viable/strict/1760673121 2025-12-04T09:14:55.9212411Z * [new tag] viable/strict/1760675352 -> viable/strict/1760675352 2025-12-04T09:14:55.9213351Z * [new tag] viable/strict/1760696731 -> viable/strict/1760696731 2025-12-04T09:14:55.9215892Z * [new tag] viable/strict/1760723515 -> viable/strict/1760723515 2025-12-04T09:14:55.9216804Z * [new tag] viable/strict/1760727234 -> viable/strict/1760727234 2025-12-04T09:14:55.9217984Z * [new tag] viable/strict/1760730578 -> viable/strict/1760730578 2025-12-04T09:14:55.9218865Z * [new tag] viable/strict/1760732726 -> viable/strict/1760732726 2025-12-04T09:14:55.9219924Z * [new tag] viable/strict/1760734180 -> viable/strict/1760734180 2025-12-04T09:14:55.9220869Z * [new tag] viable/strict/1760736251 -> viable/strict/1760736251 2025-12-04T09:14:55.9222006Z * [new tag] viable/strict/1760737772 -> viable/strict/1760737772 2025-12-04T09:14:55.9222926Z * [new tag] viable/strict/1760758005 -> viable/strict/1760758005 2025-12-04T09:14:55.9223911Z * [new tag] viable/strict/1760761532 -> viable/strict/1760761532 2025-12-04T09:14:55.9224982Z * [new tag] viable/strict/1760802581 -> viable/strict/1760802581 2025-12-04T09:14:55.9225915Z * [new tag] viable/strict/1760827772 -> viable/strict/1760827772 2025-12-04T09:14:55.9226905Z * [new tag] viable/strict/1760834524 -> viable/strict/1760834524 2025-12-04T09:14:55.9228092Z * [new tag] viable/strict/1760845009 -> viable/strict/1760845009 2025-12-04T09:14:55.9229047Z * [new tag] viable/strict/1760876836 -> viable/strict/1760876836 2025-12-04T09:14:55.9230064Z * [new tag] viable/strict/1760880329 -> viable/strict/1760880329 2025-12-04T09:14:55.9231025Z * [new tag] viable/strict/1760888987 -> viable/strict/1760888987 2025-12-04T09:14:55.9231985Z * [new tag] viable/strict/1760912664 -> viable/strict/1760912664 2025-12-04T09:14:55.9232963Z * [new tag] viable/strict/1760925321 -> viable/strict/1760925321 2025-12-04T09:14:55.9233956Z * [new tag] viable/strict/1760931488 -> viable/strict/1760931488 2025-12-04T09:14:55.9234941Z * [new tag] viable/strict/1760932693 -> viable/strict/1760932693 2025-12-04T09:14:55.9236074Z * [new tag] viable/strict/1761004184 -> viable/strict/1761004184 2025-12-04T09:14:55.9236990Z * [new tag] viable/strict/1761014748 -> viable/strict/1761014748 2025-12-04T09:14:55.9238115Z * [new tag] viable/strict/1761017491 -> viable/strict/1761017491 2025-12-04T09:14:55.9238975Z * [new tag] viable/strict/1761018806 -> viable/strict/1761018806 2025-12-04T09:14:55.9240211Z * [new tag] viable/strict/1761020754 -> viable/strict/1761020754 2025-12-04T09:14:55.9241163Z * [new tag] viable/strict/1761024303 -> viable/strict/1761024303 2025-12-04T09:14:55.9242540Z * [new tag] viable/strict/1761029582 -> viable/strict/1761029582 2025-12-04T09:14:55.9243325Z * [new tag] viable/strict/1761031535 -> viable/strict/1761031535 2025-12-04T09:14:55.9244503Z * [new tag] viable/strict/1761035196 -> viable/strict/1761035196 2025-12-04T09:14:55.9245708Z * [new tag] viable/strict/1761045825 -> viable/strict/1761045825 2025-12-04T09:14:55.9246754Z * [new tag] viable/strict/1761054796 -> viable/strict/1761054796 2025-12-04T09:14:55.9247908Z * [new tag] viable/strict/1761060314 -> viable/strict/1761060314 2025-12-04T09:14:55.9248707Z * [new tag] viable/strict/1761071198 -> viable/strict/1761071198 2025-12-04T09:14:55.9249923Z * [new tag] viable/strict/1761074628 -> viable/strict/1761074628 2025-12-04T09:14:55.9251024Z * [new tag] viable/strict/1761078351 -> viable/strict/1761078351 2025-12-04T09:14:55.9251808Z * [new tag] viable/strict/1761079822 -> viable/strict/1761079822 2025-12-04T09:14:55.9252971Z * [new tag] viable/strict/1761081873 -> viable/strict/1761081873 2025-12-04T09:14:55.9253770Z * [new tag] viable/strict/1761083392 -> viable/strict/1761083392 2025-12-04T09:14:55.9255013Z * [new tag] viable/strict/1761085465 -> viable/strict/1761085465 2025-12-04T09:14:55.9256060Z * [new tag] viable/strict/1761089099 -> viable/strict/1761089099 2025-12-04T09:14:55.9256986Z * [new tag] viable/strict/1761095535 -> viable/strict/1761095535 2025-12-04T09:14:55.9258332Z * [new tag] viable/strict/1761098119 -> viable/strict/1761098119 2025-12-04T09:14:55.9259509Z * [new tag] viable/strict/1761101330 -> viable/strict/1761101330 2025-12-04T09:14:55.9260347Z * [new tag] viable/strict/1761114425 -> viable/strict/1761114425 2025-12-04T09:14:55.9261545Z * [new tag] viable/strict/1761116036 -> viable/strict/1761116036 2025-12-04T09:14:55.9262360Z * [new tag] viable/strict/1761119379 -> viable/strict/1761119379 2025-12-04T09:14:55.9263565Z * [new tag] viable/strict/1761121601 -> viable/strict/1761121601 2025-12-04T09:14:55.9264280Z * [new tag] viable/strict/1761123234 -> viable/strict/1761123234 2025-12-04T09:14:55.9265540Z * [new tag] viable/strict/1761126621 -> viable/strict/1761126621 2025-12-04T09:14:55.9266328Z * [new tag] viable/strict/1761132259 -> viable/strict/1761132259 2025-12-04T09:14:55.9267563Z * [new tag] viable/strict/1761146746 -> viable/strict/1761146746 2025-12-04T09:14:55.9268356Z * [new tag] viable/strict/1761164752 -> viable/strict/1761164752 2025-12-04T09:14:55.9269535Z * [new tag] viable/strict/1761166198 -> viable/strict/1761166198 2025-12-04T09:14:55.9270590Z * [new tag] viable/strict/1761175424 -> viable/strict/1761175424 2025-12-04T09:14:55.9272027Z * [new tag] viable/strict/1761176983 -> viable/strict/1761176983 2025-12-04T09:14:55.9273168Z * [new tag] viable/strict/1761179891 -> viable/strict/1761179891 2025-12-04T09:14:55.9274342Z * [new tag] viable/strict/1761181930 -> viable/strict/1761181930 2025-12-04T09:14:55.9275187Z * [new tag] viable/strict/1761184516 -> viable/strict/1761184516 2025-12-04T09:14:55.9276387Z * [new tag] viable/strict/1761190179 -> viable/strict/1761190179 2025-12-04T09:14:55.9277104Z * [new tag] viable/strict/1761193558 -> viable/strict/1761193558 2025-12-04T09:14:55.9278348Z * [new tag] viable/strict/1761207990 -> viable/strict/1761207990 2025-12-04T09:14:55.9279139Z * [new tag] viable/strict/1761229539 -> viable/strict/1761229539 2025-12-04T09:14:55.9280555Z * [new tag] viable/strict/1761244031 -> viable/strict/1761244031 2025-12-04T09:14:55.9281349Z * [new tag] viable/strict/1761248986 -> viable/strict/1761248986 2025-12-04T09:14:55.9282531Z * [new tag] viable/strict/1761259791 -> viable/strict/1761259791 2025-12-04T09:14:55.9283346Z * [new tag] viable/strict/1761266139 -> viable/strict/1761266139 2025-12-04T09:14:55.9284621Z * [new tag] viable/strict/1761268316 -> viable/strict/1761268316 2025-12-04T09:14:55.9285723Z * [new tag] viable/strict/1761273805 -> viable/strict/1761273805 2025-12-04T09:14:55.9286519Z * [new tag] viable/strict/1761275261 -> viable/strict/1761275261 2025-12-04T09:14:55.9287653Z * [new tag] viable/strict/1761277913 -> viable/strict/1761277913 2025-12-04T09:14:55.9288761Z * [new tag] viable/strict/1761290701 -> viable/strict/1761290701 2025-12-04T09:14:55.9289719Z * [new tag] viable/strict/1761294396 -> viable/strict/1761294396 2025-12-04T09:14:55.9290923Z * [new tag] viable/strict/1761303047 -> viable/strict/1761303047 2025-12-04T09:14:55.9291680Z * [new tag] viable/strict/1761335388 -> viable/strict/1761335388 2025-12-04T09:14:55.9292917Z * [new tag] viable/strict/1761337551 -> viable/strict/1761337551 2025-12-04T09:14:55.9293933Z * [new tag] viable/strict/1761339007 -> viable/strict/1761339007 2025-12-04T09:14:55.9294857Z * [new tag] viable/strict/1761341050 -> viable/strict/1761341050 2025-12-04T09:14:55.9295987Z * [new tag] viable/strict/1761346188 -> viable/strict/1761346188 2025-12-04T09:14:55.9297075Z * [new tag] viable/strict/1761349792 -> viable/strict/1761349792 2025-12-04T09:14:55.9298201Z * [new tag] viable/strict/1761352620 -> viable/strict/1761352620 2025-12-04T09:14:55.9299086Z * [new tag] viable/strict/1761354730 -> viable/strict/1761354730 2025-12-04T09:14:55.9300281Z * [new tag] viable/strict/1761357298 -> viable/strict/1761357298 2025-12-04T09:14:55.9301143Z * [new tag] viable/strict/1761360201 -> viable/strict/1761360201 2025-12-04T09:14:55.9302236Z * [new tag] viable/strict/1761361753 -> viable/strict/1761361753 2025-12-04T09:14:55.9303207Z * [new tag] viable/strict/1761364351 -> viable/strict/1761364351 2025-12-04T09:14:55.9304252Z * [new tag] viable/strict/1761366338 -> viable/strict/1761366338 2025-12-04T09:14:55.9305437Z * [new tag] viable/strict/1761367802 -> viable/strict/1761367802 2025-12-04T09:14:55.9306338Z * [new tag] viable/strict/1761369889 -> viable/strict/1761369889 2025-12-04T09:14:55.9307608Z * [new tag] viable/strict/1761371385 -> viable/strict/1761371385 2025-12-04T09:14:55.9308579Z * [new tag] viable/strict/1761373581 -> viable/strict/1761373581 2025-12-04T09:14:55.9309741Z * [new tag] viable/strict/1761375054 -> viable/strict/1761375054 2025-12-04T09:14:55.9310702Z * [new tag] viable/strict/1761421785 -> viable/strict/1761421785 2025-12-04T09:14:55.9311896Z * [new tag] viable/strict/1761434614 -> viable/strict/1761434614 2025-12-04T09:14:55.9313290Z * [new tag] viable/strict/1761439254 -> viable/strict/1761439254 2025-12-04T09:14:55.9314221Z * [new tag] viable/strict/1761454187 -> viable/strict/1761454187 2025-12-04T09:14:55.9315431Z * [new tag] viable/strict/1761459991 -> viable/strict/1761459991 2025-12-04T09:14:55.9316607Z * [new tag] viable/strict/1761470668 -> viable/strict/1761470668 2025-12-04T09:14:55.9318036Z * [new tag] viable/strict/1761472188 -> viable/strict/1761472188 2025-12-04T09:14:55.9318970Z * [new tag] viable/strict/1761503178 -> viable/strict/1761503178 2025-12-04T09:14:55.9320019Z * [new tag] viable/strict/1761517492 -> viable/strict/1761517492 2025-12-04T09:14:55.9320983Z * [new tag] viable/strict/1761518981 -> viable/strict/1761518981 2025-12-04T09:14:55.9322222Z * [new tag] viable/strict/1761533609 -> viable/strict/1761533609 2025-12-04T09:14:55.9323012Z * [new tag] viable/strict/1761546438 -> viable/strict/1761546438 2025-12-04T09:14:55.9324309Z * [new tag] viable/strict/1761548133 -> viable/strict/1761548133 2025-12-04T09:14:55.9325597Z * [new tag] viable/strict/1761555186 -> viable/strict/1761555186 2025-12-04T09:14:55.9326745Z * [new tag] viable/strict/1761557178 -> viable/strict/1761557178 2025-12-04T09:14:55.9327647Z * [new tag] viable/strict/1761560772 -> viable/strict/1761560772 2025-12-04T09:14:55.9328757Z * [new tag] viable/strict/1761562266 -> viable/strict/1761562266 2025-12-04T09:14:55.9329721Z * [new tag] viable/strict/1761564260 -> viable/strict/1761564260 2025-12-04T09:14:55.9330801Z * [new tag] viable/strict/1761568072 -> viable/strict/1761568072 2025-12-04T09:14:55.9331776Z * [new tag] viable/strict/1761571683 -> viable/strict/1761571683 2025-12-04T09:14:55.9332713Z * [new tag] viable/strict/1761580199 -> viable/strict/1761580199 2025-12-04T09:14:55.9333699Z * [new tag] viable/strict/1761587383 -> viable/strict/1761587383 2025-12-04T09:14:55.9334873Z * [new tag] viable/strict/1761591165 -> viable/strict/1761591165 2025-12-04T09:14:55.9335787Z * [new tag] viable/strict/1761594575 -> viable/strict/1761594575 2025-12-04T09:14:55.9336919Z * [new tag] viable/strict/1761596710 -> viable/strict/1761596710 2025-12-04T09:14:55.9337829Z * [new tag] viable/strict/1761598189 -> viable/strict/1761598189 2025-12-04T09:14:55.9338859Z * [new tag] viable/strict/1761600254 -> viable/strict/1761600254 2025-12-04T09:14:55.9340389Z * [new tag] viable/strict/1761603879 -> viable/strict/1761603879 2025-12-04T09:14:55.9341653Z * [new tag] viable/strict/1761605429 -> viable/strict/1761605429 2025-12-04T09:14:55.9342788Z * [new tag] viable/strict/1761607468 -> viable/strict/1761607468 2025-12-04T09:14:55.9348356Z * [new tag] viable/strict/1761608983 -> viable/strict/1761608983 2025-12-04T09:14:55.9349528Z * [new tag] viable/strict/1761611846 -> viable/strict/1761611846 2025-12-04T09:14:55.9350682Z * [new tag] viable/strict/1761613922 -> viable/strict/1761613922 2025-12-04T09:14:55.9351401Z * [new tag] viable/strict/1761616504 -> viable/strict/1761616504 2025-12-04T09:14:55.9352246Z * [new tag] viable/strict/1761619599 -> viable/strict/1761619599 2025-12-04T09:14:55.9353484Z * [new tag] viable/strict/1761686693 -> viable/strict/1761686693 2025-12-04T09:14:55.9354319Z * [new tag] viable/strict/1761688179 -> viable/strict/1761688179 2025-12-04T09:14:55.9355587Z * [new tag] viable/strict/1761691973 -> viable/strict/1761691973 2025-12-04T09:14:55.9356796Z * [new tag] viable/strict/1761693884 -> viable/strict/1761693884 2025-12-04T09:14:55.9357885Z * [new tag] viable/strict/1761695389 -> viable/strict/1761695389 2025-12-04T09:14:55.9358617Z * [new tag] viable/strict/1761698408 -> viable/strict/1761698408 2025-12-04T09:14:55.9359876Z * [new tag] viable/strict/1761702931 -> viable/strict/1761702931 2025-12-04T09:14:55.9360717Z * [new tag] viable/strict/1761706307 -> viable/strict/1761706307 2025-12-04T09:14:55.9361956Z * [new tag] viable/strict/1761709065 -> viable/strict/1761709065 2025-12-04T09:14:55.9363101Z * [new tag] viable/strict/1761710285 -> viable/strict/1761710285 2025-12-04T09:14:55.9364197Z * [new tag] viable/strict/1761711983 -> viable/strict/1761711983 2025-12-04T09:14:55.9365347Z * [new tag] viable/strict/1761713514 -> viable/strict/1761713514 2025-12-04T09:14:55.9366568Z * [new tag] viable/strict/1761715523 -> viable/strict/1761715523 2025-12-04T09:14:55.9367649Z * [new tag] viable/strict/1761727973 -> viable/strict/1761727973 2025-12-04T09:14:55.9368726Z * [new tag] viable/strict/1761751558 -> viable/strict/1761751558 2025-12-04T09:14:55.9369780Z * [new tag] viable/strict/1761755187 -> viable/strict/1761755187 2025-12-04T09:14:55.9370877Z * [new tag] viable/strict/1761756826 -> viable/strict/1761756826 2025-12-04T09:14:55.9371962Z * [new tag] viable/strict/1761769551 -> viable/strict/1761769551 2025-12-04T09:14:55.9373116Z * [new tag] viable/strict/1761771032 -> viable/strict/1761771032 2025-12-04T09:14:55.9373805Z * [new tag] viable/strict/1761773101 -> viable/strict/1761773101 2025-12-04T09:14:55.9375115Z * [new tag] viable/strict/1761781792 -> viable/strict/1761781792 2025-12-04T09:14:55.9376272Z * [new tag] viable/strict/1761784788 -> viable/strict/1761784788 2025-12-04T09:14:55.9377104Z * [new tag] viable/strict/1761786740 -> viable/strict/1761786740 2025-12-04T09:14:55.9378280Z * [new tag] viable/strict/1761789332 -> viable/strict/1761789332 2025-12-04T09:14:55.9379853Z * [new tag] viable/strict/1761792569 -> viable/strict/1761792569 2025-12-04T09:14:55.9380930Z * [new tag] viable/strict/1761795289 -> viable/strict/1761795289 2025-12-04T09:14:55.9382083Z * [new tag] viable/strict/1761798345 -> viable/strict/1761798345 2025-12-04T09:14:55.9383136Z * [new tag] viable/strict/1761799827 -> viable/strict/1761799827 2025-12-04T09:14:55.9384276Z * [new tag] viable/strict/1761805604 -> viable/strict/1761805604 2025-12-04T09:14:55.9385136Z * [new tag] viable/strict/1761807202 -> viable/strict/1761807202 2025-12-04T09:14:55.9386360Z * [new tag] viable/strict/1761809094 -> viable/strict/1761809094 2025-12-04T09:14:55.9387206Z * [new tag] viable/strict/1761810576 -> viable/strict/1761810576 2025-12-04T09:14:55.9388466Z * [new tag] viable/strict/1761812771 -> viable/strict/1761812771 2025-12-04T09:14:55.9389504Z * [new tag] viable/strict/1761814363 -> viable/strict/1761814363 2025-12-04T09:14:55.9390599Z * [new tag] viable/strict/1761857410 -> viable/strict/1761857410 2025-12-04T09:14:55.9391680Z * [new tag] viable/strict/1761860985 -> viable/strict/1761860985 2025-12-04T09:14:55.9392563Z * [new tag] viable/strict/1761863094 -> viable/strict/1761863094 2025-12-04T09:14:55.9393758Z * [new tag] viable/strict/1761864590 -> viable/strict/1761864590 2025-12-04T09:14:55.9394814Z * [new tag] viable/strict/1761866675 -> viable/strict/1761866675 2025-12-04T09:14:55.9396076Z * [new tag] viable/strict/1761868178 -> viable/strict/1761868178 2025-12-04T09:14:55.9397118Z * [new tag] viable/strict/1761871111 -> viable/strict/1761871111 2025-12-04T09:14:55.9398211Z * [new tag] viable/strict/1761873126 -> viable/strict/1761873126 2025-12-04T09:14:55.9399303Z * [new tag] viable/strict/1761875714 -> viable/strict/1761875714 2025-12-04T09:14:55.9400102Z * [new tag] viable/strict/1761878924 -> viable/strict/1761878924 2025-12-04T09:14:55.9401408Z * [new tag] viable/strict/1761881727 -> viable/strict/1761881727 2025-12-04T09:14:55.9402470Z * [new tag] viable/strict/1761882959 -> viable/strict/1761882959 2025-12-04T09:14:55.9403574Z * [new tag] viable/strict/1761886268 -> viable/strict/1761886268 2025-12-04T09:14:55.9404455Z * [new tag] viable/strict/1761893641 -> viable/strict/1761893641 2025-12-04T09:14:55.9405784Z * [new tag] viable/strict/1761931517 -> viable/strict/1761931517 2025-12-04T09:14:55.9406966Z * [new tag] viable/strict/1761933080 -> viable/strict/1761933080 2025-12-04T09:14:55.9407782Z * [new tag] viable/strict/1761935217 -> viable/strict/1761935217 2025-12-04T09:14:55.9409028Z * [new tag] viable/strict/1761938533 -> viable/strict/1761938533 2025-12-04T09:14:55.9410173Z * [new tag] viable/strict/1761940184 -> viable/strict/1761940184 2025-12-04T09:14:55.9411210Z * [new tag] viable/strict/1761942338 -> viable/strict/1761942338 2025-12-04T09:14:55.9412242Z * [new tag] viable/strict/1761946100 -> viable/strict/1761946100 2025-12-04T09:14:55.9413340Z * [new tag] viable/strict/1761947374 -> viable/strict/1761947374 2025-12-04T09:14:55.9414767Z * [new tag] viable/strict/1761950978 -> viable/strict/1761950978 2025-12-04T09:14:55.9415932Z * [new tag] viable/strict/1761957727 -> viable/strict/1761957727 2025-12-04T09:14:55.9416980Z * [new tag] viable/strict/1761959532 -> viable/strict/1761959532 2025-12-04T09:14:55.9418089Z * [new tag] viable/strict/1761965366 -> viable/strict/1761965366 2025-12-04T09:14:55.9419276Z * [new tag] viable/strict/1761968066 -> viable/strict/1761968066 2025-12-04T09:14:55.9420381Z * [new tag] viable/strict/1761969322 -> viable/strict/1761969322 2025-12-04T09:14:55.9421688Z * [new tag] viable/strict/1761974723 -> viable/strict/1761974723 2025-12-04T09:14:55.9422385Z * [new tag] viable/strict/1761981837 -> viable/strict/1761981837 2025-12-04T09:14:55.9423694Z * [new tag] viable/strict/1761985546 -> viable/strict/1761985546 2025-12-04T09:14:55.9424777Z * [new tag] viable/strict/1761987030 -> viable/strict/1761987030 2025-12-04T09:14:55.9425882Z * [new tag] viable/strict/1762003554 -> viable/strict/1762003554 2025-12-04T09:14:55.9427186Z * [new tag] viable/strict/1762021560 -> viable/strict/1762021560 2025-12-04T09:14:55.9427722Z * [new tag] viable/strict/1762032190 -> viable/strict/1762032190 2025-12-04T09:14:55.9429068Z * [new tag] viable/strict/1762040981 -> viable/strict/1762040981 2025-12-04T09:14:55.9430131Z * [new tag] viable/strict/1762048525 -> viable/strict/1762048525 2025-12-04T09:14:55.9431511Z * [new tag] viable/strict/1762104223 -> viable/strict/1762104223 2025-12-04T09:14:55.9432573Z * [new tag] viable/strict/1762105778 -> viable/strict/1762105778 2025-12-04T09:14:55.9433640Z * [new tag] viable/strict/1762115109 -> viable/strict/1762115109 2025-12-04T09:14:55.9434686Z * [new tag] viable/strict/1762125840 -> viable/strict/1762125840 2025-12-04T09:14:55.9435555Z * [new tag] viable/strict/1762127377 -> viable/strict/1762127377 2025-12-04T09:14:55.9437057Z * [new tag] viable/strict/1762134925 -> viable/strict/1762134925 2025-12-04T09:14:55.9437941Z * [new tag] viable/strict/1762138338 -> viable/strict/1762138338 2025-12-04T09:14:55.9439104Z * [new tag] viable/strict/1762148993 -> viable/strict/1762148993 2025-12-04T09:14:55.9440051Z * [new tag] viable/strict/1762152871 -> viable/strict/1762152871 2025-12-04T09:14:55.9441192Z * [new tag] viable/strict/1762156183 -> viable/strict/1762156183 2025-12-04T09:14:55.9442148Z * [new tag] viable/strict/1762163457 -> viable/strict/1762163457 2025-12-04T09:14:55.9443609Z * [new tag] viable/strict/1762165569 -> viable/strict/1762165569 2025-12-04T09:14:55.9444605Z * [new tag] viable/strict/1762169035 -> viable/strict/1762169035 2025-12-04T09:14:55.9445837Z * [new tag] viable/strict/1762174936 -> viable/strict/1762174936 2025-12-04T09:14:55.9446801Z * [new tag] viable/strict/1762194412 -> viable/strict/1762194412 2025-12-04T09:14:55.9449513Z * [new tag] viable/strict/1762195876 -> viable/strict/1762195876 2025-12-04T09:14:55.9449726Z * [new tag] viable/strict/1762197788 -> viable/strict/1762197788 2025-12-04T09:14:55.9450949Z * [new tag] viable/strict/1762199389 -> viable/strict/1762199389 2025-12-04T09:14:55.9451281Z * [new tag] viable/strict/1762206585 -> viable/strict/1762206585 2025-12-04T09:14:55.9452697Z * [new tag] viable/strict/1762210184 -> viable/strict/1762210184 2025-12-04T09:14:55.9453288Z * [new tag] viable/strict/1762218736 -> viable/strict/1762218736 2025-12-04T09:14:55.9454633Z * [new tag] viable/strict/1762224529 -> viable/strict/1762224529 2025-12-04T09:14:55.9455846Z * [new tag] viable/strict/1762227253 -> viable/strict/1762227253 2025-12-04T09:14:55.9456434Z * [new tag] viable/strict/1762228515 -> viable/strict/1762228515 2025-12-04T09:14:55.9457991Z * [new tag] viable/strict/1762230349 -> viable/strict/1762230349 2025-12-04T09:14:55.9459031Z * [new tag] viable/strict/1762231859 -> viable/strict/1762231859 2025-12-04T09:14:55.9460149Z * [new tag] viable/strict/1762233925 -> viable/strict/1762233925 2025-12-04T09:14:55.9461346Z * [new tag] viable/strict/1762237630 -> viable/strict/1762237630 2025-12-04T09:14:55.9462004Z * [new tag] viable/strict/1762253522 -> viable/strict/1762253522 2025-12-04T09:14:55.9463507Z * [new tag] viable/strict/1762278588 -> viable/strict/1762278588 2025-12-04T09:14:55.9464541Z * [new tag] viable/strict/1762284203 -> viable/strict/1762284203 2025-12-04T09:14:55.9465690Z * [new tag] viable/strict/1762289446 -> viable/strict/1762289446 2025-12-04T09:14:55.9466734Z * [new tag] viable/strict/1762291515 -> viable/strict/1762291515 2025-12-04T09:14:55.9467787Z * [new tag] viable/strict/1762295100 -> viable/strict/1762295100 2025-12-04T09:14:55.9468470Z * [new tag] viable/strict/1762296590 -> viable/strict/1762296590 2025-12-04T09:14:55.9469636Z * [new tag] viable/strict/1762300179 -> viable/strict/1762300179 2025-12-04T09:14:55.9470322Z * [new tag] viable/strict/1762303207 -> viable/strict/1762303207 2025-12-04T09:14:55.9471690Z * [new tag] viable/strict/1762386584 -> viable/strict/1762386584 2025-12-04T09:14:55.9472741Z * [new tag] viable/strict/1762391537 -> viable/strict/1762391537 2025-12-04T09:14:55.9473407Z * [new tag] viable/strict/1762394119 -> viable/strict/1762394119 2025-12-04T09:14:55.9475086Z * [new tag] viable/strict/1762397437 -> viable/strict/1762397437 2025-12-04T09:14:55.9476223Z * [new tag] viable/strict/1762400256 -> viable/strict/1762400256 2025-12-04T09:14:55.9477031Z * [new tag] viable/strict/1762401469 -> viable/strict/1762401469 2025-12-04T09:14:55.9478289Z * [new tag] viable/strict/1762408195 -> viable/strict/1762408195 2025-12-04T09:14:55.9479358Z * [new tag] viable/strict/1762410411 -> viable/strict/1762410411 2025-12-04T09:14:55.9480431Z * [new tag] viable/strict/1762417613 -> viable/strict/1762417613 2025-12-04T09:14:55.9481409Z * [new tag] viable/strict/1762419198 -> viable/strict/1762419198 2025-12-04T09:14:55.9482628Z * [new tag] viable/strict/1762422656 -> viable/strict/1762422656 2025-12-04T09:14:55.9484087Z * [new tag] viable/strict/1762424746 -> viable/strict/1762424746 2025-12-04T09:14:55.9485764Z * [new tag] viable/strict/1762446386 -> viable/strict/1762446386 2025-12-04T09:14:55.9486844Z * [new tag] viable/strict/1762449912 -> viable/strict/1762449912 2025-12-04T09:14:55.9488044Z * [new tag] viable/strict/1762457031 -> viable/strict/1762457031 2025-12-04T09:14:55.9489169Z * [new tag] viable/strict/1762462441 -> viable/strict/1762462441 2025-12-04T09:14:55.9490147Z * [new tag] viable/strict/1762467909 -> viable/strict/1762467909 2025-12-04T09:14:55.9491394Z * [new tag] viable/strict/1762471493 -> viable/strict/1762471493 2025-12-04T09:14:55.9492505Z * [new tag] viable/strict/1762475990 -> viable/strict/1762475990 2025-12-04T09:14:55.9493665Z * [new tag] viable/strict/1762477933 -> viable/strict/1762477933 2025-12-04T09:14:55.9494644Z * [new tag] viable/strict/1762491053 -> viable/strict/1762491053 2025-12-04T09:14:55.9495962Z * [new tag] viable/strict/1762493118 -> viable/strict/1762493118 2025-12-04T09:14:55.9496835Z * [new tag] viable/strict/1762498442 -> viable/strict/1762498442 2025-12-04T09:14:55.9498027Z * [new tag] viable/strict/1762501778 -> viable/strict/1762501778 2025-12-04T09:14:55.9498992Z * [new tag] viable/strict/1762504001 -> viable/strict/1762504001 2025-12-04T09:14:55.9500243Z * [new tag] viable/strict/1762505583 -> viable/strict/1762505583 2025-12-04T09:14:55.9501368Z * [new tag] viable/strict/1762507523 -> viable/strict/1762507523 2025-12-04T09:14:55.9502549Z * [new tag] viable/strict/1762511140 -> viable/strict/1762511140 2025-12-04T09:14:55.9503765Z * [new tag] viable/strict/1762512632 -> viable/strict/1762512632 2025-12-04T09:14:55.9504848Z * [new tag] viable/strict/1762520467 -> viable/strict/1762520467 2025-12-04T09:14:55.9505850Z * [new tag] viable/strict/1762522016 -> viable/strict/1762522016 2025-12-04T09:14:55.9506964Z * [new tag] viable/strict/1762530591 -> viable/strict/1762530591 2025-12-04T09:14:55.9508178Z * [new tag] viable/strict/1762543405 -> viable/strict/1762543405 2025-12-04T09:14:55.9508781Z * [new tag] viable/strict/1762544998 -> viable/strict/1762544998 2025-12-04T09:14:55.9510074Z * [new tag] viable/strict/1762552182 -> viable/strict/1762552182 2025-12-04T09:14:55.9510957Z * [new tag] viable/strict/1762554297 -> viable/strict/1762554297 2025-12-04T09:14:55.9512058Z * [new tag] viable/strict/1762559381 -> viable/strict/1762559381 2025-12-04T09:14:55.9513217Z * [new tag] viable/strict/1762562222 -> viable/strict/1762562222 2025-12-04T09:14:55.9514505Z * [new tag] viable/strict/1762564319 -> viable/strict/1762564319 2025-12-04T09:14:55.9515040Z * [new tag] viable/strict/1762566904 -> viable/strict/1762566904 2025-12-04T09:14:55.9516209Z * [new tag] viable/strict/1762569781 -> viable/strict/1762569781 2025-12-04T09:14:55.9517186Z * [new tag] viable/strict/1762575940 -> viable/strict/1762575940 2025-12-04T09:14:55.9518407Z * [new tag] viable/strict/1762580974 -> viable/strict/1762580974 2025-12-04T09:14:55.9519539Z * [new tag] viable/strict/1762583185 -> viable/strict/1762583185 2025-12-04T09:14:55.9520505Z * [new tag] viable/strict/1762586647 -> viable/strict/1762586647 2025-12-04T09:14:55.9521733Z * [new tag] viable/strict/1762588183 -> viable/strict/1762588183 2025-12-04T09:14:55.9522875Z * [new tag] viable/strict/1762593886 -> viable/strict/1762593886 2025-12-04T09:14:55.9523872Z * [new tag] viable/strict/1762650743 -> viable/strict/1762650743 2025-12-04T09:14:55.9525190Z * [new tag] viable/strict/1762653328 -> viable/strict/1762653328 2025-12-04T09:14:55.9526175Z * [new tag] viable/strict/1762659342 -> viable/strict/1762659342 2025-12-04T09:14:55.9527348Z * [new tag] viable/strict/1762662360 -> viable/strict/1762662360 2025-12-04T09:14:55.9528329Z * [new tag] viable/strict/1762667377 -> viable/strict/1762667377 2025-12-04T09:14:55.9529475Z * [new tag] viable/strict/1762671090 -> viable/strict/1762671090 2025-12-04T09:14:55.9530585Z * [new tag] viable/strict/1762680284 -> viable/strict/1762680284 2025-12-04T09:14:55.9531552Z * [new tag] viable/strict/1762683900 -> viable/strict/1762683900 2025-12-04T09:14:55.9532695Z * [new tag] viable/strict/1762705541 -> viable/strict/1762705541 2025-12-04T09:14:55.9533670Z * [new tag] viable/strict/1762709004 -> viable/strict/1762709004 2025-12-04T09:14:55.9535025Z * [new tag] viable/strict/1762746004 -> viable/strict/1762746004 2025-12-04T09:14:55.9536150Z * [new tag] viable/strict/1762748799 -> viable/strict/1762748799 2025-12-04T09:14:55.9537104Z * [new tag] viable/strict/1762759504 -> viable/strict/1762759504 2025-12-04T09:14:55.9538399Z * [new tag] viable/strict/1762760973 -> viable/strict/1762760973 2025-12-04T09:14:55.9539389Z * [new tag] viable/strict/1762775374 -> viable/strict/1762775374 2025-12-04T09:14:55.9540557Z * [new tag] viable/strict/1762777661 -> viable/strict/1762777661 2025-12-04T09:14:55.9541529Z * [new tag] viable/strict/1762779774 -> viable/strict/1762779774 2025-12-04T09:14:55.9543083Z * [new tag] viable/strict/1762781259 -> viable/strict/1762781259 2025-12-04T09:14:55.9544264Z * [new tag] viable/strict/1762793628 -> viable/strict/1762793628 2025-12-04T09:14:55.9545268Z * [new tag] viable/strict/1762800711 -> viable/strict/1762800711 2025-12-04T09:14:55.9546434Z * [new tag] viable/strict/1762809894 -> viable/strict/1762809894 2025-12-04T09:14:55.9547388Z * [new tag] viable/strict/1762811384 -> viable/strict/1762811384 2025-12-04T09:14:55.9548674Z * [new tag] viable/strict/1762813841 -> viable/strict/1762813841 2025-12-04T09:14:55.9549660Z * [new tag] viable/strict/1762815047 -> viable/strict/1762815047 2025-12-04T09:14:55.9550990Z * [new tag] viable/strict/1762817094 -> viable/strict/1762817094 2025-12-04T09:14:55.9551990Z * [new tag] viable/strict/1762818582 -> viable/strict/1762818582 2025-12-04T09:14:55.9553156Z * [new tag] viable/strict/1762821623 -> viable/strict/1762821623 2025-12-04T09:14:55.9554006Z * [new tag] viable/strict/1762823531 -> viable/strict/1762823531 2025-12-04T09:14:55.9555260Z * [new tag] viable/strict/1762849583 -> viable/strict/1762849583 2025-12-04T09:14:55.9556689Z * [new tag] viable/strict/1762851200 -> viable/strict/1762851200 2025-12-04T09:14:55.9557949Z * [new tag] viable/strict/1762854603 -> viable/strict/1762854603 2025-12-04T09:14:55.9559007Z * [new tag] viable/strict/1762858276 -> viable/strict/1762858276 2025-12-04T09:14:55.9560180Z * [new tag] viable/strict/1762860891 -> viable/strict/1762860891 2025-12-04T09:14:55.9561903Z * [new tag] viable/strict/1762866174 -> viable/strict/1762866174 2025-12-04T09:14:55.9562946Z * [new tag] viable/strict/1762867653 -> viable/strict/1762867653 2025-12-04T09:14:55.9563784Z * [new tag] viable/strict/1762872669 -> viable/strict/1762872669 2025-12-04T09:14:55.9565031Z * [new tag] viable/strict/1762878380 -> viable/strict/1762878380 2025-12-04T09:14:55.9566140Z * [new tag] viable/strict/1762889003 -> viable/strict/1762889003 2025-12-04T09:14:55.9567302Z * [new tag] viable/strict/1762890589 -> viable/strict/1762890589 2025-12-04T09:14:55.9568355Z * [new tag] viable/strict/1762892743 -> viable/strict/1762892743 2025-12-04T09:14:55.9569462Z * [new tag] viable/strict/1762894271 -> viable/strict/1762894271 2025-12-04T09:14:55.9570124Z * [new tag] viable/strict/1762896287 -> viable/strict/1762896287 2025-12-04T09:14:55.9571458Z * [new tag] viable/strict/1762915871 -> viable/strict/1762915871 2025-12-04T09:14:55.9572610Z * [new tag] viable/strict/1762918569 -> viable/strict/1762918569 2025-12-04T09:14:55.9573366Z * [new tag] viable/strict/1762919776 -> viable/strict/1762919776 2025-12-04T09:14:55.9574678Z * [new tag] viable/strict/1762923072 -> viable/strict/1762923072 2025-12-04T09:14:55.9575898Z * [new tag] viable/strict/1762928826 -> viable/strict/1762928826 2025-12-04T09:14:55.9576967Z * [new tag] viable/strict/1762930451 -> viable/strict/1762930451 2025-12-04T09:14:55.9578004Z * [new tag] viable/strict/1762933780 -> viable/strict/1762933780 2025-12-04T09:14:55.9579119Z * [new tag] viable/strict/1762937638 -> viable/strict/1762937638 2025-12-04T09:14:55.9580414Z * [new tag] viable/strict/1762939545 -> viable/strict/1762939545 2025-12-04T09:14:55.9581463Z * [new tag] viable/strict/1762962692 -> viable/strict/1762962692 2025-12-04T09:14:55.9582560Z * [new tag] viable/strict/1762979143 -> viable/strict/1762979143 2025-12-04T09:14:55.9583661Z * [new tag] viable/strict/1762984188 -> viable/strict/1762984188 2025-12-04T09:14:55.9584339Z * [new tag] viable/strict/1762986306 -> viable/strict/1762986306 2025-12-04T09:14:55.9585678Z * [new tag] viable/strict/1762989903 -> viable/strict/1762989903 2025-12-04T09:14:55.9586721Z * [new tag] viable/strict/1762991377 -> viable/strict/1762991377 2025-12-04T09:14:55.9587831Z * [new tag] viable/strict/1762998921 -> viable/strict/1762998921 2025-12-04T09:14:55.9588994Z * [new tag] viable/strict/1763002287 -> viable/strict/1763002287 2025-12-04T09:14:55.9590158Z * [new tag] viable/strict/1763016840 -> viable/strict/1763016840 2025-12-04T09:14:55.9591035Z * [new tag] viable/strict/1763020180 -> viable/strict/1763020180 2025-12-04T09:14:55.9592428Z * [new tag] viable/strict/1763027421 -> viable/strict/1763027421 2025-12-04T09:14:55.9593248Z * [new tag] viable/strict/1763031120 -> viable/strict/1763031120 2025-12-04T09:14:55.9594660Z * [new tag] viable/strict/1763036861 -> viable/strict/1763036861 2025-12-04T09:14:55.9595802Z * [new tag] viable/strict/1763038993 -> viable/strict/1763038993 2025-12-04T09:14:55.9596961Z * [new tag] viable/strict/1763054703 -> viable/strict/1763054703 2025-12-04T09:14:55.9597648Z * [new tag] viable/strict/1763067061 -> viable/strict/1763067061 2025-12-04T09:14:55.9598941Z * [new tag] viable/strict/1763070847 -> viable/strict/1763070847 2025-12-04T09:14:55.9600048Z * [new tag] viable/strict/1763072706 -> viable/strict/1763072706 2025-12-04T09:14:55.9601224Z * [new tag] viable/strict/1763076302 -> viable/strict/1763076302 2025-12-04T09:14:55.9602266Z * [new tag] viable/strict/1763080816 -> viable/strict/1763080816 2025-12-04T09:14:55.9603381Z * [new tag] viable/strict/1763082732 -> viable/strict/1763082732 2025-12-04T09:14:55.9604477Z * [new tag] viable/strict/1763085329 -> viable/strict/1763085329 2025-12-04T09:14:55.9605605Z * [new tag] viable/strict/1763088623 -> viable/strict/1763088623 2025-12-04T09:14:55.9606796Z * [new tag] viable/strict/1763091402 -> viable/strict/1763091402 2025-12-04T09:14:55.9607871Z * [new tag] viable/strict/1763092602 -> viable/strict/1763092602 2025-12-04T09:14:55.9608960Z * [new tag] viable/strict/1763094355 -> viable/strict/1763094355 2025-12-04T09:14:55.9610080Z * [new tag] viable/strict/1763099390 -> viable/strict/1763099390 2025-12-04T09:14:55.9611186Z * [new tag] viable/strict/1763101608 -> viable/strict/1763101608 2025-12-04T09:14:55.9612309Z * [new tag] viable/strict/1763105102 -> viable/strict/1763105102 2025-12-04T09:14:55.9613447Z * [new tag] viable/strict/1763112347 -> viable/strict/1763112347 2025-12-04T09:14:55.9614529Z * [new tag] viable/strict/1763119471 -> viable/strict/1763119471 2025-12-04T09:14:55.9615314Z * [new tag] viable/strict/1763126835 -> viable/strict/1763126835 2025-12-04T09:14:55.9616435Z * [new tag] viable/strict/1763149779 -> viable/strict/1763149779 2025-12-04T09:14:55.9617518Z * [new tag] viable/strict/1763164178 -> viable/strict/1763164178 2025-12-04T09:14:55.9618593Z * [new tag] viable/strict/1763167104 -> viable/strict/1763167104 2025-12-04T09:14:55.9619663Z * [new tag] viable/strict/1763169132 -> viable/strict/1763169132 2025-12-04T09:14:55.9620704Z * [new tag] viable/strict/1763171708 -> viable/strict/1763171708 2025-12-04T09:14:55.9621783Z * [new tag] viable/strict/1763174759 -> viable/strict/1763174759 2025-12-04T09:14:55.9622918Z * [new tag] viable/strict/1763180744 -> viable/strict/1763180744 2025-12-04T09:14:55.9624030Z * [new tag] viable/strict/1763182227 -> viable/strict/1763182227 2025-12-04T09:14:55.9625356Z * [new tag] viable/strict/1763184309 -> viable/strict/1763184309 2025-12-04T09:14:55.9626775Z * [new tag] viable/strict/1763187991 -> viable/strict/1763187991 2025-12-04T09:14:55.9628294Z * [new tag] viable/strict/1763191445 -> viable/strict/1763191445 2025-12-04T09:14:55.9629528Z * [new tag] viable/strict/1763195152 -> viable/strict/1763195152 2025-12-04T09:14:55.9630550Z * [new tag] viable/strict/1763205769 -> viable/strict/1763205769 2025-12-04T09:14:55.9631702Z * [new tag] viable/strict/1763246990 -> viable/strict/1763246990 2025-12-04T09:14:55.9632867Z * [new tag] viable/strict/1763261578 -> viable/strict/1763261578 2025-12-04T09:14:55.9633674Z * [new tag] viable/strict/1763286573 -> viable/strict/1763286573 2025-12-04T09:14:55.9634814Z * [new tag] viable/strict/1763292167 -> viable/strict/1763292167 2025-12-04T09:14:55.9635882Z * [new tag] viable/strict/1763333386 -> viable/strict/1763333386 2025-12-04T09:14:55.9636949Z * [new tag] viable/strict/1763340082 -> viable/strict/1763340082 2025-12-04T09:14:55.9638763Z * [new tag] viable/strict/1763364324 -> viable/strict/1763364324 2025-12-04T09:14:55.9639919Z * [new tag] viable/strict/1763371569 -> viable/strict/1763371569 2025-12-04T09:14:55.9641012Z * [new tag] viable/strict/1763373067 -> viable/strict/1763373067 2025-12-04T09:14:55.9642045Z * [new tag] viable/strict/1763375157 -> viable/strict/1763375157 2025-12-04T09:14:55.9643463Z * [new tag] viable/strict/1763382462 -> viable/strict/1763382462 2025-12-04T09:14:55.9644654Z * [new tag] viable/strict/1763394661 -> viable/strict/1763394661 2025-12-04T09:14:55.9645987Z * [new tag] viable/strict/1763396797 -> viable/strict/1763396797 2025-12-04T09:14:55.9647129Z * [new tag] viable/strict/1763398542 -> viable/strict/1763398542 2025-12-04T09:14:55.9648241Z * [new tag] viable/strict/1763401807 -> viable/strict/1763401807 2025-12-04T09:14:55.9649117Z * [new tag] viable/strict/1763414698 -> viable/strict/1763414698 2025-12-04T09:14:55.9650269Z * [new tag] viable/strict/1763419807 -> viable/strict/1763419807 2025-12-04T09:14:55.9651476Z * [new tag] viable/strict/1763426369 -> viable/strict/1763426369 2025-12-04T09:14:55.9652325Z * [new tag] viable/strict/1763428331 -> viable/strict/1763428331 2025-12-04T09:14:55.9653670Z * [new tag] viable/strict/1763430922 -> viable/strict/1763430922 2025-12-04T09:14:55.9654376Z * [new tag] viable/strict/1763434184 -> viable/strict/1763434184 2025-12-04T09:14:55.9655684Z * [new tag] viable/strict/1763439973 -> viable/strict/1763439973 2025-12-04T09:14:55.9656900Z * [new tag] viable/strict/1763444995 -> viable/strict/1763444995 2025-12-04T09:14:55.9657675Z * [new tag] viable/strict/1763447206 -> viable/strict/1763447206 2025-12-04T09:14:55.9659044Z * [new tag] viable/strict/1763448826 -> viable/strict/1763448826 2025-12-04T09:14:55.9660086Z * [new tag] viable/strict/1763450717 -> viable/strict/1763450717 2025-12-04T09:14:55.9661221Z * [new tag] viable/strict/1763452183 -> viable/strict/1763452183 2025-12-04T09:14:55.9662356Z * [new tag] viable/strict/1763457945 -> viable/strict/1763457945 2025-12-04T09:14:55.9663432Z * [new tag] viable/strict/1763459439 -> viable/strict/1763459439 2025-12-04T09:14:55.9664131Z * [new tag] viable/strict/1763461556 -> viable/strict/1763461556 2025-12-04T09:14:55.9665476Z * [new tag] viable/strict/1763463103 -> viable/strict/1763463103 2025-12-04T09:14:55.9666733Z * [new tag] viable/strict/1763465100 -> viable/strict/1763465100 2025-12-04T09:14:55.9667435Z * [new tag] viable/strict/1763468866 -> viable/strict/1763468866 2025-12-04T09:14:55.9668594Z * [new tag] viable/strict/1763493823 -> viable/strict/1763493823 2025-12-04T09:14:55.9669294Z * [new tag] viable/strict/1763496249 -> viable/strict/1763496249 2025-12-04T09:14:55.9670658Z * [new tag] viable/strict/1763502620 -> viable/strict/1763502620 2025-12-04T09:14:55.9671846Z * [new tag] viable/strict/1763504715 -> viable/strict/1763504715 2025-12-04T09:14:55.9672883Z * [new tag] viable/strict/1763506208 -> viable/strict/1763506208 2025-12-04T09:14:55.9674007Z * [new tag] viable/strict/1763520590 -> viable/strict/1763520590 2025-12-04T09:14:55.9675107Z * [new tag] viable/strict/1763523357 -> viable/strict/1763523357 2025-12-04T09:14:55.9676291Z * [new tag] viable/strict/1763529922 -> viable/strict/1763529922 2025-12-04T09:14:55.9677406Z * [new tag] viable/strict/1763531408 -> viable/strict/1763531408 2025-12-04T09:14:55.9678446Z * [new tag] viable/strict/1763533622 -> viable/strict/1763533622 2025-12-04T09:14:55.9679620Z * [new tag] viable/strict/1763538576 -> viable/strict/1763538576 2025-12-04T09:14:55.9680756Z * [new tag] viable/strict/1763545823 -> viable/strict/1763545823 2025-12-04T09:14:55.9681446Z * [new tag] viable/strict/1763547951 -> viable/strict/1763547951 2025-12-04T09:14:55.9682885Z * [new tag] viable/strict/1763551477 -> viable/strict/1763551477 2025-12-04T09:14:55.9684006Z * [new tag] viable/strict/1763552982 -> viable/strict/1763552982 2025-12-04T09:14:55.9685225Z * [new tag] viable/strict/1763594698 -> viable/strict/1763594698 2025-12-04T09:14:55.9686271Z * [new tag] viable/strict/1763596178 -> viable/strict/1763596178 2025-12-04T09:14:55.9687381Z * [new tag] viable/strict/1763599155 -> viable/strict/1763599155 2025-12-04T09:14:55.9688456Z * [new tag] viable/strict/1763603717 -> viable/strict/1763603717 2025-12-04T09:14:55.9689605Z * [new tag] viable/strict/1763606923 -> viable/strict/1763606923 2025-12-04T09:14:55.9690646Z * [new tag] viable/strict/1763609715 -> viable/strict/1763609715 2025-12-04T09:14:55.9691755Z * [new tag] viable/strict/1763612757 -> viable/strict/1763612757 2025-12-04T09:14:55.9692806Z * [new tag] viable/strict/1763616325 -> viable/strict/1763616325 2025-12-04T09:14:55.9693891Z * [new tag] viable/strict/1763623509 -> viable/strict/1763623509 2025-12-04T09:14:55.9695134Z * [new tag] viable/strict/1763624984 -> viable/strict/1763624984 2025-12-04T09:14:55.9696280Z * [new tag] viable/strict/1763628796 -> viable/strict/1763628796 2025-12-04T09:14:55.9697072Z * [new tag] viable/strict/1763634343 -> viable/strict/1763634343 2025-12-04T09:14:55.9698279Z * [new tag] viable/strict/1763635867 -> viable/strict/1763635867 2025-12-04T09:14:55.9699945Z * [new tag] viable/strict/1763639382 -> viable/strict/1763639382 2025-12-04T09:14:55.9700998Z * [new tag] viable/strict/1763646626 -> viable/strict/1763646626 2025-12-04T09:14:55.9702365Z * [new tag] viable/strict/1763655997 -> viable/strict/1763655997 2025-12-04T09:14:55.9703421Z * [new tag] viable/strict/1763659444 -> viable/strict/1763659444 2025-12-04T09:14:55.9704471Z * [new tag] viable/strict/1763660992 -> viable/strict/1763660992 2025-12-04T09:14:55.9705549Z * [new tag] viable/strict/1763663201 -> viable/strict/1763663201 2025-12-04T09:14:55.9706671Z * [new tag] viable/strict/1763670362 -> viable/strict/1763670362 2025-12-04T09:14:55.9707369Z * [new tag] viable/strict/1763675378 -> viable/strict/1763675378 2025-12-04T09:14:55.9708766Z * [new tag] viable/strict/1763693343 -> viable/strict/1763693343 2025-12-04T09:14:55.9709599Z * [new tag] viable/strict/1763696088 -> viable/strict/1763696088 2025-12-04T09:14:55.9711014Z * [new tag] viable/strict/1763697343 -> viable/strict/1763697343 2025-12-04T09:14:55.9711896Z * [new tag] viable/strict/1763699165 -> viable/strict/1763699165 2025-12-04T09:14:55.9713185Z * [new tag] viable/strict/1763700660 -> viable/strict/1763700660 2025-12-04T09:14:55.9714295Z * [new tag] viable/strict/1763704209 -> viable/strict/1763704209 2025-12-04T09:14:55.9715184Z * [new tag] viable/strict/1763706411 -> viable/strict/1763706411 2025-12-04T09:14:55.9716338Z * [new tag] viable/strict/1763708082 -> viable/strict/1763708082 2025-12-04T09:14:55.9717192Z * [new tag] viable/strict/1763711381 -> viable/strict/1763711381 2025-12-04T09:14:55.9718398Z * [new tag] viable/strict/1763713593 -> viable/strict/1763713593 2025-12-04T09:14:55.9719453Z * [new tag] viable/strict/1763715201 -> viable/strict/1763715201 2025-12-04T09:14:55.9720494Z * [new tag] viable/strict/1763733017 -> viable/strict/1763733017 2025-12-04T09:14:55.9721599Z * [new tag] viable/strict/1763735108 -> viable/strict/1763735108 2025-12-04T09:14:55.9722638Z * [new tag] viable/strict/1763749579 -> viable/strict/1763749579 2025-12-04T09:14:55.9723713Z * [new tag] viable/strict/1763751113 -> viable/strict/1763751113 2025-12-04T09:14:55.9724871Z * [new tag] viable/strict/1763753035 -> viable/strict/1763753035 2025-12-04T09:14:55.9726024Z * [new tag] viable/strict/1763754578 -> viable/strict/1763754578 2025-12-04T09:14:55.9727063Z * [new tag] viable/strict/1763756748 -> viable/strict/1763756748 2025-12-04T09:14:55.9728089Z * [new tag] viable/strict/1763758205 -> viable/strict/1763758205 2025-12-04T09:14:55.9728915Z * [new tag] viable/strict/1763764050 -> viable/strict/1763764050 2025-12-04T09:14:55.9730053Z * [new tag] viable/strict/1763771887 -> viable/strict/1763771887 2025-12-04T09:14:55.9731358Z * [new tag] viable/strict/1763773920 -> viable/strict/1763773920 2025-12-04T09:14:55.9732290Z * [new tag] viable/strict/1763776501 -> viable/strict/1763776501 2025-12-04T09:14:55.9733437Z * [new tag] viable/strict/1763779437 -> viable/strict/1763779437 2025-12-04T09:14:55.9734800Z * [new tag] viable/strict/1763781038 -> viable/strict/1763781038 2025-12-04T09:14:55.9735767Z * [new tag] viable/strict/1763782245 -> viable/strict/1763782245 2025-12-04T09:14:55.9736971Z * [new tag] viable/strict/1763785568 -> viable/strict/1763785568 2025-12-04T09:14:55.9738038Z * [new tag] viable/strict/1763787006 -> viable/strict/1763787006 2025-12-04T09:14:55.9739236Z * [new tag] viable/strict/1763789103 -> viable/strict/1763789103 2025-12-04T09:14:55.9740191Z * [new tag] viable/strict/1763790578 -> viable/strict/1763790578 2025-12-04T09:14:55.9741329Z * [new tag] viable/strict/1763796275 -> viable/strict/1763796275 2025-12-04T09:14:55.9742854Z * [new tag] viable/strict/1763801465 -> viable/strict/1763801465 2025-12-04T09:14:55.9744011Z * [new tag] viable/strict/1763803522 -> viable/strict/1763803522 2025-12-04T09:14:55.9744950Z * [new tag] viable/strict/1763808581 -> viable/strict/1763808581 2025-12-04T09:14:55.9746127Z * [new tag] viable/strict/1763840977 -> viable/strict/1763840977 2025-12-04T09:14:55.9747049Z * [new tag] viable/strict/1763846659 -> viable/strict/1763846659 2025-12-04T09:14:55.9748177Z * [new tag] viable/strict/1763872065 -> viable/strict/1763872065 2025-12-04T09:14:55.9749349Z * [new tag] viable/strict/1763873648 -> viable/strict/1763873648 2025-12-04T09:14:55.9750326Z * [new tag] viable/strict/1763875506 -> viable/strict/1763875506 2025-12-04T09:14:55.9751265Z * [new tag] viable/strict/1763889904 -> viable/strict/1763889904 2025-12-04T09:14:55.9752404Z * [new tag] viable/strict/1763930999 -> viable/strict/1763930999 2025-12-04T09:14:55.9753376Z * [new tag] viable/strict/1763944964 -> viable/strict/1763944964 2025-12-04T09:14:55.9754311Z * [new tag] viable/strict/1763958474 -> viable/strict/1763958474 2025-12-04T09:14:55.9755511Z * [new tag] viable/strict/1763967263 -> viable/strict/1763967263 2025-12-04T09:14:55.9756621Z * [new tag] viable/strict/1763972803 -> viable/strict/1763972803 2025-12-04T09:14:55.9757881Z * [new tag] viable/strict/1763976376 -> viable/strict/1763976376 2025-12-04T09:14:55.9758695Z * [new tag] viable/strict/1763989404 -> viable/strict/1763989404 2025-12-04T09:14:55.9759862Z * [new tag] viable/strict/1763990887 -> viable/strict/1763990887 2025-12-04T09:14:55.9760806Z * [new tag] viable/strict/1764019919 -> viable/strict/1764019919 2025-12-04T09:14:55.9762019Z * [new tag] viable/strict/1764023134 -> viable/strict/1764023134 2025-12-04T09:14:55.9762864Z * [new tag] viable/strict/1764024593 -> viable/strict/1764024593 2025-12-04T09:14:55.9764024Z * [new tag] viable/strict/1764026706 -> viable/strict/1764026706 2025-12-04T09:14:55.9765463Z * [new tag] viable/strict/1764031139 -> viable/strict/1764031139 2025-12-04T09:14:55.9766864Z * [new tag] viable/strict/1764033131 -> viable/strict/1764033131 2025-12-04T09:14:55.9767685Z * [new tag] viable/strict/1764035725 -> viable/strict/1764035725 2025-12-04T09:14:55.9768608Z * [new tag] viable/strict/1764624265 -> viable/strict/1764624265 2025-12-04T09:14:55.9769990Z * [new tag] viable/strict/1764631514 -> viable/strict/1764631514 2025-12-04T09:14:55.9770844Z * [new tag] viable/strict/1764632987 -> viable/strict/1764632987 2025-12-04T09:14:55.9771808Z * [new tag] viable/strict/1764636063 -> viable/strict/1764636063 2025-12-04T09:14:55.9772730Z * [new tag] viable/strict/1764643975 -> viable/strict/1764643975 2025-12-04T09:14:55.9773617Z * [new tag] viable/strict/1764646859 -> viable/strict/1764646859 2025-12-04T09:14:55.9774642Z * [new tag] viable/strict/1764653120 -> viable/strict/1764653120 2025-12-04T09:14:55.9775422Z * [new tag] viable/strict/1764654632 -> viable/strict/1764654632 2025-12-04T09:14:55.9776344Z * [new tag] viable/strict/1764656821 -> viable/strict/1764656821 2025-12-04T09:14:55.9777256Z * [new tag] viable/strict/1764658557 -> viable/strict/1764658557 2025-12-04T09:14:55.9778165Z * [new tag] viable/strict/1764660333 -> viable/strict/1764660333 2025-12-04T09:14:55.9779073Z * [new tag] viable/strict/1764661812 -> viable/strict/1764661812 2025-12-04T09:14:55.9779938Z * [new tag] viable/strict/1764664023 -> viable/strict/1764664023 2025-12-04T09:14:55.9780838Z * [new tag] viable/strict/1764669150 -> viable/strict/1764669150 2025-12-04T09:14:55.9781764Z * [new tag] viable/strict/1764680709 -> viable/strict/1764680709 2025-12-04T09:14:55.9782631Z * [new tag] viable/strict/1764687619 -> viable/strict/1764687619 2025-12-04T09:14:55.9783555Z * [new tag] viable/strict/1764696355 -> viable/strict/1764696355 2025-12-04T09:14:55.9784454Z * [new tag] viable/strict/1764701767 -> viable/strict/1764701767 2025-12-04T09:14:55.9785380Z * [new tag] viable/strict/1764710768 -> viable/strict/1764710768 2025-12-04T09:14:55.9786278Z * [new tag] viable/strict/1764716202 -> viable/strict/1764716202 2025-12-04T09:14:55.9787186Z * [new tag] viable/strict/1764793566 -> viable/strict/1764793566 2025-12-04T09:14:55.9788093Z * [new tag] viable/strict/1764797093 -> viable/strict/1764797093 2025-12-04T09:14:55.9788990Z * [new tag] viable/strict/1764800729 -> viable/strict/1764800729 2025-12-04T09:14:55.9790199Z * [new tag] whc_flight_1 -> whc_flight_1 2025-12-04T09:14:55.9791333Z * [new tag] whc_flight_2 -> whc_flight_2 2025-12-04T09:14:55.9792610Z * [new tag] whc_flight_4 -> whc_flight_4 2025-12-04T09:14:56.0566902Z [command]/usr/bin/git rev-parse --verify --quiet ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32^{object} 2025-12-04T09:14:56.0595059Z ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:14:56.0598738Z ##[endgroup] 2025-12-04T09:14:56.0599160Z ##[group]Determining the checkout info 2025-12-04T09:14:56.0600103Z ##[endgroup] 2025-12-04T09:14:56.0604016Z [command]/usr/bin/git sparse-checkout disable 2025-12-04T09:14:56.0637289Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-12-04T09:14:56.0673515Z ##[group]Checking out the ref 2025-12-04T09:14:56.0677097Z [command]/usr/bin/git checkout --progress --force ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:14:57.0964901Z Updating files: 79% (16054/20121) 2025-12-04T09:14:57.1289876Z Updating files: 80% (16097/20121) 2025-12-04T09:14:57.1581498Z Updating files: 81% (16299/20121) 2025-12-04T09:14:57.1796981Z 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You can look around, make experimental 2025-12-04T09:14:57.4903381Z changes and commit them, and you can discard any commits you make in this 2025-12-04T09:14:57.4903976Z state without impacting any branches by switching back to a branch. 2025-12-04T09:14:57.4904336Z 2025-12-04T09:14:57.4904556Z If you want to create a new branch to retain commits you create, you may 2025-12-04T09:14:57.4905103Z do so (now or later) by using -c with the switch command. Example: 2025-12-04T09:14:57.4905416Z 2025-12-04T09:14:57.4905540Z git switch -c 2025-12-04T09:14:57.4905766Z 2025-12-04T09:14:57.4905875Z Or undo this operation with: 2025-12-04T09:14:57.4906066Z 2025-12-04T09:14:57.4906171Z git switch - 2025-12-04T09:14:57.4906307Z 2025-12-04T09:14:57.4906570Z Turn off this advice by setting config variable advice.detachedHead to false 2025-12-04T09:14:57.4906943Z 2025-12-04T09:14:57.4907241Z HEAD is now at ffd9b0fb435 Resolve collective autotuning test failure on arm (#168919) 2025-12-04T09:14:57.4980340Z ##[endgroup] 2025-12-04T09:14:57.4980788Z ##[group]Setting up auth for fetching submodules 2025-12-04T09:14:57.4987563Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-12-04T09:14:57.5029348Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-12-04T09:14:57.5058803Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-12-04T09:14:57.5088534Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-12-04T09:14:57.5114021Z ##[endgroup] 2025-12-04T09:14:57.5114525Z ##[group]Fetching submodules 2025-12-04T09:14:57.5118285Z [command]/usr/bin/git submodule sync --recursive 2025-12-04T09:14:57.5496535Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-12-04T09:14:57.5902044Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-12-04T09:14:57.5904678Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-12-04T09:14:57.5907430Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-12-04T09:14:57.5910250Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-12-04T09:14:57.5913194Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-12-04T09:14:57.5916509Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-12-04T09:14:57.5919447Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-12-04T09:14:57.5922649Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-12-04T09:14:57.5926291Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-12-04T09:14:57.5929959Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-12-04T09:14:57.5933638Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-12-04T09:14:57.5937064Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-12-04T09:14:57.5940870Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-12-04T09:14:57.5945362Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-12-04T09:14:57.5949389Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-12-04T09:14:57.5953569Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-12-04T09:14:57.5959132Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-12-04T09:14:57.5963398Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-12-04T09:14:57.5968095Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-12-04T09:14:57.5972424Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-12-04T09:14:57.5977104Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-12-04T09:14:57.5981663Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-12-04T09:14:57.5986410Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-12-04T09:14:57.5991269Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-12-04T09:14:57.5996286Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-12-04T09:14:57.6001274Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-12-04T09:14:57.6006426Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-12-04T09:14:57.6011538Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-12-04T09:14:57.6017137Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-12-04T09:14:57.6022326Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-12-04T09:14:57.6027885Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-12-04T09:14:57.6033466Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-12-04T09:14:57.6039290Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-12-04T09:14:57.6046928Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-12-04T09:14:57.6052997Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-12-04T09:14:57.6058881Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-12-04T09:14:57.6065100Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-12-04T09:14:57.6101976Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/android/libs/fbjni'... 2025-12-04T09:14:57.8541941Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FXdiv'... 2025-12-04T09:14:57.8543690Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FP16'... 2025-12-04T09:14:57.8545131Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NNPACK'... 2025-12-04T09:14:57.8576953Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fmt'... 2025-12-04T09:15:01.1847876Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/benchmark'... 2025-12-04T09:15:01.1849352Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NVTX'... 2025-12-04T09:15:01.1850728Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gloo'... 2025-12-04T09:15:01.1852275Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-12-04T09:15:01.1853919Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention'... 2025-12-04T09:15:01.1855422Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-12-04T09:15:01.1857248Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-12-04T09:15:01.1888296Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep'... 2025-12-04T09:15:01.1889963Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ittapi'... 2025-12-04T09:15:01.1891561Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kleidiai'... 2025-12-04T09:15:01.1893486Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pocketfft'... 2025-12-04T09:15:01.1895409Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-12-04T09:15:01.1897096Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/psimd'... 2025-12-04T09:15:01.1898743Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/googletest'... 2025-12-04T09:15:01.2057115Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-12-04T09:15:01.7533190Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-12-04T09:15:01.7534775Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/mimalloc'... 2025-12-04T09:15:01.7536185Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto'... 2025-12-04T09:15:01.7537789Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-12-04T09:15:01.7539477Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-12-04T09:15:01.8534616Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx'... 2025-12-04T09:15:05.4918826Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-12-04T09:15:05.4920662Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/sleef'... 2025-12-04T09:15:05.4922172Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pybind11'... 2025-12-04T09:15:05.4923680Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm'... 2025-12-04T09:15:05.4925239Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cutlass'... 2025-12-04T09:15:05.5920533Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-12-04T09:15:24.9406467Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-12-04T09:15:24.9407362Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/nlohmann'... 2025-12-04T09:15:24.9408203Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-12-04T09:15:24.9409311Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter'... 2025-12-04T09:15:24.9410070Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf'... 2025-12-04T09:15:24.9604338Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-12-04T09:15:24.9770624Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-12-04T09:15:24.9904550Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-12-04T09:15:25.0209912Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-12-04T09:15:25.1163983Z Submodule path 'third_party/NVTX': checked out '3ebbc93ded7285963bff932c678fa367eb393ba6' 2025-12-04T09:15:25.1735634Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-12-04T09:15:25.9659893Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-12-04T09:15:26.1667454Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-12-04T09:15:26.1691425Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-12-04T09:15:26.1722626Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-12-04T09:15:31.5855514Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-12-04T09:15:31.6125420Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-12-04T09:15:31.9960304Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-12-04T09:15:32.0492499Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-12-04T09:15:32.1536812Z Submodule path 'third_party/cpuinfo': checked out 'f858c30bcb16f8effd5ff46996f0514539e17abc' 2025-12-04T09:15:32.2064933Z Submodule path 'third_party/cudnn_frontend': checked out '0b1577c8c83401237d601d0d0db5210506705396' 2025-12-04T09:15:32.8994781Z Submodule path 'third_party/cutlass': checked out 'f88806b1e31dfa579842638740216dd41fc6c588' 2025-12-04T09:15:33.0681009Z Submodule path 'third_party/fbgemm': checked out 'c0b988d39a9e47c794d699f29930ed4d7c7e13a4' 2025-12-04T09:15:33.0706317Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-12-04T09:15:33.0709660Z Submodule 'external/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-12-04T09:15:33.0712032Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-12-04T09:15:33.0715145Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-12-04T09:15:33.0718461Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-12-04T09:15:33.0721730Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-12-04T09:15:33.0724635Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-12-04T09:15:33.0758308Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-12-04T09:15:34.4678991Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-12-04T09:15:34.4679996Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-12-04T09:15:34.4681252Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-12-04T09:15:34.5680389Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-12-04T09:15:38.1044456Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-12-04T09:15:38.2045445Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-12-04T09:15:41.0531363Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-12-04T09:15:41.4250997Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-12-04T09:15:41.5310562Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-12-04T09:15:42.1992901Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '98125ce499b0fdf7ffbe0e3052f5b8709f4840f8' 2025-12-04T09:15:42.2488899Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-12-04T09:15:42.2619151Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-12-04T09:15:42.3687438Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-12-04T09:15:42.4427925Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-12-04T09:15:42.4449511Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-12-04T09:15:42.4452078Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-12-04T09:15:42.4482667Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-12-04T09:15:47.4383170Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-12-04T09:15:47.6968138Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-12-04T09:15:48.2952544Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-12-04T09:15:48.4433161Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-12-04T09:15:48.4753555Z Submodule path 'third_party/fmt': checked out '407c905e45ad75fc29bf0f9bb7c5c2fd3475976f' 2025-12-04T09:15:48.5184949Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-12-04T09:15:48.5460400Z Submodule path 'third_party/gloo': checked out '54cbae0d3a67fa890b4c3d9ee162b7860315e341' 2025-12-04T09:15:48.5943184Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-12-04T09:15:48.6085517Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-12-04T09:15:48.6105906Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-12-04T09:15:48.6134528Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-12-04T09:16:05.7163348Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-12-04T09:16:05.7395286Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-12-04T09:16:05.8314632Z Submodule path 'third_party/kineto': checked out '31f85df8fbd89c188f14ef10f1ec65379786b943' 2025-12-04T09:16:05.8337199Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-12-04T09:16:05.8339780Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-12-04T09:16:05.8343472Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-12-04T09:16:05.8376671Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-12-04T09:16:06.9326321Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-12-04T09:16:07.4947658Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-12-04T09:16:07.5940404Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out 'd2ffe0a4e3acace628db49974246b66fc3e85fb1' 2025-12-04T09:16:07.5960926Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-12-04T09:16:07.5963654Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-12-04T09:16:07.5966744Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-12-04T09:16:07.5969874Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-12-04T09:16:07.5972968Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-12-04T09:16:07.5976316Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-12-04T09:16:07.5979650Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-12-04T09:16:07.5983110Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-12-04T09:16:07.5986763Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp' 2025-12-04T09:16:07.6020984Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-12-04T09:16:09.6301986Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-12-04T09:16:09.6303316Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-12-04T09:16:09.6304643Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp'... 2025-12-04T09:16:09.6305947Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-12-04T09:16:09.6307183Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-12-04T09:16:09.6308451Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-12-04T09:16:09.6309727Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-12-04T09:16:09.7303433Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-12-04T09:16:16.2874534Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-12-04T09:16:16.3076102Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-12-04T09:16:16.3477877Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-12-04T09:16:16.3638609Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-12-04T09:16:16.3658510Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-12-04T09:16:16.3689399Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-12-04T09:16:16.6586848Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-12-04T09:16:16.6800095Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-12-04T09:16:16.7298248Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-12-04T09:16:16.8397495Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-12-04T09:16:16.8587246Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 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'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-12-04T09:16:38.1018849Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-12-04T09:16:38.1370492Z Entering 'android/libs/fbjni' 2025-12-04T09:16:38.1433582Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-12-04T09:16:38.1454783Z Entering 'third_party/FP16' 2025-12-04T09:16:38.1516238Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-12-04T09:16:38.1536931Z Entering 'third_party/FXdiv' 2025-12-04T09:16:38.1599318Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-12-04T09:16:38.1619051Z Entering 'third_party/NNPACK' 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2025-12-04T09:16:39.2085021Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-12-04T09:16:39.2132225Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-12-04T09:16:39.2182844Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-12-04T09:16:39.2230471Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-12-04T09:16:39.2279584Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-12-04T09:16:39.2327393Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T09:16:39.2380051Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T09:16:39.2430500Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-12-04T09:16:39.2500199Z Entering 'third_party/pocketfft' 2025-12-04T09:16:39.2551628Z Entering 'third_party/protobuf' 2025-12-04T09:16:39.2604459Z Entering 'third_party/protobuf/third_party/benchmark' 2025-12-04T09:16:39.2652659Z Entering 'third_party/protobuf/third_party/googletest' 2025-12-04T09:16:39.2702636Z Entering 'third_party/psimd' 2025-12-04T09:16:39.2753641Z Entering 'third_party/pthreadpool' 2025-12-04T09:16:39.2803777Z Entering 'third_party/pybind11' 2025-12-04T09:16:39.2855029Z Entering 'third_party/python-peachpy' 2025-12-04T09:16:39.2904229Z Entering 'third_party/sleef' 2025-12-04T09:16:39.2956343Z Entering 'third_party/tensorpipe' 2025-12-04T09:16:39.3005470Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-12-04T09:16:39.3053403Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-12-04T09:16:39.3099801Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-12-04T09:16:39.3150404Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-12-04T09:16:39.3198005Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-12-04T09:16:39.3266098Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-12-04T09:16:39.3616674Z Entering 'android/libs/fbjni' 2025-12-04T09:16:39.3668113Z Entering 'third_party/FP16' 2025-12-04T09:16:39.3719298Z Entering 'third_party/FXdiv' 2025-12-04T09:16:39.3769828Z Entering 'third_party/NNPACK' 2025-12-04T09:16:39.3821521Z Entering 'third_party/NVTX' 2025-12-04T09:16:39.3872491Z Entering 'third_party/VulkanMemoryAllocator' 2025-12-04T09:16:39.3923165Z Entering 'third_party/XNNPACK' 2025-12-04T09:16:39.3989280Z Entering 'third_party/aiter' 2025-12-04T09:16:39.4042537Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-12-04T09:16:39.4100794Z Entering 'third_party/benchmark' 2025-12-04T09:16:39.4151275Z Entering 'third_party/composable_kernel' 2025-12-04T09:16:39.4210801Z Entering 'third_party/cpp-httplib' 2025-12-04T09:16:39.4259881Z Entering 'third_party/cpuinfo' 2025-12-04T09:16:39.4311874Z Entering 'third_party/cudnn_frontend' 2025-12-04T09:16:39.4362162Z Entering 'third_party/cutlass' 2025-12-04T09:16:39.4421934Z Entering 'third_party/fbgemm' 2025-12-04T09:16:39.4475344Z Entering 'third_party/fbgemm/external/asmjit' 2025-12-04T09:16:39.4523586Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-12-04T09:16:39.4579392Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-12-04T09:16:39.4629155Z Entering 'third_party/fbgemm/external/cutlass' 2025-12-04T09:16:39.4687561Z Entering 'third_party/fbgemm/external/googletest' 2025-12-04T09:16:39.4735604Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-12-04T09:16:39.4784682Z Entering 'third_party/fbgemm/external/json' 2025-12-04T09:16:39.4836345Z Entering 'third_party/flash-attention' 2025-12-04T09:16:39.4889705Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-12-04T09:16:39.4944925Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-12-04T09:16:39.5001731Z Entering 'third_party/flatbuffers' 2025-12-04T09:16:39.5054645Z Entering 'third_party/fmt' 2025-12-04T09:16:39.5104407Z Entering 'third_party/gemmlowp/gemmlowp' 2025-12-04T09:16:39.5156010Z Entering 'third_party/gloo' 2025-12-04T09:16:39.5204888Z Entering 'third_party/googletest' 2025-12-04T09:16:39.5254601Z Entering 'third_party/ideep' 2025-12-04T09:16:39.5303049Z Entering 'third_party/ideep/mkl-dnn' 2025-12-04T09:16:39.5360175Z Entering 'third_party/ittapi' 2025-12-04T09:16:39.5410720Z Entering 'third_party/kineto' 2025-12-04T09:16:39.5461092Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-12-04T09:16:39.5510140Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-12-04T09:16:39.5561058Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-12-04T09:16:39.5609474Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-12-04T09:16:39.5659533Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-12-04T09:16:39.5708752Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-12-04T09:16:39.5759457Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-12-04T09:16:39.5808966Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-12-04T09:16:39.5857145Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-12-04T09:16:39.5906215Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-12-04T09:16:39.5954590Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp' 2025-12-04T09:16:39.6003520Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T09:16:39.6055909Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T09:16:39.6110404Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-12-04T09:16:39.6158822Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-12-04T09:16:39.6208985Z Entering 'third_party/kleidiai' 2025-12-04T09:16:39.6261102Z Entering 'third_party/mimalloc' 2025-12-04T09:16:39.6312671Z Entering 'third_party/nlohmann' 2025-12-04T09:16:39.6365114Z Entering 'third_party/onnx' 2025-12-04T09:16:39.6432506Z Entering 'third_party/onnx/third_party/pybind11' 2025-12-04T09:16:39.6483608Z Entering 'third_party/opentelemetry-cpp' 2025-12-04T09:16:39.6536869Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-12-04T09:16:39.6585523Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-12-04T09:16:39.6633294Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-12-04T09:16:39.6680929Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-12-04T09:16:39.6729737Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-12-04T09:16:39.6777162Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-12-04T09:16:39.6825493Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-12-04T09:16:39.6872740Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T09:16:39.6921852Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T09:16:39.6972316Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-12-04T09:16:39.7041787Z Entering 'third_party/pocketfft' 2025-12-04T09:16:39.7093080Z Entering 'third_party/protobuf' 2025-12-04T09:16:39.7147409Z Entering 'third_party/protobuf/third_party/benchmark' 2025-12-04T09:16:39.7194726Z Entering 'third_party/protobuf/third_party/googletest' 2025-12-04T09:16:39.7247237Z Entering 'third_party/psimd' 2025-12-04T09:16:39.7296498Z Entering 'third_party/pthreadpool' 2025-12-04T09:16:39.7350290Z Entering 'third_party/pybind11' 2025-12-04T09:16:39.7400459Z Entering 'third_party/python-peachpy' 2025-12-04T09:16:39.7451737Z Entering 'third_party/sleef' 2025-12-04T09:16:39.7501545Z Entering 'third_party/tensorpipe' 2025-12-04T09:16:39.7552359Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-12-04T09:16:39.7601493Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-12-04T09:16:39.7649785Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-12-04T09:16:39.7697690Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-12-04T09:16:39.7745769Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-12-04T09:16:39.7810537Z ##[endgroup] 2025-12-04T09:16:39.7851085Z [command]/usr/bin/git log -1 --format=%H 2025-12-04T09:16:39.7876577Z ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:16:39.7991390Z ##[group]Run cd "${GITHUB_WORKSPACE}" 2025-12-04T09:16:39.7991787Z cd "${GITHUB_WORKSPACE}" 2025-12-04T09:16:39.7992114Z # Clean stale submodule dirs 2025-12-04T09:16:39.7992456Z if [ -z "${NO_SUDO}" ]; then 2025-12-04T09:16:39.7992875Z  sudo git submodule foreach --recursive git clean -ffdx 2025-12-04T09:16:39.7993281Z else 2025-12-04T09:16:39.7993763Z  git submodule foreach --recursive git clean -ffdx 2025-12-04T09:16:39.7994157Z fi 2025-12-04T09:16:39.8004705Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:39.8005119Z env: 2025-12-04T09:16:39.8005348Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:39.8005615Z NO_SUDO: true 2025-12-04T09:16:39.8005850Z ##[endgroup] 2025-12-04T09:16:39.8380646Z Entering 'android/libs/fbjni' 2025-12-04T09:16:39.8417936Z Entering 'third_party/FP16' 2025-12-04T09:16:39.8456531Z Entering 'third_party/FXdiv' 2025-12-04T09:16:39.8490988Z Entering 'third_party/NNPACK' 2025-12-04T09:16:39.8531921Z Entering 'third_party/NVTX' 2025-12-04T09:16:39.8574625Z Entering 'third_party/VulkanMemoryAllocator' 2025-12-04T09:16:39.8613036Z Entering 'third_party/XNNPACK' 2025-12-04T09:16:39.8741573Z Entering 'third_party/aiter' 2025-12-04T09:16:39.8790664Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-12-04T09:16:39.8904510Z Entering 'third_party/benchmark' 2025-12-04T09:16:39.8943560Z Entering 'third_party/composable_kernel' 2025-12-04T09:16:39.9067258Z Entering 'third_party/cpp-httplib' 2025-12-04T09:16:39.9105000Z Entering 'third_party/cpuinfo' 2025-12-04T09:16:39.9147344Z Entering 'third_party/cudnn_frontend' 2025-12-04T09:16:39.9186728Z Entering 'third_party/cutlass' 2025-12-04T09:16:39.9299241Z Entering 'third_party/fbgemm' 2025-12-04T09:16:39.9366934Z Entering 'third_party/fbgemm/external/asmjit' 2025-12-04T09:16:39.9402462Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-12-04T09:16:39.9524752Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-12-04T09:16:39.9564988Z Entering 'third_party/fbgemm/external/cutlass' 2025-12-04T09:16:39.9669949Z Entering 'third_party/fbgemm/external/googletest' 2025-12-04T09:16:39.9707121Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-12-04T09:16:39.9740547Z Entering 'third_party/fbgemm/external/json' 2025-12-04T09:16:39.9791339Z Entering 'third_party/flash-attention' 2025-12-04T09:16:39.9835968Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-12-04T09:16:39.9939107Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-12-04T09:16:40.0035634Z Entering 'third_party/flatbuffers' 2025-12-04T09:16:40.0114603Z Entering 'third_party/fmt' 2025-12-04T09:16:40.0153263Z Entering 'third_party/gemmlowp/gemmlowp' 2025-12-04T09:16:40.0190407Z Entering 'third_party/gloo' 2025-12-04T09:16:40.0228811Z Entering 'third_party/googletest' 2025-12-04T09:16:40.0266783Z Entering 'third_party/ideep' 2025-12-04T09:16:40.0301357Z Entering 'third_party/ideep/mkl-dnn' 2025-12-04T09:16:40.0392875Z Entering 'third_party/ittapi' 2025-12-04T09:16:40.0430711Z Entering 'third_party/kineto' 2025-12-04T09:16:40.0470170Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-12-04T09:16:40.0511903Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-12-04T09:16:40.0563441Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-12-04T09:16:40.0598442Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-12-04T09:16:40.0636310Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-12-04T09:16:40.0670867Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-12-04T09:16:40.0707109Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-12-04T09:16:40.0742678Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-12-04T09:16:40.0781020Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-12-04T09:16:40.0825999Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-12-04T09:16:40.0863904Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp' 2025-12-04T09:16:40.0899178Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T09:16:40.0952517Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T09:16:40.0994495Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-12-04T09:16:40.1030050Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-12-04T09:16:40.1069163Z Entering 'third_party/kleidiai' 2025-12-04T09:16:40.1114068Z Entering 'third_party/mimalloc' 2025-12-04T09:16:40.1152601Z Entering 'third_party/nlohmann' 2025-12-04T09:16:40.1202104Z Entering 'third_party/onnx' 2025-12-04T09:16:40.1550692Z Entering 'third_party/onnx/third_party/pybind11' 2025-12-04T09:16:40.1591635Z Entering 'third_party/opentelemetry-cpp' 2025-12-04T09:16:40.1655422Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-12-04T09:16:40.1690271Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-12-04T09:16:40.1728571Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-12-04T09:16:40.1763686Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-12-04T09:16:40.1810903Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-12-04T09:16:40.1847377Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-12-04T09:16:40.1882177Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-12-04T09:16:40.1917529Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T09:16:40.1970414Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T09:16:40.2009372Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-12-04T09:16:40.2277885Z Entering 'third_party/pocketfft' 2025-12-04T09:16:40.2313014Z Entering 'third_party/protobuf' 2025-12-04T09:16:40.2397270Z Entering 'third_party/protobuf/third_party/benchmark' 2025-12-04T09:16:40.2432174Z Entering 'third_party/protobuf/third_party/googletest' 2025-12-04T09:16:40.2473190Z Entering 'third_party/psimd' 2025-12-04T09:16:40.2507831Z Entering 'third_party/pthreadpool' 2025-12-04T09:16:40.2543166Z Entering 'third_party/pybind11' 2025-12-04T09:16:40.2581348Z Entering 'third_party/python-peachpy' 2025-12-04T09:16:40.2616716Z Entering 'third_party/sleef' 2025-12-04T09:16:40.2655526Z Entering 'third_party/tensorpipe' 2025-12-04T09:16:40.2695109Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-12-04T09:16:40.2733205Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-12-04T09:16:40.2767314Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-12-04T09:16:40.2806156Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-12-04T09:16:40.2840654Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-12-04T09:16:40.3022537Z Prepare all required actions 2025-12-04T09:16:40.3023162Z Getting action download info 2025-12-04T09:16:40.4774637Z ##[group]Run ./.github/actions/setup-linux 2025-12-04T09:16:40.4774982Z env: 2025-12-04T09:16:40.4775216Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.4775490Z ##[endgroup] 2025-12-04T09:16:40.4818333Z ##[group]Run set -euo pipefail 2025-12-04T09:16:40.4818715Z set -euo pipefail 2025-12-04T09:16:40.4819027Z function get_ec2_metadata() { 2025-12-04T09:16:40.4819432Z  # Pulled from instance metadata endpoint for EC2 2025-12-04T09:16:40.4820104Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-12-04T09:16:40.4820710Z  category=$1 2025-12-04T09:16:40.4821095Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-12-04T09:16:40.4821573Z  runner_name_str=i-0ed9e7c329090f0b0 2025-12-04T09:16:40.4821983Z  if [[ -f /.inarc ]]; then 2025-12-04T09:16:40.4822342Z  echo "ARC Runner, no info on ec2 metadata" 2025-12-04T09:16:40.4822757Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-12-04T09:16:40.4823259Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-12-04T09:16:40.4823719Z  else 2025-12-04T09:16:40.4824646Z  curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}" 2025-12-04T09:16:40.4825645Z  fi 2025-12-04T09:16:40.4825871Z } 2025-12-04T09:16:40.4826150Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-12-04T09:16:40.4826593Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-12-04T09:16:40.4827109Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-12-04T09:16:40.4827562Z echo "system info $(uname -a)" 2025-12-04T09:16:40.4834072Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:40.4834478Z env: 2025-12-04T09:16:40.4834702Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.4834960Z ##[endgroup] 2025-12-04T09:16:40.4997792Z ami-id: ami-08982f1c5bf93d976 2025-12-04T09:16:40.5108982Z instance-id: i-0ed9e7c329090f0b0 2025-12-04T09:16:40.5218625Z instance-type: c5.4xlarge 2025-12-04T09:16:40.5231308Z system info Linux ip-10-0-5-68.ec2.internal 6.1.150-174.273.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Tue Sep 9 12:21:26 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux 2025-12-04T09:16:40.5253067Z ##[group]Run if [ -f /usr/bin/nvidia-smi ]; then nvidia-smi; fi 2025-12-04T09:16:40.5253587Z if [ -f /usr/bin/nvidia-smi ]; then nvidia-smi; fi 2025-12-04T09:16:40.5259944Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:40.5260353Z env: 2025-12-04T09:16:40.5260708Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.5260989Z ##[endgroup] 2025-12-04T09:16:40.5305700Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:16:40.5306713Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:16:40.5312720Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:40.5313124Z env: 2025-12-04T09:16:40.5313345Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.5313624Z ##[endgroup] 2025-12-04T09:16:40.5365423Z ##[group]Run if systemctl is-active --quiet docker; then 2025-12-04T09:16:40.5365892Z if systemctl is-active --quiet docker; then 2025-12-04T09:16:40.5366309Z  echo "Docker daemon is running..."; 2025-12-04T09:16:40.5366665Z else 2025-12-04T09:16:40.5367034Z  echo "Starting docker daemon..." && sudo systemctl start docker; 2025-12-04T09:16:40.5367512Z fi 2025-12-04T09:16:40.5373207Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:40.5373622Z env: 2025-12-04T09:16:40.5373839Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.5374116Z ##[endgroup] 2025-12-04T09:16:40.5463385Z Docker daemon is running... 2025-12-04T09:16:40.5502505Z ##[group]Run nick-fields/retry@v3.0.0 2025-12-04T09:16:40.5502815Z with: 2025-12-04T09:16:40.5503027Z shell: bash 2025-12-04T09:16:40.5503255Z timeout_minutes: 5 2025-12-04T09:16:40.5503508Z max_attempts: 3 2025-12-04T09:16:40.5503742Z retry_wait_seconds: 30 2025-12-04T09:16:40.5506296Z command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\") aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" # For LF Runners we need to make sure we also login to Meta's ECR docker registry too. META_AWS_ACCOUNT_ID=308535385114 if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" fi 2025-12-04T09:16:40.5508869Z polling_interval_seconds: 1 2025-12-04T09:16:40.5509168Z warning_on_retry: true 2025-12-04T09:16:40.5509444Z continue_on_error: false 2025-12-04T09:16:40.5509698Z env: 2025-12-04T09:16:40.5509918Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:40.5510196Z AWS_RETRY_MODE: standard 2025-12-04T09:16:40.5510456Z AWS_MAX_ATTEMPTS: 5 2025-12-04T09:16:40.5510723Z AWS_DEFAULT_REGION: us-east-1 2025-12-04T09:16:40.5511008Z ##[endgroup] 2025-12-04T09:16:41.8026844Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-12-04T09:16:41.8027547Z Configure a credential helper to remove this warning. See 2025-12-04T09:16:41.8028700Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-12-04T09:16:41.8029199Z 2025-12-04T09:16:41.8029293Z Login Succeeded 2025-12-04T09:16:42.7135266Z Command completed after 1 attempt(s). 2025-12-04T09:16:42.7187676Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:16:42.7188256Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:16:42.7188761Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:16:42.7196529Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:42.7196929Z env: 2025-12-04T09:16:42.7197163Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:42.7197444Z ##[endgroup] 2025-12-04T09:16:42.7283818Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-12-04T09:16:42.7284558Z # ignore expansion of "docker ps -q" since it could be empty 2025-12-04T09:16:42.7285028Z # shellcheck disable=SC2046 2025-12-04T09:16:42.7285376Z docker stop $(docker ps -q) || true 2025-12-04T09:16:42.7285894Z # Prune all of the docker images 2025-12-04T09:16:42.7286262Z docker system prune -af 2025-12-04T09:16:42.7292294Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:42.7292693Z env: 2025-12-04T09:16:42.7292919Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:42.7293196Z ##[endgroup] 2025-12-04T09:16:42.7727581Z "docker stop" requires at least 1 argument. 2025-12-04T09:16:42.7728242Z See 'docker stop --help'. 2025-12-04T09:16:42.7728445Z 2025-12-04T09:16:42.7728618Z Usage: docker stop [OPTIONS] CONTAINER [CONTAINER...] 2025-12-04T09:16:42.7728931Z 2025-12-04T09:16:42.7729048Z Stop one or more running containers 2025-12-04T09:16:42.7931364Z Total reclaimed space: 0B 2025-12-04T09:16:42.8126503Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-12-04T09:16:42.8127023Z with: 2025-12-04T09:16:42.8127891Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8128893Z use-custom-docker-registry: true 2025-12-04T09:16:42.8129225Z docker-build-dir: .ci/docker 2025-12-04T09:16:42.8129535Z docker-build-script: ./build.sh 2025-12-04T09:16:42.8129835Z working-directory: . 2025-12-04T09:16:42.8130201Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:42.8130632Z force-push: false 2025-12-04T09:16:42.8130857Z env: 2025-12-04T09:16:42.8131071Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:42.8131339Z ##[endgroup] 2025-12-04T09:16:42.8150627Z ##[group]Run set -ex 2025-12-04T09:16:42.8150956Z set -ex 2025-12-04T09:16:42.8151195Z  2025-12-04T09:16:42.8151903Z # If the docker build directory or the build script doesn't exist, the action will 2025-12-04T09:16:42.8152633Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-12-04T09:16:42.8153238Z # job could then download the pre-built image as usual 2025-12-04T09:16:42.8153999Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-12-04T09:16:42.8154709Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8155051Z else 2025-12-04T09:16:42.8155326Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8155809Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8156249Z  2025-12-04T09:16:42.8156841Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-12-04T09:16:42.8157545Z  exit 0 2025-12-04T09:16:42.8157779Z fi 2025-12-04T09:16:42.8157986Z  2025-12-04T09:16:42.8158345Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-12-04T09:16:42.8159001Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-12-04T09:16:42.8159582Z  # use it as it is, but first let's extract the tag 2025-12-04T09:16:42.8160089Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-12-04T09:16:42.8160641Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8161170Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8161609Z else 2025-12-04T09:16:42.8161876Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-12-04T09:16:42.8162286Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-12-04T09:16:42.8162712Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-12-04T09:16:42.8163057Z  fi 2025-12-04T09:16:42.8163545Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-12-04T09:16:42.8164418Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8165118Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8165870Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8166334Z fi 2025-12-04T09:16:42.8172407Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:42.8172794Z env: 2025-12-04T09:16:42.8173020Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:42.8173307Z REPO_NAME: pytorch 2025-12-04T09:16:42.8174334Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8175284Z DOCKER_BUILD_DIR: .ci/docker 2025-12-04T09:16:42.8175585Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-12-04T09:16:42.8175989Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:42.8176418Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-12-04T09:16:42.8176728Z CUSTOM_TAG_PREFIX: 2025-12-04T09:16:42.8176980Z ##[endgroup] 2025-12-04T09:16:42.8202979Z + [[ -d .ci/docker ]] 2025-12-04T09:16:42.8203271Z + [[ -f .ci/docker/./build.sh ]] 2025-12-04T09:16:42.8203570Z + [[ true == \t\r\u\e ]] 2025-12-04T09:16:42.8203836Z + echo skip=false 2025-12-04T09:16:42.8205346Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a == *\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* ]] 2025-12-04T09:16:42.8210802Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8211722Z ++ awk -F '[:,]' '{print $2}' 2025-12-04T09:16:42.8235826Z + DOCKER_TAG=pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8236841Z + echo docker-tag=pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8238888Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8262372Z ##[group]Run set +e 2025-12-04T09:16:42.8262686Z set +e 2025-12-04T09:16:42.8262911Z set -x 2025-12-04T09:16:42.8263145Z  2025-12-04T09:16:42.8263367Z login() { 2025-12-04T09:16:42.8263866Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-12-04T09:16:42.8264494Z } 2025-12-04T09:16:42.8264723Z  2025-12-04T09:16:42.8264929Z retry () { 2025-12-04T09:16:42.8265215Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-12-04T09:16:42.8265551Z } 2025-12-04T09:16:42.8265752Z  2025-12-04T09:16:42.8266000Z retry login "${DOCKER_REGISTRY}" 2025-12-04T09:16:42.8266327Z  2025-12-04T09:16:42.8266554Z START_TIME=$(date +%s) 2025-12-04T09:16:42.8266855Z # Wait up to 120 minutes 2025-12-04T09:16:42.8267242Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-12-04T09:16:42.8267775Z  # Check if image already exists, if it does then skip building it 2025-12-04T09:16:42.8268292Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-12-04T09:16:42.8268684Z  exit 0 2025-12-04T09:16:42.8268928Z  fi 2025-12-04T09:16:42.8269139Z  2025-12-04T09:16:42.8269552Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-12-04T09:16:42.8270278Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-12-04T09:16:42.8270999Z  # latter, it will wait for the Docker images to become available before continuing 2025-12-04T09:16:42.8271694Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-12-04T09:16:42.8272126Z  # It's a Docker build job, let's build the image 2025-12-04T09:16:42.8272503Z  break 2025-12-04T09:16:42.8272751Z  else 2025-12-04T09:16:42.8273103Z  # It's a regular build job, wait for the image to become available 2025-12-04T09:16:42.8273552Z  sleep 300 2025-12-04T09:16:42.8273809Z  fi 2025-12-04T09:16:42.8274021Z done 2025-12-04T09:16:42.8274243Z  2025-12-04T09:16:42.8274613Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-12-04T09:16:42.8275320Z # be empty. The default action would be to continue rebuild the image 2025-12-04T09:16:42.8275875Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-12-04T09:16:42.8276365Z  # if we're on the base branch then use the parent commit 2025-12-04T09:16:42.8276806Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-12-04T09:16:42.8277134Z else 2025-12-04T09:16:42.8277479Z  # otherwise we're on a PR, so use the most recent base commit 2025-12-04T09:16:42.8277993Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-12-04T09:16:42.8278369Z fi 2025-12-04T09:16:42.8278586Z  2025-12-04T09:16:42.8278827Z if [[ -z "${MERGE_BASE}" ]]; then 2025-12-04T09:16:42.8279208Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8279550Z  2025-12-04T09:16:42.8280050Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-12-04T09:16:42.8280651Z  exit 0 2025-12-04T09:16:42.8280872Z fi 2025-12-04T09:16:42.8281086Z  2025-12-04T09:16:42.8281407Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-12-04T09:16:42.8282147Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-12-04T09:16:42.8282779Z  exit 1 2025-12-04T09:16:42.8283011Z fi 2025-12-04T09:16:42.8283233Z  2025-12-04T09:16:42.8283607Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-12-04T09:16:42.8284456Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-12-04T09:16:42.8285104Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-12-04T09:16:42.8285855Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-12-04T09:16:42.8286690Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-12-04T09:16:42.8287211Z fi 2025-12-04T09:16:42.8287418Z  2025-12-04T09:16:42.8287697Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-12-04T09:16:42.8293581Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:42.8293982Z env: 2025-12-04T09:16:42.8294208Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:42.8294485Z DOCKER_BUILD_DIR: .ci/docker 2025-12-04T09:16:42.8294853Z BASE_REVISION: ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:16:42.8295857Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8297095Z DOCKER_TAG: pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:42.8297813Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:42.8298235Z DOCKER_PUSH: 2025-12-04T09:16:42.8298469Z ##[endgroup] 2025-12-04T09:16:42.8337824Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:42.8338291Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:42.8340728Z + aws ecr get-login-password --region us-east-1 2025-12-04T09:16:42.8342476Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:43.3867604Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-12-04T09:16:43.3868279Z Configure a credential helper to remove this warning. See 2025-12-04T09:16:43.3868908Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-12-04T09:16:43.3869333Z 2025-12-04T09:16:43.3869867Z Login Succeeded 2025-12-04T09:16:43.3885580Z ++ date +%s 2025-12-04T09:16:43.3897319Z + START_TIME=1764839803 2025-12-04T09:16:43.3900550Z ++ date +%s 2025-12-04T09:16:43.3911805Z + [[ 1764832603 -lt 1764839803 ]] 2025-12-04T09:16:43.3912803Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:43.5776663Z { 2025-12-04T09:16:43.5777026Z "schemaVersion": 2, 2025-12-04T09:16:43.5777555Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-12-04T09:16:43.5778028Z "config": { 2025-12-04T09:16:43.5778378Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-12-04T09:16:43.5778792Z "size": 34863, 2025-12-04T09:16:43.5779338Z "digest": "sha256:4c2670599273a4ccf01817c9877ac311e1c84c6633d386cde9e253e0b3fe4d36" 2025-12-04T09:16:43.5779839Z }, 2025-12-04T09:16:43.5780040Z "layers": [ 2025-12-04T09:16:43.5780244Z { 2025-12-04T09:16:43.5780589Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5781039Z "size": 30447951, 2025-12-04T09:16:43.5781494Z "digest": "sha256:63e5bc7682b85ae57a1221210f64d62e7a90b0a30f19af4ca734b8242ae49d63" 2025-12-04T09:16:43.5781998Z }, 2025-12-04T09:16:43.5782197Z { 2025-12-04T09:16:43.5782522Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5782958Z "size": 1554, 2025-12-04T09:16:43.5783398Z "digest": "sha256:3a5718b5258e28918133dd74ea64bd506b2c15530a2fa8a72c45c5b0d8f7c7b0" 2025-12-04T09:16:43.5783886Z }, 2025-12-04T09:16:43.5784081Z { 2025-12-04T09:16:43.5784420Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5784850Z "size": 313276069, 2025-12-04T09:16:43.5785305Z "digest": "sha256:68ad27e1ba4bcd150faeb9708d0a711910f472edfef933b4445ce0247f39903d" 2025-12-04T09:16:43.5785812Z }, 2025-12-04T09:16:43.5786007Z { 2025-12-04T09:16:43.5786333Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5786774Z "size": 787, 2025-12-04T09:16:43.5787218Z "digest": "sha256:80061bf5dcbb9a4e38ac865a9cdc0a615bb294e3e6bfa357a6d515dcf3f54abc" 2025-12-04T09:16:43.5787722Z }, 2025-12-04T09:16:43.5787916Z { 2025-12-04T09:16:43.5788254Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5788679Z "size": 106, 2025-12-04T09:16:43.5789108Z "digest": "sha256:d76398f0d4a200bef308e3996c3ed9839c1b37237715b3ebb5ae749dedd9a0cf" 2025-12-04T09:16:43.5789618Z }, 2025-12-04T09:16:43.5789802Z { 2025-12-04T09:16:43.5790249Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5790693Z "size": 704, 2025-12-04T09:16:43.5791122Z "digest": "sha256:9d58e5257cefd43e8226153d71d28a865253662146aa9fce9a9f95af67b497fa" 2025-12-04T09:16:43.5791607Z }, 2025-12-04T09:16:43.5791801Z { 2025-12-04T09:16:43.5792140Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5792566Z "size": 1217, 2025-12-04T09:16:43.5792989Z "digest": "sha256:339c3135e2d933e793710040f02f034f4546962ce027e2b03baa1387f0a7f9c6" 2025-12-04T09:16:43.5793482Z }, 2025-12-04T09:16:43.5793670Z { 2025-12-04T09:16:43.5794032Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5794530Z "size": 485, 2025-12-04T09:16:43.5794959Z "digest": "sha256:6931c5f20e80e481e4f484471ff3a02878b4f8c54a9a5a4717213fdaa35c0bff" 2025-12-04T09:16:43.5795643Z }, 2025-12-04T09:16:43.5795839Z { 2025-12-04T09:16:43.5796175Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5796602Z "size": 110362482, 2025-12-04T09:16:43.5797052Z "digest": "sha256:4ecf2b717b9e98a9074b539d758d4611f72ebe0b33cda95a52c92205b1bacf20" 2025-12-04T09:16:43.5797556Z }, 2025-12-04T09:16:43.5797741Z { 2025-12-04T09:16:43.5798081Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5798516Z "size": 4961, 2025-12-04T09:16:43.5798937Z "digest": "sha256:b88143493ed8b13e327ce6a0651c2864a1876bcdd41de79a109d8ec2b91734bb" 2025-12-04T09:16:43.5799438Z }, 2025-12-04T09:16:43.5799635Z { 2025-12-04T09:16:43.5800057Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5800495Z "size": 1755, 2025-12-04T09:16:43.5800926Z "digest": "sha256:9748c5348f39a11c960c49fd9219fdea1c23e612ed11a02d71501424defc80f5" 2025-12-04T09:16:43.5801429Z }, 2025-12-04T09:16:43.5801610Z { 2025-12-04T09:16:43.5801946Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5802385Z "size": 724, 2025-12-04T09:16:43.5802804Z "digest": 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"sha256:7c5834cbf748248c8b5d277bc29b328ccd8afd1cc0892bd467732161bb375c02" 2025-12-04T09:16:43.5895663Z }, 2025-12-04T09:16:43.5895862Z { 2025-12-04T09:16:43.5896275Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5896703Z "size": 724, 2025-12-04T09:16:43.5897138Z "digest": "sha256:8539cc3f8d8a138501ed0255c0cd7ec491bc0add9e4a62095f1c0f9533daa1cc" 2025-12-04T09:16:43.5897643Z }, 2025-12-04T09:16:43.5897832Z { 2025-12-04T09:16:43.5898168Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5898608Z "size": 154, 2025-12-04T09:16:43.5899059Z "digest": "sha256:a33cee02f40ccfe12e7dec5dd60dd3d81cd5ed1ed26ccf1c9a9c8fecc9959cdd" 2025-12-04T09:16:43.5899568Z }, 2025-12-04T09:16:43.5899761Z { 2025-12-04T09:16:43.5900095Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5900521Z "size": 32, 2025-12-04T09:16:43.5900950Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-12-04T09:16:43.5901455Z }, 2025-12-04T09:16:43.5901633Z { 2025-12-04T09:16:43.5901965Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5902404Z "size": 187, 2025-12-04T09:16:43.5902822Z "digest": "sha256:0883ea0533f459bb5acb99cd44b73df22ab2750e764a3f066700d0e4840fa407" 2025-12-04T09:16:43.5903323Z }, 2025-12-04T09:16:43.5903518Z { 2025-12-04T09:16:43.5903841Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5904284Z "size": 1370, 2025-12-04T09:16:43.5904716Z "digest": "sha256:63fdd143f389d88477b3e1246d5f7c008743547fe625fcd4d20d39ce0b486ce1" 2025-12-04T09:16:43.5905324Z }, 2025-12-04T09:16:43.5905509Z { 2025-12-04T09:16:43.5905846Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5906289Z "size": 32, 2025-12-04T09:16:43.5906708Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-12-04T09:16:43.5907219Z }, 2025-12-04T09:16:43.5907419Z { 2025-12-04T09:16:43.5907741Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5908175Z "size": 136, 2025-12-04T09:16:43.5908609Z "digest": "sha256:7617fa66daf836584fe0d439da821e7eac7271494e14d6781b51c300a6fe79bc" 2025-12-04T09:16:43.5909097Z }, 2025-12-04T09:16:43.5909289Z { 2025-12-04T09:16:43.5909622Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5910052Z "size": 528, 2025-12-04T09:16:43.5910480Z "digest": "sha256:8339a8e956d0d4e749ffeaded94746ae84a3547272336209675fdff7b06172b5" 2025-12-04T09:16:43.5910982Z }, 2025-12-04T09:16:43.5911176Z { 2025-12-04T09:16:43.5911499Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5911936Z "size": 32, 2025-12-04T09:16:43.5912369Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-12-04T09:16:43.5912862Z }, 2025-12-04T09:16:43.5913057Z { 2025-12-04T09:16:43.5913393Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5913816Z "size": 104, 2025-12-04T09:16:43.5914252Z "digest": "sha256:42a3794810c826b548faccc07dd5efc39749a04182bed16b2ee60a2b13608cfb" 2025-12-04T09:16:43.5914756Z }, 2025-12-04T09:16:43.5914938Z { 2025-12-04T09:16:43.5915271Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5915798Z "size": 436, 2025-12-04T09:16:43.5916240Z "digest": "sha256:07a663ff8df7feb8a4ef87dc8a3493f16cacb3e74120be593b1da8538c8e8244" 2025-12-04T09:16:43.5916739Z }, 2025-12-04T09:16:43.5916937Z { 2025-12-04T09:16:43.5917272Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5917699Z "size": 32, 2025-12-04T09:16:43.5918135Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-12-04T09:16:43.5918642Z }, 2025-12-04T09:16:43.5918823Z { 2025-12-04T09:16:43.5919156Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5919587Z "size": 109, 2025-12-04T09:16:43.5920074Z "digest": "sha256:5b9d4fd10da29fc645961c09e9901fbd8a9e414100404eb20d997dab789b8e9d" 2025-12-04T09:16:43.5920579Z }, 2025-12-04T09:16:43.5920769Z { 2025-12-04T09:16:43.5921089Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5921527Z "size": 1896, 2025-12-04T09:16:43.5921969Z "digest": "sha256:e87038dce9bc8e13bd64006847d30ddcaf77455256c4985fccfec83f82d4b925" 2025-12-04T09:16:43.5922473Z }, 2025-12-04T09:16:43.5922652Z { 2025-12-04T09:16:43.5922988Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5923427Z "size": 245591901, 2025-12-04T09:16:43.5923870Z "digest": "sha256:51bd8214b9e0ddaaf7d2f66ddcf9a00327383c196d690a8a5438d084870c3254" 2025-12-04T09:16:43.5924477Z }, 2025-12-04T09:16:43.5924678Z { 2025-12-04T09:16:43.5925003Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5925444Z "size": 106, 2025-12-04T09:16:43.5925871Z "digest": "sha256:5cf788429720c12c8df2475927563dcb04369f98fd586ba0f51e9f9de813b4f0" 2025-12-04T09:16:43.5926364Z }, 2025-12-04T09:16:43.5926558Z { 2025-12-04T09:16:43.5926891Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5927315Z "size": 165, 2025-12-04T09:16:43.5927742Z "digest": "sha256:0d8f60a2a38249b0b2f0345f8e81434755ee710b8f3f080ce708cb7dc9038eb3" 2025-12-04T09:16:43.5928246Z }, 2025-12-04T09:16:43.5928440Z { 2025-12-04T09:16:43.5928764Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5929204Z "size": 7943, 2025-12-04T09:16:43.5929641Z "digest": "sha256:56773452d568b3fda8d3e898b300a67fb5eb1beecbd430ec2428ade1c6e5ba40" 2025-12-04T09:16:43.5930136Z }, 2025-12-04T09:16:43.5930333Z { 2025-12-04T09:16:43.5930676Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5931102Z "size": 8072, 2025-12-04T09:16:43.5931544Z "digest": "sha256:ce7e07b9ef1f3b607e0b491c0a7cca98eb4089d271beddda09b062682e1cb5e7" 2025-12-04T09:16:43.5932058Z }, 2025-12-04T09:16:43.5932245Z { 2025-12-04T09:16:43.5932592Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5933038Z "size": 302, 2025-12-04T09:16:43.5933467Z "digest": "sha256:6f2a5d33b946e561219b9968769773e36ce1d28bee8c62eff652098b7825fc79" 2025-12-04T09:16:43.5933957Z }, 2025-12-04T09:16:43.5934153Z { 2025-12-04T09:16:43.5934493Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5934920Z "size": 13360696, 2025-12-04T09:16:43.5935359Z "digest": "sha256:e0614b64361bbae329d78a51b5841eb411816609909a936a288b115bff2c176e" 2025-12-04T09:16:43.5935855Z }, 2025-12-04T09:16:43.5936036Z { 2025-12-04T09:16:43.5936370Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5936804Z "size": 108, 2025-12-04T09:16:43.5937215Z "digest": "sha256:b751b498b470db1d613227f32d4536d12012e07fe003e7a0133da2906fcf4d90" 2025-12-04T09:16:43.5937708Z }, 2025-12-04T09:16:43.5937897Z { 2025-12-04T09:16:43.5938227Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5938665Z "size": 54145699, 2025-12-04T09:16:43.5939100Z "digest": "sha256:665341d00b246408753c5658fdf0fc11b3ba1d3ec923c98865bc39cb8f8d78e3" 2025-12-04T09:16:43.5939596Z }, 2025-12-04T09:16:43.5939859Z { 2025-12-04T09:16:43.5940195Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-12-04T09:16:43.5940633Z "size": 32, 2025-12-04T09:16:43.5941054Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-12-04T09:16:43.5941558Z } 2025-12-04T09:16:43.5941753Z ] 2025-12-04T09:16:43.5941931Z } 2025-12-04T09:16:43.5942145Z + exit 0 2025-12-04T09:16:43.5969684Z ##[group]Run set -eux 2025-12-04T09:16:43.5969989Z set -eux 2025-12-04T09:16:43.5970445Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-12-04T09:16:43.5971849Z 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 2025-12-04T09:16:43.5978681Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:43.5979089Z env: 2025-12-04T09:16:43.5979331Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:43.5979596Z ##[endgroup] 2025-12-04T09:16:43.6009406Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-12-04T09:16:43.6010120Z + jq --raw-output .SecretString 2025-12-04T09:16:43.6011477Z + jq -r .docker_hub_readonly_token 2025-12-04T09:16:43.6012676Z + docker login --username pytorchbot --password-stdin 2025-12-04T09:16:44.1875291Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-12-04T09:16:44.1875962Z Configure a credential helper to remove this warning. See 2025-12-04T09:16:44.1889485Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-12-04T09:16:44.1890043Z 2025-12-04T09:16:44.1890224Z Login Succeeded 2025-12-04T09:16:44.1971432Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-12-04T09:16:44.1971840Z tag=${ECR_DOCKER_IMAGE##*:} 2025-12-04T09:16:44.1972267Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-12-04T09:16:44.1978595Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:44.1978989Z env: 2025-12-04T09:16:44.1979216Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:44.1980123Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.1981050Z ##[endgroup] 2025-12-04T09:16:44.2011081Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.2060468Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-12-04T09:16:44.2060952Z with: 2025-12-04T09:16:44.2061782Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.2062827Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:44.2063254Z env: 2025-12-04T09:16:44.2063472Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:44.2063734Z ##[endgroup] 2025-12-04T09:16:44.2079175Z ##[group]Run set -x 2025-12-04T09:16:44.2079472Z set -x 2025-12-04T09:16:44.2079700Z set +e 2025-12-04T09:16:44.2079932Z  2025-12-04T09:16:44.2080155Z login() { 2025-12-04T09:16:44.2080661Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-12-04T09:16:44.2081221Z } 2025-12-04T09:16:44.2081440Z  2025-12-04T09:16:44.2081692Z retry () { 2025-12-04T09:16:44.2081966Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-12-04T09:16:44.2082304Z } 2025-12-04T09:16:44.2082518Z  2025-12-04T09:16:44.2082755Z retry login "${DOCKER_REGISTRY}" 2025-12-04T09:16:44.2083075Z  2025-12-04T09:16:44.2083599Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-12-04T09:16:44.2084565Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-12-04T09:16:44.2084960Z  2025-12-04T09:16:44.2085176Z set -e 2025-12-04T09:16:44.2085541Z # ignore output since only exit code is used for conditional 2025-12-04T09:16:44.2086075Z # only pull docker image if it's not available locally 2025-12-04T09:16:44.2086654Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-12-04T09:16:44.2087211Z  retry docker pull "${DOCKER_IMAGE}" 2025-12-04T09:16:44.2087553Z fi 2025-12-04T09:16:44.2093532Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:16:44.2093937Z env: 2025-12-04T09:16:44.2094162Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:16:44.2095048Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.2096098Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:44.2096516Z ##[endgroup] 2025-12-04T09:16:44.2123309Z + set +e 2025-12-04T09:16:44.2123954Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:44.2124480Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:44.2127044Z + aws ecr get-login-password --region us-east-1 2025-12-04T09:16:44.2128522Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-12-04T09:16:44.7567381Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-12-04T09:16:44.7568056Z Configure a credential helper to remove this warning. See 2025-12-04T09:16:44.7568676Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-12-04T09:16:44.7569098Z 2025-12-04T09:16:44.7572973Z Login Succeeded 2025-12-04T09:16:44.7591353Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.7592472Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-12-04T09:16:44.9824286Z + IMAGE_SIZE=12735.252056121826 2025-12-04T09:16:44.9825028Z + echo 'Compressed size of image in MB: 12735.252056121826' 2025-12-04T09:16:44.9825554Z + set -e 2025-12-04T09:16:44.9826451Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.9827722Z Compressed size of image in MB: 12735.252056121826 2025-12-04T09:16:44.9939308Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:44.9940889Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:16:45.2401176Z pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a: Pulling from pytorch/ci-image 2025-12-04T09:16:45.2402637Z 63e5bc7682b8: Pulling fs layer 2025-12-04T09:16:45.2403145Z 3a5718b5258e: Pulling fs layer 2025-12-04T09:16:45.2403679Z 68ad27e1ba4b: Pulling fs layer 2025-12-04T09:16:45.2404247Z 80061bf5dcbb: Pulling fs layer 2025-12-04T09:16:45.2404806Z d76398f0d4a2: Pulling fs layer 2025-12-04T09:16:45.2405104Z 9d58e5257cef: Pulling fs layer 2025-12-04T09:16:45.2405417Z 339c3135e2d9: Pulling fs layer 2025-12-04T09:16:45.2405696Z 6931c5f20e80: Pulling fs layer 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2025-12-04T09:17:41.5552078Z 51bd8214b9e0: Download complete 2025-12-04T09:17:41.6430422Z 5cf788429720: Verifying Checksum 2025-12-04T09:17:41.6430798Z 5cf788429720: Download complete 2025-12-04T09:17:41.7202065Z 0d8f60a2a382: Verifying Checksum 2025-12-04T09:17:41.7202720Z 0d8f60a2a382: Download complete 2025-12-04T09:17:41.8312524Z 56773452d568: Verifying Checksum 2025-12-04T09:17:41.8312924Z 56773452d568: Download complete 2025-12-04T09:17:41.9236575Z ce7e07b9ef1f: Download complete 2025-12-04T09:17:42.0088322Z 6f2a5d33b946: Verifying Checksum 2025-12-04T09:17:42.0088682Z 6f2a5d33b946: Download complete 2025-12-04T09:17:42.5349818Z e0614b64361b: Verifying Checksum 2025-12-04T09:17:42.5350213Z e0614b64361b: Download complete 2025-12-04T09:17:42.6259202Z b751b498b470: Verifying Checksum 2025-12-04T09:17:42.6259601Z b751b498b470: Download complete 2025-12-04T09:17:44.1065941Z 665341d00b24: Verifying Checksum 2025-12-04T09:17:44.1066336Z 665341d00b24: Download complete 2025-12-04T09:17:56.5680568Z c94cfaf301ba: Verifying Checksum 2025-12-04T09:17:56.5680968Z c94cfaf301ba: Download complete 2025-12-04T09:18:10.2099706Z daf94b7dcf5a: Verifying Checksum 2025-12-04T09:18:10.2100111Z daf94b7dcf5a: Download complete 2025-12-04T09:19:04.6852538Z 5e09dea1b498: Pull complete 2025-12-04T09:19:04.8318606Z 4f4fb700ef54: Pull complete 2025-12-04T09:19:04.9226948Z 32fbb88555c4: Pull complete 2025-12-04T09:19:04.9888343Z 39625b7d1b93: Pull complete 2025-12-04T09:19:05.0690425Z 760004b6b0ba: Pull complete 2025-12-04T09:19:05.2186929Z 2401a405ca6a: Pull complete 2025-12-04T09:19:05.2561378Z 0f4872219ee6: Pull complete 2025-12-04T09:19:05.2837577Z ae06ff2d542a: Pull complete 2025-12-04T09:19:05.3230184Z 7cbd98b45db7: Pull complete 2025-12-04T09:19:05.4161852Z a26ff2361220: Pull complete 2025-12-04T09:20:18.0446953Z daf94b7dcf5a: Pull complete 2025-12-04T09:20:18.2214864Z 3c4fd2d54638: Pull complete 2025-12-04T09:20:18.9716150Z eb1deb0b4825: Pull complete 2025-12-04T09:20:19.0137434Z 8d8fda9987ff: Pull complete 2025-12-04T09:20:19.0461103Z ce919d4bf5ee: Pull complete 2025-12-04T09:20:31.2985699Z ad0c5c675f84: Pull complete 2025-12-04T09:20:31.3249035Z 1d2876cb221a: Pull complete 2025-12-04T09:20:31.3614040Z d6630aa6f375: Pull complete 2025-12-04T09:20:31.5512983Z 3b7e925cd02b: Pull complete 2025-12-04T09:20:31.6060753Z fa273daa0037: Pull complete 2025-12-04T09:20:32.0161562Z 5b8f1bada8cb: Pull complete 2025-12-04T09:20:32.0511179Z 3f721a25bd20: Pull complete 2025-12-04T09:20:32.0845237Z d3573d61c28e: Pull complete 2025-12-04T09:20:32.1500906Z f9b32f08c490: Pull complete 2025-12-04T09:20:32.2228118Z 3a0206399d60: Pull complete 2025-12-04T09:20:32.3169581Z 386f322edd1c: Pull complete 2025-12-04T09:20:32.4934746Z 7e9fd57c1c30: Pull complete 2025-12-04T09:20:32.5525993Z 72a05bd502a9: Pull complete 2025-12-04T09:20:32.6365557Z b76cce50d862: Pull complete 2025-12-04T09:20:37.9708152Z 9d54d5403b2f: Pull complete 2025-12-04T09:21:59.9143774Z c94cfaf301ba: Pull complete 2025-12-04T09:22:00.1047632Z 78269d211f75: Pull complete 2025-12-04T09:22:00.1910557Z 46d7ca27c4a3: Pull complete 2025-12-04T09:22:00.2727189Z 9a5fbb21a05b: Pull complete 2025-12-04T09:22:00.3340301Z a9e30ff5f552: Pull complete 2025-12-04T09:22:00.4176965Z 6d55d16d0cdf: Pull complete 2025-12-04T09:22:00.5275662Z 9b5aac9c786e: Pull complete 2025-12-04T09:22:00.6753373Z 4660758215d2: Pull complete 2025-12-04T09:22:00.7261583Z 7c5834cbf748: Pull complete 2025-12-04T09:22:00.9010427Z a33cee02f40c: Pull complete 2025-12-04T09:22:00.9699382Z 0883ea0533f4: Pull complete 2025-12-04T09:22:01.0419288Z 63fdd143f389: Pull complete 2025-12-04T09:22:01.3906348Z 7617fa66daf8: Pull complete 2025-12-04T09:22:01.5717956Z 8339a8e956d0: Pull complete 2025-12-04T09:22:01.9007143Z 42a3794810c8: Pull complete 2025-12-04T09:22:02.0016156Z 07a663ff8df7: Pull complete 2025-12-04T09:22:02.1791289Z 5b9d4fd10da2: Pull complete 2025-12-04T09:22:02.2517009Z e87038dce9bc: Pull complete 2025-12-04T09:22:10.2804171Z 51bd8214b9e0: Pull complete 2025-12-04T09:22:10.4187706Z 5cf788429720: Pull complete 2025-12-04T09:22:10.5245305Z 0d8f60a2a382: Pull complete 2025-12-04T09:22:10.5777382Z 56773452d568: Pull complete 2025-12-04T09:22:10.6103102Z ce7e07b9ef1f: Pull complete 2025-12-04T09:22:10.6407772Z 6f2a5d33b946: Pull complete 2025-12-04T09:22:11.8871575Z e0614b64361b: Pull complete 2025-12-04T09:22:11.9346867Z b751b498b470: Pull complete 2025-12-04T09:22:14.1659455Z 665341d00b24: Pull complete 2025-12-04T09:22:14.3968021Z Digest: sha256:d69b2cd9ebb8a0bf2d9eb1e4955b13b1e68dc1e57f400c237179d0d16df9c770 2025-12-04T09:22:14.4208940Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:14.4390404Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:14.4479078Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4480167Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4489769Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:14.4490176Z env: 2025-12-04T09:22:14.4490394Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.4490669Z ##[endgroup] 2025-12-04T09:22:14.4691802Z ##[group]Run pytorch/test-infra/.github/actions/setup-nvidia@main 2025-12-04T09:22:14.4692246Z with: 2025-12-04T09:22:14.4692474Z driver-version: 580.82.07 2025-12-04T09:22:14.4692732Z env: 2025-12-04T09:22:14.4692951Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.4693225Z ##[endgroup] 2025-12-04T09:22:14.4716966Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4717986Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4724832Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:14.4725234Z env: 2025-12-04T09:22:14.4725455Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.4725721Z ##[endgroup] 2025-12-04T09:22:14.4781536Z ##[group]Run set -euo pipefail 2025-12-04T09:22:14.4781885Z set -euo pipefail 2025-12-04T09:22:14.4782225Z  2025-12-04T09:22:14.4782440Z has_gpu=false 2025-12-04T09:22:14.4782714Z devices="" 2025-12-04T09:22:14.4782965Z  2025-12-04T09:22:14.4783247Z if command -v nvidia-smi >/dev/null 2>&1; then 2025-12-04T09:22:14.4783740Z  if nvidia-smi -L >/tmp/nvidia_devices 2>/dev/null; then 2025-12-04T09:22:14.4784162Z  has_gpu=true 2025-12-04T09:22:14.4784475Z  devices=$(cat /tmp/nvidia_devices) 2025-12-04T09:22:14.4784990Z  fi 2025-12-04T09:22:14.4785213Z fi 2025-12-04T09:22:14.4785431Z  2025-12-04T09:22:14.4785656Z if [ "$has_gpu" = false ]; then 2025-12-04T09:22:14.4786080Z  if ls /dev/nvidia* >/tmp/nvidia_devices 2>/dev/null; then 2025-12-04T09:22:14.4786501Z  has_gpu=true 2025-12-04T09:22:14.4786801Z  devices=$(cat /tmp/nvidia_devices) 2025-12-04T09:22:14.4787139Z  fi 2025-12-04T09:22:14.4787366Z fi 2025-12-04T09:22:14.4787577Z  2025-12-04T09:22:14.4787902Z if [ "$has_gpu" = false ] && command -v lspci >/dev/null 2>&1; then 2025-12-04T09:22:14.4788458Z  if lspci | grep -i 'nvidia' >/tmp/nvidia_devices 2>/dev/null; then 2025-12-04T09:22:14.4788907Z  has_gpu=true 2025-12-04T09:22:14.4789203Z  devices=$(cat /tmp/nvidia_devices) 2025-12-04T09:22:14.4789537Z  fi 2025-12-04T09:22:14.4789756Z fi 2025-12-04T09:22:14.4789957Z  2025-12-04T09:22:14.4790275Z printf 'HAS_NVIDIA=%s\n' "$has_gpu" >> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4790857Z printf 'DETECTED_DEVICES<> "$GITHUB_OUTPUT" 2025-12-04T09:22:14.4796683Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:14.4797090Z env: 2025-12-04T09:22:14.4797314Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.4797573Z ##[endgroup] 2025-12-04T09:22:14.5451100Z ##[group]Run if [ "${HAS_NVIDIA}" = "true" ]; then 2025-12-04T09:22:14.5451517Z if [ "${HAS_NVIDIA}" = "true" ]; then 2025-12-04T09:22:14.5451922Z  echo "HAS_NVIDIA_GPU=true" >> "${GITHUB_ENV}" 2025-12-04T09:22:14.5452483Z  echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-12-04T09:22:14.5452982Z else 2025-12-04T09:22:14.5453267Z  echo "HAS_NVIDIA_GPU=false" >> "${GITHUB_ENV}" 2025-12-04T09:22:14.5453637Z fi 2025-12-04T09:22:14.5460221Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:14.5460606Z env: 2025-12-04T09:22:14.5460830Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.5461106Z HAS_NVIDIA: false 2025-12-04T09:22:14.5461334Z ##[endgroup] 2025-12-04T09:22:14.5609003Z Prepare all required actions 2025-12-04T09:22:14.5801849Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-12-04T09:22:14.5802200Z with: 2025-12-04T09:22:14.5802807Z github-token: *** 2025-12-04T09:22:14.5803050Z env: 2025-12-04T09:22:14.5803261Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.5803545Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:14.5803804Z ##[endgroup] 2025-12-04T09:22:14.5911076Z ##[group]Run set -eux 2025-12-04T09:22:14.5911339Z set -eux 2025-12-04T09:22:14.5911818Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-12-04T09:22:14.5917643Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:14.5918033Z env: 2025-12-04T09:22:14.5918271Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:14.5918556Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:14.5918982Z GITHUB_TOKEN: *** 2025-12-04T09:22:14.5919213Z ##[endgroup] 2025-12-04T09:22:14.5944230Z + python3 .github/scripts/get_workflow_job_id.py 19922826259 i-0ed9e7c329090f0b0 2025-12-04T09:22:16.8087795Z Setting output job-id=57117865590 2025-12-04T09:22:16.8088564Z Setting output job-name=linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:16.8481734Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-12-04T09:22:16.8482559Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-12-04T09:22:16.8483620Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-12-04T09:22:16.8484673Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-12-04T09:22:16.8492142Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:16.8492535Z env: 2025-12-04T09:22:16.8492770Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:16.8493058Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:16.8493308Z JOB_ID: 57117865590 2025-12-04T09:22:16.8493843Z JOB_NAME: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:16.8494466Z WORKFLOW_NAME: periodic 2025-12-04T09:22:16.8494813Z WORKFLOW_RUN_ID: 19922826259 2025-12-04T09:22:16.8495096Z MONITOR_LOG_INTERVAL: 5 2025-12-04T09:22:16.8495383Z MONITOR_DATA_COLLECT_INTERVAL: 1 2025-12-04T09:22:16.8495695Z ##[endgroup] 2025-12-04T09:22:19.0530467Z Defaulting to user installation because normal site-packages is not writeable 2025-12-04T09:22:19.5759653Z Collecting psutil==5.9.8 2025-12-04T09:22:19.5931801Z Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (288 kB) 2025-12-04T09:22:19.7392328Z Collecting dataclasses_json==0.6.7 2025-12-04T09:22:19.7427892Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-12-04T09:22:19.8037230Z Collecting nvidia-ml-py==11.525.84 2025-12-04T09:22:19.8074673Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-12-04T09:22:19.9575269Z Collecting marshmallow<4.0.0,>=3.18.0 2025-12-04T09:22:19.9613703Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-12-04T09:22:20.0600127Z Collecting typing-inspect<1,>=0.4.0 2025-12-04T09:22:20.0641142Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-12-04T09:22:20.1533706Z Collecting packaging>=17.0 2025-12-04T09:22:20.1568501Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-12-04T09:22:20.2452972Z Collecting mypy-extensions>=0.3.0 2025-12-04T09:22:20.2491837Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-12-04T09:22:20.4031544Z Collecting typing-extensions>=3.7.4 2025-12-04T09:22:20.4069472Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-12-04T09:22:20.6573488Z Installing collected packages: typing-extensions, packaging, mypy-extensions, typing-inspect, marshmallow, psutil, nvidia-ml-py, dataclasses-json 2025-12-04T09:22:21.3360989Z Successfully installed dataclasses-json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.8 typing-extensions-4.15.0 typing-inspect-0.9.0 2025-12-04T09:22:21.5909255Z Prepare all required actions 2025-12-04T09:22:21.5909690Z Getting action download info 2025-12-04T09:22:21.7997370Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-12-04T09:22:22.1579541Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-12-04T09:22:24.6721959Z ##[group]Run ./.github/actions/download-build-artifacts 2025-12-04T09:22:24.6722343Z with: 2025-12-04T09:22:24.6722604Z name: linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:22:24.6722979Z s3-bucket: gha-artifacts 2025-12-04T09:22:24.6723235Z env: 2025-12-04T09:22:24.6723457Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:24.6723738Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:24.6724000Z ##[endgroup] 2025-12-04T09:22:24.6785541Z ##[group]Run seemethere/download-artifact-s3@v4 2025-12-04T09:22:24.6785914Z with: 2025-12-04T09:22:24.6786177Z name: linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:22:24.6786575Z s3-bucket: gha-artifacts 2025-12-04T09:22:24.6786861Z region: us-east-1 2025-12-04T09:22:24.6787086Z env: 2025-12-04T09:22:24.6787307Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:24.6787592Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:24.6787839Z ##[endgroup] 2025-12-04T09:22:25.3698160Z (node:44672) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-12-04T09:22:25.3698717Z 2025-12-04T09:22:25.3698930Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-12-04T09:22:25.3699746Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-12-04T09:22:25.3700365Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-12-04T09:22:26.5339828Z Found 1 objects with prefix pytorch/pytorch/19922826259/linux-jammy-cuda13.0-py3.10-gcc11/ 2025-12-04T09:22:26.5340664Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip 2025-12-04T09:22:32.7439154Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip 2025-12-04T09:22:32.7445566Z Artifact download has finished successfully 2025-12-04T09:22:32.7648836Z ##[group]Run unzip -o artifacts.zip 2025-12-04T09:22:32.7649182Z unzip -o artifacts.zip 2025-12-04T09:22:32.7656104Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:32.7656508Z env: 2025-12-04T09:22:32.7656720Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:32.7657004Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:32.7657266Z ##[endgroup] 2025-12-04T09:22:32.8023420Z Archive: artifacts.zip 2025-12-04T09:22:32.8024681Z creating: dist/ 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.additional_ci_files/test-class-times.json 2025-12-04T09:22:42.2525408Z ##[group]Run rm artifacts.zip 2025-12-04T09:22:42.2525721Z rm artifacts.zip 2025-12-04T09:22:42.2532072Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:42.2532494Z env: 2025-12-04T09:22:42.2532707Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:42.2532992Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:42.2533250Z ##[endgroup] 2025-12-04T09:22:42.3576223Z ##[group]Run df -H 2025-12-04T09:22:42.3576470Z df -H 2025-12-04T09:22:42.3582037Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:42.3582444Z env: 2025-12-04T09:22:42.3582797Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:42.3583085Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:42.3583348Z ##[endgroup] 2025-12-04T09:22:42.3756998Z Filesystem Size Used Avail Use% Mounted on 2025-12-04T09:22:42.3757402Z devtmpfs 4.2M 0 4.2M 0% /dev 2025-12-04T09:22:42.3757758Z tmpfs 17G 0 17G 0% /dev/shm 2025-12-04T09:22:42.3758117Z tmpfs 6.6G 521k 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HAS_NVIDIA_GPU: false 2025-12-04T09:22:42.5490824Z ##[endgroup] 2025-12-04T09:22:43.0485218Z (node:44694) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-12-04T09:22:43.0486179Z 2025-12-04T09:22:43.0486383Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-12-04T09:22:43.0486969Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-12-04T09:22:43.0487561Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-12-04T09:22:43.1707760Z Found 1 objects with prefix pytorch/pytorch/19922826259/td_results/ 2025-12-04T09:22:43.1708483Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-12-04T09:22:43.2291101Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-12-04T09:22:43.2296428Z Artifact download has finished successfully 2025-12-04T09:22:43.2455405Z ##[group]Run mkdir -p .additional_ci_files 2025-12-04T09:22:43.2455828Z mkdir -p .additional_ci_files 2025-12-04T09:22:43.2456302Z mv td_results.json .additional_ci_files/td_results.json || true 2025-12-04T09:22:43.2462577Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:43.2462970Z env: 2025-12-04T09:22:43.2463202Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:43.2463490Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:43.2463740Z ##[endgroup] 2025-12-04T09:22:43.2600138Z ##[group]Run .github/scripts/parse_ref.py 2025-12-04T09:22:43.2600559Z .github/scripts/parse_ref.py 2025-12-04T09:22:43.2606404Z shell: /usr/bin/bash -e {0} 2025-12-04T09:22:43.2606698Z env: 2025-12-04T09:22:43.2606927Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:43.2607199Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:43.2607461Z ##[endgroup] 2025-12-04T09:22:43.2843755Z Setting output branch=main 2025-12-04T09:22:43.2982882Z Prepare all required actions 2025-12-04T09:22:43.2983288Z Getting action download info 2025-12-04T09:22:43.4409081Z ##[group]Run ./.github/actions/filter-test-configs 2025-12-04T09:22:43.4409434Z with: 2025-12-04T09:22:43.4409845Z github-token: *** 2025-12-04T09:22:43.4415354Z test-matrix: {"include": [{"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests"}]} 2025-12-04T09:22:43.4421368Z job-name: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:43.4421961Z env: 2025-12-04T09:22:43.4422188Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:43.4422477Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:43.4422742Z ##[endgroup] 2025-12-04T09:22:43.4459020Z ##[group]Run nick-fields/retry@v3.0.0 2025-12-04T09:22:43.4459343Z with: 2025-12-04T09:22:43.4459705Z shell: bash 2025-12-04T09:22:43.4459930Z timeout_minutes: 10 2025-12-04T09:22:43.4460193Z max_attempts: 5 2025-12-04T09:22:43.4460445Z retry_wait_seconds: 30 2025-12-04T09:22:43.4461300Z 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 2025-12-04T09:22:43.4462220Z polling_interval_seconds: 1 2025-12-04T09:22:43.4462520Z warning_on_retry: true 2025-12-04T09:22:43.4462783Z continue_on_error: false 2025-12-04T09:22:43.4463046Z env: 2025-12-04T09:22:43.4463262Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:43.4463542Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:43.4463953Z GITHUB_TOKEN: *** 2025-12-04T09:22:43.4464194Z ##[endgroup] 2025-12-04T09:22:43.5550310Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-12-04T09:22:43.7993466Z Defaulting to user installation because normal site-packages is not writeable 2025-12-04T09:22:43.9144327Z Collecting requests==2.27.1 2025-12-04T09:22:43.9316242Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-12-04T09:22:44.1138504Z Collecting pyyaml==6.0.2 2025-12-04T09:22:44.1177941Z Downloading PyYAML-6.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (737 kB) 2025-12-04T09:22:44.5479037Z Collecting charset-normalizer~=2.0.0 2025-12-04T09:22:44.5519099Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-12-04T09:22:44.6048674Z Collecting certifi>=2017.4.17 2025-12-04T09:22:44.6089588Z Downloading certifi-2025.11.12-py3-none-any.whl (159 kB) 2025-12-04T09:22:44.6161330Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (1.25.10) 2025-12-04T09:22:44.6170604Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (2.10) 2025-12-04T09:22:44.7036592Z Installing collected packages: charset-normalizer, certifi, requests, pyyaml 2025-12-04T09:22:44.8265200Z Successfully installed certifi-2025.11.12 charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-12-04T09:22:45.5309044Z Command completed after 1 attempt(s). 2025-12-04T09:22:45.5358760Z ##[group]Run set -x 2025-12-04T09:22:45.5359025Z set -x 2025-12-04T09:22:45.5359267Z  2025-12-04T09:22:45.5359682Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-12-04T09:22:45.5360197Z # in runner workspace 2025-12-04T09:22:45.5360622Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-12-04T09:22:45.5367235Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:45.5367647Z env: 2025-12-04T09:22:45.5367885Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.5368178Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.5368448Z ##[endgroup] 2025-12-04T09:22:45.5397013Z + python3 /home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-12-04T09:22:45.5594814Z Setting output branch=main 2025-12-04T09:22:45.5649082Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-12-04T09:22:45.5649548Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-12-04T09:22:45.5649910Z echo "Job name: ${JOB_NAME}" 2025-12-04T09:22:45.5650211Z  2025-12-04T09:22:45.5650615Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-12-04T09:22:45.5651162Z # in runner workspace 2025-12-04T09:22:45.5651610Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-12-04T09:22:45.5652136Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-12-04T09:22:45.5652510Z  --job-name "${JOB_NAME}" \ 2025-12-04T09:22:45.5658210Z  --test-matrix "{"include": [{"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests"}]}" \ 2025-12-04T09:22:45.5664179Z  --selected-test-configs "" \ 2025-12-04T09:22:45.5664533Z  --pr-number "${PR_NUMBER}" \ 2025-12-04T09:22:45.5677789Z  --tag "${TAG}" \ 2025-12-04T09:22:45.5678188Z  --event-name "${EVENT_NAME}" \ 2025-12-04T09:22:45.5678534Z  --schedule "${SCHEDULE}" \ 2025-12-04T09:22:45.5678873Z  --branch "${HEAD_BRANCH}" 2025-12-04T09:22:45.5685292Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:45.5685704Z env: 2025-12-04T09:22:45.5685941Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.5686232Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.5686756Z GITHUB_TOKEN: *** 2025-12-04T09:22:45.5687290Z JOB_NAME: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:45.5687896Z PR_NUMBER: 2025-12-04T09:22:45.5688124Z TAG: 2025-12-04T09:22:45.5688340Z EVENT_NAME: schedule 2025-12-04T09:22:45.5688586Z SCHEDULE: 29 8 * * * 2025-12-04T09:22:45.5688839Z HEAD_BRANCH: main 2025-12-04T09:22:45.5689084Z ##[endgroup] 2025-12-04T09:22:45.5714843Z Workflow: periodic 2025-12-04T09:22:45.5715400Z Job name: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:45.7586064Z Setting output keep-going=True 2025-12-04T09:22:45.7586484Z Setting output ci-verbose-test-logs=False 2025-12-04T09:22:45.7586892Z Setting output ci-test-showlocals=False 2025-12-04T09:22:45.7587240Z Setting output ci-no-test-timeout=False 2025-12-04T09:22:45.7587585Z Setting output ci-no-td=False 2025-12-04T09:22:45.7587906Z Setting output ci-td-distributed=False 2025-12-04T09:22:45.7588254Z Setting output is-unstable=False 2025-12-04T09:22:45.7588574Z Setting output reenabled-issues= 2025-12-04T09:22:45.7601556Z Setting output test-matrix={"include": [{"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests"}]} 2025-12-04T09:22:45.7614672Z Setting output is-test-matrix-empty=False 2025-12-04T09:22:45.7724462Z ##[group]Run echo "Filtered matrix:" 2025-12-04T09:22:45.7724873Z echo "Filtered matrix:" 2025-12-04T09:22:45.7737524Z echo "{"include": [{"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 1, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 2, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_AVX512", "shard": 3, "num_shards": 3, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 1, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "nogpu_NO_AVX2", "shard": 2, "num_shards": 2, "runner": "linux.4xlarge", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "mem_leak_check": "mem_leak_check", "rerun_disabled_tests": "rerun_disabled_tests"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests", "mem_leak_check": "mem_leak_check"}, {"config": "jit_legacy", "shard": 1, "num_shards": 1, "runner": "linux.g4dn.4xlarge.nvidia.gpu", "rerun_disabled_tests": "rerun_disabled_tests"}]}" 2025-12-04T09:22:45.7750788Z  2025-12-04T09:22:45.7751006Z echo 2025-12-04T09:22:45.7751284Z echo "Is the current job unstable? False" 2025-12-04T09:22:45.7751646Z  2025-12-04T09:22:45.7751857Z echo 2025-12-04T09:22:45.7752116Z echo "Is keep-going label set? True" 2025-12-04T09:22:45.7752455Z  2025-12-04T09:22:45.7752662Z echo 2025-12-04T09:22:45.7752905Z echo "Reenabled issues? " 2025-12-04T09:22:45.7759040Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:45.7759459Z env: 2025-12-04T09:22:45.7759689Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.7759956Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.7760213Z ##[endgroup] 2025-12-04T09:22:45.7786003Z Filtered matrix: 2025-12-04T09:22:45.7801516Z {include: [{config: nogpu_AVX512, shard: 1, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 1, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_AVX512, shard: 1, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 1, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_AVX512, shard: 2, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 2, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_AVX512, shard: 2, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 2, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_AVX512, shard: 3, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 3, num_shards: 3, runner: linux.4xlarge, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_AVX512, shard: 3, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: nogpu_AVX512, shard: 3, num_shards: 3, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_NO_AVX2, shard: 1, num_shards: 2, runner: linux.4xlarge, mem_leak_check: mem_leak_check}, {config: nogpu_NO_AVX2, shard: 1, num_shards: 2, runner: linux.4xlarge, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_NO_AVX2, shard: 1, num_shards: 2, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: nogpu_NO_AVX2, shard: 1, num_shards: 2, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_NO_AVX2, shard: 2, num_shards: 2, runner: linux.4xlarge, mem_leak_check: mem_leak_check}, {config: nogpu_NO_AVX2, shard: 2, num_shards: 2, runner: linux.4xlarge, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: nogpu_NO_AVX2, shard: 2, num_shards: 2, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: nogpu_NO_AVX2, shard: 2, num_shards: 2, runner: linux.4xlarge, rerun_disabled_tests: rerun_disabled_tests}, {config: jit_legacy, shard: 1, num_shards: 1, runner: linux.g4dn.4xlarge.nvidia.gpu, mem_leak_check: mem_leak_check}, {config: jit_legacy, shard: 1, num_shards: 1, runner: linux.g4dn.4xlarge.nvidia.gpu, mem_leak_check: mem_leak_check, rerun_disabled_tests: rerun_disabled_tests}, {config: jit_legacy, shard: 1, num_shards: 1, runner: linux.g4dn.4xlarge.nvidia.gpu, rerun_disabled_tests: rerun_disabled_tests, mem_leak_check: mem_leak_check}, {config: jit_legacy, shard: 1, num_shards: 1, runner: linux.g4dn.4xlarge.nvidia.gpu, rerun_disabled_tests: rerun_disabled_tests}]} 2025-12-04T09:22:45.7814046Z 2025-12-04T09:22:45.7814176Z Is the current job unstable? False 2025-12-04T09:22:45.7814393Z 2025-12-04T09:22:45.7814502Z Is keep-going label set? True 2025-12-04T09:22:45.7814708Z 2025-12-04T09:22:45.7814801Z Reenabled issues? 2025-12-04T09:22:45.7846723Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-12-04T09:22:45.7847293Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-12-04T09:22:45.7852962Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:45.7853352Z env: 2025-12-04T09:22:45.7853576Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.7853861Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.7854122Z JOB_TIMEOUT: 240 2025-12-04T09:22:45.7854358Z ##[endgroup] 2025-12-04T09:22:45.7901428Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:22:45.7901984Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:22:45.7902749Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-12-04T09:22:45.7908161Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T09:22:45.7908564Z env: 2025-12-04T09:22:45.7908787Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.7909065Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.7909311Z ##[endgroup] 2025-12-04T09:22:45.8012904Z ##[group]Run set -x 2025-12-04T09:22:45.8013252Z set -x 2025-12-04T09:22:45.8013486Z  2025-12-04T09:22:45.8013753Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-12-04T09:22:45.8014163Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-12-04T09:22:45.8014590Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-12-04T09:22:45.8015090Z  TEST_COMMAND=.ci/onnx/test.sh 2025-12-04T09:22:45.8015401Z else 2025-12-04T09:22:45.8015663Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-12-04T09:22:45.8015995Z fi 2025-12-04T09:22:45.8016198Z  2025-12-04T09:22:45.8016476Z # Leaving 1GB for the runner and other things 2025-12-04T09:22:45.8017110Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-12-04T09:22:45.8018064Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-12-04T09:22:45.8018845Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-12-04T09:22:45.8019422Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-12-04T09:22:45.8019875Z  2025-12-04T09:22:45.8020141Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-12-04T09:22:45.8020520Z  SHM_OPTS= 2025-12-04T09:22:45.8020785Z  JENKINS_USER= 2025-12-04T09:22:45.8021148Z  # ensure that docker container cleanly exits in 12 hours 2025-12-04T09:22:45.8021663Z  # if for some reason cleanup action doesn't stop container 2025-12-04T09:22:45.8022090Z  # when job is cancelled 2025-12-04T09:22:45.8022418Z  DOCKER_SHELL_CMD="sleep 12h" 2025-12-04T09:22:45.8022761Z  USED_IMAGE="${DOCKER_IMAGE_S390X}" 2025-12-04T09:22:45.8023090Z else 2025-12-04T09:22:45.8023349Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-12-04T09:22:45.8023699Z  JENKINS_USER="--user jenkins" 2025-12-04T09:22:45.8024033Z  DOCKER_SHELL_CMD= 2025-12-04T09:22:45.8024335Z  USED_IMAGE="${DOCKER_IMAGE}" 2025-12-04T09:22:45.8024639Z fi 2025-12-04T09:22:45.8024850Z  2025-12-04T09:22:45.8025221Z # detached container should get cleaned up by teardown_ec2_linux 2025-12-04T09:22:45.8025810Z # TODO: Stop building test binaries as part of the build phase 2025-12-04T09:22:45.8026480Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-12-04T09:22:45.8027052Z # shellcheck disable=SC2086,SC2090 2025-12-04T09:22:45.8027416Z container_name=$(docker run \ 2025-12-04T09:22:45.8027749Z  ${GPU_FLAG:-} \ 2025-12-04T09:22:45.8028060Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-12-04T09:22:45.8028434Z  -e BUILD_ENVIRONMENT \ 2025-12-04T09:22:45.8028755Z  -e PR_NUMBER \ 2025-12-04T09:22:45.8029040Z  -e GITHUB_ACTIONS \ 2025-12-04T09:22:45.8029352Z  -e GITHUB_REPOSITORY \ 2025-12-04T09:22:45.8029674Z  -e GITHUB_WORKFLOW \ 2025-12-04T09:22:45.8029985Z  -e GITHUB_JOB \ 2025-12-04T09:22:45.8030259Z  -e GITHUB_RUN_ID \ 2025-12-04T09:22:45.8030561Z  -e GITHUB_RUN_NUMBER \ 2025-12-04T09:22:45.8030879Z  -e GITHUB_RUN_ATTEMPT \ 2025-12-04T09:22:45.8031173Z  -e JOB_ID \ 2025-12-04T09:22:45.8031441Z  -e JOB_NAME \ 2025-12-04T09:22:45.8031714Z  -e BASE_SHA \ 2025-12-04T09:22:45.8031969Z  -e BRANCH \ 2025-12-04T09:22:45.8032227Z  -e SHA1 \ 2025-12-04T09:22:45.8032490Z  -e AWS_DEFAULT_REGION \ 2025-12-04T09:22:45.8032789Z  -e IN_WHEEL_TEST \ 2025-12-04T09:22:45.8033078Z  -e SHARD_NUMBER \ 2025-12-04T09:22:45.8033367Z  -e TEST_CONFIG \ 2025-12-04T09:22:45.8033655Z  -e NUM_TEST_SHARDS \ 2025-12-04T09:22:45.8034064Z  -e REENABLED_ISSUES \ 2025-12-04T09:22:45.8034391Z  -e CONTINUE_THROUGH_ERROR \ 2025-12-04T09:22:45.8034726Z  -e VERBOSE_TEST_LOGS \ 2025-12-04T09:22:45.8035028Z  -e TEST_SHOWLOCALS \ 2025-12-04T09:22:45.8035334Z  -e NO_TEST_TIMEOUT \ 2025-12-04T09:22:45.8035630Z  -e NO_TD \ 2025-12-04T09:22:45.8035950Z  -e TD_DISTRIBUTED \ 2025-12-04T09:22:45.8036248Z  -e PR_LABELS \ 2025-12-04T09:22:45.8036561Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-12-04T09:22:45.8036916Z  -e SCCACHE_BUCKET \ 2025-12-04T09:22:45.8037204Z  -e SCCACHE_REGION \ 2025-12-04T09:22:45.8037497Z  -e XLA_CUDA \ 2025-12-04T09:22:45.8037803Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-12-04T09:22:45.8038178Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-12-04T09:22:45.8038573Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-12-04T09:22:45.8038972Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-12-04T09:22:45.8039324Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-12-04T09:22:45.8039675Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-12-04T09:22:45.8040040Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-12-04T09:22:45.8040386Z  -e DASHBOARD_TAG \ 2025-12-04T09:22:45.8040679Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-12-04T09:22:45.8041072Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-12-04T09:22:45.8041519Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-12-04T09:22:45.8041952Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-12-04T09:22:45.8042762Z  --security-opt seccomp=unconfined \ 2025-12-04T09:22:45.8043138Z  --cap-add=SYS_PTRACE \ 2025-12-04T09:22:45.8043453Z  --ipc=host \ 2025-12-04T09:22:45.8043713Z  ${SHM_OPTS} \ 2025-12-04T09:22:45.8043983Z  --tty \ 2025-12-04T09:22:45.8044230Z  --detach \ 2025-12-04T09:22:45.8044562Z  --name="${container_name}" \ 2025-12-04T09:22:45.8044900Z  ${JENKINS_USER} \ 2025-12-04T09:22:45.8045269Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-12-04T09:22:45.8045688Z  -w /var/lib/jenkins/workspace \ 2025-12-04T09:22:45.8046027Z  "${USED_IMAGE}" \ 2025-12-04T09:22:45.8046318Z  ${DOCKER_SHELL_CMD} 2025-12-04T09:22:45.8046590Z ) 2025-12-04T09:22:45.8046942Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-12-04T09:22:45.8047386Z  2025-12-04T09:22:45.8047661Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-12-04T09:22:45.8048279Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-12-04T09:22:45.8048847Z fi 2025-12-04T09:22:45.8049065Z  2025-12-04T09:22:45.8049589Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-12-04T09:22:45.8055203Z shell: /usr/bin/bash -e {0} 2025-12-04T09:22:45.8055488Z env: 2025-12-04T09:22:45.8055708Z GIT_DEFAULT_BRANCH: main 2025-12-04T09:22:45.8055975Z HAS_NVIDIA_GPU: false 2025-12-04T09:22:45.8056313Z BUILD_ENVIRONMENT: linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:22:45.8056697Z PR_NUMBER: 2025-12-04T09:22:45.8056943Z GITHUB_REPOSITORY: pytorch/pytorch 2025-12-04T09:22:45.8057268Z GITHUB_WORKFLOW: periodic 2025-12-04T09:22:45.8057546Z GITHUB_JOB: test 2025-12-04T09:22:45.8057781Z GITHUB_RUN_ID: 19922826259 2025-12-04T09:22:45.8058064Z GITHUB_RUN_NUMBER: 19107 2025-12-04T09:22:45.8058343Z GITHUB_RUN_ATTEMPT: 1 2025-12-04T09:22:45.8058586Z JOB_ID: 57117865590 2025-12-04T09:22:45.8059129Z JOB_NAME: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:22:45.8059731Z BRANCH: main 2025-12-04T09:22:45.8060005Z SHA1: ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:22:45.8060536Z BASE_SHA: ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:22:45.8060917Z TEST_CONFIG: nogpu_AVX512 2025-12-04T09:22:45.8061195Z SHARD_NUMBER: 1 2025-12-04T09:22:45.8061422Z NUM_TEST_SHARDS: 3 2025-12-04T09:22:45.8061667Z EXTRA_FLAGS: 2025-12-04T09:22:45.8061906Z OP_BENCHMARK_TESTS: 2025-12-04T09:22:45.8062157Z REENABLED_ISSUES: 2025-12-04T09:22:45.8062503Z CONTINUE_THROUGH_ERROR: True 2025-12-04T09:22:45.8062801Z VERBOSE_TEST_LOGS: False 2025-12-04T09:22:45.8063071Z TEST_SHOWLOCALS: False 2025-12-04T09:22:45.8063349Z NO_TEST_TIMEOUT: False 2025-12-04T09:22:45.8063615Z NO_TD: False 2025-12-04T09:22:45.8063855Z TD_DISTRIBUTED: False 2025-12-04T09:22:45.8064169Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-12-04T09:22:45.8064560Z SCCACHE_REGION: us-east-1 2025-12-04T09:22:45.8064837Z SHM_SIZE: 1g 2025-12-04T09:22:45.8065678Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:45.8067244Z DOCKER_IMAGE_S390X: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:45.8068189Z XLA_CUDA: 2025-12-04T09:22:45.8068569Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-12-04T09:22:45.8069054Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-12-04T09:22:45.8069403Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 1 2025-12-04T09:22:45.8069727Z DASHBOARD_TAG: 2025-12-04T09:22:45.8070192Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-12-04T09:22:45.8070611Z HUGGING_FACE_HUB_TOKEN: *** 2025-12-04T09:22:45.8071053Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-12-04T09:22:45.8071500Z ARTIFACTS_FILE_SUFFIX: test-nogpu_AVX512-1-3-linux.4xlarge_57117865590 2025-12-04T09:22:45.8071957Z ##[endgroup] 2025-12-04T09:22:45.8095814Z + [[ nogpu_AVX512 == \m\u\l\t\i\g\p\u ]] 2025-12-04T09:22:45.8096218Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *onnx* ]] 2025-12-04T09:22:45.8096610Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-12-04T09:22:45.8099235Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-12-04T09:22:45.8171737Z + TOTAL_AVAILABLE_MEMORY_IN_GB='29.422 ' 2025-12-04T09:22:45.8172088Z + TOTAL_MEMORY_WITH_SWAP=32 2025-12-04T09:22:45.8172445Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *\s\3\9\0\x* ]] 2025-12-04T09:22:45.8172835Z + SHM_OPTS=--shm-size=1g 2025-12-04T09:22:45.8173121Z + JENKINS_USER='--user jenkins' 2025-12-04T09:22:45.8173414Z + DOCKER_SHELL_CMD= 2025-12-04T09:22:45.8174252Z + USED_IMAGE=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:45.8181216Z +++ nproc --ignore=2 2025-12-04T09:22:45.8207535Z ++ docker run -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=14 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e VLLM_TEST_HUGGING_FACE_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=29g --memory-swap=32g --env-file=/tmp/github_env_19922826259 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=1g --tty --detach --name= --user jenkins -v /home/ec2-user/actions-runner/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11-f0cd68561080d537ef3d3d6f81b25a6416ad600a 2025-12-04T09:22:56.1836594Z + container_name=40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T09:22:56.1837643Z + echo DOCKER_CONTAINER_ID=40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T09:22:56.1838539Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *\s\3\9\0\x* ]] 2025-12-04T09:22:56.1841903Z ++ echo dist/torch-2.10.0a0+gitffd9b0f-cp310-cp310-linux_x86_64.whl 2025-12-04T09:22:56.1845261Z + docker exec -t 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 sh -c 'python3 -m pip install dist/torch-2.10.0a0+gitffd9b0f-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-12-04T09:22:56.6993560Z Processing ./dist/torch-2.10.0a0+gitffd9b0f-cp310-cp310-linux_x86_64.whl (from torch==2.10.0a0+gitffd9b0f) 2025-12-04T09:22:57.4537067Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (3.18.0) 2025-12-04T09:22:57.4541692Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (4.12.2) 2025-12-04T09:22:57.4547318Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (1.13.3) 2025-12-04T09:22:57.4552908Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (2.8.8) 2025-12-04T09:22:57.4557120Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (3.1.6) 2025-12-04T09:22:57.4562610Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (2025.10.0) 2025-12-04T09:22:57.4577058Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (3.3.0) 2025-12-04T09:22:57.4964510Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from opt-einsum>=3.3->torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (1.22.4) 2025-12-04T09:22:57.4985208Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from sympy>=1.13.3->torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (1.3.0) 2025-12-04T09:22:57.5045816Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from jinja2->torch==2.10.0a0+gitffd9b0f->torch==2.10.0a0+gitffd9b0f) (3.0.3) 2025-12-04T09:22:57.8882614Z Installing collected packages: torch 2025-12-04T09:23:08.6454585Z Successfully installed torch-2.10.0a0+gitffd9b0f 2025-12-04T09:23:08.7512614Z + export TERM=vt100 2025-12-04T09:23:08.7512928Z + TERM=vt100 2025-12-04T09:23:08.7514825Z ++ dirname .ci/pytorch/test.sh 2025-12-04T09:23:08.7641325Z + source .ci/pytorch/common.sh 2025-12-04T09:23:08.7697719Z +++ dirname .ci/pytorch/common.sh 2025-12-04T09:23:08.7706148Z ++ source .ci/pytorch/common_utils.sh 2025-12-04T09:23:08.7758757Z +++ declare -f -t trap_add 2025-12-04T09:23:08.7763808Z ++ set -ex -o pipefail 2025-12-04T09:23:08.7764444Z ++ [[ linux-jammy-cuda13.0-py3.10-gcc11 == *rocm* ]] 2025-12-04T09:23:08.7764973Z ++ BUILD_TEST_LIBTORCH=0 2025-12-04T09:23:08.7767551Z ++ dirname .ci/pytorch/test.sh 2025-12-04T09:23:08.7775755Z + source .ci/pytorch/common-build.sh 2025-12-04T09:23:08.7817234Z ++ [[ linux-jammy-cuda13.0-py3.10-gcc11 != *win-* ]] 2025-12-04T09:23:08.7824073Z ++++ dirname .ci/pytorch/common-build.sh 2025-12-04T09:23:08.7833016Z +++ cd .ci/pytorch 2025-12-04T09:23:08.7836747Z +++ pwd -P 2025-12-04T09:23:08.7837292Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-12-04T09:23:08.7838047Z ++ [[ linux-jammy-cuda13.0-py3.10-gcc11 == *-pch* ]] 2025-12-04T09:23:08.7838434Z ++ which sccache 2025-12-04T09:23:08.7945475Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-12-04T09:23:08.7946146Z ++ sccache --stop-server 2025-12-04T09:23:08.8226275Z ++ true 2025-12-04T09:23:08.8226724Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-12-04T09:23:08.8312011Z ++ trap_add sccache_epilogue EXIT 2025-12-04T09:23:08.8312374Z ++ trap_add_cmd=sccache_epilogue 2025-12-04T09:23:08.8312679Z ++ shift 2025-12-04T09:23:08.8312902Z ++ for trap_add_name in "$@" 2025-12-04T09:23:08.8319531Z ++++ trap -p EXIT 2025-12-04T09:23:08.8322357Z +++ eval 'extract_trap_cmd ' 2025-12-04T09:23:08.8322864Z ++++ extract_trap_cmd 2025-12-04T09:23:08.8325635Z ++++ printf '%s\n' '' 2025-12-04T09:23:08.8326045Z +++ printf '%s\n' sccache_epilogue 2025-12-04T09:23:08.8326523Z ++ trap -- ' 2025-12-04T09:23:08.8326770Z sccache_epilogue' EXIT 2025-12-04T09:23:08.8327040Z ++ [[ -n 1 ]] 2025-12-04T09:23:08.8327456Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-12-04T09:23:08.8328108Z Skipping sccache server initialization, setting environment variables 2025-12-04T09:23:08.8328591Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-12-04T09:23:08.8328888Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-12-04T09:23:08.8329259Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-12-04T09:23:08.8329746Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-12-04T09:23:08.8334325Z ++ export RUST_LOG=sccache::server=error 2025-12-04T09:23:08.8334711Z ++ RUST_LOG=sccache::server=error 2025-12-04T09:23:08.8335034Z ++ sccache --zero-stats 2025-12-04T09:23:09.0153306Z Statistics zeroed. 2025-12-04T09:23:09.0157825Z ++ which ccache 2025-12-04T09:23:09.0217990Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *rocm* ]] 2025-12-04T09:23:09.0218430Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *s390x* ]] 2025-12-04T09:23:09.0218832Z + [[ -d /var/lib/jenkins/workspace ]] 2025-12-04T09:23:09.0221179Z ++ stat -c %u /var/lib/jenkins/workspace 2025-12-04T09:23:09.0463595Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-12-04T09:23:09.0463955Z + trap_add cleanup_workspace EXIT 2025-12-04T09:23:09.0464285Z + trap_add_cmd=cleanup_workspace 2025-12-04T09:23:09.0464588Z + shift 2025-12-04T09:23:09.0464805Z + for trap_add_name in "$@" 2025-12-04T09:23:09.0470805Z +++ trap -p EXIT 2025-12-04T09:23:09.0473657Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-12-04T09:23:09.0474040Z sccache_epilogue'\'' EXIT' 2025-12-04T09:23:09.0474332Z +++ extract_trap_cmd trap -- ' 2025-12-04T09:23:09.0474630Z sccache_epilogue' EXIT 2025-12-04T09:23:09.0474897Z +++ printf '%s\n' ' 2025-12-04T09:23:09.0475131Z sccache_epilogue' 2025-12-04T09:23:09.0475395Z ++ printf '%s\n' cleanup_workspace 2025-12-04T09:23:09.0476891Z + trap -- ' 2025-12-04T09:23:09.0477105Z sccache_epilogue 2025-12-04T09:23:09.0477361Z cleanup_workspace' EXIT 2025-12-04T09:23:09.0477693Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-12-04T09:23:10.1216730Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-12-04T09:23:10.2644744Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *cuda* ]] 2025-12-04T09:23:10.2647689Z ++ python -c 'import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))' 2025-12-04T09:23:10.7296110Z + NUMBA_CUDA_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda 2025-12-04T09:23:10.7296798Z + '[' -n /opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda ']' 2025-12-04T09:23:10.7301972Z +++ realpath .ci/pytorch/test.sh 2025-12-04T09:23:10.7323038Z ++ dirname /var/lib/jenkins/workspace/.ci/pytorch/test.sh 2025-12-04T09:23:10.7340515Z + NUMBA_PATCH=/var/lib/jenkins/workspace/.ci/pytorch/numba-cuda-13.patch 2025-12-04T09:23:10.7341133Z + pushd /opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda 2025-12-04T09:23:10.7341774Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda ~/workspace 2025-12-04T09:23:10.7342527Z + patch -p4 2025-12-04T09:23:10.7379181Z patching file cudadrv/driver.py 2025-12-04T09:23:10.7379821Z Hunk #1 succeeded at 357 (offset -8 lines). 2025-12-04T09:23:10.7388967Z + popd 2025-12-04T09:23:10.7389196Z ~/workspace 2025-12-04T09:23:10.7389480Z + echo 'Environment variables:' 2025-12-04T09:23:10.7389791Z Environment variables: 2025-12-04T09:23:10.7390047Z + env 2025-12-04T09:23:10.7411348Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-12-04T09:23:10.7412320Z CONTINUE_THROUGH_ERROR=True 2025-12-04T09:23:10.7412858Z BUILD_ENVIRONMENT=linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:23:10.7413795Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-12-04T09:23:10.7414094Z HOSTNAME=40bac2ce78e3 2025-12-04T09:23:10.7414974Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7415849Z GITHUB_ACTION=__run_3 2025-12-04T09:23:10.7416130Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-12-04T09:23:10.7416438Z GITHUB_RUN_NUMBER=19107 2025-12-04T09:23:10.7416717Z TEST_CONFIG=nogpu_AVX512 2025-12-04T09:23:10.7417026Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-12-04T09:23:10.7417367Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-12-04T09:23:10.7417703Z SCCACHE_IDLE_TIMEOUT=0 2025-12-04T09:23:10.7418127Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-12-04T09:23:10.7418440Z GITHUB_TRIGGERING_ACTOR=huydhn 2025-12-04T09:23:10.7418722Z GITHUB_REF_TYPE=branch 2025-12-04T09:23:10.7419035Z BASE_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7419401Z XLA_CUDA= 2025-12-04T09:23:10.7419624Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-12-04T09:23:10.7420111Z HUGGING_FACE_HUB_TOKEN=*** 2025-12-04T09:23:10.7420665Z *** 2025-12-04T09:23:10.7420962Z GITHUB_REPOSITORY_ID=65600975 2025-12-04T09:23:10.7421357Z GITHUB_ACTIONS=true 2025-12-04T09:23:10.7421785Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-12-04T09:23:10.7422403Z SHA1=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7423011Z GITHUB_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7423963Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/periodic.yml@refs/heads/main 2025-12-04T09:23:10.7424856Z UCC_HOME=/usr 2025-12-04T09:23:10.7425246Z VERBOSE_TEST_LOGS=False 2025-12-04T09:23:10.7425720Z GITHUB_REF=refs/heads/main 2025-12-04T09:23:10.7426153Z SHARD_NUMBER=1 2025-12-04T09:23:10.7426525Z GITHUB_REF_PROTECTED=true 2025-12-04T09:23:10.7426939Z HOME=/var/lib/jenkins 2025-12-04T09:23:10.7427445Z GITHUB_API_URL=https://api.github.com 2025-12-04T09:23:10.7428020Z PYTORCH_TEST_RERUN_DISABLED_TESTS=1 2025-12-04T09:23:10.7428642Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-12-04T09:23:10.7429229Z USE_SYSTEM_NCCL=1 2025-12-04T09:23:10.7429638Z NUM_TEST_SHARDS=3 2025-12-04T09:23:10.7430006Z UCX_HOME=/usr 2025-12-04T09:23:10.7431091Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7432807Z JOB_NAME=linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:23:10.7434449Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7435844Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-12-04T09:23:10.7436803Z GITHUB_EVENT_NAME=schedule 2025-12-04T09:23:10.7437236Z DASHBOARD_TAG= 2025-12-04T09:23:10.7437620Z GITHUB_RUN_ID=19922826259 2025-12-04T09:23:10.7438070Z INSTALLED_OPENBLAS= 2025-12-04T09:23:10.7438860Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7439606Z GITHUB_ACTOR=huydhn 2025-12-04T09:23:10.7439847Z PR_NUMBER= 2025-12-04T09:23:10.7440056Z DESIRED_CUDA=13.0.0 2025-12-04T09:23:10.7440298Z GITHUB_RUN_ATTEMPT=1 2025-12-04T09:23:10.7440563Z ANACONDA_PYTHON_VERSION=3.10 2025-12-04T09:23:10.7440914Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-12-04T09:23:10.7441285Z TERM=vt100 2025-12-04T09:23:10.7441503Z INSTALLED_VISION=yes 2025-12-04T09:23:10.7441896Z BRANCH=main 2025-12-04T09:23:10.7442126Z SCCACHE_REGION=us-east-1 2025-12-04T09:23:10.7442765Z OPENSSL_ROOT_DIR=/opt/openssl 2025-12-04T09:23:10.7443068Z BUILD_AOT_INDUCTOR_TEST= 2025-12-04T09:23:10.7443335Z CUDA_PATH=/usr/local/cuda 2025-12-04T09:23:10.7443902Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-12-04T09:23:10.7444773Z GITHUB_SERVER_URL=https://github.com 2025-12-04T09:23:10.7445143Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-12-04T09:23:10.7445511Z REENABLED_ISSUES= 2025-12-04T09:23:10.7445747Z DOCS= 2025-12-04T09:23:10.7445938Z SHLVL=1 2025-12-04T09:23:10.7446145Z MAX_JOBS=14 2025-12-04T09:23:10.7446369Z GITHUB_ACTOR_ID=475357 2025-12-04T09:23:10.7446717Z GITHUB_WORKFLOW_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7447130Z GITHUB_REF_NAME=main 2025-12-04T09:23:10.7447533Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-12-04T09:23:10.7447980Z GITHUB_JOB=test 2025-12-04T09:23:10.7448236Z NO_TEST_TIMEOUT=False 2025-12-04T09:23:10.7448493Z TD_DISTRIBUTED=False 2025-12-04T09:23:10.7448770Z GITHUB_REPOSITORY=pytorch/pytorch 2025-12-04T09:23:10.7449078Z GITHUB_RETENTION_DAYS=90 2025-12-04T09:23:10.7449355Z OPENSSL_DIR=/opt/openssl 2025-12-04T09:23:10.7449635Z GITHUB_ACTION_REPOSITORY= 2025-12-04T09:23:10.7450472Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-12-04T09:23:10.7451364Z GITHUB_BASE_REF= 2025-12-04T09:23:10.7451601Z INSTALLED_ACL= 2025-12-04T09:23:10.7451957Z ARTIFACTS_FILE_SUFFIX=test-nogpu_AVX512-1-3-linux.4xlarge_57117865590 2025-12-04T09:23:10.7452405Z CI=true 2025-12-04T09:23:10.7452633Z GITHUB_REPOSITORY_OWNER=pytorch 2025-12-04T09:23:10.7452966Z RUST_LOG=sccache::server=error 2025-12-04T09:23:10.7453254Z JOB_ID=57117865590 2025-12-04T09:23:10.7453488Z GITHUB_HEAD_REF= 2025-12-04T09:23:10.7453713Z GITHUB_ACTION_REF= 2025-12-04T09:23:10.7454021Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-12-04T09:23:10.7454393Z TEST_SHOWLOCALS=False 2025-12-04T09:23:10.7454662Z GITHUB_WORKFLOW=periodic 2025-12-04T09:23:10.7454937Z DEBIAN_FRONTEND=noninteractive 2025-12-04T09:23:10.7455620Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7456321Z NO_TD=False 2025-12-04T09:23:10.7456545Z SKIP_SCCACHE_INITIALIZATION=1 2025-12-04T09:23:10.7456863Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-12-04T09:23:10.7457187Z _=/usr/bin/env 2025-12-04T09:23:10.7457553Z OLDPWD=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda 2025-12-04T09:23:10.7458125Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-12-04T09:23:10.7551844Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-12-04T09:23:10.7552516Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T09:23:10.7553444Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-12-04T09:23:10.7554091Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-12-04T09:23:10.7554591Z + BUILD_DIR=build 2025-12-04T09:23:10.7554841Z + BUILD_RENAMED_DIR=build_renamed 2025-12-04T09:23:10.7555216Z + BUILD_BIN_DIR=build/bin 2025-12-04T09:23:10.7555493Z + SHARD_NUMBER=1 2025-12-04T09:23:10.7555730Z + NUM_TEST_SHARDS=3 2025-12-04T09:23:10.7555987Z + export TORCH_SERIALIZATION_DEBUG=1 2025-12-04T09:23:10.7556325Z + TORCH_SERIALIZATION_DEBUG=1 2025-12-04T09:23:10.7556621Z + export VALGRIND=ON 2025-12-04T09:23:10.7556924Z + VALGRIND=ON 2025-12-04T09:23:10.7557297Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *clang9* ]] 2025-12-04T09:23:10.7557719Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *xpu* ]] 2025-12-04T09:23:10.7558070Z + detect_cuda_arch 2025-12-04T09:23:10.7558359Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *cuda* ]] 2025-12-04T09:23:10.7558733Z + command -v nvidia-smi 2025-12-04T09:23:10.7559194Z + [[ nogpu_AVX512 == *nogpu* ]] 2025-12-04T09:23:10.7559553Z + TORCH_CUDA_ARCH_LIST=8.0 2025-12-04T09:23:10.7559960Z + export TORCH_CUDA_ARCH_LIST 2025-12-04T09:23:10.7560312Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *s390x* ]] 2025-12-04T09:23:10.7560782Z + [[ 1 == \1 ]] 2025-12-04T09:23:10.7561013Z + ulimit -c 0 2025-12-04T09:23:10.7561300Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *bazel* ]] 2025-12-04T09:23:10.7561799Z ++ realpath build/custom_test_artifacts 2025-12-04T09:23:10.7578966Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-12-04T09:23:10.7579567Z + [[ -n '' ]] 2025-12-04T09:23:10.7579899Z + echo 'Environment variables' 2025-12-04T09:23:10.7580209Z Environment variables 2025-12-04T09:23:10.7580463Z + env 2025-12-04T09:23:10.7599710Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-12-04T09:23:10.7600362Z CONTINUE_THROUGH_ERROR=True 2025-12-04T09:23:10.7600729Z BUILD_ENVIRONMENT=linux-jammy-cuda13.0-py3.10-gcc11 2025-12-04T09:23:10.7601551Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-12-04T09:23:10.7601981Z HOSTNAME=40bac2ce78e3 2025-12-04T09:23:10.7602794Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7603710Z GITHUB_ACTION=__run_3 2025-12-04T09:23:10.7603991Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-12-04T09:23:10.7604459Z GITHUB_RUN_NUMBER=19107 2025-12-04T09:23:10.7604780Z TEST_CONFIG=nogpu_AVX512 2025-12-04T09:23:10.7605125Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-12-04T09:23:10.7605637Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-12-04T09:23:10.7605965Z SCCACHE_IDLE_TIMEOUT=0 2025-12-04T09:23:10.7606388Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-12-04T09:23:10.7606694Z GITHUB_TRIGGERING_ACTOR=huydhn 2025-12-04T09:23:10.7606974Z GITHUB_REF_TYPE=branch 2025-12-04T09:23:10.7607236Z TORCH_CUDA_ARCH_LIST=8.0 2025-12-04T09:23:10.7607565Z BASE_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7607913Z XLA_CUDA= 2025-12-04T09:23:10.7608153Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-12-04T09:23:10.7608938Z HUGGING_FACE_HUB_TOKEN=*** 2025-12-04T09:23:10.7609270Z *** 2025-12-04T09:23:10.7609476Z GITHUB_REPOSITORY_ID=65600975 2025-12-04T09:23:10.7609769Z GITHUB_ACTIONS=true 2025-12-04T09:23:10.7610084Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-12-04T09:23:10.7610497Z SHA1=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7610902Z GITHUB_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7611477Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/periodic.yml@refs/heads/main 2025-12-04T09:23:10.7611995Z UCC_HOME=/usr 2025-12-04T09:23:10.7612225Z TORCH_SERIALIZATION_DEBUG=1 2025-12-04T09:23:10.7612514Z VERBOSE_TEST_LOGS=False 2025-12-04T09:23:10.7612784Z GITHUB_REF=refs/heads/main 2025-12-04T09:23:10.7613042Z SHARD_NUMBER=1 2025-12-04T09:23:10.7613287Z GITHUB_REF_PROTECTED=true 2025-12-04T09:23:10.7613563Z HOME=/var/lib/jenkins 2025-12-04T09:23:10.7613845Z GITHUB_API_URL=https://api.github.com 2025-12-04T09:23:10.7614194Z PYTORCH_TEST_RERUN_DISABLED_TESTS=1 2025-12-04T09:23:10.7614559Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-12-04T09:23:10.7614908Z USE_SYSTEM_NCCL=1 2025-12-04T09:23:10.7615147Z NUM_TEST_SHARDS=3 2025-12-04T09:23:10.7615379Z UCX_HOME=/usr 2025-12-04T09:23:10.7615981Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7616970Z JOB_NAME=linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T09:23:10.7617926Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7618815Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-12-04T09:23:10.7619350Z GITHUB_EVENT_NAME=schedule 2025-12-04T09:23:10.7619625Z DASHBOARD_TAG= 2025-12-04T09:23:10.7619862Z GITHUB_RUN_ID=19922826259 2025-12-04T09:23:10.7620261Z INSTALLED_OPENBLAS= 2025-12-04T09:23:10.7620936Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7621677Z GITHUB_ACTOR=huydhn 2025-12-04T09:23:10.7621916Z PR_NUMBER= 2025-12-04T09:23:10.7622125Z DESIRED_CUDA=13.0.0 2025-12-04T09:23:10.7622373Z GITHUB_RUN_ATTEMPT=1 2025-12-04T09:23:10.7622696Z VALGRIND=ON 2025-12-04T09:23:10.7622919Z ANACONDA_PYTHON_VERSION=3.10 2025-12-04T09:23:10.7623275Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-12-04T09:23:10.7623641Z TERM=vt100 2025-12-04T09:23:10.7623853Z INSTALLED_VISION=yes 2025-12-04T09:23:10.7624103Z BRANCH=main 2025-12-04T09:23:10.7624328Z SCCACHE_REGION=us-east-1 2025-12-04T09:23:10.7624600Z OPENSSL_ROOT_DIR=/opt/openssl 2025-12-04T09:23:10.7624894Z BUILD_AOT_INDUCTOR_TEST= 2025-12-04T09:23:10.7625166Z CUDA_PATH=/usr/local/cuda 2025-12-04T09:23:10.7625717Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-12-04T09:23:10.7626350Z GITHUB_SERVER_URL=https://github.com 2025-12-04T09:23:10.7626723Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-12-04T09:23:10.7627090Z REENABLED_ISSUES= 2025-12-04T09:23:10.7627308Z DOCS= 2025-12-04T09:23:10.7627507Z SHLVL=1 2025-12-04T09:23:10.7627710Z MAX_JOBS=14 2025-12-04T09:23:10.7627922Z GITHUB_ACTOR_ID=475357 2025-12-04T09:23:10.7628292Z GITHUB_WORKFLOW_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T09:23:10.7628709Z GITHUB_REF_NAME=main 2025-12-04T09:23:10.7629098Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-12-04T09:23:10.7629557Z GITHUB_JOB=test 2025-12-04T09:23:10.7629795Z NO_TEST_TIMEOUT=False 2025-12-04T09:23:10.7630039Z TD_DISTRIBUTED=False 2025-12-04T09:23:10.7630309Z GITHUB_REPOSITORY=pytorch/pytorch 2025-12-04T09:23:10.7630626Z GITHUB_RETENTION_DAYS=90 2025-12-04T09:23:10.7630889Z OPENSSL_DIR=/opt/openssl 2025-12-04T09:23:10.7631166Z GITHUB_ACTION_REPOSITORY= 2025-12-04T09:23:10.7632030Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-12-04T09:23:10.7632916Z GITHUB_BASE_REF= 2025-12-04T09:23:10.7633154Z INSTALLED_ACL= 2025-12-04T09:23:10.7633514Z ARTIFACTS_FILE_SUFFIX=test-nogpu_AVX512-1-3-linux.4xlarge_57117865590 2025-12-04T09:23:10.7633964Z CI=true 2025-12-04T09:23:10.7634190Z GITHUB_REPOSITORY_OWNER=pytorch 2025-12-04T09:23:10.7634511Z RUST_LOG=sccache::server=error 2025-12-04T09:23:10.7634797Z JOB_ID=57117865590 2025-12-04T09:23:10.7635032Z GITHUB_HEAD_REF= 2025-12-04T09:23:10.7635258Z GITHUB_ACTION_REF= 2025-12-04T09:23:10.7635564Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-12-04T09:23:10.7635942Z TEST_SHOWLOCALS=False 2025-12-04T09:23:10.7636214Z GITHUB_WORKFLOW=periodic 2025-12-04T09:23:10.7636485Z DEBIAN_FRONTEND=noninteractive 2025-12-04T09:23:10.7637180Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_a2f63b9f-2e0d-4b13-bb94-2273fa7cd1e1 2025-12-04T09:23:10.7637876Z NO_TD=False 2025-12-04T09:23:10.7638101Z SKIP_SCCACHE_INITIALIZATION=1 2025-12-04T09:23:10.7638423Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-12-04T09:23:10.7638906Z OLDPWD=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/numba/cuda 2025-12-04T09:23:10.7639348Z _=/usr/bin/env 2025-12-04T09:23:10.7639602Z + echo 'Testing pytorch' 2025-12-04T09:23:10.7639870Z Testing pytorch 2025-12-04T09:23:10.7640103Z + export LANG=C.UTF-8 2025-12-04T09:23:10.7640355Z + LANG=C.UTF-8 2025-12-04T09:23:10.7643012Z + PR_NUMBER= 2025-12-04T09:23:10.7643300Z + [[ nogpu_AVX512 == \d\e\f\a\u\l\t ]] 2025-12-04T09:23:10.7643810Z + [[ nogpu_AVX512 == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-12-04T09:23:10.7644164Z + [[ nogpu_AVX512 == \s\l\o\w ]] 2025-12-04T09:23:10.7644706Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *slow-gradcheck* ]] 2025-12-04T09:23:10.7645230Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *cuda* ]] 2025-12-04T09:23:10.7645637Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-12-04T09:23:10.7646256Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-12-04T09:23:10.7646607Z + [[ nogpu_AVX512 == *crossref* ]] 2025-12-04T09:23:10.7646949Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *rocm* ]] 2025-12-04T09:23:10.7647360Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *xpu* ]] 2025-12-04T09:23:10.7647782Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *-bazel-* ]] 2025-12-04T09:23:10.7648232Z + pip_install ninja==1.10.2 2025-12-04T09:23:10.7648619Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-12-04T09:23:10.7649116Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-12-04T09:23:11.2346192Z Collecting ninja==1.10.2 2025-12-04T09:23:11.2605661Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-12-04T09:23:11.2719635Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-12-04T09:23:11.6714598Z Installing collected packages: ninja 2025-12-04T09:23:11.6715022Z Attempting uninstall: ninja 2025-12-04T09:23:11.6723072Z Found existing installation: ninja 1.11.1.4 2025-12-04T09:23:11.6746012Z Uninstalling ninja-1.11.1.4: 2025-12-04T09:23:11.6807625Z Successfully uninstalled ninja-1.11.1.4 2025-12-04T09:23:11.7163133Z Successfully installed ninja-1.10.2 2025-12-04T09:23:11.7792084Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-12-04T09:23:11.7793890Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-12-04T09:23:11.7799782Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *aarch64* ]] 2025-12-04T09:23:11.7800597Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *asan* ]] 2025-12-04T09:23:11.7801137Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *-debug* ]] 2025-12-04T09:23:11.7801607Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *-bazel-* ]] 2025-12-04T09:23:11.7802225Z + echo 'We are not in debug mode: linux-jammy-cuda13.0-py3.10-gcc11. Expect the assertion to pass' 2025-12-04T09:23:11.7802987Z We are not in debug mode: linux-jammy-cuda13.0-py3.10-gcc11. Expect the assertion to pass 2025-12-04T09:23:11.7805373Z + cd test 2025-12-04T09:23:11.7805820Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-12-04T09:23:13.4286252Z + [[ nogpu_AVX512 == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-12-04T09:23:13.4286658Z + [[ nogpu_AVX512 == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-12-04T09:23:13.4287028Z + export ATEN_CPU_CAPABILITY=avx2 2025-12-04T09:23:13.4287357Z + ATEN_CPU_CAPABILITY=avx2 2025-12-04T09:23:13.4287716Z + [[ nogpu_AVX512 == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-12-04T09:23:13.4293266Z + DYNAMO_BENCHMARK_FLAGS=() 2025-12-04T09:23:13.4293795Z + [[ nogpu_AVX512 == *pr_time_benchmarks* ]] 2025-12-04T09:23:13.4294385Z + [[ nogpu_AVX512 == *dynamo_eager* ]] 2025-12-04T09:23:13.4294755Z + [[ nogpu_AVX512 == *aot_eager* ]] 2025-12-04T09:23:13.4295077Z + [[ nogpu_AVX512 == *aot_inductor* ]] 2025-12-04T09:23:13.4295428Z + [[ nogpu_AVX512 == *max_autotune_inductor* ]] 2025-12-04T09:23:13.4295769Z + [[ nogpu_AVX512 == *inductor* ]] 2025-12-04T09:23:13.4296084Z + [[ nogpu_AVX512 == *dynamic* ]] 2025-12-04T09:23:13.4296394Z + [[ nogpu_AVX512 == *cpu* ]] 2025-12-04T09:23:13.4296679Z + [[ nogpu_AVX512 == *xpu* ]] 2025-12-04T09:23:13.4297000Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-12-04T09:23:13.4321567Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *libtorch* ]] 2025-12-04T09:23:13.4321999Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *-bazel-* ]] 2025-12-04T09:23:13.4325826Z + cd test 2025-12-04T09:23:13.4326272Z + python -c 'import torch; print(torch.__config__.show())' 2025-12-04T09:23:14.7514730Z PyTorch built with: 2025-12-04T09:23:14.7515051Z - GCC 11.4 2025-12-04T09:23:14.7515276Z - C++ Version: 201703 2025-12-04T09:23:14.7516177Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-12-04T09:23:14.7516988Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-12-04T09:23:14.7517455Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-12-04T09:23:14.7517820Z - LAPACK is enabled (usually provided by MKL) 2025-12-04T09:23:14.7518288Z - NNPACK is enabled 2025-12-04T09:23:14.7518547Z - CPU capability usage: AVX2 2025-12-04T09:23:14.7523867Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32, CUDA_VERSION=13.0, CUDNN_VERSION=9.13.0, CXX_COMPILER=/opt/cache/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -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 -Werror -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, FORCE_FALLBACK_CUDA_MPI=1, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=ON, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=ON, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 2025-12-04T09:23:14.7529494Z 2025-12-04T09:23:15.0714701Z + cd test 2025-12-04T09:23:15.0715132Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-12-04T09:23:16.3800250Z ATen/Parallel: 2025-12-04T09:23:16.3800681Z at::get_num_threads() : 8 2025-12-04T09:23:16.3801030Z at::get_num_interop_threads() : 8 2025-12-04T09:23:16.3801379Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-12-04T09:23:16.3801698Z omp_get_max_threads() : 8 2025-12-04T09:23:16.3802307Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-12-04T09:23:16.3802960Z mkl_get_max_threads() : 8 2025-12-04T09:23:16.3803358Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-12-04T09:23:16.3803850Z std::thread::hardware_concurrency() : 16 2025-12-04T09:23:16.3804191Z Environment variables: 2025-12-04T09:23:16.3804509Z OMP_NUM_THREADS : [not set] 2025-12-04T09:23:16.3804808Z MKL_NUM_THREADS : [not set] 2025-12-04T09:23:16.3805109Z ATen parallel backend: OpenMP 2025-12-04T09:23:16.3805306Z 2025-12-04T09:23:16.6775659Z + [[ nogpu_AVX512 == *numpy_2* ]] 2025-12-04T09:23:16.6776463Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *aarch64* ]] 2025-12-04T09:23:16.6777110Z + [[ nogpu_AVX512 == *backward* ]] 2025-12-04T09:23:16.6777780Z + [[ nogpu_AVX512 == *libtorch_agnostic_targetting* ]] 2025-12-04T09:23:16.6778307Z + [[ nogpu_AVX512 == *xla* ]] 2025-12-04T09:23:16.6778599Z + [[ nogpu_AVX512 == *vllm* ]] 2025-12-04T09:23:16.6778888Z + [[ nogpu_AVX512 == *executorch* ]] 2025-12-04T09:23:16.6779225Z + [[ nogpu_AVX512 == \j\i\t\_\l\e\g\a\c\y ]] 2025-12-04T09:23:16.6779580Z + [[ nogpu_AVX512 == \q\u\a\n\t\i\z\a\t\i\o\n ]] 2025-12-04T09:23:16.6779973Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *libtorch* ]] 2025-12-04T09:23:16.6780378Z + [[ nogpu_AVX512 == distributed ]] 2025-12-04T09:23:16.6780711Z + [[ nogpu_AVX512 == *operator_benchmark* ]] 2025-12-04T09:23:16.6781084Z + [[ nogpu_AVX512 == *operator_microbenchmark* ]] 2025-12-04T09:23:16.6781470Z + [[ nogpu_AVX512 == *attention_microbenchmark* ]] 2025-12-04T09:23:16.6781855Z + [[ nogpu_AVX512 == *inductor_distributed* ]] 2025-12-04T09:23:16.6782215Z + [[ nogpu_AVX512 == *inductor-halide* ]] 2025-12-04T09:23:16.6782557Z + [[ nogpu_AVX512 == *inductor-pallas* ]] 2025-12-04T09:23:16.6782916Z + [[ nogpu_AVX512 == *inductor-triton-cpu* ]] 2025-12-04T09:23:16.6783548Z + [[ nogpu_AVX512 == *inductor-micro-benchmark* ]] 2025-12-04T09:23:16.6784003Z + [[ nogpu_AVX512 == *aoti_cross_compile_for_windows* ]] 2025-12-04T09:23:16.6784385Z + [[ nogpu_AVX512 == *huggingface* ]] 2025-12-04T09:23:16.6784710Z + [[ nogpu_AVX512 == *timm* ]] 2025-12-04T09:23:16.6785014Z + [[ nogpu_AVX512 == cachebench ]] 2025-12-04T09:23:16.6785324Z + [[ nogpu_AVX512 == verify_cachebench ]] 2025-12-04T09:23:16.6785772Z + [[ nogpu_AVX512 == *torchbench* ]] 2025-12-04T09:23:16.6786111Z + [[ nogpu_AVX512 == *inductor_cpp_wrapper* ]] 2025-12-04T09:23:16.6786457Z + [[ nogpu_AVX512 == *inductor_core* ]] 2025-12-04T09:23:16.6786781Z + [[ nogpu_AVX512 == *inductor* ]] 2025-12-04T09:23:16.6787090Z + [[ nogpu_AVX512 == *einops* ]] 2025-12-04T09:23:16.6787382Z + [[ nogpu_AVX512 == *dynamo_core* ]] 2025-12-04T09:23:16.6787712Z + [[ nogpu_AVX512 == *dynamo_wrapped* ]] 2025-12-04T09:23:16.6788087Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *rocm* ]] 2025-12-04T09:23:16.6788443Z + [[ 1 == 1 ]] 2025-12-04T09:23:16.6788675Z + [[ 3 -gt 1 ]] 2025-12-04T09:23:16.6788942Z + test_lazy_tensor_meta_reference_disabled 2025-12-04T09:23:16.6789365Z + export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1 2025-12-04T09:23:16.6789810Z + TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1 2025-12-04T09:23:16.6790279Z + echo 'Testing lazy tensor operations without meta reference' 2025-12-04T09:23:16.6790776Z Testing lazy tensor operations without meta reference 2025-12-04T09:23:16.6791280Z + python test/run_test.py --include lazy/test_ts_opinfo.py --verbose 2025-12-04T09:23:18.3036875Z W1204 09:23:18.302000 170 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:23:21.7520307Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T09:23:21.8114127Z Ignoring disabled issues: [''] 2025-12-04T09:23:21.8218959Z Found test times from artifacts 2025-12-04T09:23:21.8619148Z Found test times from artifacts 2025-12-04T09:23:21.8632171Z Running all tests 2025-12-04T09:23:21.8635290Z Running parallel tests on 3 processes 2025-12-04T09:23:21.8635950Z Name: tests to run (est. time: 0.01min) 2025-12-04T09:23:21.8636492Z Serial tests (0): 2025-12-04T09:23:21.8636753Z Parallel tests (1): 2025-12-04T09:23:21.8637030Z lazy/test_ts_opinfo 1/1 2025-12-04T09:23:21.8637334Z Name: excluded (est. time: 0.0min) 2025-12-04T09:23:21.8637639Z Serial tests (0): 2025-12-04T09:23:21.8637887Z Parallel tests (0): 2025-12-04T09:23:21.8639707Z Running lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:23:21.863673][744.549445923] 2025-12-04T09:23:21.8640467Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:23:21.8643956Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:23:21.864050] 2025-12-04T09:23:26.4887008Z 2025-12-04T09:23:26.4888548Z 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_226345881e804c98_.log 2025-12-04T09:23:26.4889394Z Running 0 items in this shard: 2025-12-04T09:23:26.4889595Z 2025-12-04T09:23:26.4889915Z Finished lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:23:26.488668][749.174435972], took 0.08min 2025-12-04T09:23:26.4895379Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-26c938cbe96a9c7d.xml 2025-12-04T09:23:26.9334518Z Uploading artifacts took 0.16 seconds 2025-12-04T09:23:28.6166561Z W1204 09:23:28.615000 226 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:23:28.6374126Z W1204 09:23:28.636000 227 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:23:28.6563055Z W1204 09:23:28.655000 228 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:23:29.9776638Z Running lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:23:29.977198][752.662967766] 2025-12-04T09:23:29.9777171Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:23:29.9780296Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:23:29.977678] 2025-12-04T09:23:34.6067811Z 2025-12-04T09:23:34.6068873Z 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_35c2c66c5a74c277_.log 2025-12-04T09:23:34.6069711Z Running 0 items in this shard: 2025-12-04T09:23:34.6069914Z 2025-12-04T09:23:34.6070236Z Finished lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:23:34.606715][757.292483954], took 0.08min 2025-12-04T09:23:34.6079895Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-0c9dfc571604cfde.xml 2025-12-04T09:23:35.4491430Z Running test batch 'tests to run' cost 13.59 seconds 2025-12-04T09:23:36.1405267Z 2025-12-04T09:23:36.1405751Z real 0m19.462s 2025-12-04T09:23:36.1406037Z user 0m27.847s 2025-12-04T09:23:36.1406268Z sys 0m7.169s 2025-12-04T09:23:36.1406617Z + export -n TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE 2025-12-04T09:23:36.1407133Z + test_without_numpy 2025-12-04T09:23:36.1408855Z ++ dirname .ci/pytorch/test.sh 2025-12-04T09:23:36.1421842Z + pushd .ci/pytorch 2025-12-04T09:23:36.1422195Z ~/workspace/.ci/pytorch ~/workspace 2025-12-04T09:23:36.1423130Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');from unittest import TestCase;import torch;x=torch.randn(3,3);TestCase().assertRaises(RuntimeError, lambda: x.numpy())' 2025-12-04T09:23:36.9553908Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:283: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-12-04T09:23:36.9555518Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-12-04T09:23:37.7656101Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch;print(torch.tensor([torch.tensor(0.), torch.tensor(1.)]))' 2025-12-04T09:23:38.5507985Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:283: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-12-04T09:23:38.5510935Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-12-04T09:23:39.0171286Z tensor([0., 1.]) 2025-12-04T09:23:39.3235527Z + [[ nogpu_AVX512 == *dynamo_wrapped* ]] 2025-12-04T09:23:39.3236165Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch; import torch.onnx' 2025-12-04T09:23:40.1149639Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:283: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-12-04T09:23:40.1152644Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-12-04T09:23:40.9082703Z + popd 2025-12-04T09:23:40.9083008Z ~/workspace 2025-12-04T09:23:40.9083252Z + install_torchvision 2025-12-04T09:23:40.9083527Z + local orig_preload 2025-12-04T09:23:40.9083782Z + local commit 2025-12-04T09:23:40.9086945Z ++ get_pinned_commit vision 2025-12-04T09:23:40.9087268Z ++ cat .github/ci_commit_pins/vision.txt 2025-12-04T09:23:40.9118241Z + commit=617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:40.9118678Z + orig_preload= 2025-12-04T09:23:40.9118942Z + '[' -n '' ']' 2025-12-04T09:23:40.9119246Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *cuda* ]] 2025-12-04T09:23:40.9119620Z + export FORCE_CUDA=1 2025-12-04T09:23:40.9119878Z + FORCE_CUDA=1 2025-12-04T09:23:40.9120099Z + export WITH_CUDA=1 2025-12-04T09:23:40.9120486Z + WITH_CUDA=1 2025-12-04T09:23:40.9121123Z + pip_build_and_install git+https://github.com/pytorch/vision.git@617079d944b0e72632311c30ae2bbdf1168b901e dist/vision 2025-12-04T09:23:40.9122099Z + local build_target=git+https://github.com/pytorch/vision.git@617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:40.9122727Z + local wheel_dir=dist/vision 2025-12-04T09:23:40.9123020Z + local found_whl=0 2025-12-04T09:23:40.9123288Z + for file in "${wheel_dir}"/*.whl 2025-12-04T09:23:40.9123595Z + [[ -f dist/vision/*.whl ]] 2025-12-04T09:23:40.9123876Z + '[' 0 == 0 ']' 2025-12-04T09:23:40.9124696Z + python3 -m pip wheel --no-build-isolation --no-deps -w dist/vision git+https://github.com/pytorch/vision.git@617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:41.2403284Z Collecting git+https://github.com/pytorch/vision.git@617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:41.2408163Z Cloning https://github.com/pytorch/vision.git (to revision 617079d944b0e72632311c30ae2bbdf1168b901e) to /tmp/pip-req-build-bwa6bpwn 2025-12-04T09:23:41.2552833Z Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-bwa6bpwn 2025-12-04T09:23:42.9928527Z Running command git rev-parse -q --verify 'sha^617079d944b0e72632311c30ae2bbdf1168b901e' 2025-12-04T09:23:42.9953090Z Running command git fetch -q https://github.com/pytorch/vision.git 617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:43.1306700Z Resolved https://github.com/pytorch/vision.git to commit 617079d944b0e72632311c30ae2bbdf1168b901e 2025-12-04T09:23:45.0730158Z Preparing metadata (pyproject.toml) ... [?25l- \ done 2025-12-04T09:23:45.0766441Z [?25hBuilding wheels for collected packages: torchvision 2025-12-04T09:25:10.2801486Z Building wheel for torchvision (pyproject.toml) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / done 2025-12-04T09:25:10.2869866Z [?25h Created wheel for torchvision: filename=torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl size=1797792 sha256=c0b916bbc48a9ef938c6d89045cbd21044e19a8cf644aefd39f207db0f9bfc14 2025-12-04T09:25:10.2872575Z Stored in directory: /var/lib/jenkins/.cache/pip/wheels/12/b2/29/1f82685c5b5173629e1f36a9b93989ce92ce563e5fb91d27ac 2025-12-04T09:25:10.2915067Z Successfully built torchvision 2025-12-04T09:25:10.4038088Z + for file in "${wheel_dir}"/*.whl 2025-12-04T09:25:10.4038710Z + pip_install_whl dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl 2025-12-04T09:25:10.4039464Z + args=('dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl') 2025-12-04T09:25:10.4039960Z + local args 2025-12-04T09:25:10.4040391Z + [[ dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-12-04T09:25:10.4040915Z + for path in "${args[@]}" 2025-12-04T09:25:10.4041431Z + echo 'Installing dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl' 2025-12-04T09:25:10.4042193Z Installing dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl 2025-12-04T09:25:10.4043338Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl 2025-12-04T09:25:10.7699797Z Processing ./dist/vision/torchvision-0.25.0a0+617079d-cp310-cp310-linux_x86_64.whl 2025-12-04T09:25:10.7836241Z Installing collected packages: torchvision 2025-12-04T09:25:11.2957964Z Successfully installed torchvision-0.25.0a0+617079d 2025-12-04T09:25:11.3662029Z + '[' -n '' ']' 2025-12-04T09:25:11.3662334Z + test_python_shard 1 2025-12-04T09:25:11.3662977Z + [[ -z 3 ]] 2025-12-04T09:25:11.3663806Z + python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests --shard 1 3 --verbose --upload-artifacts-while-running 2025-12-04T09:25:13.2115252Z W1204 09:25:13.210000 1827 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:25:16.8820305Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T09:25:16.8925818Z Found test times from artifacts 2025-12-04T09:25:16.9335707Z Found test times from artifacts 2025-12-04T09:25:16.9349404Z Running all tests 2025-12-04T09:25:16.9806469Z Running parallel tests on 3 processes 2025-12-04T09:25:16.9819160Z Name: tests to run (est. time: 33.28min) 2025-12-04T09:25:16.9819558Z Serial tests (47): 2025-12-04T09:25:16.9819842Z inductor/test_flex_attention 1/1 2025-12-04T09:25:16.9820234Z test_privateuseone_python_backend 1/1 2025-12-04T09:25:16.9820574Z test_ci_sanity_check_fail 1/1 2025-12-04T09:25:16.9820882Z test_overrides 1/1 2025-12-04T09:25:16.9821157Z inductor/test_max_autotune 1/1 2025-12-04T09:25:16.9821452Z doctests 1/1 2025-12-04T09:25:16.9821718Z inductor/test_cutlass_backend 1/1 2025-12-04T09:25:16.9822063Z inductor/test_benchmark_fusion 1/1 2025-12-04T09:25:16.9822417Z inductor/test_distributed_patterns 1/1 2025-12-04T09:25:16.9822778Z dynamo/test_fake_distributed 1/1 2025-12-04T09:25:16.9823102Z test_sort_and_select 1/1 2025-12-04T09:25:16.9823383Z test_cpp_api_parity 1/1 2025-12-04T09:25:16.9823679Z test_extension_utils 1/1 2025-12-04T09:25:16.9823970Z test_show_pickle 1/1 2025-12-04T09:25:16.9824223Z test_torch 1/1 2025-12-04T09:25:16.9824475Z test_tensorexpr 1/1 2025-12-04T09:25:16.9824738Z test_utils 1/1 2025-12-04T09:25:16.9824988Z test_namedtuple_return_api 1/1 2025-12-04T09:25:16.9825303Z test_fake_tensor 1/1 2025-12-04T09:25:16.9825598Z test_multiprocessing 1/1 2025-12-04T09:25:16.9825880Z test_fx 1/1 2025-12-04T09:25:16.9826116Z test_autograd_fallback 1/1 2025-12-04T09:25:16.9826407Z test_autocast 1/1 2025-12-04T09:25:16.9826672Z test_python_dispatch 1/1 2025-12-04T09:25:16.9826948Z test_jit_disabled 1/1 2025-12-04T09:25:16.9827243Z test_cpp_extensions_mtia_backend 1/1 2025-12-04T09:25:16.9827614Z functorch/test_memory_efficient_fusion 1/1 2025-12-04T09:25:16.9827966Z test_tensor_creation_ops 1/1 2025-12-04T09:25:16.9828299Z test_cpp_extensions_stream_and_event 1/1 2025-12-04T09:25:16.9828635Z test_dispatch 1/1 2025-12-04T09:25:16.9828888Z nn/test_convolution 1/1 2025-12-04T09:25:16.9829181Z test_cpp_extensions_jit 1/1 2025-12-04T09:25:16.9829473Z test_nn 1/1 2025-12-04T09:25:16.9829719Z test_multiprocessing_spawn 1/1 2025-12-04T09:25:16.9830036Z nn/test_pooling 1/1 2025-12-04T09:25:16.9830301Z test_cuda_trace 1/1 2025-12-04T09:25:16.9830548Z test_native_mha 1/1 2025-12-04T09:25:16.9830824Z test_cuda_nvml_based_avail 1/1 2025-12-04T09:25:16.9831147Z test_mobile_optimizer 1/1 2025-12-04T09:25:16.9831451Z test_cuda_primary_ctx 1/1 2025-12-04T09:25:16.9831729Z test_reductions 1/1 2025-12-04T09:25:16.9831999Z test_spectral_ops 1/1 2025-12-04T09:25:16.9832309Z distributions/test_distributions 1/1 2025-12-04T09:25:16.9832650Z test_autoload_disable 1/1 2025-12-04T09:25:16.9832946Z test_autoload_enable 1/1 2025-12-04T09:25:16.9833255Z test_cpp_extensions_aot_ninja 1/1 2025-12-04T09:25:16.9833583Z test_cpp_extensions_aot_no_ninja 1/1 2025-12-04T09:25:16.9834079Z Parallel tests (123): 2025-12-04T09:25:16.9834363Z inductor/test_aot_inductor 1/1 2025-12-04T09:25:16.9834690Z inductor/test_torchinductor_opinfo 1/1 2025-12-04T09:25:16.9835048Z inductor/test_cudagraph_trees 1/1 2025-12-04T09:25:16.9835394Z inductor/test_compile_subprocess 1/1 2025-12-04T09:25:16.9835723Z inductor/test_native_matmul 1/1 2025-12-04T09:25:16.9836285Z inductor/test_op_dtype_prop 1/1 2025-12-04T09:25:16.9836622Z inductor/test_unbacked_symints 1/1 2025-12-04T09:25:16.9836956Z inductor/test_padding 1/1 2025-12-04T09:25:16.9837243Z test_varlen_attention 1/1 2025-12-04T09:25:16.9837556Z test_ops_fwd_gradients 1/1 2025-12-04T09:25:16.9837843Z test_linalg 1/1 2025-12-04T09:25:16.9838208Z inductor/test_select_algorithm 1/1 2025-12-04T09:25:16.9838548Z dynamo/test_dynamic_shapes 2/2 2025-12-04T09:25:16.9838885Z inductor/test_compiled_autograd 2/2 2025-12-04T09:25:16.9839219Z inductor/test_custom_lowering 1/1 2025-12-04T09:25:16.9839547Z inductor/test_perf 1/1 2025-12-04T09:25:16.9839844Z inductor/test_fused_attention 1/1 2025-12-04T09:25:16.9840161Z inductor/test_binary_folding 1/1 2025-12-04T09:25:16.9840507Z inductor/test_mkldnn_pattern_matcher 1/2 2025-12-04T09:25:16.9840874Z inductor/test_cpu_select_algorithm 1/1 2025-12-04T09:25:16.9841219Z inductor/test_aot_inductor_arrayref 2/2 2025-12-04T09:25:16.9841619Z inductor/test_torchinductor_strided_blocks 1/1 2025-12-04T09:25:16.9841989Z test_custom_ops 1/1 2025-12-04T09:25:16.9842556Z inductor/test_multi_kernel 1/1 2025-12-04T09:25:16.9842872Z inductor/test_analysis 1/1 2025-12-04T09:25:16.9843204Z inductor/test_triton_extension_backend 1/1 2025-12-04T09:25:16.9843570Z test_sparse_semi_structured 1/1 2025-12-04T09:25:16.9843948Z inductor/test_op_completeness 1/1 2025-12-04T09:25:16.9844357Z inductor/test_triton_heuristics 1/1 2025-12-04T09:25:16.9844708Z inductor/test_cutedsl_grouped_mm 1/1 2025-12-04T09:25:16.9845066Z inductor/test_cpp_wrapper_hipify 1/1 2025-12-04T09:25:16.9845446Z inductor/test_template_heuristics_registry 1/1 2025-12-04T09:25:16.9845836Z inductor/test_async_compile 1/1 2025-12-04T09:25:16.9846173Z inductor/test_gpu_cpp_wrapper 1/1 2025-12-04T09:25:16.9846544Z export/test_export_training_ir_to_run_decomp 1/1 2025-12-04T09:25:16.9846939Z dynamo/test_deque_reconstruct 1/1 2025-12-04T09:25:16.9847290Z inductor/test_indexing 1/1 2025-12-04T09:25:16.9847593Z inductor/test_inductor_annotations 1/1 2025-12-04T09:25:16.9847941Z inductor/test_compile_worker 1/1 2025-12-04T09:25:16.9848259Z dynamo/test_einops 1/1 2025-12-04T09:25:16.9848545Z inductor/test_external_callables 1/1 2025-12-04T09:25:16.9848869Z test_testing 1/1 2025-12-04T09:25:16.9849141Z dynamo/test_fx_passes_pre_grad 1/1 2025-12-04T09:25:16.9849462Z export/test_strict_export_v2 1/1 2025-12-04T09:25:16.9849788Z inductor/test_flex_flash 1/1 2025-12-04T09:25:16.9850105Z inductor/test_selective_lowering 1/1 2025-12-04T09:25:16.9850447Z inductor/test_inductor_scheduler 1/1 2025-12-04T09:25:16.9850795Z inductor/test_inplace_padding 1/1 2025-12-04T09:25:16.9851125Z inductor/test_control_deps 1/1 2025-12-04T09:25:16.9851444Z inductor/test_inplacing_pass 1/1 2025-12-04T09:25:16.9851754Z inductor/test_profiler 1/1 2025-12-04T09:25:16.9852070Z inductor/test_aot_inductor_utils 1/1 2025-12-04T09:25:16.9852406Z dynamo/test_cudagraphs 1/1 2025-12-04T09:25:16.9852716Z inductor/test_custom_partitioner_fn 1/1 2025-12-04T09:25:16.9853108Z dynamo/test_cudagraphs_expandable_segments 1/1 2025-12-04T09:25:16.9853484Z dynamo/test_minifier 1/1 2025-12-04T09:25:16.9853768Z export/test_sparse 2/2 2025-12-04T09:25:16.9854049Z test_foreach 1/1 2025-12-04T09:25:16.9854301Z xpu/test_gemm 1/1 2025-12-04T09:25:16.9854544Z xpu/test_conv 1/1 2025-12-04T09:25:16.9854806Z test_numpy_interop 1/1 2025-12-04T09:25:16.9855081Z test_modules 1/1 2025-12-04T09:25:16.9855331Z nn/test_packed_sequence 1/1 2025-12-04T09:25:16.9855625Z test_numa_binding 1/1 2025-12-04T09:25:16.9855897Z test_pruning_op 1/1 2025-12-04T09:25:16.9856148Z test_jit_fuser_te 1/1 2025-12-04T09:25:16.9856411Z test_logging 1/1 2025-12-04T09:25:16.9856666Z nn/test_lazy_modules 1/1 2025-12-04T09:25:16.9856948Z nn/test_pruning 1/1 2025-12-04T09:25:16.9857332Z test_monitor 1/1 2025-12-04T09:25:16.9857600Z test_bundled_inputs 1/1 2025-12-04T09:25:16.9857924Z torch_np/numpy_tests/core/test_numeric 1/1 2025-12-04T09:25:16.9858306Z torch_np/numpy_tests/core/test_multiarray 1/1 2025-12-04T09:25:16.9858669Z test_itt 1/1 2025-12-04T09:25:16.9858961Z torch_np/numpy_tests/lib/test_function_base 1/1 2025-12-04T09:25:16.9859397Z test_sympy_utils 1/1 2025-12-04T09:25:16.9859673Z test_subclass 1/1 2025-12-04T09:25:16.9859935Z test_import_stats 1/1 2025-12-04T09:25:16.9860225Z functorch/test_vmap_registrations 1/1 2025-12-04T09:25:16.9860586Z nn/test_parametrization 1/1 2025-12-04T09:25:16.9860886Z test_mkldnn_fusion 1/1 2025-12-04T09:25:16.9861152Z lazy/test_ts_opinfo 1/1 2025-12-04T09:25:16.9861435Z test_dynamic_shapes 1/1 2025-12-04T09:25:16.9861742Z complex_tensor/test_complex_tensor 1/1 2025-12-04T09:25:16.9862232Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 2025-12-04T09:25:16.9862753Z torch_np/numpy_tests/lib/test_histograms 1/1 2025-12-04T09:25:16.9863134Z torch_np/test_indexing 1/1 2025-12-04T09:25:16.9863428Z test_schema_check 1/1 2025-12-04T09:25:16.9863691Z test_tensorboard 1/1 2025-12-04T09:25:16.9864000Z torch_np/numpy_tests/core/test_indexing 1/1 2025-12-04T09:25:16.9864347Z test_futures 1/1 2025-12-04T09:25:16.9864591Z nn/test_dropout 1/1 2025-12-04T09:25:16.9864871Z functorch/dim/test_split 1/1 2025-12-04T09:25:16.9865211Z torch_np/numpy_tests/lib/test_type_check 1/1 2025-12-04T09:25:16.9865540Z test_jit 1/1 2025-12-04T09:25:16.9865779Z test_datapipe 1/1 2025-12-04T09:25:16.9866047Z test_numba_integration 1/1 2025-12-04T09:25:16.9866340Z test_functional_optim 1/1 2025-12-04T09:25:16.9866635Z test_maskedtensor 1/1 2025-12-04T09:25:16.9866943Z benchmark_utils/test_benchmark_utils 1/1 2025-12-04T09:25:16.9867328Z torch_np/numpy_tests/core/test_scalarmath 1/1 2025-12-04T09:25:16.9867683Z test_scaled_matmul_cuda 1/1 2025-12-04T09:25:16.9868026Z torch_np/numpy_tests/core/test_shape_base 1/1 2025-12-04T09:25:16.9868379Z test_vulkan 1/1 2025-12-04T09:25:16.9868620Z lazy/test_generator 1/1 2025-12-04T09:25:16.9868942Z torch_np/numpy_tests/linalg/test_linalg 1/1 2025-12-04T09:25:16.9869328Z torch_np/numpy_tests/core/test_dtype 1/1 2025-12-04T09:25:16.9869668Z lazy/test_debug_util 1/1 2025-12-04T09:25:16.9869970Z nn/test_load_state_dict 1/1 2025-12-04T09:25:16.9870270Z nn/test_module_hooks 1/1 2025-12-04T09:25:16.9870585Z torch_np/numpy_tests/lib/test_twodim_base 1/1 2025-12-04T09:25:16.9870965Z profiler/test_memory_profiler 1/1 2025-12-04T09:25:16.9871292Z test_jit_llga_fuser 1/1 2025-12-04T09:25:16.9871569Z test_serialization 1/1 2025-12-04T09:25:16.9871850Z test_indexing 1/1 2025-12-04T09:25:16.9872153Z torch_np/numpy_tests/fft/test_pocketfft 1/1 2025-12-04T09:25:16.9872547Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 2025-12-04T09:25:16.9872934Z torch_np/numpy_tests/core/test_getlimits 1/1 2025-12-04T09:25:16.9873307Z torch_np/test_ndarray_methods 1/1 2025-12-04T09:25:16.9873629Z test_type_info 1/1 2025-12-04T09:25:16.9873895Z functorch/test_aotdispatch 1/1 2025-12-04T09:25:16.9874214Z test_cuda_multigpu 1/1 2025-12-04T09:25:16.9874495Z test_accelerator 1/1 2025-12-04T09:25:16.9874769Z Name: excluded (est. time: 0.0min) 2025-12-04T09:25:16.9875079Z Serial tests (0): 2025-12-04T09:25:16.9875330Z Parallel tests (0): 2025-12-04T09:25:16.9875779Z Running inductor/test_flex_attention 1/1 ... [2025-12-04 09:25:16.986150][859.671922839] 2025-12-04T09:25:16.9876317Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:25:16.9877695Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_flex_attention.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:25:16.986600] 2025-12-04T09:25:28.6289725Z 2025-12-04T09:25:28.6290740Z inductor/test_flex_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_attention_1.1_197b416127597c7b_.log 2025-12-04T09:25:28.6291680Z Running 0 items in this shard: 2025-12-04T09:25:28.6291881Z 2025-12-04T09:25:28.6292239Z Finished inductor/test_flex_attention 1/1 ... [2025-12-04 09:25:28.628918][871.314687576], took 0.19min 2025-12-04T09:25:28.6301258Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_flex_attention/inductor.test_flex_attention-af820a2477dc6bce.xml 2025-12-04T09:25:28.9054955Z Uploading artifacts took 0.11 seconds 2025-12-04T09:25:28.9060095Z Running test_privateuseone_python_backend 1/1 ... [2025-12-04 09:25:28.905742][871.591511217] 2025-12-04T09:25:28.9061024Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:25:28.9066591Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_privateuseone_python_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:25:28.906240] 2025-12-04T09:25:32.2261844Z 2025-12-04T09:25:32.2262919Z test_privateuseone_python_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_privateuseone_python_backend_1.1_bcd5c354743f2425_.log 2025-12-04T09:25:32.2263923Z Running 0 items in this shard: 2025-12-04T09:25:32.2264122Z 2025-12-04T09:25:32.2264485Z Finished test_privateuseone_python_backend 1/1 ... [2025-12-04 09:25:32.225979][874.911750155], took 0.06min 2025-12-04T09:25:32.2272443Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_privateuseone_python_backend/test_privateuseone_python_backend-6db6140fd0f05c8b.xml 2025-12-04T09:25:32.2563058Z Running test_ci_sanity_check_fail 1/1 ... [2025-12-04 09:25:32.256039][874.941811582] 2025-12-04T09:25:32.2563572Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:25:32.2566657Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_ci_sanity_check_fail.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:25:32.256417] 2025-12-04T09:25:35.5349384Z Finished test_ci_sanity_check_fail 1/1 ... [2025-12-04 09:25:35.534507][878.22026929], took 0.05min 2025-12-04T09:25:35.5361355Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_ci_sanity_check_fail/test_ci_sanity_check_fail-05f200249794d09c.xml 2025-12-04T09:25:35.6829365Z Uploading logs for 57117865590 to S3 2025-12-04T09:25:35.7104313Z Uploading artifacts took 0.14 seconds 2025-12-04T09:25:35.7104964Z test_ci_sanity_check_fail 1/1 failed! 2025-12-04T09:25:35.7110252Z Running test_overrides 1/1 ... [2025-12-04 09:25:35.710799][878.396568692] 2025-12-04T09:25:35.7110987Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:25:35.7116829Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_overrides.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:25:35.711294] 2025-12-04T09:25:38.8978347Z 2025-12-04T09:25:38.8979199Z test_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_overrides_1.1_8e145fe4524137ff_.log 2025-12-04T09:25:38.8979863Z 2025-12-04T09:25:38.8980151Z Finished test_overrides 1/1 ... [2025-12-04 09:25:38.897630][881.583399703], took 0.05min 2025-12-04T09:25:38.8994129Z Running inductor/test_max_autotune 1/1 ... [2025-12-04 09:25:38.899225][881.584997332] 2025-12-04T09:25:38.8994647Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:25:38.8998822Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_max_autotune.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:25:38.899610] 2025-12-04T09:25:46.8532049Z 2025-12-04T09:25:46.8533070Z inductor/test_max_autotune 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_max_autotune_1.1_80ffb8ba15ba523d_.log 2025-12-04T09:25:46.8534197Z 2025-12-04T09:25:46.8534528Z Finished inductor/test_max_autotune 1/1 ... [2025-12-04 09:25:46.852955][889.538726044], took 0.13min 2025-12-04T09:25:46.8547577Z Running doctests 1/1 ... [2025-12-04 09:25:46.854571][889.540343714] 2025-12-04T09:25:47.4065063Z msg = Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=368. 2025-12-04T09:25:47.4066027Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.4066676Z Registers the function implementation as the fallback for the given key. 2025-12-04T09:25:47.4067069Z 2025-12-04T09:25:47.4067295Z This function only works for a library with global namespace ("_"). 2025-12-04T09:25:47.4067647Z 2025-12-04T09:25:47.4067747Z Args: 2025-12-04T09:25:47.4068184Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-12-04T09:25:47.4068742Z to register a fallthrough. 2025-12-04T09:25:47.4069316Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-12-04T09:25:47.4069958Z the dispatch key that the library was created with. 2025-12-04T09:25:47.4070634Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-12-04T09:25:47.4071509Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-12-04T09:25:47.4071977Z 2025-12-04T09:25:47.4072109Z Example:: 2025-12-04T09:25:47.4072252Z 2025-12-04T09:25:47.4072361Z >>> my_lib = Library("_", "IMPL") 2025-12-04T09:25:47.4072733Z >>> def fallback_kernel(op, *args, **kwargs): 2025-12-04T09:25:47.4073123Z >>> # Handle all autocast ops generically 2025-12-04T09:25:47.4073471Z >>> # ... 2025-12-04T09:25:47.4073773Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-12-04T09:25:47.4074129Z 2025-12-04T09:25:47.4074927Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-12-04T09:25:47.4075720Z 2025-12-04T09:25:47.4075853Z my_lib.fallback(fallback_kernel, "Autocast") 2025-12-04T09:25:47.4076192Z ^ 2025-12-04T09:25:47.4209467Z msg = Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=958. 2025-12-04T09:25:47.4210362Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.4211018Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-12-04T09:25:47.4211381Z 2025-12-04T09:25:47.4211564Z Also sometimes known as a "meta kernel", "abstract impl". 2025-12-04T09:25:47.4211882Z 2025-12-04T09:25:47.4212135Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-12-04T09:25:47.4212751Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-12-04T09:25:47.4213357Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-12-04T09:25:47.4213884Z what the properties of the output Tensors are. 2025-12-04T09:25:47.4214147Z 2025-12-04T09:25:47.4214399Z The FakeTensor implementation has the same signature as the operator. 2025-12-04T09:25:47.4215885Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-12-04T09:25:47.4216481Z implementation, assume that all Tensor inputs to the operator are 2025-12-04T09:25:47.4217049Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-12-04T09:25:47.4217589Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-12-04T09:25:47.4218278Z The FakeTensor implementation must consist of only PyTorch operations 2025-12-04T09:25:47.4218853Z (and may not directly access the storage or data of any input or 2025-12-04T09:25:47.4219285Z intermediate Tensors). 2025-12-04T09:25:47.4219466Z 2025-12-04T09:25:47.4219622Z This API may be used as a decorator (see examples). 2025-12-04T09:25:47.4219910Z 2025-12-04T09:25:47.4220053Z For a detailed guide on custom ops, please see 2025-12-04T09:25:47.4220581Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-12-04T09:25:47.4220945Z 2025-12-04T09:25:47.4221029Z Args: 2025-12-04T09:25:47.4221392Z op_name: Operator name (along with the overload) or OpOverload object. 2025-12-04T09:25:47.4221871Z func: Fake tensor implementation. 2025-12-04T09:25:47.4222320Z lib (Optional[Library]): Library to register the fake tensor to. 2025-12-04T09:25:47.4222830Z allow_override: Flag controlling if we want to override an 2025-12-04T09:25:47.4223336Z existing registered fake impl. This is by default off, 2025-12-04T09:25:47.4223831Z and will error you're trying to register a fake impl to 2025-12-04T09:25:47.4224309Z an operator that already has a fake impl. This also only 2025-12-04T09:25:47.4224785Z applies if the custom operator was not created via 2025-12-04T09:25:47.4225273Z torch.library.custom_op, as overriding and existing fake 2025-12-04T09:25:47.4225718Z impl is already allowed. 2025-12-04T09:25:47.4225951Z 2025-12-04T09:25:47.4226040Z Examples: 2025-12-04T09:25:47.4226274Z >>> import torch 2025-12-04T09:25:47.4226552Z >>> import numpy as np 2025-12-04T09:25:47.4226839Z >>> from torch import Tensor 2025-12-04T09:25:47.4227138Z >>> 2025-12-04T09:25:47.4227457Z >>> # Example 1: an operator without data-dependent output shape 2025-12-04T09:25:47.4228003Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-12-04T09:25:47.4228581Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-12-04T09:25:47.4229127Z >>> raise NotImplementedError("Implementation goes here") 2025-12-04T09:25:47.4229522Z >>> 2025-12-04T09:25:47.4229809Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-12-04T09:25:47.4230211Z >>> def _(x, weight, bias): 2025-12-04T09:25:47.4230521Z >>> assert x.dim() == 2 2025-12-04T09:25:47.4230826Z >>> assert weight.dim() == 2 2025-12-04T09:25:47.4231164Z >>> assert bias.dim() == 1 2025-12-04T09:25:47.4231510Z >>> assert x.shape[1] == weight.shape[1] 2025-12-04T09:25:47.4231879Z >>> assert weight.shape[0] == bias.shape[0] 2025-12-04T09:25:47.4232255Z >>> assert x.device == weight.device 2025-12-04T09:25:47.4232580Z >>> 2025-12-04T09:25:47.4232822Z >>> return (x @ weight.t()) + bias 2025-12-04T09:25:47.4233132Z >>> 2025-12-04T09:25:47.4233434Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-12-04T09:25:47.4233848Z >>> x = torch.randn(2, 3) 2025-12-04T09:25:47.4234158Z >>> w = torch.randn(3, 3) 2025-12-04T09:25:47.4234476Z >>> b = torch.randn(3) 2025-12-04T09:25:47.4234821Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-12-04T09:25:47.4235155Z >>> 2025-12-04T09:25:47.4235383Z >>> assert y.shape == (2, 3) 2025-12-04T09:25:47.4235676Z >>> 2025-12-04T09:25:47.4236053Z >>> # Example 2: an operator with data-dependent output shape 2025-12-04T09:25:47.4236596Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-12-04T09:25:47.4237082Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-12-04T09:25:47.4237452Z >>> x_np = x.numpy(force=True) 2025-12-04T09:25:47.4237806Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-12-04T09:25:47.4238275Z >>> return torch.tensor(res, device=x.device) 2025-12-04T09:25:47.4238618Z >>> 2025-12-04T09:25:47.4238938Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-12-04T09:25:47.4239337Z >>> def _(x): 2025-12-04T09:25:47.4239641Z >>> # Number of nonzero-elements is data-dependent. 2025-12-04T09:25:47.4240078Z >>> # Since we cannot peek at the data in an fake impl, 2025-12-04T09:25:47.4240530Z >>> # we use the ctx object to construct a new symint that 2025-12-04T09:25:47.4240940Z >>> # represents the data-dependent size. 2025-12-04T09:25:47.4241322Z >>> ctx = torch.library.get_ctx() 2025-12-04T09:25:47.4241684Z >>> nnz = ctx.new_dynamic_size() 2025-12-04T09:25:47.4242027Z >>> shape = [nnz, x.dim()] 2025-12-04T09:25:47.4242838Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-12-04T09:25:47.4243225Z >>> return result 2025-12-04T09:25:47.4243508Z >>> 2025-12-04T09:25:47.4243811Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-12-04T09:25:47.4244312Z >>> 2025-12-04T09:25:47.4244556Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-12-04T09:25:47.4245036Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-12-04T09:25:47.4245543Z >>> trace.print_readable() 2025-12-04T09:25:47.4245842Z >>> 2025-12-04T09:25:47.4246184Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-12-04T09:25:47.4246555Z 2025-12-04T09:25:47.4246640Z 2025-12-04T09:25:47.4247337Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-12-04T09:25:47.4248017Z 2025-12-04T09:25:47.4248112Z _._ = None 2025-12-04T09:25:47.4248304Z ^ 2025-12-04T09:25:47.4353368Z msg = Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=1530. 2025-12-04T09:25:47.4354282Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.4354887Z Returns the computed kernel for a given operator and dispatch key. 2025-12-04T09:25:47.4355229Z 2025-12-04T09:25:47.4355462Z This function retrieves the kernel that would be executed for a given 2025-12-04T09:25:47.4356066Z operator and dispatch key combination. The returned SafeKernelFunction 2025-12-04T09:25:47.4356643Z can be used to call the kernel in a boxed fashion. The intended use 2025-12-04T09:25:47.4357197Z case for this function is to retrieve the original kernel for a given 2025-12-04T09:25:47.4357768Z dispatch key and then register another kernel to the same dispatch key 2025-12-04T09:25:47.4358301Z that calls into the original kernel for certain cases. 2025-12-04T09:25:47.4358586Z 2025-12-04T09:25:47.4358682Z Args: 2025-12-04T09:25:47.4359002Z op: Operator name (along with the overload) or OpOverload object 2025-12-04T09:25:47.4359586Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-12-04T09:25:47.4360219Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-12-04T09:25:47.4360822Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-12-04T09:25:47.4361141Z 2025-12-04T09:25:47.4361227Z Returns: 2025-12-04T09:25:47.4361610Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-12-04T09:25:47.4362084Z call the kernel. 2025-12-04T09:25:47.4362263Z 2025-12-04T09:25:47.4362506Z Raises: 2025-12-04T09:25:47.4362770Z RuntimeError: If the operator does not exist. 2025-12-04T09:25:47.4363048Z 2025-12-04T09:25:47.4363135Z Example: 2025-12-04T09:25:47.4363389Z >>> # Get the CPU kernel for torch.add 2025-12-04T09:25:47.4363818Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-12-04T09:25:47.4364384Z >>> 2025-12-04T09:25:47.4364640Z >>> # You can also use DispatchKey enum 2025-12-04T09:25:47.4365145Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-12-04T09:25:47.4365638Z >>> 2025-12-04T09:25:47.4365881Z >>> # Or use an OpOverload directly 2025-12-04T09:25:47.4366352Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-12-04T09:25:47.4366793Z >>> 2025-12-04T09:25:47.4367141Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-12-04T09:25:47.4367623Z >>> # Get the original kernel for torch.sin 2025-12-04T09:25:47.4368085Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-12-04T09:25:47.4368525Z >>> 2025-12-04T09:25:47.4368885Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-12-04T09:25:47.4369394Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-12-04T09:25:47.4369744Z >>> if (x < 0).any(): 2025-12-04T09:25:47.4370127Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-12-04T09:25:47.4370541Z >>> else: 2025-12-04T09:25:47.4370798Z >>> return torch.zeros_like(x) 2025-12-04T09:25:47.4371118Z >>> 2025-12-04T09:25:47.4371383Z >>> lib = torch.library.Library("aten", "IMPL") 2025-12-04T09:25:47.4371902Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-12-04T09:25:47.4372502Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-12-04T09:25:47.4373022Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-12-04T09:25:47.4373434Z >>> 2025-12-04T09:25:47.4373657Z >>> # Test the conditional behavior 2025-12-04T09:25:47.4374013Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-12-04T09:25:47.4374377Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-12-04T09:25:47.4374712Z >>> torch.sin(x_positive) 2025-12-04T09:25:47.4375014Z tensor([0., 0.]) 2025-12-04T09:25:47.4375284Z >>> torch.sin(x_mixed) 2025-12-04T09:25:47.4375558Z tensor([-0.8415, 0.9093]) 2025-12-04T09:25:47.4375835Z 2025-12-04T09:25:47.4376465Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-12-04T09:25:47.4377093Z 2025-12-04T09:25:47.4377289Z which needs to be the first argument to ``kernel.call_boxed`` 2025-12-04T09:25:47.4377678Z ^ 2025-12-04T09:25:47.7445266Z msg = Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py line=70. 2025-12-04T09:25:47.7446251Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.7446893Z Check if the current accelerator is available at runtime: it was build, all the 2025-12-04T09:25:47.7447532Z required drivers are available and at least one device is visible. 2025-12-04T09:25:47.7448039Z See :ref:`accelerator` for details. 2025-12-04T09:25:47.7448306Z 2025-12-04T09:25:47.7448407Z Returns: 2025-12-04T09:25:47.7448820Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-12-04T09:25:47.7449249Z 2025-12-04T09:25:47.7449538Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-12-04T09:25:47.7450197Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-12-04T09:25:47.7451068Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-12-04T09:25:47.7451616Z :ref:`multiprocessing-poison-fork-note`. 2025-12-04T09:25:47.7451890Z 2025-12-04T09:25:47.7451983Z Example:: 2025-12-04T09:25:47.7452114Z 2025-12-04T09:25:47.7452407Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:25:47.7452995Z 2025-12-04T09:25:47.7453712Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-12-04T09:25:47.7454447Z 2025-12-04T09:25:47.7454717Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:25:47.7455223Z ^ 2025-12-04T09:25:47.7478972Z msg = Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py line=239. 2025-12-04T09:25:47.7479952Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.7480561Z Wait for all kernels in all streams on the given device to complete. 2025-12-04T09:25:47.7480896Z 2025-12-04T09:25:47.7480997Z Args: 2025-12-04T09:25:47.7481452Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-12-04T09:25:47.7482162Z the current :ref:`accelerator` device type. If not given, 2025-12-04T09:25:47.7482738Z use :func:`torch.accelerator.current_device_index` by default. 2025-12-04T09:25:47.7483063Z 2025-12-04T09:25:47.7483404Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-12-04T09:25:47.7483856Z 2025-12-04T09:25:47.7483946Z Example:: 2025-12-04T09:25:47.7484093Z 2025-12-04T09:25:47.7484287Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-12-04T09:25:47.7484838Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:25:47.7485396Z >>> start_event = torch.Event(enable_timing=True) 2025-12-04T09:25:47.7485791Z >>> end_event = torch.Event(enable_timing=True) 2025-12-04T09:25:47.7486162Z >>> start_event.record() 2025-12-04T09:25:47.7486613Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-12-04T09:25:47.7487094Z >>> sum = torch.sum(tensor) 2025-12-04T09:25:47.7487412Z >>> end_event.record() 2025-12-04T09:25:47.7487732Z >>> torch.accelerator.synchronize() 2025-12-04T09:25:47.7488139Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-12-04T09:25:47.7488523Z 2025-12-04T09:25:47.7489238Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-12-04T09:25:47.7489949Z 2025-12-04T09:25:47.7490236Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:25:47.7490725Z ^ 2025-12-04T09:25:47.9076301Z msg = Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py line=448. 2025-12-04T09:25:47.9077219Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:47.9077742Z Retrieves the CUDA runtime API module. 2025-12-04T09:25:47.9077969Z 2025-12-04T09:25:47.9077973Z 2025-12-04T09:25:47.9078248Z This function initializes the CUDA runtime environment if it is not already 2025-12-04T09:25:47.9078871Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-12-04T09:25:47.9079476Z runtime API module provides access to various CUDA runtime functions. 2025-12-04T09:25:47.9079835Z 2025-12-04T09:25:47.9079930Z Args: 2025-12-04T09:25:47.9080128Z ``None`` 2025-12-04T09:25:47.9080278Z 2025-12-04T09:25:47.9080360Z Returns: 2025-12-04T09:25:47.9080891Z module: The CUDA runtime API module (_cudart). 2025-12-04T09:25:47.9081159Z 2025-12-04T09:25:47.9081256Z Raises: 2025-12-04T09:25:47.9081610Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-12-04T09:25:47.9082362Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-12-04T09:25:47.9082976Z 2025-12-04T09:25:47.9083123Z Example of CUDA operations with profiling: 2025-12-04T09:25:47.9083466Z >>> import torch 2025-12-04T09:25:47.9083778Z >>> from torch.cuda import cudart, check_error 2025-12-04T09:25:47.9084191Z >>> import os 2025-12-04T09:25:47.9084429Z >>> 2025-12-04T09:25:47.9084675Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-12-04T09:25:47.9084992Z >>> 2025-12-04T09:25:47.9085256Z >>> def perform_cuda_operations_with_streams(): 2025-12-04T09:25:47.9085624Z >>> stream = torch.cuda.Stream() 2025-12-04T09:25:47.9085989Z >>> with torch.cuda.stream(stream): 2025-12-04T09:25:47.9086370Z >>> x = torch.randn(100, 100, device='cuda') 2025-12-04T09:25:47.9086747Z >>> y = torch.randn(100, 100, device='cuda') 2025-12-04T09:25:47.9087107Z >>> z = torch.mul(x, y) 2025-12-04T09:25:47.9087418Z >>> return z 2025-12-04T09:25:47.9087662Z >>> 2025-12-04T09:25:47.9087895Z >>> torch.cuda.synchronize() 2025-12-04T09:25:47.9088249Z >>> print("====== Start nsys profiling ======") 2025-12-04T09:25:47.9088636Z >>> check_error(cudart().cudaProfilerStart()) 2025-12-04T09:25:47.9089042Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-12-04T09:25:47.9089462Z >>> result = perform_cuda_operations_with_streams() 2025-12-04T09:25:47.9089871Z >>> print("CUDA operations completed.") 2025-12-04T09:25:47.9090279Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-12-04T09:25:47.9090706Z >>> print("====== End nsys profiling ======") 2025-12-04T09:25:47.9090954Z 2025-12-04T09:25:47.9091172Z To run this example and save the profiling information, execute: 2025-12-04T09:25:47.9091879Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-12-04T09:25:47.9092392Z 2025-12-04T09:25:47.9092648Z This command profiles the CUDA operations in the provided script and saves 2025-12-04T09:25:47.9093243Z the profiling information to a file named `trace_name.prof`. 2025-12-04T09:25:47.9093833Z The `--profile-from-start off` option ensures that profiling starts only 2025-12-04T09:25:47.9094345Z after the `cudaProfilerStart` call in the script. 2025-12-04T09:25:47.9094852Z The `--csv` and `--print-summary` options format the profiling output as a 2025-12-04T09:25:47.9095353Z CSV file and print a summary, respectively. 2025-12-04T09:25:47.9095870Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-12-04T09:25:47.9096408Z overwrite of the output file if it already exists. 2025-12-04T09:25:47.9096771Z 2025-12-04T09:25:47.9097586Z 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)) 2025-12-04T09:25:47.9098408Z 2025-12-04T09:25:47.9098779Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-12-04T09:25:47.9099361Z ^ 2025-12-04T09:25:49.3692390Z msg = Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/apis.py line=39. 2025-12-04T09:25:49.3693489Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:49.3693993Z 2025-12-04T09:25:49.3694388Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-12-04T09:25:49.3695425Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-12-04T09:25:49.3696290Z pushes the map into PyTorch operations called by ``func``, effectively 2025-12-04T09:25:49.3696767Z vectorizing those operations. 2025-12-04T09:25:49.3696968Z 2025-12-04T09:25:49.3697190Z vmap is useful for handling batch dimensions: one can write a function 2025-12-04T09:25:49.3697782Z ``func`` that runs on examples and then lift it to a function that can 2025-12-04T09:25:49.3698448Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-12-04T09:25:49.3698974Z compute batched gradients when composed with autograd. 2025-12-04T09:25:49.3699267Z 2025-12-04T09:25:49.3699405Z .. note:: 2025-12-04T09:25:49.3699713Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-12-04T09:25:49.3700168Z convenience. Use whichever one you'd like. 2025-12-04T09:25:49.3700432Z 2025-12-04T09:25:49.3700517Z Args: 2025-12-04T09:25:49.3700860Z func (function): A Python function that takes one or more arguments. 2025-12-04T09:25:49.3701320Z Must return one or more Tensors. 2025-12-04T09:25:49.3701764Z in_dims (int or nested structure): Specifies which dimension of the 2025-12-04T09:25:49.3702285Z inputs should be mapped over. ``in_dims`` should have a 2025-12-04T09:25:49.3702785Z structure like the inputs. If the ``in_dim`` for a particular 2025-12-04T09:25:49.3703314Z input is None, then that indicates there is no map dimension. 2025-12-04T09:25:49.3703740Z Default: 0. 2025-12-04T09:25:49.3704088Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-12-04T09:25:49.3704624Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-12-04T09:25:49.3705112Z it should have one element per output. Default: 0. 2025-12-04T09:25:49.3705586Z randomness (str): Specifies whether the randomness in this 2025-12-04T09:25:49.3706110Z vmap should be the same or different across batches. If 'different', 2025-12-04T09:25:49.3706672Z the randomness for each batch will be different. If 'same', the 2025-12-04T09:25:49.3707232Z randomness will be the same across batches. If 'error', any calls to 2025-12-04T09:25:49.3707791Z random functions will error. Default: 'error'. WARNING: this flag 2025-12-04T09:25:49.3708349Z only applies to random PyTorch operations and does not apply to 2025-12-04T09:25:49.3708880Z Python's random module or numpy randomness. 2025-12-04T09:25:49.3709384Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-12-04T09:25:49.3709980Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-12-04T09:25:49.3710612Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-12-04T09:25:49.3711285Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-12-04T09:25:49.3711703Z 2025-12-04T09:25:49.3711788Z Returns: 2025-12-04T09:25:49.3712111Z Returns a new "batched" function. It takes the same inputs as 2025-12-04T09:25:49.3712606Z ``func``, except each input has an extra dimension at the index 2025-12-04T09:25:49.3713120Z specified by ``in_dims``. It takes returns the same outputs as 2025-12-04T09:25:49.3713639Z ``func``, except each output has an extra dimension at the index 2025-12-04T09:25:49.3714066Z specified by ``out_dims``. 2025-12-04T09:25:49.3714260Z 2025-12-04T09:25:49.3714347Z .. warning: 2025-12-04T09:25:49.3714690Z :func:`vmap` works best with functional-style code. Please do not 2025-12-04T09:25:49.3726795Z perform any side-effects in ``func``, with the exception of 2025-12-04T09:25:49.3727826Z in-place PyTorch operations. Examples of side-effects include mutating 2025-12-04T09:25:49.3728727Z Python data structures and assigning values to variables not captured 2025-12-04T09:25:49.3729193Z in ``func``. 2025-12-04T09:25:49.3729336Z 2025-12-04T09:25:49.3729584Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-12-04T09:25:49.3730325Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-12-04T09:25:49.3730917Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-12-04T09:25:49.3731270Z 2025-12-04T09:25:49.3731399Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:25:49.3731832Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-12-04T09:25:49.3732383Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-12-04T09:25:49.3732737Z >>> batched_dot(x, y) 2025-12-04T09:25:49.3732911Z 2025-12-04T09:25:49.3733147Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-12-04T09:25:49.3733624Z model authoring experience. 2025-12-04T09:25:49.3733809Z 2025-12-04T09:25:49.3733932Z >>> batch_size, feature_size = 3, 5 2025-12-04T09:25:49.3734329Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-12-04T09:25:49.3734714Z >>> 2025-12-04T09:25:49.3734939Z >>> def model(feature_vec): 2025-12-04T09:25:49.3735260Z >>> # Very simple linear model with activation 2025-12-04T09:25:49.3735645Z >>> return feature_vec.dot(weights).relu() 2025-12-04T09:25:49.3735985Z >>> 2025-12-04T09:25:49.3736262Z >>> examples = torch.randn(batch_size, feature_size) 2025-12-04T09:25:49.3736649Z >>> result = torch.vmap(model)(examples) 2025-12-04T09:25:49.3736900Z 2025-12-04T09:25:49.3737161Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-12-04T09:25:49.3737795Z or impossible to batch. One example is higher-order gradient computation. 2025-12-04T09:25:49.3738388Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-12-04T09:25:49.3738988Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-12-04T09:25:49.3739614Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-12-04T09:25:49.3740249Z we can vectorize the whole computation, computing the Jacobian in a single 2025-12-04T09:25:49.3740723Z call to ``autograd.grad``. 2025-12-04T09:25:49.3740917Z 2025-12-04T09:25:49.3741001Z >>> # Setup 2025-12-04T09:25:49.3741228Z >>> N = 5 2025-12-04T09:25:49.3741443Z >>> f = lambda x: x**2 2025-12-04T09:25:49.3741746Z >>> x = torch.randn(N, requires_grad=True) 2025-12-04T09:25:49.3742079Z >>> y = f(x) 2025-12-04T09:25:49.3742621Z >>> I_N = torch.eye(N) 2025-12-04T09:25:49.3742893Z >>> 2025-12-04T09:25:49.3743117Z >>> # Sequential approach 2025-12-04T09:25:49.3743525Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-12-04T09:25:49.3743997Z >>> for v in I_N.unbind()] 2025-12-04T09:25:49.3744360Z >>> jacobian = torch.stack(jacobian_rows) 2025-12-04T09:25:49.3744688Z >>> 2025-12-04T09:25:49.3744915Z >>> # vectorized gradient computation 2025-12-04T09:25:49.3745249Z >>> def get_vjp(v): 2025-12-04T09:25:49.3745540Z >>> return torch.autograd.grad(y, x, v) 2025-12-04T09:25:49.3745903Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-12-04T09:25:49.3746148Z 2025-12-04T09:25:49.3746422Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-12-04T09:25:49.3746827Z 2025-12-04T09:25:49.3746944Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:25:49.3747266Z >>> batched_dot = torch.vmap( 2025-12-04T09:25:49.3747565Z ... torch.vmap(torch.dot) 2025-12-04T09:25:49.3747892Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-12-04T09:25:49.3748274Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-12-04T09:25:49.3748654Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-12-04T09:25:49.3748912Z 2025-12-04T09:25:49.3749159Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-12-04T09:25:49.3749698Z the dimension that each inputs are batched along as 2025-12-04T09:25:49.3749974Z 2025-12-04T09:25:49.3750090Z >>> torch.dot # [N], [N] -> [] 2025-12-04T09:25:49.3750667Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-12-04T09:25:49.3751166Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-12-04T09:25:49.3751510Z >>> batched_dot( 2025-12-04T09:25:49.3751742Z ... x, y 2025-12-04T09:25:49.3752082Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-12-04T09:25:49.3752404Z 2025-12-04T09:25:49.3752777Z If there are multiple inputs each of which is batched along different dimensions, 2025-12-04T09:25:49.3753377Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-12-04T09:25:49.3753721Z 2025-12-04T09:25:49.3753825Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:25:49.3754286Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-12-04T09:25:49.3754793Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-12-04T09:25:49.3755118Z >>> batched_dot( 2025-12-04T09:25:49.3755366Z ... x, y 2025-12-04T09:25:49.3755713Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-12-04T09:25:49.3756040Z 2025-12-04T09:25:49.3756282Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-12-04T09:25:49.3756778Z matching the shape of the input: 2025-12-04T09:25:49.3756995Z 2025-12-04T09:25:49.3757138Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-12-04T09:25:49.3757529Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-12-04T09:25:49.3757862Z >>> input = {"x": x, "y": y} 2025-12-04T09:25:49.3758243Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-12-04T09:25:49.3758655Z >>> batched_dot(input) 2025-12-04T09:25:49.3758830Z 2025-12-04T09:25:49.3759113Z By default, the output is batched along the first dimension. However, it can be batched 2025-12-04T09:25:49.3759655Z along any dimension by using ``out_dims`` 2025-12-04T09:25:49.3759902Z 2025-12-04T09:25:49.3760000Z >>> f = lambda x: x**2 2025-12-04T09:25:49.3760280Z >>> x = torch.randn(2, 5) 2025-12-04T09:25:49.3760590Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-12-04T09:25:49.3760944Z >>> batched_pow(x) # [5, 2] 2025-12-04T09:25:49.3761140Z 2025-12-04T09:25:49.3761453Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-12-04T09:25:49.3761969Z accept kwargs 2025-12-04T09:25:49.3762119Z 2025-12-04T09:25:49.3762224Z >>> x = torch.randn([2, 5]) 2025-12-04T09:25:49.3762519Z >>> def fn(x, scale=4.): 2025-12-04T09:25:49.3762793Z >>> return x * scale 2025-12-04T09:25:49.3763058Z >>> 2025-12-04T09:25:49.3763287Z >>> batched_pow = torch.vmap(fn) 2025-12-04T09:25:49.3763653Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-12-04T09:25:49.3764218Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-12-04T09:25:49.3764600Z 2025-12-04T09:25:49.3764702Z .. note:: 2025-12-04T09:25:49.3765061Z vmap does not provide general autobatching or handle variable-length 2025-12-04T09:25:49.3765519Z sequences out of the box. 2025-12-04T09:25:49.3765722Z 2025-12-04T09:25:49.3766280Z Original Error: IndentationError('expected an indented block after function definition on line 4', ('', 5, 1, '_._ = None\n', 5, 2)) 2025-12-04T09:25:49.3766972Z 2025-12-04T09:25:49.3767057Z _._ = None 2025-12-04T09:25:49.3767270Z ^ 2025-12-04T09:25:49.3767933Z msg = Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/apis.py line=306. 2025-12-04T09:25:49.3768814Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:49.3769449Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-12-04T09:25:49.3770037Z input(s) specified by ``argnums``. This operator can be nested to 2025-12-04T09:25:49.3770479Z compute higher-order gradients. 2025-12-04T09:25:49.3770714Z 2025-12-04T09:25:49.3770796Z Args: 2025-12-04T09:25:49.3771223Z func (Callable): A Python function that takes one or more arguments. 2025-12-04T09:25:49.3771852Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-12-04T09:25:49.3772526Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-12-04T09:25:49.3773042Z ``(output, aux)``. 2025-12-04T09:25:49.3773525Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-12-04T09:25:49.3774200Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-12-04T09:25:49.3774770Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-12-04T09:25:49.3775300Z auxiliary objects: ``(output, aux)``. Default: False. 2025-12-04T09:25:49.3775592Z 2025-12-04T09:25:49.3775694Z Returns: 2025-12-04T09:25:49.3776113Z Function to compute gradients with respect to its inputs. By default, the output of 2025-12-04T09:25:49.3776793Z the function is the gradient tensor(s) with respect to the first argument. 2025-12-04T09:25:49.3777454Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-12-04T09:25:49.3778132Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-12-04T09:25:49.3778662Z respect to each ``argnums`` value is returned. 2025-12-04T09:25:49.3778944Z 2025-12-04T09:25:49.3779046Z Example of using ``grad``: 2025-12-04T09:25:49.3779237Z 2025-12-04T09:25:49.3779348Z >>> # xdoctest: +SKIP 2025-12-04T09:25:49.3779638Z >>> from torch.func import grad 2025-12-04T09:25:49.3779967Z >>> x = torch.randn([]) 2025-12-04T09:25:49.3780285Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-12-04T09:25:49.3780649Z >>> assert torch.allclose(cos_x, x.cos()) 2025-12-04T09:25:49.3780982Z >>> 2025-12-04T09:25:49.3781215Z >>> # Second-order gradients 2025-12-04T09:25:49.3781589Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-12-04T09:25:49.3781997Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-12-04T09:25:49.3782263Z 2025-12-04T09:25:49.3782522Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-12-04T09:25:49.3782916Z 2025-12-04T09:25:49.3783015Z >>> # xdoctest: +SKIP 2025-12-04T09:25:49.3783330Z >>> from torch.func import grad, vmap 2025-12-04T09:25:49.3783688Z >>> batch_size, feature_size = 3, 5 2025-12-04T09:25:49.3783993Z >>> 2025-12-04T09:25:49.3784232Z >>> def model(weights, feature_vec): 2025-12-04T09:25:49.3784601Z >>> # Very simple linear model with activation 2025-12-04T09:25:49.3784959Z >>> assert feature_vec.dim() == 1 2025-12-04T09:25:49.3785320Z >>> return feature_vec.dot(weights).relu() 2025-12-04T09:25:49.3785653Z >>> 2025-12-04T09:25:49.3785903Z >>> def compute_loss(weights, example, target): 2025-12-04T09:25:49.3786276Z >>> y = model(weights, example) 2025-12-04T09:25:49.3786644Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-12-04T09:25:49.3786988Z >>> 2025-12-04T09:25:49.3787281Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-12-04T09:25:49.3787746Z >>> examples = torch.randn(batch_size, feature_size) 2025-12-04T09:25:49.3788142Z >>> targets = torch.randn(batch_size) 2025-12-04T09:25:49.3788496Z >>> inputs = (weights, examples, targets) 2025-12-04T09:25:49.3788986Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-12-04T09:25:49.3789448Z ... *inputs 2025-12-04T09:25:49.3789685Z ... ) 2025-12-04T09:25:49.3789821Z 2025-12-04T09:25:49.3789999Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-12-04T09:25:49.3790313Z 2025-12-04T09:25:49.3790410Z >>> # xdoctest: +SKIP 2025-12-04T09:25:49.3790708Z >>> from torch.func import grad 2025-12-04T09:25:49.3791096Z >>> def my_loss_func(y, y_pred): 2025-12-04T09:25:49.3791460Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-12-04T09:25:49.3791839Z >>> loss = loss_per_sample.mean() 2025-12-04T09:25:49.3792191Z >>> return loss, (y_pred, loss_per_sample) 2025-12-04T09:25:49.3792536Z >>> 2025-12-04T09:25:49.3792818Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-12-04T09:25:49.3793262Z >>> y_true = torch.rand(4) 2025-12-04T09:25:49.3793609Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-12-04T09:25:49.3793974Z >>> out = fn(y_true, y_preds) 2025-12-04T09:25:49.3794444Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-12-04T09:25:49.3794825Z 2025-12-04T09:25:49.3794919Z .. note:: 2025-12-04T09:25:49.3795228Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-12-04T09:25:49.3795525Z 2025-12-04T09:25:49.3795687Z Case 1: Using ``torch.no_grad`` inside a function: 2025-12-04T09:25:49.3795959Z 2025-12-04T09:25:49.3796070Z >>> # xdoctest: +SKIP 2025-12-04T09:25:49.3796353Z >>> def f(x): 2025-12-04T09:25:49.3796629Z >>> with torch.no_grad(): 2025-12-04T09:25:49.3796951Z >>> c = x ** 2 2025-12-04T09:25:49.3797237Z >>> return x - c 2025-12-04T09:25:49.3797441Z 2025-12-04T09:25:49.3797643Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-12-04T09:25:49.3797972Z 2025-12-04T09:25:49.3798171Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-12-04T09:25:49.3798486Z 2025-12-04T09:25:49.3798598Z >>> # xdoctest: +SKIP 2025-12-04T09:25:49.3798895Z >>> with torch.no_grad(): 2025-12-04T09:25:49.3799205Z >>> grad(f)(x) 2025-12-04T09:25:49.3799384Z 2025-12-04T09:25:49.3799627Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-12-04T09:25:49.3800211Z outer one. This is because ``grad`` is a "function transform": its result 2025-12-04T09:25:49.3800801Z should not depend on the result of a context manager outside of ``f``. 2025-12-04T09:25:49.3801153Z 2025-12-04T09:25:49.3801247Z 2025-12-04T09:25:49.3801914Z Original Error: IndentationError('expected an indented block after function definition on line 5', ('', 6, 1, '_._ = None\n', 6, 2)) 2025-12-04T09:25:49.3802596Z 2025-12-04T09:25:49.3802680Z _._ = None 2025-12-04T09:25:49.3802885Z ^ 2025-12-04T09:25:52.5478472Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py line=402. 2025-12-04T09:25:52.5479548Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:52.5480132Z Register a FakeTensor implementation for this custom op. 2025-12-04T09:25:52.5480438Z 2025-12-04T09:25:52.5480725Z This is necessary to get the operator to work efficiently with torch.compile. 2025-12-04T09:25:52.5481125Z 2025-12-04T09:25:52.5481353Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-12-04T09:25:52.5481947Z specifies the behavior of this operator on Tensors that carry no data. 2025-12-04T09:25:52.5482471Z Given some input Tensors with certain properties 2025-12-04T09:25:52.5483020Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-12-04T09:25:52.5483530Z the output Tensors are. 2025-12-04T09:25:52.5483724Z 2025-12-04T09:25:52.5483945Z Please see :func:`torch.library.register_fake` for more details. 2025-12-04T09:25:52.5484347Z 2025-12-04T09:25:52.5484434Z Args: 2025-12-04T09:25:52.5484750Z fn (Callable): The function to register as the FakeTensor 2025-12-04T09:25:52.5485161Z implementation. 2025-12-04T09:25:52.5485351Z 2025-12-04T09:25:52.5485507Z Examples: 2025-12-04T09:25:52.5485769Z >>> import torch 2025-12-04T09:25:52.5486316Z >>> import numpy as np 2025-12-04T09:25:52.5486638Z >>> from torch import Tensor 2025-12-04T09:25:52.5486938Z >>> 2025-12-04T09:25:52.5487273Z >>> # Example 1: an operator without data-dependent output shape 2025-12-04T09:25:52.5487831Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-12-04T09:25:52.5488452Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-12-04T09:25:52.5489061Z >>> return (x @ weight.t()) + bias 2025-12-04T09:25:52.5489420Z >>> 2025-12-04T09:25:52.5489668Z >>> @linear.register_fake 2025-12-04T09:25:52.5489981Z >>> def _(x, weight, bias): 2025-12-04T09:25:52.5490302Z >>> assert x.dim() == 2 2025-12-04T09:25:52.5490633Z >>> assert weight.dim() == 2 2025-12-04T09:25:52.5490975Z >>> assert bias.dim() == 1 2025-12-04T09:25:52.5491328Z >>> assert x.shape[1] == weight.shape[1] 2025-12-04T09:25:52.5491721Z >>> assert weight.shape[0] == bias.shape[0] 2025-12-04T09:25:52.5492112Z >>> assert x.device == weight.device 2025-12-04T09:25:52.5492500Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-12-04T09:25:52.5492862Z >>> 2025-12-04T09:25:52.5493113Z >>> x = torch.randn(2, 2) 2025-12-04T09:25:52.5493429Z >>> weight = torch.randn(2, 2) 2025-12-04T09:25:52.5493763Z >>> bias = torch.randn(2) 2025-12-04T09:25:52.5494123Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:25:52.5494574Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-12-04T09:25:52.5495049Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:25:52.5495567Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-12-04T09:25:52.5496046Z >>> 2025-12-04T09:25:52.5496359Z >>> # Example 2: an operator with data-dependent output shape 2025-12-04T09:25:52.5496881Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-12-04T09:25:52.5497333Z >>> def nonzero(x: Tensor) -> Tensor: 2025-12-04T09:25:52.5497673Z >>> x_np = x.cpu().numpy() 2025-12-04T09:25:52.5498040Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-12-04T09:25:52.5498443Z >>> return torch.tensor(res, device=x.device) 2025-12-04T09:25:52.5498792Z >>> 2025-12-04T09:25:52.5499026Z >>> @nonzero.register_fake 2025-12-04T09:25:52.5499339Z >>> def _(x): 2025-12-04T09:25:52.5499662Z >>> # Number of nonzero-elements is data-dependent. 2025-12-04T09:25:52.5500097Z >>> # Since we cannot peek at the data in an abstract impl, 2025-12-04T09:25:52.5500557Z >>> # we use the ctx object to construct a new symint that 2025-12-04T09:25:52.5500987Z >>> # represents the data-dependent size. 2025-12-04T09:25:52.5501352Z >>> ctx = torch.library.get_ctx() 2025-12-04T09:25:52.5501716Z >>> nnz = ctx.new_dynamic_size() 2025-12-04T09:25:52.5502065Z >>> shape = [nnz, x.dim()] 2025-12-04T09:25:52.5502442Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-12-04T09:25:52.5502816Z >>> return result 2025-12-04T09:25:52.5503096Z >>> 2025-12-04T09:25:52.5503354Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-12-04T09:25:52.5503723Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:25:52.5504137Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-12-04T09:25:52.5504548Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:25:52.5504931Z >>> assert torch.allclose(out, x.nonzero()) 2025-12-04T09:25:52.5505190Z 2025-12-04T09:25:52.5505272Z 2025-12-04T09:25:52.5506058Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-12-04T09:25:52.5506749Z 2025-12-04T09:25:52.5506847Z _._ = None 2025-12-04T09:25:52.5507042Z ^ 2025-12-04T09:25:52.5709182Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_profile.py line=94. 2025-12-04T09:25:52.5710397Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-12-04T09:25:52.5710799Z 2025-12-04T09:25:52.5711049Z Registers a fake kernel based on the given operator profiles. This fake 2025-12-04T09:25:52.5711684Z kernel registration will override any existing fake kernel registrations. 2025-12-04T09:25:52.5712078Z 2025-12-04T09:25:52.5712299Z The input is a dictionary mapping operator names to a set of operator 2025-12-04T09:25:52.5712891Z profiles, which we will use to generate fake kernels. The operator profiles 2025-12-04T09:25:52.5713479Z are a record of the input and output tensor metadata. Based on this 2025-12-04T09:25:52.5714048Z information we will match a given input to the recorded profile, and return 2025-12-04T09:25:52.5714662Z an output with the same metadata as in the recorded profile. If a profile 2025-12-04T09:25:52.5715166Z doesn't exist then an exception will be thrown. 2025-12-04T09:25:52.5715427Z 2025-12-04T09:25:52.5715675Z The fake kernel generation is considered unsafe because it relies on the 2025-12-04T09:25:52.5716267Z rigid, pre-defined operator profiles that do not account for potential 2025-12-04T09:25:52.5716894Z variations in output behavior. Specifically, the generated kernels assume a 2025-12-04T09:25:52.5717544Z fixed relationship between input and output ranks. However, in reality, it's 2025-12-04T09:25:52.5718178Z possible that data-dependent operations may produce outputs of different 2025-12-04T09:25:52.5718789Z ranks even when given inputs of the same rank. The generated fake kernels 2025-12-04T09:25:52.5719379Z are inflexible and unable to accommodate these nuances, making them 2025-12-04T09:25:52.5719829Z potentially unsafe. 2025-12-04T09:25:52.5719980Z 2025-12-04T09:25:52.5720064Z Args: 2025-12-04T09:25:52.5720409Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-12-04T09:25:52.5720971Z name to a set of operator profiles from which we will generate fake 2025-12-04T09:25:52.5721388Z kernels. 2025-12-04T09:25:52.5721537Z 2025-12-04T09:25:52.5721624Z Examples: 2025-12-04T09:25:52.5721746Z 2025-12-04T09:25:52.5721931Z >>> # Example: Registering an op-profile from draft-export 2025-12-04T09:25:52.5722324Z >>> import torch 2025-12-04T09:25:52.5722635Z >>> from torch.export._draft_export import draft_export 2025-12-04T09:25:52.5723006Z >>> 2025-12-04T09:25:52.5723319Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-12-04T09:25:52.5723738Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-12-04T09:25:52.5724085Z >>> return x + y 2025-12-04T09:25:52.5724424Z >>> 2025-12-04T09:25:52.5724637Z >>> class M(torch.nn.Module): 2025-12-04T09:25:52.5724951Z >>> def forward(self, a, b): 2025-12-04T09:25:52.5725315Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-12-04T09:25:52.5725668Z >>> return res 2025-12-04T09:25:52.5725930Z >>> 2025-12-04T09:25:52.5726227Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-12-04T09:25:52.5726598Z >>> 2025-12-04T09:25:52.5727024Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-12-04T09:25:52.5727592Z >>> decomp = ep.run_decompositions() 2025-12-04T09:25:52.5727843Z 2025-12-04T09:25:52.5727847Z 2025-12-04T09:25:52.5728352Z Original Error: IncompleteParseError('ill-formed doctest: all parts have been processed but the doctest source is not balanced') 2025-12-04T09:25:52.5728986Z 2025-12-04T09:25:53.1899115Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-12-04T09:25:53.1900466Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:53.1900853Z 2025-12-04T09:25:53.1901148Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-12-04T09:25:53.1901894Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-12-04T09:25:53.1902519Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-12-04T09:25:53.1903006Z input by the user. 2025-12-04T09:25:53.1903397Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-12-04T09:25:53.1903902Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-12-04T09:25:53.1904190Z 2025-12-04T09:25:53.1904317Z Note:: 2025-12-04T09:25:53.1904775Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-12-04T09:25:53.1905241Z 2025-12-04T09:25:53.1905323Z Args: 2025-12-04T09:25:53.1905537Z model (nn.Module): 2025-12-04T09:25:53.1905932Z The model whose layers will be sparsified. The layers that needs to be 2025-12-04T09:25:53.1906543Z sparsified should be added separately using the register_layer() function 2025-12-04T09:25:53.1907030Z aggregate_fn (Optional, Callable): 2025-12-04T09:25:53.1907525Z default aggregate_fn that is used if not specified while registering the layer. 2025-12-04T09:25:53.1908093Z specifies how inputs should be aggregated over time. 2025-12-04T09:25:53.1908670Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-12-04T09:25:53.1909189Z Example 2025-12-04T09:25:53.1909511Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-12-04T09:25:53.1909935Z reduce_fn (Optional, Callable): 2025-12-04T09:25:53.1910414Z default reduce_fn that is used if not specified while registering the layer. 2025-12-04T09:25:53.1911066Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-12-04T09:25:53.1911584Z calling agg_fn() on all inputs. 2025-12-04T09:25:53.1911904Z Example 2025-12-04T09:25:53.1912268Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-12-04T09:25:53.1912725Z mask_fn (Optional, Callable): 2025-12-04T09:25:53.1913270Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-12-04T09:25:53.1913990Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-12-04T09:25:53.1914490Z register_layer(). 2025-12-04T09:25:53.1915060Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-12-04T09:25:53.1915643Z arguments. 2025-12-04T09:25:53.1915935Z features (Optional, list): 2025-12-04T09:25:53.1916291Z default selected features to sparsify. 2025-12-04T09:25:53.1916811Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-12-04T09:25:53.1917320Z For example, 2025-12-04T09:25:53.1917777Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-12-04T09:25:53.1918291Z feature_dim (Optional, int): 2025-12-04T09:25:53.1918801Z default dimension of input features. Again, features along this dim will be chosen 2025-12-04T09:25:53.1919333Z for sparsification. 2025-12-04T09:25:53.1919649Z sparse_config (Dict): 2025-12-04T09:25:53.1920072Z Default configuration for the mask_fn. This config will be passed 2025-12-04T09:25:53.1920538Z with the mask_fn() 2025-12-04T09:25:53.1920750Z 2025-12-04T09:25:53.1920913Z Example: 2025-12-04T09:25:53.1921144Z >>> # xdoctest: +SKIP 2025-12-04T09:25:53.1921410Z >>> model = SomeModel() 2025-12-04T09:25:53.1921854Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-12-04T09:25:53.1922347Z >>> # Initialize aggregate_fn 2025-12-04T09:25:53.1922639Z >>> def agg_fn(x, y): 2025-12-04T09:25:53.1922996Z >>> return x + y 2025-12-04T09:25:53.1923255Z >>> 2025-12-04T09:25:53.1923462Z >>> # Initialize reduce_fn 2025-12-04T09:25:53.1923750Z >>> def reduce_fn(x): 2025-12-04T09:25:53.1924023Z >>> return torch.mean(x, dim=0) 2025-12-04T09:25:53.1924441Z >>> 2025-12-04T09:25:53.1924664Z >>> # Initialize mask_fn 2025-12-04T09:25:53.1924941Z >>> def mask_fn(data): 2025-12-04T09:25:53.1925268Z >>> return torch.eye(data.shape).to(data.device) 2025-12-04T09:25:53.1925626Z >>> 2025-12-04T09:25:53.1925832Z >>> 2025-12-04T09:25:53.1926057Z >>> act_sparsifier.register_layer( 2025-12-04T09:25:53.1926395Z ... model.some_layer, 2025-12-04T09:25:53.1926694Z ... aggregate_fn=agg_fn, 2025-12-04T09:25:53.1926982Z ... reduce_fn=reduce_fn, 2025-12-04T09:25:53.1927281Z ... mask_fn=mask_fn, 2025-12-04T09:25:53.1927554Z ... ) 2025-12-04T09:25:53.1927750Z >>> 2025-12-04T09:25:53.1927975Z >>> # start training process 2025-12-04T09:25:53.1928276Z >>> for _ in [...]: 2025-12-04T09:25:53.1928519Z >>> # epoch starts 2025-12-04T09:25:53.1928852Z >>> # model.forward(), compute_loss() and model.backwards() 2025-12-04T09:25:53.1929248Z >>> # epoch ends 2025-12-04T09:25:53.1929497Z >>> act_sparsifier.step() 2025-12-04T09:25:53.1929806Z >>> # end training process 2025-12-04T09:25:53.1930109Z >>> sparsifier.squash_mask() 2025-12-04T09:25:53.1930308Z 2025-12-04T09:25:53.1930858Z Original Error: IndentationError("expected an indented block after 'for' statement on line 25", ('', 26, 1, '_._ = None\n', 26, 2)) 2025-12-04T09:25:53.1931504Z 2025-12-04T09:25:53.1931590Z _._ = None 2025-12-04T09:25:53.1931796Z ^ 2025-12-04T09:25:54.0827163Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py line=547. 2025-12-04T09:25:54.0828213Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:54.0828631Z 2025-12-04T09:25:54.0828928Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-12-04T09:25:54.0829609Z The submesh created consists of the dimensions and the communicators indicated by 2025-12-04T09:25:54.0830114Z ``mesh_dim_names`` 2025-12-04T09:25:54.0830263Z 2025-12-04T09:25:54.0830359Z Args: 2025-12-04T09:25:54.0830711Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-12-04T09:25:54.0831281Z mesh dimension of the DeviceMesh to create the submesh for. 2025-12-04T09:25:54.0831686Z Returns: 2025-12-04T09:25:54.0831927Z A :class:`DeviceMesh` object 2025-12-04T09:25:54.0832125Z 2025-12-04T09:25:54.0832419Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-12-04T09:25:54.0832942Z In the first example: 2025-12-04T09:25:54.0833372Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-12-04T09:25:54.0834015Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-12-04T09:25:54.0834642Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-12-04T09:25:54.0835239Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-12-04T09:25:54.0835838Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-12-04T09:25:54.0836440Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-12-04T09:25:54.0836814Z 2025-12-04T09:25:54.0836911Z In the second example: 2025-12-04T09:25:54.0837628Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-12-04T09:25:54.0838317Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-12-04T09:25:54.0838988Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-12-04T09:25:54.0839770Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-12-04T09:25:54.0840183Z 2025-12-04T09:25:54.0840303Z Example:: 2025-12-04T09:25:54.0840425Z 2025-12-04T09:25:54.0840541Z >>> # xdoctest: +SKIP("no rank") 2025-12-04T09:25:54.0840924Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-12-04T09:25:54.0841310Z >>> 2025-12-04T09:25:54.0841639Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-12-04T09:25:54.0842109Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-12-04T09:25:54.0843001Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-12-04T09:25:54.0843513Z >>> tp_mesh = mesh_2d["tp"] 2025-12-04T09:25:54.0843803Z >>> dp_mesh = mesh_2d["dp"] 2025-12-04T09:25:54.0844088Z >>> 2025-12-04T09:25:54.0844383Z >>> # Initialize a 3D mesh. 2025-12-04T09:25:54.0844871Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-12-04T09:25:54.0845605Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-12-04T09:25:54.0846173Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-12-04T09:25:54.0846519Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-12-04T09:25:54.0846742Z 2025-12-04T09:25:54.0847460Z 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)) 2025-12-04T09:25:54.0848314Z 2025-12-04T09:25:54.0848572Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-12-04T09:25:54.0849083Z ^ 2025-12-04T09:25:54.6438494Z msg = Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-12-04T09:25:54.6439582Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:54.6439984Z 2025-12-04T09:25:54.6440285Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-12-04T09:25:54.6440717Z 2025-12-04T09:25:54.6441040Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-12-04T09:25:54.6441481Z 2025-12-04T09:25:54.6441782Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-12-04T09:25:54.6442545Z will be visible to the whole process. 2025-12-04T09:25:54.6442787Z 2025-12-04T09:25:54.6443089Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-12-04T09:25:54.6443510Z 2025-12-04T09:25:54.6443650Z 1) set_up_planner - called on all ranks. 2025-12-04T09:25:54.6444004Z Signals the start of a checkpoint save. 2025-12-04T09:25:54.6444299Z 2025-12-04T09:25:54.6444424Z 2) create_local_plan - called on all ranks. 2025-12-04T09:25:54.6444975Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-12-04T09:25:54.6445403Z 2025-12-04T09:25:54.6445605Z 3) create_global_plan - called on the coordinator rank only. 2025-12-04T09:25:54.6446108Z Takes the SavePlan from all ranks and make any global decision. 2025-12-04T09:25:54.6446449Z 2025-12-04T09:25:54.6446561Z 4) finish_plan - called on all ranks. 2025-12-04T09:25:54.6447010Z This gives each rank a chance to adjust to global planning decisions. 2025-12-04T09:25:54.6447389Z 2025-12-04T09:25:54.6447761Z 5) resolve_data - called multiple times on each rank 2025-12-04T09:25:54.6448255Z Lookups a value on the `state_dict` for the storage layer to write. 2025-12-04T09:25:54.6448590Z 2025-12-04T09:25:54.6448905Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-12-04T09:25:54.6449550Z most changes can be expressed by changes in a single method. 2025-12-04T09:25:54.6449957Z 2025-12-04T09:25:54.6450093Z There are 3 usual patterns of extension: 2025-12-04T09:25:54.6450326Z 2025-12-04T09:25:54.6450601Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-12-04T09:25:54.6451226Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-12-04T09:25:54.6451597Z 2025-12-04T09:25:54.6451710Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6452075Z >>> class RenamePlanner(DefaultSavePlanner): 2025-12-04T09:25:54.6452418Z >>> def set_up_planner( 2025-12-04T09:25:54.6452691Z >>> self, 2025-12-04T09:25:54.6452952Z >>> state_dict: STATE_DICT_TYPE, 2025-12-04T09:25:54.6453295Z >>> storage_meta: Optional[StorageMeta], 2025-12-04T09:25:54.6453650Z >>> is_coordinator: bool, 2025-12-04T09:25:54.6453949Z >>> ) -> None: 2025-12-04T09:25:54.6454193Z >>> # prefix all keys with `foo_`` 2025-12-04T09:25:54.6454716Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-12-04T09:25:54.6455160Z 2025-12-04T09:25:54.6455510Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-12-04T09:25:54.6455990Z 2025-12-04T09:25:54.6456117Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6456466Z >>> class FP16Planner(DefaultSavePlanner): 2025-12-04T09:25:54.6456825Z >>> def create_local_plan(self): 2025-12-04T09:25:54.6457167Z >>> plan = super().create_local_plan() 2025-12-04T09:25:54.6457508Z >>> for p in plan: 2025-12-04T09:25:54.6457801Z >>> if p.tensor_data is not None: 2025-12-04T09:25:54.6458204Z >>> p.tensor_data.properties.dtype = torch.float16 2025-12-04T09:25:54.6458585Z >>> return plan 2025-12-04T09:25:54.6458821Z >>> 2025-12-04T09:25:54.6459052Z >>> def resolve_data(self, write_item): 2025-12-04T09:25:54.6459431Z >>> item = super().resolve_data(write_item) 2025-12-04T09:25:54.6460079Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-12-04T09:25:54.6460512Z 2025-12-04T09:25:54.6460991Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-12-04T09:25:54.6461910Z 2025-12-04T09:25:54.6462122Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6462475Z >>> from itertools import zip_longest 2025-12-04T09:25:54.6462800Z >>> from dataclasses import replace 2025-12-04T09:25:54.6463192Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-12-04T09:25:54.6463780Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-12-04T09:25:54.6464320Z >>> # This sample doesn't handle ShardedTensors 2025-12-04T09:25:54.6464705Z >>> def create_global_plan(self, all_plans): 2025-12-04T09:25:54.6465112Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-12-04T09:25:54.6465494Z >>> items_per_rank = [ 2025-12-04T09:25:54.6465812Z >>> [item for item in items if item is not None] 2025-12-04T09:25:54.6466240Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-12-04T09:25:54.6466614Z >>> ] 2025-12-04T09:25:54.6466830Z >>> all_plans = [ 2025-12-04T09:25:54.6467121Z >>> replace(plan, items=items) 2025-12-04T09:25:54.6467548Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-12-04T09:25:54.6467948Z >>> ] 2025-12-04T09:25:54.6468222Z >>> return super().create_global_plan(all_plans) 2025-12-04T09:25:54.6468484Z 2025-12-04T09:25:54.6468871Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-12-04T09:25:54.6469570Z accomplished by having each rank contribute their data items in the local plan and 2025-12-04T09:25:54.6470096Z the global planner aggregate them: 2025-12-04T09:25:54.6470322Z 2025-12-04T09:25:54.6470434Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6470829Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-12-04T09:25:54.6471296Z >>> def create_local_plan(self) -> SavePlan: 2025-12-04T09:25:54.6471669Z >>> plan = super().create_local_plan() 2025-12-04T09:25:54.6472076Z >>> return replace(plan, planner_data="per-rank-data") 2025-12-04T09:25:54.6472441Z >>> 2025-12-04T09:25:54.6472873Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-12-04T09:25:54.6473521Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-12-04T09:25:54.6474019Z >>> merged_data = [p.planner_data for p in global_plan] 2025-12-04T09:25:54.6474475Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-12-04T09:25:54.6474889Z >>> return global_plan, metadata 2025-12-04T09:25:54.6475113Z 2025-12-04T09:25:54.6475686Z Original Error: IndentationError('expected an indented block after function definition on line 3', ('', 9, 0, '_._ = None\n', 9, -1)) 2025-12-04T09:25:54.6476372Z 2025-12-04T09:25:54.6476468Z _._ = None 2025-12-04T09:25:54.6476667Z ^ 2025-12-04T09:25:54.6477447Z msg = Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-12-04T09:25:54.6478465Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:54.6478848Z 2025-12-04T09:25:54.6479162Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-12-04T09:25:54.6479594Z 2025-12-04T09:25:54.6479915Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-12-04T09:25:54.6480346Z 2025-12-04T09:25:54.6480641Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-12-04T09:25:54.6481186Z will be visible to the whole process. 2025-12-04T09:25:54.6481409Z 2025-12-04T09:25:54.6481710Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-12-04T09:25:54.6482136Z 2025-12-04T09:25:54.6482255Z 1) set_up_planner - called on all ranks. 2025-12-04T09:25:54.6482623Z Signals the start of loading a checkpoint. 2025-12-04T09:25:54.6482882Z 2025-12-04T09:25:54.6483004Z 2) create_local_plan - called on all ranks. 2025-12-04T09:25:54.6483550Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-12-04T09:25:54.6483978Z 2025-12-04T09:25:54.6484247Z 3) create_global_plan - called on the coordinator rank only. 2025-12-04T09:25:54.6484773Z Takes the LoadPlan from all ranks and make any global decision. 2025-12-04T09:25:54.6485113Z 2025-12-04T09:25:54.6485263Z 4) load_bytes - called multiple times on each rank 2025-12-04T09:25:54.6485708Z This is called once per non-tensor value in state_dict. 2025-12-04T09:25:54.6486000Z 2025-12-04T09:25:54.6486231Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-12-04T09:25:54.6486785Z They are called in pair for each Tensor value in state_dict. 2025-12-04T09:25:54.6487094Z 2025-12-04T09:25:54.6487422Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-12-04T09:25:54.6488055Z most changes can be expressed by changes in a single method. 2025-12-04T09:25:54.6488377Z 2025-12-04T09:25:54.6488504Z There are two usual patterns of extension: 2025-12-04T09:25:54.6488758Z 2025-12-04T09:25:54.6489019Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-12-04T09:25:54.6489683Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-12-04T09:25:54.6490381Z to keep a reference to the original state_dict as load happens in place so 2025-12-04T09:25:54.6490876Z we need to be able to perform it in place 2025-12-04T09:25:54.6491126Z 2025-12-04T09:25:54.6491239Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6491606Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-12-04T09:25:54.6491950Z >>> def set_up_planner( 2025-12-04T09:25:54.6492291Z >>> self, 2025-12-04T09:25:54.6492550Z >>> state_dict: STATE_DICT_TYPE, 2025-12-04T09:25:54.6492865Z >>> metadata: Metadata, 2025-12-04T09:25:54.6493168Z >>> is_coordinator: bool, 2025-12-04T09:25:54.6493463Z >>> ) -> None: 2025-12-04T09:25:54.6493726Z >>> self.original_state_dict = state_dict 2025-12-04T09:25:54.6494151Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-12-04T09:25:54.6494560Z >>> 2025-12-04T09:25:54.6494781Z >>> if self.flatten_sharded_tensors: 2025-12-04T09:25:54.6495176Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-12-04T09:25:54.6495552Z >>> 2025-12-04T09:25:54.6495765Z >>> if self.flatten_state_dict: 2025-12-04T09:25:54.6496185Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-12-04T09:25:54.6496597Z >>> 2025-12-04T09:25:54.6496815Z >>> self.state_dict = state_dict 2025-12-04T09:25:54.6497157Z >>> self.metadata = metadata 2025-12-04T09:25:54.6497505Z >>> self.is_coordinator = is_coordinator 2025-12-04T09:25:54.6497838Z >>> 2025-12-04T09:25:54.6498066Z >>> def load_bytes(self, read_item, value): 2025-12-04T09:25:54.6498421Z >>> # Remove the "foo_" prefix 2025-12-04T09:25:54.6498956Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-12-04T09:25:54.6499420Z 2025-12-04T09:25:54.6499424Z 2025-12-04T09:25:54.6499696Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-12-04T09:25:54.6500108Z 2025-12-04T09:25:54.6500224Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:25:54.6500617Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-12-04T09:25:54.6501023Z >>> def resolve_tensor(self, read_item): 2025-12-04T09:25:54.6501385Z >>> tensor = super().resolve_tensor(read_item) 2025-12-04T09:25:54.6501794Z >>> return torch.empty_like(tensor, device="cpu") 2025-12-04T09:25:54.6502152Z >>> 2025-12-04T09:25:54.6502387Z >>> def commit_tensor(self, read_item, tensor): 2025-12-04T09:25:54.6502807Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-12-04T09:25:54.6503087Z 2025-12-04T09:25:54.6503666Z Original Error: IndentationError('expected an indented block after function definition on line 22', ('', 23, 0, '_._ = None\n', 23, -1)) 2025-12-04T09:25:54.6504356Z 2025-12-04T09:25:54.6504453Z _._ = None 2025-12-04T09:25:54.6504649Z ^ 2025-12-04T09:25:54.9532358Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/api.py line=295. 2025-12-04T09:25:54.9533394Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:54.9533780Z 2025-12-04T09:25:54.9533994Z ``FullStateDictConfig`` is a config class meant to be used with 2025-12-04T09:25:54.9534539Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-12-04T09:25:54.9535080Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-12-04T09:25:54.9535662Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-12-04T09:25:54.9536215Z is meant to be used via the :func:`state_dict_type` context manager as 2025-12-04T09:25:54.9536639Z follows: 2025-12-04T09:25:54.9536758Z 2025-12-04T09:25:54.9536900Z >>> # xdoctest: +SKIP("undefined variables") 2025-12-04T09:25:54.9537383Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-12-04T09:25:54.9537888Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-12-04T09:25:54.9549475Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-12-04T09:25:54.9550118Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-12-04T09:25:54.9550753Z >>> state = fsdp.state_dict() 2025-12-04T09:25:54.9551272Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-12-04T09:25:54.9551876Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-12-04T09:25:54.9552607Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-12-04T09:25:54.9553096Z >>> if dist.get_rank() == 0: 2025-12-04T09:25:54.9553492Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-12-04T09:25:54.9553940Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-12-04T09:25:54.9554334Z >>> model.load_state_dict(state_dict) 2025-12-04T09:25:54.9554825Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-12-04T09:25:54.9555446Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-12-04T09:25:54.9555925Z >>> fsdp = FSDP( 2025-12-04T09:25:54.9556174Z ... model, 2025-12-04T09:25:54.9556456Z ... device_id=torch.cuda.current_device(), 2025-12-04T09:25:54.9556810Z ... auto_wrap_policy=..., 2025-12-04T09:25:54.9557124Z ... sync_module_states=True, 2025-12-04T09:25:54.9557431Z ... ) 2025-12-04T09:25:54.9557768Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-12-04T09:25:54.9558134Z 2025-12-04T09:25:54.9558223Z Attributes: 2025-12-04T09:25:54.9558565Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-12-04T09:25:54.9559098Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-12-04T09:25:54.9559600Z ranks save the full state dict. (Default: ``False``) 2025-12-04T09:25:54.9559897Z 2025-12-04T09:25:54.9560432Z Original Error: IndentationError("expected an indented block after 'if' statement on line 10", ('', 11, 1, '_._ = None\n', 11, 2)) 2025-12-04T09:25:54.9561079Z 2025-12-04T09:25:54.9561176Z _._ = None 2025-12-04T09:25:54.9561372Z ^ 2025-12-04T09:25:57.3303544Z msg = Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrize.py line=437. 2025-12-04T09:25:57.3304646Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:57.3305190Z Register a parametrization to a tensor in a module. 2025-12-04T09:25:57.3305524Z 2025-12-04T09:25:57.3305813Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-12-04T09:25:57.3306534Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-12-04T09:25:57.3307239Z If the original tensor requires a gradient, the backward pass will differentiate 2025-12-04T09:25:57.3307978Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-12-04T09:25:57.3308413Z 2025-12-04T09:25:57.3308740Z The first time that a module registers a parametrization, this function will add an attribute 2025-12-04T09:25:57.3309459Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-12-04T09:25:57.3309836Z 2025-12-04T09:25:57.3310112Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-12-04T09:25:57.3310645Z ``module.parametrizations.weight``. 2025-12-04T09:25:57.3310884Z 2025-12-04T09:25:57.3311020Z The original tensor will be accessible under 2025-12-04T09:25:57.3311437Z ``module.parametrizations.weight.original``. 2025-12-04T09:25:57.3311702Z 2025-12-04T09:25:57.3311992Z Parametrizations may be concatenated by registering several parametrizations 2025-12-04T09:25:57.3312499Z on the same attribute. 2025-12-04T09:25:57.3312691Z 2025-12-04T09:25:57.3312941Z The training mode of a registered parametrization is updated on registration 2025-12-04T09:25:57.3313745Z to match the training mode of the host module 2025-12-04T09:25:57.3314004Z 2025-12-04T09:25:57.3314340Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-12-04T09:25:57.3314914Z using the context manager :func:`cached`. 2025-12-04T09:25:57.3315173Z 2025-12-04T09:25:57.3315427Z A :attr:`parametrization` may optionally implement a method with signature 2025-12-04T09:25:57.3315913Z 2025-12-04T09:25:57.3316068Z .. code-block:: python 2025-12-04T09:25:57.3316246Z 2025-12-04T09:25:57.3316488Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-12-04T09:25:57.3316838Z 2025-12-04T09:25:57.3317114Z This method is called on the unparametrized tensor when the first parametrization 2025-12-04T09:25:57.3317749Z is registered to compute the initial value of the original tensor. 2025-12-04T09:25:57.3318599Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-12-04T09:25:57.3319057Z 2025-12-04T09:25:57.3319408Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-12-04T09:25:57.3320169Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-12-04T09:25:57.3320617Z 2025-12-04T09:25:57.3320856Z It is possible for the first parametrization to depend on several inputs. 2025-12-04T09:25:57.3321493Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-12-04T09:25:57.3322112Z (see the example implementation of a ``RankOne`` parametrization below). 2025-12-04T09:25:57.3322498Z 2025-12-04T09:25:57.3322849Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-12-04T09:25:57.3323471Z with names ``original0``, ``original1``,... 2025-12-04T09:25:57.3323719Z 2025-12-04T09:25:57.3323827Z .. note:: 2025-12-04T09:25:57.3323960Z 2025-12-04T09:25:57.3324305Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-12-04T09:25:57.3324875Z once to perform a number of consistency checks. 2025-12-04T09:25:57.3325432Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-12-04T09:25:57.3325973Z and nothing will be called otherwise. 2025-12-04T09:25:57.3326215Z 2025-12-04T09:25:57.3326302Z .. note:: 2025-12-04T09:25:57.3326444Z 2025-12-04T09:25:57.3326654Z In most situations, ``right_inverse`` will be a function such that 2025-12-04T09:25:57.3327118Z ``forward(right_inverse(X)) == X`` (see 2025-12-04T09:25:57.3327657Z `right inverse `_). 2025-12-04T09:25:57.3328349Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-12-04T09:25:57.3328846Z to relax this. 2025-12-04T09:25:57.3329004Z 2025-12-04T09:25:57.3331322Z .. warning:: 2025-12-04T09:25:57.3331481Z 2025-12-04T09:25:57.3331792Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-12-04T09:25:57.3332489Z will register a number of new parameters. If such parametrization is registered 2025-12-04T09:25:57.3333181Z after the optimizer is created, these new parameters will need to be added manually 2025-12-04T09:25:57.3333818Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-12-04T09:25:57.3334143Z 2025-12-04T09:25:57.3334228Z Args: 2025-12-04T09:25:57.3334576Z module (nn.Module): module on which to register the parametrization 2025-12-04T09:25:57.3335154Z tensor_name (str): name of the parameter or buffer on which to register 2025-12-04T09:25:57.3335603Z the parametrization 2025-12-04T09:25:57.3336020Z parametrization (nn.Module): the parametrization to register 2025-12-04T09:25:57.3336454Z Keyword args: 2025-12-04T09:25:57.3336939Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-12-04T09:25:57.3337496Z may change the dtype and shape of the tensor. Default: `False` 2025-12-04T09:25:57.3338117Z Warning: the parametrization is not checked for consistency upon registration. 2025-12-04T09:25:57.3338656Z Enable this flag at your own risk. 2025-12-04T09:25:57.3338895Z 2025-12-04T09:25:57.3339047Z Raises: 2025-12-04T09:25:57.3339480Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-12-04T09:25:57.3339922Z 2025-12-04T09:25:57.3340011Z Examples: 2025-12-04T09:25:57.3340309Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-12-04T09:25:57.3340673Z >>> import torch 2025-12-04T09:25:57.3340953Z >>> import torch.nn as nn 2025-12-04T09:25:57.3341304Z >>> import torch.nn.utils.parametrize as P 2025-12-04T09:25:57.3341646Z >>> 2025-12-04T09:25:57.3341889Z >>> class Symmetric(nn.Module): 2025-12-04T09:25:57.3342522Z >>> def forward(self, X): 2025-12-04T09:25:57.3342915Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-12-04T09:25:57.3343321Z >>> 2025-12-04T09:25:57.3343563Z >>> def right_inverse(self, A): 2025-12-04T09:25:57.3343886Z >>> return A.triu() 2025-12-04T09:25:57.3344185Z >>> 2025-12-04T09:25:57.3344416Z >>> m = nn.Linear(5, 5) 2025-12-04T09:25:57.3344785Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-12-04T09:25:57.3345326Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-12-04T09:25:57.3345797Z True 2025-12-04T09:25:57.3346036Z >>> A = torch.rand(5, 5) 2025-12-04T09:25:57.3346340Z >>> A = A + A.T # A is now symmetric 2025-12-04T09:25:57.3346784Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-12-04T09:25:57.3347252Z >>> print(torch.allclose(m.weight, A)) 2025-12-04T09:25:57.3347573Z True 2025-12-04T09:25:57.3347713Z 2025-12-04T09:25:57.3347820Z >>> class RankOne(nn.Module): 2025-12-04T09:25:57.3348145Z >>> def forward(self, x, y): 2025-12-04T09:25:57.3348516Z >>> # Form a rank 1 matrix multiplying two vectors 2025-12-04T09:25:57.3348909Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-12-04T09:25:57.3349259Z >>> 2025-12-04T09:25:57.3349497Z >>> def right_inverse(self, Z): 2025-12-04T09:25:57.3349836Z >>> # Project Z onto the rank 1 matrices 2025-12-04T09:25:57.3350232Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-12-04T09:25:57.3350641Z >>> # Return rescaled singular vectors 2025-12-04T09:25:57.3350993Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-12-04T09:25:57.3351396Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-12-04T09:25:57.3351766Z >>> 2025-12-04T09:25:57.3352035Z >>> linear_rank_one = P.register_parametrization( 2025-12-04T09:25:57.3352440Z ... nn.Linear(4, 4), "weight", RankOne() 2025-12-04T09:25:57.3352774Z ... ) 2025-12-04T09:25:57.3353126Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-12-04T09:25:57.3353547Z 1 2025-12-04T09:25:57.3353665Z 2025-12-04T09:25:57.3353758Z 2025-12-04T09:25:57.3354431Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 3, 0, '_._ = None\n', 3, -1)) 2025-12-04T09:25:57.3355124Z 2025-12-04T09:25:57.3355206Z _._ = None 2025-12-04T09:25:57.3355416Z ^ 2025-12-04T09:25:57.4412145Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py line=1586. 2025-12-04T09:25:57.4413165Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:25:57.4413773Z Reduce learning rate when a metric has stopped improving. 2025-12-04T09:25:57.4414363Z 2025-12-04T09:25:57.4414592Z Models often benefit from reducing the learning rate by a factor 2025-12-04T09:25:57.4415128Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-12-04T09:25:57.4415638Z quantity and if no improvement is seen for a 'patience' number 2025-12-04T09:25:57.4416093Z of epochs, the learning rate is reduced. 2025-12-04T09:25:57.4416435Z 2025-12-04T09:25:57.4416532Z Args: 2025-12-04T09:25:57.4416780Z optimizer (Optimizer): Wrapped optimizer. 2025-12-04T09:25:57.4417198Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-12-04T09:25:57.4417642Z be reduced when the quantity monitored has stopped 2025-12-04T09:25:57.4418082Z decreasing; in `max` mode it will be reduced when the 2025-12-04T09:25:57.4418580Z quantity monitored has stopped increasing. Default: 'min'. 2025-12-04T09:25:57.4419087Z factor (float): Factor by which the learning rate will be 2025-12-04T09:25:57.4419538Z reduced. new_lr = lr * factor. Default: 0.1. 2025-12-04T09:25:57.4420019Z patience (int): The number of allowed epochs with no improvement after 2025-12-04T09:25:57.4420512Z which the learning rate will be reduced. 2025-12-04T09:25:57.4421006Z For example, consider the case of having no patience (`patience = 0`). 2025-12-04T09:25:57.4421757Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-12-04T09:25:57.4422482Z In the second epoch, if the performance is worse than the baseline, 2025-12-04T09:25:57.4422982Z we have what is considered an intolerable epoch. 2025-12-04T09:25:57.4423544Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-12-04T09:25:57.4424115Z the learning rate is reduced at the end of this epoch. 2025-12-04T09:25:57.4424763Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-12-04T09:25:57.4425575Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-12-04T09:25:57.4426164Z the learning rate is not adjusted. 2025-12-04T09:25:57.4426489Z Default: 10. 2025-12-04T09:25:57.4426851Z threshold (float): Threshold for measuring the new optimum, 2025-12-04T09:25:57.4427340Z to only focus on significant changes. Default: 1e-4. 2025-12-04T09:25:57.4427798Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-12-04T09:25:57.4428268Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-12-04T09:25:57.4428710Z mode or best * ( 1 - threshold ) in `min` mode. 2025-12-04T09:25:57.4429131Z In `abs` mode, dynamic_threshold = best + threshold in 2025-12-04T09:25:57.4429604Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-12-04T09:25:57.4430100Z cooldown (int): Number of epochs to wait before resuming 2025-12-04T09:25:57.4430584Z normal operation after lr has been reduced. Default: 0. 2025-12-04T09:25:57.4431049Z min_lr (float or list): A scalar or a list of scalars. A 2025-12-04T09:25:57.4431506Z lower bound on the learning rate of all param groups 2025-12-04T09:25:57.4431932Z or each group respectively. Default: 0. 2025-12-04T09:25:57.4432363Z eps (float): Minimal decay applied to lr. If the difference 2025-12-04T09:25:57.4432857Z between new and old lr is smaller than eps, the update is 2025-12-04T09:25:57.4433273Z ignored. Default: 1e-8. 2025-12-04T09:25:57.4433482Z 2025-12-04T09:25:57.4433580Z Example: 2025-12-04T09:25:57.4433800Z >>> # xdoctest: +SKIP 2025-12-04T09:25:57.4434227Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-12-04T09:25:57.4434755Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-12-04T09:25:57.4435202Z >>> for epoch in range(10): 2025-12-04T09:25:57.4435517Z >>> train(...) 2025-12-04T09:25:57.4435801Z >>> val_loss = validate(...) 2025-12-04T09:25:57.4436169Z >>> # Note that step should be called after validate() 2025-12-04T09:25:57.4436567Z >>> scheduler.step(val_loss) 2025-12-04T09:25:57.4436805Z 2025-12-04T09:25:57.4437098Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-12-04T09:25:57.4437508Z 2025-12-04T09:25:57.4438051Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-12-04T09:25:57.4438625Z 2025-12-04T09:25:57.4438729Z scheduler.step(val_loss) 2025-12-04T09:25:57.4439007Z ^ 2025-12-04T09:26:00.9979325Z running 894 test(s) 2025-12-04T09:26:00.9984916Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::typename:0, line 1111 <- wrt source file 2025-12-04T09:26:01.0057792Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::typename:0 2025-12-04T09:26:01.0059867Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::is_tensor:0, line 1142 <- wrt source file 2025-12-04T09:26:01.0064730Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::is_tensor:0 2025-12-04T09:26:01.0066964Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::is_storage:0, line 1157 <- wrt source file 2025-12-04T09:26:01.0075891Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::is_storage:0 2025-12-04T09:26:01.0078275Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_device:0, line 1247 <- wrt source file 2025-12-04T09:26:01.0080803Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_device:0 2025-12-04T09:26:01.0083302Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1296 <- wrt source file 2025-12-04T09:26:01.0085995Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_tensor_type:0 2025-12-04T09:26:01.0088479Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_dtype:0, line 1333 <- wrt source file 2025-12-04T09:26:01.0090995Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::set_default_dtype:0 2025-12-04T09:26:01.0093515Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1497 <- wrt source file 2025-12-04T09:26:01.0096176Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::use_deterministic_algorithms:0 2025-12-04T09:26:01.0098533Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::compile:0, line 2655 <- wrt source file 2025-12-04T09:26:01.0100769Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::compile:0 2025-12-04T09:26:01.0103320Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2963 <- wrt source file 2025-12-04T09:26:01.0106227Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0 2025-12-04T09:26:01.0109004Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_C.cpython-310-x86_64-linux-gnu.so::Generator:0, line 15 <- wrt source file 2025-12-04T09:26:01.0112158Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_C.cpython-310-x86_64-linux-gnu.so::Generator:0 2025-12-04T09:26:01.0114962Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_C.cpython-310-x86_64-linux-gnu.so::_LinAlgError:0, line 5 <- wrt source file 2025-12-04T09:26:01.0117730Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_C.cpython-310-x86_64-linux-gnu.so::_LinAlgError:0 2025-12-04T09:26:01.0120310Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file 2025-12-04T09:26:01.0122607Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::custom_op:0 2025-12-04T09:26:01.0124683Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file 2025-12-04T09:26:01.0126777Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::impl:0 2025-12-04T09:26:01.0129017Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file 2025-12-04T09:26:01.0656612Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_custom_ops.py::impl_abstract:0 2025-12-04T09:26:01.0659329Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file 2025-12-04T09:26:01.0661863Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_namedtensor_internals.py::update_names:0 2025-12-04T09:26:01.0664077Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 681 <- wrt source file 2025-12-04T09:26:01.0868934Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.register_hook:0 2025-12-04T09:26:01.0871513Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 738 <- wrt source file 2025-12-04T09:26:01.1361385Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0 2025-12-04T09:26:01.1363812Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1374 <- wrt source file 2025-12-04T09:26:01.1517783Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.refine_names:0 2025-12-04T09:26:01.1522219Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1419 <- wrt source file 2025-12-04T09:26:01.1530097Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.align_to:0 2025-12-04T09:26:01.1532563Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.rename:0, line 1492 <- wrt source file 2025-12-04T09:26:01.1557421Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.rename:0 2025-12-04T09:26:01.1559583Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1522 <- wrt source file 2025-12-04T09:26:01.1765792Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0 2025-12-04T09:26:01.1768210Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.dim_order:0, line 1554 <- wrt source file 2025-12-04T09:26:01.1799068Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py::Tensor.dim_order:0 2025-12-04T09:26:01.1801641Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file 2025-12-04T09:26:01.1854606Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor_str.py::set_printoptions:0 2025-12-04T09:26:01.1856973Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file 2025-12-04T09:26:01.1890877Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::broadcast_tensors:0 2025-12-04T09:26:01.1893249Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file 2025-12-04T09:26:01.1897226Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::broadcast_shapes:0 2025-12-04T09:26:01.1899444Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::split:0, line 144 <- wrt source file 2025-12-04T09:26:01.1928906Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::split:0 2025-12-04T09:26:01.1930997Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::einsum:0, line 258 <- wrt source file 2025-12-04T09:26:01.2006563Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::einsum:0 2025-12-04T09:26:01.2008777Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::meshgrid:0, line 450 <- wrt source file 2025-12-04T09:26:01.2061792Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::meshgrid:0 2025-12-04T09:26:01.2063930Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_unique_impl:0, line 835 <- wrt source file 2025-12-04T09:26:01.2218896Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_unique_impl:0 2025-12-04T09:26:01.2221273Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 992 <- wrt source file 2025-12-04T09:26:01.2235284Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_unique_consecutive_impl:0 2025-12-04T09:26:01.2237676Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::tensordot:0, line 1267 <- wrt source file 2025-12-04T09:26:01.2342606Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::tensordot:0 2025-12-04T09:26:01.2345006Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::cartesian_prod:0, line 1351 <- wrt source file 2025-12-04T09:26:01.2353702Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::cartesian_prod:0 2025-12-04T09:26:01.2356149Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::block_diag:0, line 1385 <- wrt source file 2025-12-04T09:26:01.2377791Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::block_diag:0 2025-12-04T09:26:01.2380116Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::cdist:0, line 1441 <- wrt source file 2025-12-04T09:26:01.2406842Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::cdist:0 2025-12-04T09:26:01.2408942Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_1d:0, line 1482 <- wrt source file 2025-12-04T09:26:01.2438043Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_1d:0 2025-12-04T09:26:01.2440458Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_2d:0, line 1520 <- wrt source file 2025-12-04T09:26:01.2462482Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_2d:0 2025-12-04T09:26:01.2464649Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_3d:0, line 1560 <- wrt source file 2025-12-04T09:26:01.2491750Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::atleast_3d:0 2025-12-04T09:26:01.2493949Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::norm:0, line 1735 <- wrt source file 2025-12-04T09:26:01.2570689Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::norm:0 2025-12-04T09:26:01.2572997Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::unravel_index:0, line 1905 <- wrt source file 2025-12-04T09:26:01.2617405Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::unravel_index:0 2025-12-04T09:26:01.2619864Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::chain_matmul:0, line 2005 <- wrt source file 2025-12-04T09:26:01.2622409Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::chain_matmul:0 2025-12-04T09:26:01.2624765Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_lu_impl:0, line 2106 <- wrt source file 2025-12-04T09:26:01.2627204Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/functional.py::_lu_impl:0 2025-12-04T09:26:01.2629297Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::list:0, line 477 <- wrt source file 2025-12-04T09:26:01.2631223Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::list:0 2025-12-04T09:26:01.2633035Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::help:0, line 537 <- wrt source file 2025-12-04T09:26:01.2635107Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::help:0 2025-12-04T09:26:01.2637075Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::load:0, line 628 <- wrt source file 2025-12-04T09:26:01.2638949Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::load:0 2025-12-04T09:26:01.2640790Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::_load_local:0, line 676 <- wrt source file 2025-12-04T09:26:01.2642983Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::_load_local:0 2025-12-04T09:26:01.2645044Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::download_url_to_file:0, line 711 <- wrt source file 2025-12-04T09:26:01.2647250Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::download_url_to_file:0 2025-12-04T09:26:01.2649649Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::load_state_dict_from_url:0, line 852 <- wrt source file 2025-12-04T09:26:01.2652032Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/hub.py::load_state_dict_from_url:0 2025-12-04T09:26:01.2654228Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library.define:0, line 145 <- wrt source file 2025-12-04T09:26:01.2656637Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library.define:0 2025-12-04T09:26:01.2659421Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 239 <- wrt source file 2025-12-04T09:26:01.2662056Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library._impl_with_aoti_compile:0 2025-12-04T09:26:01.2664284Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library.impl:0, line 300 <- wrt source file 2025-12-04T09:26:01.2666595Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::Library.impl:0 2025-12-04T09:26:01.2668464Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::define:0, line 521 <- wrt source file 2025-12-04T09:26:01.2725180Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::define:0 2025-12-04T09:26:01.2727411Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::impl:0, line 627 <- wrt source file 2025-12-04T09:26:01.2746436Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::impl:0 2025-12-04T09:26:01.2748827Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_kernel:0, line 809 <- wrt source file 2025-12-04T09:26:01.2751364Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_kernel:0 2025-12-04T09:26:01.2753879Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_autocast:0, line 877 <- wrt source file 2025-12-04T09:26:01.2756453Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_autocast:0 2025-12-04T09:26:01.2758995Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_autograd:0, line 1164 <- wrt source file 2025-12-04T09:26:01.3016854Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_autograd:0 2025-12-04T09:26:01.3019496Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_torch_dispatch:0, line 1280 <- wrt source file 2025-12-04T09:26:01.3119162Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_torch_dispatch:0 2025-12-04T09:26:01.3121697Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_vmap:0, line 1369 <- wrt source file 2025-12-04T09:26:01.3348686Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::register_vmap:0 2025-12-04T09:26:01.3350889Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::opcheck:0, line 1694 <- wrt source file 2025-12-04T09:26:01.3353050Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py::opcheck:0 2025-12-04T09:26:01.3355155Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::get_ignored_functions:0, line 117 <- wrt source file 2025-12-04T09:26:01.3359738Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::get_ignored_functions:0 2025-12-04T09:26:01.3362154Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::get_testing_overrides:0, line 435 <- wrt source file 2025-12-04T09:26:01.3404741Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::get_testing_overrides:0 2025-12-04T09:26:01.3407172Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::wrap_torch_function:0, line 1589 <- wrt source file 2025-12-04T09:26:01.3410366Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::wrap_torch_function:0 2025-12-04T09:26:01.3413040Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::handle_torch_function:0, line 1725 <- wrt source file 2025-12-04T09:26:01.3416340Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::handle_torch_function:0 2025-12-04T09:26:01.3418993Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1974 <- wrt source file 2025-12-04T09:26:01.3456519Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::is_tensor_method_or_property:0 2025-12-04T09:26:01.3458968Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::is_tensor_like:0, line 1993 <- wrt source file 2025-12-04T09:26:01.3468628Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/overrides.py::is_tensor_like:0 2025-12-04T09:26:01.3471106Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file 2025-12-04T09:26:01.3473595Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/quasirandom.py::SobolEngine:0 2025-12-04T09:26:01.3476099Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::add_safe_globals:0, line 300 <- wrt source file 2025-12-04T09:26:01.3478753Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::add_safe_globals:0 2025-12-04T09:26:01.3481208Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::safe_globals:0, line 325 <- wrt source file 2025-12-04T09:26:01.3483587Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::safe_globals:0 2025-12-04T09:26:01.3486076Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::skip_data:0, line 401 <- wrt source file 2025-12-04T09:26:01.3488522Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::skip_data:0 2025-12-04T09:26:01.3491019Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::register_package:0, line 473 <- wrt source file 2025-12-04T09:26:01.3493671Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::register_package:0 2025-12-04T09:26:01.3496049Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::save:0, line 960 <- wrt source file 2025-12-04T09:26:01.3498377Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::save:0 2025-12-04T09:26:01.3500591Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::load:0, line 1379 <- wrt source file 2025-12-04T09:26:01.3502963Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/serialization.py::load:0 2025-12-04T09:26:01.3505170Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file 2025-12-04T09:26:01.3507674Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/torch_version.py::TorchVersion:0 2025-12-04T09:26:01.3510180Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 349 <- wrt source file 2025-12-04T09:26:01.3512851Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/__init__.py::list_mode_options:0 2025-12-04T09:26:01.3515612Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/__init__.py::list_options:0, line 388 <- wrt source file 2025-12-04T09:26:01.3527636Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/__init__.py::list_options:0 2025-12-04T09:26:01.3530235Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_prims_common/__init__.py::compute_required_storage_length:0, line 1911 <- wrt source file 2025-12-04T09:26:01.3536868Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_prims_common/__init__.py::compute_required_storage_length:0 2025-12-04T09:26:01.3539641Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 117 <- wrt source file 2025-12-04T09:26:01.3550790Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::current_accelerator:0 2025-12-04T09:26:01.3553586Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::get_device_capability:0, line 171 <- wrt source file 2025-12-04T09:26:01.3556365Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::get_device_capability:0 2025-12-04T09:26:01.3559028Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::device_index:0, line 276 <- wrt source file 2025-12-04T09:26:01.3561542Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py::device_index:0 2025-12-04T09:26:01.3563941Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 130 <- wrt source file 2025-12-04T09:26:01.3566550Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::allow_in_graph:0 2025-12-04T09:26:01.3568873Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 186 <- wrt source file 2025-12-04T09:26:01.6328364Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::substitute_in_graph:0 2025-12-04T09:26:01.6330615Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 416 <- wrt source file 2025-12-04T09:26:01.6332991Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::wrap_numpy:0 2025-12-04T09:26:01.6335417Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_compiling:0, line 448 <- wrt source file 2025-12-04T09:26:01.6337895Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_compiling:0 2025-12-04T09:26:01.6340469Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0, line 469 <- wrt source file 2025-12-04T09:26:01.6343466Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0 2025-12-04T09:26:01.6345926Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_exporting:0, line 487 <- wrt source file 2025-12-04T09:26:01.6348593Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::is_exporting:0 2025-12-04T09:26:01.6351235Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 502 <- wrt source file 2025-12-04T09:26:01.6354022Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0 2025-12-04T09:26:01.6357009Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 522 <- wrt source file 2025-12-04T09:26:01.6359809Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0 2025-12-04T09:26:01.6362425Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1788 <- wrt source file 2025-12-04T09:26:01.6365290Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py::_compile_kernel:0 2025-12-04T09:26:01.6367575Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::save:0, line 349 <- wrt source file 2025-12-04T09:26:01.6369760Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::save:0 2025-12-04T09:26:01.6372027Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::load:0, line 422 <- wrt source file 2025-12-04T09:26:01.6374292Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::load:0 2025-12-04T09:26:01.6376564Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::register_dataclass:0, line 581 <- wrt source file 2025-12-04T09:26:01.6379150Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/__init__.py::register_dataclass:0 2025-12-04T09:26:01.6381586Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.then:0, line 152 <- wrt source file 2025-12-04T09:26:01.6384118Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.then:0 2025-12-04T09:26:01.6386768Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 201 <- wrt source file 2025-12-04T09:26:01.6389539Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.add_done_callback:0 2025-12-04T09:26:01.6392192Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.set_result:0, line 235 <- wrt source file 2025-12-04T09:26:01.6394746Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.set_result:0 2025-12-04T09:26:01.6397321Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 265 <- wrt source file 2025-12-04T09:26:01.6400036Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::Future.set_exception:0 2025-12-04T09:26:01.6402384Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::collect_all:0, line 299 <- wrt source file 2025-12-04T09:26:01.6404277Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/futures/__init__.py::collect_all:0 2025-12-04T09:26:01.6405530Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/jit/__init__.py::annotate:0, line 147 <- wrt source file 2025-12-04T09:26:01.6406755Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/jit/__init__.py::annotate:0 2025-12-04T09:26:01.6408063Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0, line 22 <- wrt source file 2025-12-04T09:26:01.6409527Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0 2025-12-04T09:26:01.6411003Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/mps/__init__.py::compile_shader:0, line 148 <- wrt source file 2025-12-04T09:26:01.6412281Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/mps/__init__.py::compile_shader:0 2025-12-04T09:26:01.6413806Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::as_nested_tensor:0, line 61 <- wrt source file 2025-12-04T09:26:01.6495545Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::as_nested_tensor:0 2025-12-04T09:26:01.6497936Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::nested_tensor:0, line 240 <- wrt source file 2025-12-04T09:26:01.6504258Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::nested_tensor:0 2025-12-04T09:26:01.6506626Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::narrow:0, line 315 <- wrt source file 2025-12-04T09:26:01.6611398Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::narrow:0 2025-12-04T09:26:01.6613840Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0, line 405 <- wrt source file 2025-12-04T09:26:01.6621608Z W1204 09:26:01.661000 1827 site-packages/torch/fx/_symbolic_trace.py:53] is_fx_tracing will return true for both fx.symbolic_trace and torch.export. Please use is_fx_tracing_symbolic_tracing() for specifically fx.symbolic_trace or torch.compiler.is_compiling() for specifically torch.export/compile. 2025-12-04T09:26:01.6642705Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0 2025-12-04T09:26:01.6645298Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::masked_select:0, line 481 <- wrt source file 2025-12-04T09:26:01.6699742Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nested/__init__.py::masked_select:0 2025-12-04T09:26:01.6702092Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::sum:0, line 223 <- wrt source file 2025-12-04T09:26:01.6757923Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::sum:0 2025-12-04T09:26:01.6760443Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0, line 475 <- wrt source file 2025-12-04T09:26:01.6863022Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0 2025-12-04T09:26:01.6865636Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::as_sparse_gradcheck:0, line 561 <- wrt source file 2025-12-04T09:26:01.6960378Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/__init__.py::as_sparse_gradcheck:0 2025-12-04T09:26:01.6963077Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0, line 361 <- wrt source file 2025-12-04T09:26:01.6967128Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0 2025-12-04T09:26:01.6969054Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0, line 328 <- wrt source file 2025-12-04T09:26:01.6971049Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0 2025-12-04T09:26:01.6973406Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/higher_order_ops.py::speculate_subgraph_with_auto_output_flattening:0, line 1316 <- wrt source file 2025-12-04T09:26:01.6975797Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/higher_order_ops.py::speculate_subgraph_with_auto_output_flattening:0 2025-12-04T09:26:01.6977904Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0, line 1441 <- wrt source file 2025-12-04T09:26:01.6979962Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0 2025-12-04T09:26:01.6982009Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0, line 194 <- wrt source file 2025-12-04T09:26:01.6984175Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0 2025-12-04T09:26:01.6986118Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/wrappers.py::allow_in_pre_dispatch_graph:0, line 262 <- wrt source file 2025-12-04T09:26:01.6987982Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/wrappers.py::allow_in_pre_dispatch_graph:0 2025-12-04T09:26:01.6989770Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py::aot_function:0, line 771 <- wrt source file 2025-12-04T09:26:01.7359993Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py::aot_function:0 2025-12-04T09:26:01.7361447Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0, line 184 <- wrt source file 2025-12-04T09:26:01.7362986Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0 2025-12-04T09:26:01.7364442Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::vjp:0, line 234 <- wrt source file 2025-12-04T09:26:01.7485865Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::vjp:0 2025-12-04T09:26:01.7487206Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jacrev:0, line 476 <- wrt source file 2025-12-04T09:26:01.7607955Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jacrev:0 2025-12-04T09:26:01.7609312Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jvp:0, line 1024 <- wrt source file 2025-12-04T09:26:02.0231369Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jvp:0 2025-12-04T09:26:02.0232746Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0, line 1182 <- wrt source file 2025-12-04T09:26:02.0308628Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0 2025-12-04T09:26:02.0310012Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::hessian:0, line 1342 <- wrt source file 2025-12-04T09:26:02.0332804Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::hessian:0 2025-12-04T09:26:02.0334204Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1506 <- wrt source file 2025-12-04T09:26:02.0339026Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::functionalize:0 2025-12-04T09:26:02.0340456Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1705 <- wrt source file 2025-12-04T09:26:02.0554346Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/eager_transforms.py::linearize:0 2025-12-04T09:26:02.0555920Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file 2025-12-04T09:26:02.0560607Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/functional_call.py::functional_call:0 2025-12-04T09:26:02.0561994Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file 2025-12-04T09:26:02.0563338Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/fx_minifier.py::minifier:0 2025-12-04T09:26:02.0564891Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1111 <- wrt source file 2025-12-04T09:26:02.0566574Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0 2025-12-04T09:26:02.0568204Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0, line 1166 <- wrt source file 2025-12-04T09:26:02.0569879Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0 2025-12-04T09:26:02.0571447Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 183 <- wrt source file 2025-12-04T09:26:02.0572987Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0 2025-12-04T09:26:02.0574542Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 319 <- wrt source file 2025-12-04T09:26:02.0576151Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0 2025-12-04T09:26:02.0577561Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 139 <- wrt source file 2025-12-04T09:26:02.0578843Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/cond.py::cond:0 2025-12-04T09:26:02.0580209Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file 2025-12-04T09:26:02.0581691Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0 2025-12-04T09:26:02.0583017Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/map.py::map:0, line 80 <- wrt source file 2025-12-04T09:26:02.0584286Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/map.py::map:0 2025-12-04T09:26:02.0585786Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/partitioner.py::HopPartitionedGraph._reorder_fw_output:0, line 133 <- wrt source file 2025-12-04T09:26:02.0587648Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/partitioner.py::HopPartitionedGraph._reorder_fw_output:0 2025-12-04T09:26:02.0589098Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 130 <- wrt source file 2025-12-04T09:26:02.0590381Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_higher_order_ops/scan.py::scan:0 2025-12-04T09:26:02.0591799Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/codecache.py::WritableTempFile:0, line 385 <- wrt source file 2025-12-04T09:26:02.0593203Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/codecache.py::WritableTempFile:0 2025-12-04T09:26:02.0594685Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1845 <- wrt source file 2025-12-04T09:26:02.0596290Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0 2025-12-04T09:26:02.0597832Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 4328 <- wrt source file 2025-12-04T09:26:02.0599341Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0 2025-12-04T09:26:02.0600818Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/fx_passes/graph_view.py::_clean_stack_name:0, line 100 <- wrt source file 2025-12-04T09:26:02.0602298Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/fx_passes/graph_view.py::_clean_stack_name:0 2025-12-04T09:26:02.0603745Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/kernel/custom_op.py::CustomOpConfig:0, line 56 <- wrt source file 2025-12-04T09:26:02.0605310Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/kernel/custom_op.py::CustomOpConfig:0 2025-12-04T09:26:02.0606812Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/kernel/custom_op.py::register_custom_op_autotuning:0, line 423 <- wrt source file 2025-12-04T09:26:02.0608411Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/kernel/custom_op.py::register_custom_op_autotuning:0 2025-12-04T09:26:02.0609992Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/runtime/caching/locks.py::_acquire_lock_with_timeout:0, line 69 <- wrt source file 2025-12-04T09:26:02.0611614Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/runtime/caching/locks.py::_unsafe_acquire_flock_with_timeout:0, line 179 <- wrt source file 2025-12-04T09:26:02.0621657Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/runtime/caching/locks.py::_unsafe_acquire_flock_with_timeout:0 2025-12-04T09:26:02.0623345Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/template_heuristics/registry.py::register_template_heuristic:0, line 54 <- wrt source file 2025-12-04T09:26:02.0625052Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_inductor/template_heuristics/registry.py::register_template_heuristic:0 2025-12-04T09:26:02.0626606Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::custom_op:0, line 101 <- wrt source file 2025-12-04T09:26:02.1041471Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::custom_op:0 2025-12-04T09:26:02.1043311Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 241 <- wrt source file 2025-12-04T09:26:02.1155376Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0 2025-12-04T09:26:02.1156868Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 310 <- wrt source file 2025-12-04T09:26:02.1158392Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0 2025-12-04T09:26:02.1159881Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0, line 549 <- wrt source file 2025-12-04T09:26:02.1378634Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0 2025-12-04T09:26:02.1380122Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 724 <- wrt source file 2025-12-04T09:26:02.1599930Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0 2025-12-04T09:26:02.1601418Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 810 <- wrt source file 2025-12-04T09:26:02.1602955Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0 2025-12-04T09:26:02.1604499Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 273 <- wrt source file 2025-12-04T09:26:02.1606020Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0 2025-12-04T09:26:02.1607479Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file 2025-12-04T09:26:02.1704249Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0 2025-12-04T09:26:02.1705650Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 53 <- wrt source file 2025-12-04T09:26:02.1713672Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/infer_schema.py::infer_schema:0 2025-12-04T09:26:02.1714966Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/triton.py::triton_op:0, line 136 <- wrt source file 2025-12-04T09:26:02.1716221Z * SKIPPED: 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2025-12-04T09:26:02.1759703Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::print_assert_equal:0, line 302 <- wrt source file 2025-12-04T09:26:02.1761121Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::print_assert_equal:0 2025-12-04T09:26:02.1762496Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_almost_equal:0, line 375 <- wrt source file 2025-12-04T09:26:02.1810417Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_almost_equal:0 2025-12-04T09:26:02.1811813Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_approx_equal:0, line 496 <- wrt source file 2025-12-04T09:26:02.1814820Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_approx_equal:0 2025-12-04T09:26:02.1816205Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_equal:0, line 793 <- wrt source file 2025-12-04T09:26:02.1909965Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_equal:0 2025-12-04T09:26:02.1911401Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal:0, line 899 <- wrt source file 2025-12-04T09:26:02.1975827Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal:0 2025-12-04T09:26:02.1977259Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file 2025-12-04T09:26:02.2033503Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0 2025-12-04T09:26:02.2034914Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file 2025-12-04T09:26:02.2036347Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0 2025-12-04T09:26:02.2037735Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file 2025-12-04T09:26:02.2075977Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0 2025-12-04T09:26:02.2077433Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file 2025-12-04T09:26:02.2081567Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0 2025-12-04T09:26:02.2083041Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file 2025-12-04T09:26:02.2087148Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0 2025-12-04T09:26:02.2088593Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file 2025-12-04T09:26:02.2089925Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0 2025-12-04T09:26:02.2091241Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file 2025-12-04T09:26:02.2095163Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::assert_warns:0 2025-12-04T09:26:02.2096561Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::clear_and_catch_warnings:0, line 1881 <- wrt source file 2025-12-04T09:26:02.2098929Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_numpy/testing/utils.py::clear_and_catch_warnings:0 2025-12-04T09:26:02.2100290Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file 2025-12-04T09:26:02.2101592Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_prims/context.py::TorchRefsMode:0 2025-12-04T09:26:02.2103013Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/complex_tensor/_ops/common.py::is_complex_tensor:0, line 47 <- wrt source file 2025-12-04T09:26:02.2104595Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/complex_tensor/_ops/common.py::is_complex_tensor:0 2025-12-04T09:26:02.2106004Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file 2025-12-04T09:26:02.2107272Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/amp/grad_scaler.py::GradScaler:0 2025-12-04T09:26:02.2108706Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 34 <- wrt source file 2025-12-04T09:26:02.2110315Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0 2025-12-04T09:26:02.2111982Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file 2025-12-04T09:26:02.2113780Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0 2025-12-04T09:26:02.2115472Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file 2025-12-04T09:26:02.2117169Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0 2025-12-04T09:26:02.2118856Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file 2025-12-04T09:26:02.2120586Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0 2025-12-04T09:26:02.2122355Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file 2025-12-04T09:26:02.2124040Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0 2025-12-04T09:26:02.2137155Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 29 <- wrt source file 2025-12-04T09:26:02.2213943Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0 2025-12-04T09:26:02.2215532Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file 2025-12-04T09:26:02.2250781Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0 2025-12-04T09:26:02.2253093Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 210 <- wrt source file 2025-12-04T09:26:02.2254505Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0 2025-12-04T09:26:02.2255880Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0, line 282 <- wrt source file 2025-12-04T09:26:02.2257280Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0 2025-12-04T09:26:02.2258626Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 358 <- wrt source file 2025-12-04T09:26:02.2260015Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0 2025-12-04T09:26:02.2261413Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file 2025-12-04T09:26:02.2262902Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0 2025-12-04T09:26:02.2264342Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file 2025-12-04T09:26:02.2269485Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0 2025-12-04T09:26:02.2270970Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file 2025-12-04T09:26:02.2272509Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0 2025-12-04T09:26:02.2274003Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 126 <- wrt source file 2025-12-04T09:26:02.2275510Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0 2025-12-04T09:26:02.2276996Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 212 <- wrt source file 2025-12-04T09:26:02.2278513Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0 2025-12-04T09:26:02.2280067Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 300 <- wrt source file 2025-12-04T09:26:02.2281898Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0 2025-12-04T09:26:02.2283506Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 383 <- wrt source file 2025-12-04T09:26:02.2285243Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0 2025-12-04T09:26:02.2286953Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 466 <- wrt source file 2025-12-04T09:26:02.2288589Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0 2025-12-04T09:26:02.2290148Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file 2025-12-04T09:26:02.2291681Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0 2025-12-04T09:26:02.2293162Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 516 <- wrt source file 2025-12-04T09:26:02.2294645Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0 2025-12-04T09:26:02.2296092Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 803 <- wrt source file 2025-12-04T09:26:02.2297553Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0 2025-12-04T09:26:02.2299024Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1209 <- wrt source file 2025-12-04T09:26:02.2300542Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0 2025-12-04T09:26:02.2302043Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1276 <- wrt source file 2025-12-04T09:26:02.2303576Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0 2025-12-04T09:26:02.2305079Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1329 <- wrt source file 2025-12-04T09:26:02.2306594Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0 2025-12-04T09:26:02.2308271Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file 2025-12-04T09:26:02.2310173Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0 2025-12-04T09:26:02.2311949Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv1d:0, line 376 <- wrt source file 2025-12-04T09:26:02.2313735Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv1d:0 2025-12-04T09:26:02.2315472Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 506 <- wrt source file 2025-12-04T09:26:02.2317256Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0 2025-12-04T09:26:02.2319054Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 636 <- wrt source file 2025-12-04T09:26:02.2320844Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0 2025-12-04T09:26:02.2322678Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 893 <- wrt source file 2025-12-04T09:26:02.2324763Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0 2025-12-04T09:26:02.2326681Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1015 <- wrt source file 2025-12-04T09:26:02.2328625Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0 2025-12-04T09:26:02.2330539Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1141 <- wrt source file 2025-12-04T09:26:02.2332492Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0 2025-12-04T09:26:02.2334425Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file 2025-12-04T09:26:02.2336397Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0 2025-12-04T09:26:02.2338371Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file 2025-12-04T09:26:02.2340404Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0 2025-12-04T09:26:02.2342666Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file 2025-12-04T09:26:02.2344853Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0 2025-12-04T09:26:02.2346923Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file 2025-12-04T09:26:02.2349062Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0 2025-12-04T09:26:02.2350989Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 135 <- wrt source file 2025-12-04T09:26:02.2352813Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0 2025-12-04T09:26:02.2354551Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/rnn.py::LSTM:0, line 24 <- wrt source file 2025-12-04T09:26:02.2356285Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/nn/quantized/modules/rnn.py::LSTM:0 2025-12-04T09:26:02.2358451Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py::BaseDataScheduler.get_schedule_param:0, line 98 <- wrt source file 2025-12-04T09:26:02.2385815Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py::BaseDataScheduler.get_schedule_param:0 2025-12-04T09:26:02.2388439Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file 2025-12-04T09:26:02.2390882Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0 2025-12-04T09:26:02.2393118Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file 2025-12-04T09:26:02.2395086Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0 2025-12-04T09:26:02.2397057Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file 2025-12-04T09:26:02.2399129Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0 2025-12-04T09:26:02.2401251Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier.squash_mask:0, line 251 <- wrt source file 2025-12-04T09:26:02.2403487Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier.squash_mask:0 2025-12-04T09:26:02.2405527Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 175 <- wrt source file 2025-12-04T09:26:02.2407391Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0 2025-12-04T09:26:02.2409297Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 32 <- wrt source file 2025-12-04T09:26:02.2411270Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0 2025-12-04T09:26:02.2413255Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 83 <- wrt source file 2025-12-04T09:26:02.2417849Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0 2025-12-04T09:26:02.2419860Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 143 <- wrt source file 2025-12-04T09:26:02.2424586Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0 2025-12-04T09:26:02.2426601Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 182 <- wrt source file 2025-12-04T09:26:02.2431942Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0 2025-12-04T09:26:02.2433851Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file 2025-12-04T09:26:02.2435626Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/observer.py::_with_args:0 2025-12-04T09:26:02.2437425Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file 2025-12-04T09:26:02.2439414Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0 2025-12-04T09:26:02.2441219Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file 2025-12-04T09:26:02.2443203Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0 2025-12-04T09:26:02.2445200Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file 2025-12-04T09:26:02.2447032Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0 2025-12-04T09:26:02.2448841Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file 2025-12-04T09:26:02.2450752Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0 2025-12-04T09:26:02.2452571Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file 2025-12-04T09:26:02.2454389Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0 2025-12-04T09:26:02.2456254Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file 2025-12-04T09:26:02.2458257Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0 2025-12-04T09:26:02.2460312Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file 2025-12-04T09:26:02.2462494Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0 2025-12-04T09:26:02.2464532Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file 2025-12-04T09:26:02.2466037Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0 2025-12-04T09:26:02.2468146Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file 2025-12-04T09:26:02.2469710Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0 2025-12-04T09:26:02.2471205Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file 2025-12-04T09:26:02.2473188Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0 2025-12-04T09:26:02.2475209Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 171 <- wrt source file 2025-12-04T09:26:02.2477464Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0 2025-12-04T09:26:02.2479663Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 553 <- wrt source file 2025-12-04T09:26:02.2481518Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0 2025-12-04T09:26:02.2483103Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 575 <- wrt source file 2025-12-04T09:26:02.2484897Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0 2025-12-04T09:26:02.2486508Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 589 <- wrt source file 2025-12-04T09:26:02.2488425Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0 2025-12-04T09:26:02.2489987Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 611 <- wrt source file 2025-12-04T09:26:02.2491414Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0 2025-12-04T09:26:02.2492826Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 738 <- wrt source file 2025-12-04T09:26:02.2494247Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0 2025-12-04T09:26:02.2495790Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/backend_config/backend_config.py::DTypeConfig:0, line 216 <- wrt source file 2025-12-04T09:26:02.2497760Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/backend_config/backend_config.py::DTypeConfig:0 2025-12-04T09:26:02.2499542Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file 2025-12-04T09:26:02.2501271Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0 2025-12-04T09:26:02.2503065Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report.py::ModelReport:0, line 85 <- wrt source file 2025-12-04T09:26:02.2504709Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report.py::ModelReport:0 2025-12-04T09:26:02.2506731Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_filtered_tables:0, line 341 <- wrt source file 2025-12-04T09:26:02.2508909Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_filtered_tables:0 2025-12-04T09:26:02.2511062Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_table_visualization:0, line 429 <- wrt source file 2025-12-04T09:26:02.2513400Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_table_visualization:0 2025-12-04T09:26:02.2515683Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_plot_visualization:0, line 591 <- wrt source file 2025-12-04T09:26:02.2517895Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_plot_visualization:0 2025-12-04T09:26:02.2520318Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py::ModelReportVisualizer.generate_histogram_visualization:0, line 664 <- wrt source file 2025-12-04T09:26:02.2522584Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0, line 189 <- wrt source file 2025-12-04T09:26:02.2533586Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0 2025-12-04T09:26:02.2535401Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0, line 442 <- wrt source file 2025-12-04T09:26:02.2537160Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0 2025-12-04T09:26:02.2538693Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0, line 28 <- wrt source file 2025-12-04T09:26:02.2540093Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0 2025-12-04T09:26:02.2541531Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file 2025-12-04T09:26:02.2543373Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::make_dual:0 2025-12-04T09:26:02.2544688Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::unpack_dual:0, line 151 <- wrt source file 2025-12-04T09:26:02.2546037Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::unpack_dual:0 2025-12-04T09:26:02.2547338Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::dual_level:0, line 187 <- wrt source file 2025-12-04T09:26:02.2548668Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/forward_ad.py::dual_level:0 2025-12-04T09:26:02.2550078Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0, line 72 <- wrt source file 2025-12-04T09:26:02.2551621Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0 2025-12-04T09:26:02.2553114Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0, line 116 <- wrt source file 2025-12-04T09:26:02.2554642Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0 2025-12-04T09:26:02.2556223Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0, line 169 <- wrt source file 2025-12-04T09:26:02.2557688Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0 2025-12-04T09:26:02.2559208Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0, line 216 <- wrt source file 2025-12-04T09:26:02.2561048Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0 2025-12-04T09:26:02.2562637Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0, line 245 <- wrt source file 2025-12-04T09:26:02.2564386Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0 2025-12-04T09:26:02.2565813Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::Function:0, line 487 <- wrt source file 2025-12-04T09:26:02.2567108Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/function.py::Function:0 2025-12-04T09:26:02.2568361Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::vjp:0, line 300 <- wrt source file 2025-12-04T09:26:02.2569637Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::vjp:0 2025-12-04T09:26:02.2570879Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::jvp:0, line 402 <- wrt source file 2025-12-04T09:26:02.2572147Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::jvp:0 2025-12-04T09:26:02.2573406Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::jacobian:0, line 642 <- wrt source file 2025-12-04T09:26:02.2574724Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::jacobian:0 2025-12-04T09:26:02.2576008Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::hessian:0, line 907 <- wrt source file 2025-12-04T09:26:02.2577321Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::hessian:0 2025-12-04T09:26:02.2578716Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::vhp:0, line 1026 <- wrt source file 2025-12-04T09:26:02.2579996Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::vhp:0 2025-12-04T09:26:02.2581824Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::hvp:0, line 1125 <- wrt source file 2025-12-04T09:26:02.2583391Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/functional.py::hvp:0 2025-12-04T09:26:02.2584614Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::no_grad:0, line 50 <- wrt source file 2025-12-04T09:26:02.2585894Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::no_grad:0 2025-12-04T09:26:02.2587172Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::enable_grad:0, line 108 <- wrt source file 2025-12-04T09:26:02.2588487Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::enable_grad:0 2025-12-04T09:26:02.2589903Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0, line 166 <- wrt source file 2025-12-04T09:26:02.2591280Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0 2025-12-04T09:26:02.2592626Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::inference_mode:0, line 252 <- wrt source file 2025-12-04T09:26:02.2594046Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py::inference_mode:0 2025-12-04T09:26:02.2595338Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.name:0, line 60 <- wrt source file 2025-12-04T09:26:02.2596900Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.name:0 2025-12-04T09:26:02.2598203Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.register_hook:0, line 117 <- wrt source file 2025-12-04T09:26:02.2599565Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.register_hook:0 2025-12-04T09:26:02.2600918Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 154 <- wrt source file 2025-12-04T09:26:02.2602335Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::Node.register_prehook:0 2025-12-04T09:26:02.2603692Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 292 <- wrt source file 2025-12-04T09:26:02.2605142Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0 2025-12-04T09:26:02.2606448Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::save_on_cpu:0, line 362 <- wrt source file 2025-12-04T09:26:02.2607714Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::save_on_cpu:0 2025-12-04T09:26:02.2609074Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0, line 419 <- wrt source file 2025-12-04T09:26:02.2610549Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0 2025-12-04T09:26:02.2611969Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0, line 503 <- wrt source file 2025-12-04T09:26:02.2613395Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0 2025-12-04T09:26:02.2614836Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0, line 777 <- wrt source file 2025-12-04T09:26:02.2618393Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0 2025-12-04T09:26:02.2620157Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::profile:0, line 182 <- wrt source file 2025-12-04T09:26:02.2622007Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::profile:0 2025-12-04T09:26:02.2623605Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::record_function:0, line 760 <- wrt source file 2025-12-04T09:26:02.2625781Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::record_function:0 2025-12-04T09:26:02.2627510Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::emit_itt:0, line 899 <- wrt source file 2025-12-04T09:26:02.2629580Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::emit_itt:0 2025-12-04T09:26:02.2631452Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::emit_nvtx:0, line 972 <- wrt source file 2025-12-04T09:26:02.2633366Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler.py::emit_nvtx:0 2025-12-04T09:26:02.2635039Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler_util.py::EventList:0, line 60 <- wrt source file 2025-12-04T09:26:02.2636776Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/autograd/profiler_util.py::EventList:0 2025-12-04T09:26:02.2638612Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 43 <- wrt source file 2025-12-04T09:26:02.2640259Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::gds_register_buffer:0 2025-12-04T09:26:02.2641852Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 59 <- wrt source file 2025-12-04T09:26:02.2643737Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0 2025-12-04T09:26:02.2645335Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::GdsFile:0, line 86 <- wrt source file 2025-12-04T09:26:02.2646511Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/gds.py::GdsFile:0 2025-12-04T09:26:02.2647732Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file 2025-12-04T09:26:02.2649426Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0 2025-12-04T09:26:02.2651060Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file 2025-12-04T09:26:02.2652720Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1 2025-12-04T09:26:02.2654182Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file 2025-12-04T09:26:02.2655486Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2 2025-12-04T09:26:02.2656861Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file 2025-12-04T09:26:02.2658619Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0 2025-12-04T09:26:02.2660056Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file 2025-12-04T09:26:02.2661659Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/profiler.py::profile:0 2025-12-04T09:26:02.2663053Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.composition:0, line 125 <- wrt source file 2025-12-04T09:26:02.2664593Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.composition:0 2025-12-04T09:26:02.2666104Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.complement:0, line 142 <- wrt source file 2025-12-04T09:26:02.2667768Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.complement:0 2025-12-04T09:26:02.2669296Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.remap_to_tensor:0, line 281 <- wrt source file 2025-12-04T09:26:02.2670945Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/_mesh_layout.py::_MeshLayout.remap_to_tensor:0 2025-12-04T09:26:02.2672406Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0, line 167 <- wrt source file 2025-12-04T09:26:02.2673786Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0 2025-12-04T09:26:02.2675824Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0, line 1027 <- wrt source file 2025-12-04T09:26:02.2677398Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0 2025-12-04T09:26:02.2679162Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0, line 1317 <- wrt source file 2025-12-04T09:26:02.2680627Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0 2025-12-04T09:26:02.2682111Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0, line 2652 <- wrt source file 2025-12-04T09:26:02.2683936Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0 2025-12-04T09:26:02.2685538Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2754 <- wrt source file 2025-12-04T09:26:02.2687060Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0 2025-12-04T09:26:02.2688542Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::batch_isend_irecv:0, line 2801 <- wrt source file 2025-12-04T09:26:02.2690256Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::batch_isend_irecv:0 2025-12-04T09:26:02.2691910Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_reduce:0, line 2938 <- wrt source file 2025-12-04T09:26:02.2693735Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_reduce:0 2025-12-04T09:26:02.2695218Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3221 <- wrt source file 2025-12-04T09:26:02.2697097Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0 2025-12-04T09:26:02.2699111Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::gather_object:0, line 3325 <- wrt source file 2025-12-04T09:26:02.2700612Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::gather_object:0 2025-12-04T09:26:02.2702083Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3457 <- wrt source file 2025-12-04T09:26:02.2703662Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0 2025-12-04T09:26:02.2705156Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0, line 3574 <- wrt source file 2025-12-04T09:26:02.2706674Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0 2025-12-04T09:26:02.2708252Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0, line 3719 <- wrt source file 2025-12-04T09:26:02.2709834Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0 2025-12-04T09:26:02.2711355Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0, line 3844 <- wrt source file 2025-12-04T09:26:02.2712902Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0 2025-12-04T09:26:02.2714373Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather:0, line 3947 <- wrt source file 2025-12-04T09:26:02.2715838Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather:0 2025-12-04T09:26:02.2717322Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0, line 4054 <- wrt source file 2025-12-04T09:26:02.2718887Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0 2025-12-04T09:26:02.2720437Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0, line 4192 <- wrt source file 2025-12-04T09:26:02.2722000Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0 2025-12-04T09:26:02.2723457Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::gather:0, line 4298 <- wrt source file 2025-12-04T09:26:02.2725252Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::gather:0 2025-12-04T09:26:02.2727143Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::scatter:0, line 4383 <- wrt source file 2025-12-04T09:26:02.2728797Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::scatter:0 2025-12-04T09:26:02.2730455Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0, line 4521 <- wrt source file 2025-12-04T09:26:02.2732032Z * 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DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/format_utils.py::DynamicMetaLoadPlanner:0, line 173 <- wrt source file 2025-12-04T09:26:02.2941571Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/format_utils.py::DynamicMetaLoadPlanner:0 2025-12-04T09:26:02.2943739Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/optimizer.py::load_sharded_optimizer_state_dict:0, line 228 <- wrt source file 2025-12-04T09:26:02.2945532Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/optimizer.py::load_sharded_optimizer_state_dict:0 2025-12-04T09:26:02.2947490Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict.py::get_state_dict:0, line 1276 <- wrt source file 2025-12-04T09:26:02.2949164Z * SKIPPED: 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wrt source file 2025-12-04T09:26:02.2958883Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict_loader.py::load:0 2025-12-04T09:26:02.2960376Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict_saver.py::save:0, line 160 <- wrt source file 2025-12-04T09:26:02.2961897Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict_saver.py::save:0 2025-12-04T09:26:02.2963727Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict_saver.py::async_save:0, line 275 <- wrt source file 2025-12-04T09:26:02.2965393Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/state_dict_saver.py::async_save:0 2025-12-04T09:26:02.2967018Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/_experimental/barriers.py::BarrierConfig:0, line 50 <- wrt source file 2025-12-04T09:26:02.2968715Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/_experimental/barriers.py::BarrierConfig:0 2025-12-04T09:26:02.2970428Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_sync_checkpointer:0, line 78 <- wrt source file 2025-12-04T09:26:02.2972217Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_sync_checkpointer:0 2025-12-04T09:26:02.2973957Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/_experimental/builder.py::make_async_checkpointer:0, line 139 <- wrt source file 2025-12-04T09:26:02.2975737Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0, line 125 <- wrt source file 2025-12-04T09:26:02.3014823Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0 2025-12-04T09:26:02.3016797Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.set_state_dict_type:0, line 651 <- wrt source file 2025-12-04T09:26:02.3019111Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.set_state_dict_type:0 2025-12-04T09:26:02.3021070Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.state_dict_type:0, line 805 <- wrt source file 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/nn/api/remote_module.py::_RemoteModule.init_from_module_rref:0, line 527 <- wrt source file 2025-12-04T09:26:02.3062505Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/nn/api/remote_module.py::_RemoteModule.init_from_module_rref:0 2025-12-04T09:26:02.3064113Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/nn/api/remote_module.py::RemoteModule:0, line 658 <- wrt source file 2025-12-04T09:26:02.3065645Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/nn/api/remote_module.py::RemoteModule:0 2025-12-04T09:26:02.3067295Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/optim/apply_optimizer_in_backward.py::_apply_optimizer_in_backward:0, line 43 <- wrt source file 2025-12-04T09:26:02.3069128Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/categorical.py::Categorical:0 2025-12-04T09:26:02.3249408Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file 2025-12-04T09:26:02.3250713Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/cauchy.py::Cauchy:0 2025-12-04T09:26:02.3251963Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file 2025-12-04T09:26:02.3253221Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/chi2.py::Chi2:0 2025-12-04T09:26:02.3254538Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/constraints.py::is_dependent:0, line 167 <- wrt source file 2025-12-04T09:26:02.3255982Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/constraints.py::is_dependent:0 2025-12-04T09:26:02.3257452Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 188 <- wrt source file 2025-12-04T09:26:02.3258984Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/constraints.py::_DependentProperty:0 2025-12-04T09:26:02.3260672Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file 2025-12-04T09:26:02.3262329Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0 2025-12-04T09:26:02.3263816Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 44 <- wrt source file 2025-12-04T09:26:02.3265273Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/dirichlet.py::Dirichlet:0 2025-12-04T09:26:02.3266648Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file 2025-12-04T09:26:02.3268091Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/exponential.py::Exponential:0 2025-12-04T09:26:02.3269560Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file 2025-12-04T09:26:02.3271079Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0 2025-12-04T09:26:02.3272442Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file 2025-12-04T09:26:02.3273716Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/gamma.py::Gamma:0 2025-12-04T09:26:02.3275139Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file 2025-12-04T09:26:02.3276738Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0 2025-12-04T09:26:02.3278197Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file 2025-12-04T09:26:02.3293310Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/geometric.py::Geometric:0 2025-12-04T09:26:02.3294647Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file 2025-12-04T09:26:02.3295979Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/gumbel.py::Gumbel:0 2025-12-04T09:26:02.3297312Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file 2025-12-04T09:26:02.3298726Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0 2025-12-04T09:26:02.3300092Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file 2025-12-04T09:26:02.3301496Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/half_normal.py::HalfNormal:0 2025-12-04T09:26:02.3302902Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file 2025-12-04T09:26:02.3304343Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/independent.py::Independent:0 2025-12-04T09:26:02.3305751Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file 2025-12-04T09:26:02.3307212Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0 2025-12-04T09:26:02.3308749Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file 2025-12-04T09:26:02.3310191Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0 2025-12-04T09:26:02.3311537Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file 2025-12-04T09:26:02.3312936Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/laplace.py::Laplace:0 2025-12-04T09:26:02.3314290Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file 2025-12-04T09:26:02.3315716Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0 2025-12-04T09:26:02.3317086Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file 2025-12-04T09:26:02.3318453Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/log_normal.py::LogNormal:0 2025-12-04T09:26:02.3319880Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file 2025-12-04T09:26:02.3321394Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0 2025-12-04T09:26:02.3323025Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/lowrank_multivariate_normal.py::LowRankMultivariateNormal:0, line 63 <- wrt source file 2025-12-04T09:26:02.3324888Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/lowrank_multivariate_normal.py::LowRankMultivariateNormal:0 2025-12-04T09:26:02.3326550Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/mixture_same_family.py::MixtureSameFamily:0, line 24 <- wrt source file 2025-12-04T09:26:02.3328140Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/mixture_same_family.py::MixtureSameFamily:0 2025-12-04T09:26:02.3329638Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file 2025-12-04T09:26:02.3331074Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/multinomial.py::Multinomial:0 2025-12-04T09:26:02.3332572Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file 2025-12-04T09:26:02.3334204Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0 2025-12-04T09:26:02.3335624Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file 2025-12-04T09:26:02.3336924Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/normal.py::Normal:0 2025-12-04T09:26:02.3338336Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file 2025-12-04T09:26:02.3339924Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0 2025-12-04T09:26:02.3341337Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file 2025-12-04T09:26:02.3343169Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/pareto.py::Pareto:0 2025-12-04T09:26:02.3344478Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file 2025-12-04T09:26:02.3345814Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/poisson.py::Poisson:0 2025-12-04T09:26:02.3347322Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/relaxed_bernoulli.py::RelaxedBernoulli:0, line 130 <- wrt source file 2025-12-04T09:26:02.3348886Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/relaxed_bernoulli.py::RelaxedBernoulli:0 2025-12-04T09:26:02.3350487Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/relaxed_categorical.py::RelaxedOneHotCategorical:0, line 117 <- wrt source file 2025-12-04T09:26:02.3352166Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/relaxed_categorical.py::RelaxedOneHotCategorical:0 2025-12-04T09:26:02.3353653Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file 2025-12-04T09:26:02.3355013Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/studentT.py::StudentT:0 2025-12-04T09:26:02.3356399Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1076 <- wrt source file 2025-12-04T09:26:02.3357827Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/weibull.py::Weibull:0 2025-12-04T09:26:02.3376257Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file 2025-12-04T09:26:02.3377567Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributions/wishart.py::Wishart:0 2025-12-04T09:26:02.3378907Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_unlift.py::_convert_guards_code_to_fn:0, line 158 <- wrt source file 2025-12-04T09:26:02.3380391Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_unlift.py::_convert_guards_code_to_fn:0 2025-12-04T09:26:02.3381720Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 123 <- wrt source file 2025-12-04T09:26:02.3382981Z * SKIPPED: 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0 2025-12-04T09:26:02.4562564Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2198 <- wrt source file 2025-12-04T09:26:02.4593505Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::gumbel_softmax:0 2025-12-04T09:26:02.4595170Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::embedding:0, line 2503 <- wrt source file 2025-12-04T09:26:02.4612015Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::embedding:0 2025-12-04T09:26:02.4613632Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::embedding_bag:0, line 2645 <- wrt source file 2025-12-04T09:26:02.4650855Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::embedding_bag:0 2025-12-04T09:26:02.4652436Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::ctc_loss:0, line 3087 <- wrt source file 2025-12-04T09:26:02.4675921Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::ctc_loss:0 2025-12-04T09:26:02.4677464Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::nll_loss:0, line 3157 <- wrt source file 2025-12-04T09:26:02.4697148Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::nll_loss:0 2025-12-04T09:26:02.4698745Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::cross_entropy:0, line 3476 <- wrt source file 2025-12-04T09:26:02.4707389Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::cross_entropy:0 2025-12-04T09:26:02.4709069Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3542 <- wrt source file 2025-12-04T09:26:02.4722408Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::binary_cross_entropy:0 2025-12-04T09:26:02.4724289Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3613 <- wrt source file 2025-12-04T09:26:02.4748163Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0 2025-12-04T09:26:02.4749849Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::pad:0, line 5387 <- wrt source file 2025-12-04T09:26:02.4760530Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/functional.py::pad:0 2025-12-04T09:26:02.4761995Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file 2025-12-04T09:26:02.4800780Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv1d_input:0 2025-12-04T09:26:02.4802298Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file 2025-12-04T09:26:02.4807106Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv1d_weight:0 2025-12-04T09:26:02.4808603Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file 2025-12-04T09:26:02.4824574Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv2d_input:0 2025-12-04T09:26:02.4826104Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file 2025-12-04T09:26:02.4830573Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv2d_weight:0 2025-12-04T09:26:02.4832228Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file 2025-12-04T09:26:02.5231203Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv3d_input:0 2025-12-04T09:26:02.5232995Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file 2025-12-04T09:26:02.5254947Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/grad.py::conv3d_weight:0 2025-12-04T09:26:02.5256744Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::calculate_gain:0, line 172 <- wrt source file 2025-12-04T09:26:02.5259521Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::calculate_gain:0 2025-12-04T09:26:02.5260998Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::uniform_:0, line 231 <- wrt source file 2025-12-04T09:26:02.5263727Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::uniform_:0 2025-12-04T09:26:02.5265139Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::normal_:0, line 258 <- wrt source file 2025-12-04T09:26:02.5268249Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::normal_:0 2025-12-04T09:26:02.5269718Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::trunc_normal_:0, line 293 <- wrt source file 2025-12-04T09:26:02.5290511Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::trunc_normal_:0 2025-12-04T09:26:02.5291968Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::constant_:0, line 307 <- wrt source file 2025-12-04T09:26:02.5294908Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::constant_:0 2025-12-04T09:26:02.5296329Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::ones_:0, line 324 <- wrt source file 2025-12-04T09:26:02.5299213Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::ones_:0 2025-12-04T09:26:02.5300603Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::zeros_:0, line 337 <- wrt source file 2025-12-04T09:26:02.5303221Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::zeros_:0 2025-12-04T09:26:02.5304601Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::eye_:0, line 353 <- wrt source file 2025-12-04T09:26:02.5307660Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::eye_:0 2025-12-04T09:26:02.5309059Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::dirac_:0, line 375 <- wrt source file 2025-12-04T09:26:02.5313799Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::dirac_:0 2025-12-04T09:26:02.5315275Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::xavier_uniform_:0, line 461 <- wrt source file 2025-12-04T09:26:02.5318591Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::xavier_uniform_:0 2025-12-04T09:26:02.5320323Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::xavier_normal_:0, line 493 <- wrt source file 2025-12-04T09:26:02.5322957Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::xavier_normal_:0 2025-12-04T09:26:02.5324530Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 545 <- wrt source file 2025-12-04T09:26:02.5327832Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::kaiming_uniform_:0 2025-12-04T09:26:02.5329376Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::kaiming_normal_:0, line 610 <- wrt source file 2025-12-04T09:26:02.5332528Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::kaiming_normal_:0 2025-12-04T09:26:02.5334024Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::orthogonal_:0, line 649 <- wrt source file 2025-12-04T09:26:02.5335537Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::orthogonal_:0 2025-12-04T09:26:02.5336977Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::sparse_:0, line 702 <- wrt source file 2025-12-04T09:26:02.5340550Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/init.py::sparse_:0 2025-12-04T09:26:02.5342179Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 124 <- wrt source file 2025-12-04T09:26:02.5344224Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0 2025-12-04T09:26:02.5346066Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/_registry.py::register_flash_attention_impl:0, line 47 <- wrt source file 2025-12-04T09:26:02.5348048Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/_registry.py::register_flash_attention_impl:0 2025-12-04T09:26:02.5349994Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/_registry.py::activate_flash_attention_impl:0, line 78 <- wrt source file 2025-12-04T09:26:02.5351969Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/_registry.py::activate_flash_attention_impl:0 2025-12-04T09:26:02.5353742Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 94 <- wrt source file 2025-12-04T09:26:02.5355395Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/bias.py::CausalBias:0 2025-12-04T09:26:02.5357044Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/varlen.py::varlen_attn:0, line 166 <- wrt source file 2025-12-04T09:26:02.5358747Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/attention/varlen.py::varlen_attn:0 2025-12-04T09:26:02.5360394Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file 2025-12-04T09:26:02.5362544Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Threshold:0 2025-12-04T09:26:02.5364221Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ReLU:0, line 120 <- wrt source file 2025-12-04T09:26:02.5370547Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ReLU:0 2025-12-04T09:26:02.5372338Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::RReLU:0, line 185 <- wrt source file 2025-12-04T09:26:02.5375995Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::RReLU:0 2025-12-04T09:26:02.5377635Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 247 <- wrt source file 2025-12-04T09:26:02.5381493Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardtanh:0 2025-12-04T09:26:02.5383119Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 318 <- wrt source file 2025-12-04T09:26:02.5386535Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ReLU6:0 2025-12-04T09:26:02.5388190Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 349 <- wrt source file 2025-12-04T09:26:02.5391319Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Sigmoid:0 2025-12-04T09:26:02.5392652Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 384 <- wrt source file 2025-12-04T09:26:02.5396591Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0 2025-12-04T09:26:02.5397906Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Tanh:0, line 420 <- wrt source file 2025-12-04T09:26:02.5401926Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Tanh:0 2025-12-04T09:26:02.5403194Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::SiLU:0, line 456 <- wrt source file 2025-12-04T09:26:02.5406920Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::SiLU:0 2025-12-04T09:26:02.5408182Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Mish:0, line 501 <- wrt source file 2025-12-04T09:26:02.5412152Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Mish:0 2025-12-04T09:26:02.5413462Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 552 <- wrt source file 2025-12-04T09:26:02.5417424Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardswish:0 2025-12-04T09:26:02.5418716Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ELU:0, line 598 <- wrt source file 2025-12-04T09:26:02.5422737Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::ELU:0 2025-12-04T09:26:02.5424003Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::CELU:0, line 646 <- wrt source file 2025-12-04T09:26:02.5428035Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::CELU:0 2025-12-04T09:26:02.5429321Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::SELU:0, line 705 <- wrt source file 2025-12-04T09:26:02.5433125Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::SELU:0 2025-12-04T09:26:02.5434392Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::GLU:0, line 751 <- wrt source file 2025-12-04T09:26:02.5438668Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::GLU:0 2025-12-04T09:26:02.5439949Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::GELU:0, line 799 <- wrt source file 2025-12-04T09:26:02.5447336Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::GELU:0 2025-12-04T09:26:02.5449136Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 848 <- wrt source file 2025-12-04T09:26:02.5452564Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Hardshrink:0 2025-12-04T09:26:02.5454245Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 903 <- wrt source file 2025-12-04T09:26:02.5462906Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LeakyReLU:0 2025-12-04T09:26:02.5464586Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 945 <- wrt source file 2025-12-04T09:26:02.5468075Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LogSigmoid:0 2025-12-04T09:26:02.5469757Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softplus:0, line 981 <- wrt source file 2025-12-04T09:26:02.5473612Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softplus:0 2025-12-04T09:26:02.5475289Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 1030 <- wrt source file 2025-12-04T09:26:02.5478785Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softshrink:0 2025-12-04T09:26:02.5480588Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1148 <- wrt source file 2025-12-04T09:26:02.5482464Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0 2025-12-04T09:26:02.5484250Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1613 <- wrt source file 2025-12-04T09:26:02.5494100Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::PReLU:0 2025-12-04T09:26:02.5495749Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1664 <- wrt source file 2025-12-04T09:26:02.5499366Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softsign:0 2025-12-04T09:26:02.5501041Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1690 <- wrt source file 2025-12-04T09:26:02.5504570Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Tanhshrink:0 2025-12-04T09:26:02.5506256Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1728 <- wrt source file 2025-12-04T09:26:02.5510044Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmin:0 2025-12-04T09:26:02.5511702Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1792 <- wrt source file 2025-12-04T09:26:02.5515577Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmax:0 2025-12-04T09:26:02.5517382Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1839 <- wrt source file 2025-12-04T09:26:02.5520808Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::Softmax2d:0 2025-12-04T09:26:02.5522505Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1878 <- wrt source file 2025-12-04T09:26:02.5526316Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/activation.py::LogSoftmax:0 2025-12-04T09:26:02.5528007Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 341 <- wrt source file 2025-12-04T09:26:02.5582019Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0 2025-12-04T09:26:02.5583748Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 453 <- wrt source file 2025-12-04T09:26:02.5818216Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0 2025-12-04T09:26:02.5820176Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 565 <- wrt source file 2025-12-04T09:26:02.8448670Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0 2025-12-04T09:26:02.8615185Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::SyncBatchNorm:0, line 690 <- wrt source file 2025-12-04T09:26:02.8618206Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::SyncBatchNorm:0 2025-12-04T09:26:02.8619760Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::SyncBatchNorm.convert_sync_batchnorm:0, line 857 <- wrt source file 2025-12-04T09:26:02.8621423Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/batchnorm.py::SyncBatchNorm.convert_sync_batchnorm:0 2025-12-04T09:26:02.8622967Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file 2025-12-04T09:26:02.8653304Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0 2025-12-04T09:26:02.8655059Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file 2025-12-04T09:26:02.8656772Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential:0 2025-12-04T09:26:02.8658502Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 263 <- wrt source file 2025-12-04T09:26:02.8666465Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.append:0 2025-12-04T09:26:02.8668260Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 286 <- wrt source file 2025-12-04T09:26:02.8677042Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.insert:0 2025-12-04T09:26:02.8678830Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 317 <- wrt source file 2025-12-04T09:26:02.8689390Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::Sequential.extend:0 2025-12-04T09:26:02.8691112Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ModuleList:0, line 346 <- wrt source file 2025-12-04T09:26:02.8692814Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ModuleList:0 2025-12-04T09:26:02.8694644Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 529 <- wrt source file 2025-12-04T09:26:02.8696345Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ModuleDict:0 2025-12-04T09:26:02.8698034Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ParameterList:0, line 661 <- wrt source file 2025-12-04T09:26:02.8699795Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ParameterList:0 2025-12-04T09:26:02.8701521Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 819 <- wrt source file 2025-12-04T09:26:02.8703279Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py::ParameterDict:0 2025-12-04T09:26:02.8705016Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file 2025-12-04T09:26:02.8706787Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0 2025-12-04T09:26:02.8708530Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 81 <- wrt source file 2025-12-04T09:26:02.8714923Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0 2025-12-04T09:26:02.8716604Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file 2025-12-04T09:26:02.8720889Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout:0 2025-12-04T09:26:02.8722495Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 108 <- wrt source file 2025-12-04T09:26:02.8728161Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout1d:0 2025-12-04T09:26:02.8729786Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 163 <- wrt source file 2025-12-04T09:26:02.8754783Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout2d:0 2025-12-04T09:26:02.8756476Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 211 <- wrt source file 2025-12-04T09:26:02.8839563Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::Dropout3d:0 2025-12-04T09:26:02.8841289Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 257 <- wrt source file 2025-12-04T09:26:02.8845770Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0 2025-12-04T09:26:02.8847519Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 309 <- wrt source file 2025-12-04T09:26:02.8930091Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0 2025-12-04T09:26:02.8932144Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 29 <- wrt source file 2025-12-04T09:26:02.8938308Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/flatten.py::Flatten:0 2025-12-04T09:26:02.8939901Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/flatten.py::Unflatten:0, line 86 <- wrt source file 2025-12-04T09:26:02.8958130Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/flatten.py::Unflatten:0 2025-12-04T09:26:02.8959690Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file 2025-12-04T09:26:02.8965854Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/fold.py::Fold:0 2025-12-04T09:26:02.8967382Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/fold.py::Unfold:0, line 395 <- wrt source file 2025-12-04T09:26:02.9011318Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/fold.py::Unfold:0 2025-12-04T09:26:02.9012998Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 188 <- wrt source file 2025-12-04T09:26:02.9026996Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0 2025-12-04T09:26:02.9028801Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 304 <- wrt source file 2025-12-04T09:26:02.9233593Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0 2025-12-04T09:26:02.9235492Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 420 <- wrt source file 2025-12-04T09:26:03.1855673Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0 2025-12-04T09:26:03.2022971Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file 2025-12-04T09:26:03.2028386Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0 2025-12-04T09:26:03.2029703Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file 2025-12-04T09:26:03.2037413Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Identity:0 2025-12-04T09:26:03.2038690Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Linear:0, line 83 <- wrt source file 2025-12-04T09:26:03.2065592Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Linear:0 2025-12-04T09:26:03.2066838Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 191 <- wrt source file 2025-12-04T09:26:03.2088158Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py::Bilinear:0 2025-12-04T09:26:03.2089582Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 116 <- wrt source file 2025-12-04T09:26:03.2097515Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::L1Loss:0 2025-12-04T09:26:03.2099018Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 213 <- wrt source file 2025-12-04T09:26:03.2149534Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::NLLLoss:0 2025-12-04T09:26:03.2151158Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 327 <- wrt source file 2025-12-04T09:26:03.2158018Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0 2025-12-04T09:26:03.2159697Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 416 <- wrt source file 2025-12-04T09:26:03.2175740Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0 2025-12-04T09:26:03.2177362Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 531 <- wrt source file 2025-12-04T09:26:03.2185785Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::KLDivLoss:0 2025-12-04T09:26:03.2187346Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 613 <- wrt source file 2025-12-04T09:26:03.2212191Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MSELoss:0 2025-12-04T09:26:03.2213746Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 696 <- wrt source file 2025-12-04T09:26:03.2220831Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCELoss:0 2025-12-04T09:26:03.2222471Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 762 <- wrt source file 2025-12-04T09:26:03.2234947Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0 2025-12-04T09:26:03.2236655Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 810 <- wrt source file 2025-12-04T09:26:03.2242972Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1 2025-12-04T09:26:03.2244773Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 958 <- wrt source file 2025-12-04T09:26:03.2253903Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0 2025-12-04T09:26:03.2255633Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1284 <- wrt source file 2025-12-04T09:26:03.2265392Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0 2025-12-04T09:26:03.2267104Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1, line 1311 <- wrt source file 2025-12-04T09:26:03.2269260Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1 2025-12-04T09:26:03.2271001Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1464 <- wrt source file 2025-12-04T09:26:03.2280676Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0 2025-12-04T09:26:03.2282397Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1531 <- wrt source file 2025-12-04T09:26:03.2290310Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0 2025-12-04T09:26:03.2292018Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1612 <- wrt source file 2025-12-04T09:26:03.2300549Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0 2025-12-04T09:26:03.2303131Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1714 <- wrt source file 2025-12-04T09:26:03.2314623Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0 2025-12-04T09:26:03.2316469Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::TripletMarginWithDistanceLoss:0, line 1827 <- wrt source file 2025-12-04T09:26:03.2338813Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::TripletMarginWithDistanceLoss:0 2025-12-04T09:26:03.2340584Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CTCLoss:0, line 1959 <- wrt source file 2025-12-04T09:26:03.2368727Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/loss.py::CTCLoss:0 2025-12-04T09:26:03.2370431Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 554 <- wrt source file 2025-12-04T09:26:03.2372284Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.register_buffer:0 2025-12-04T09:26:03.2374015Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1048 <- wrt source file 2025-12-04T09:26:03.2388022Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.apply:0 2025-12-04T09:26:03.2389651Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.to:0, line 1299 <- wrt source file 2025-12-04T09:26:03.2398411Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.to:0 2025-12-04T09:26:03.2400086Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2232 <- wrt source file 2025-12-04T09:26:03.2401842Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.state_dict:0 2025-12-04T09:26:03.2403576Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2678 <- wrt source file 2025-12-04T09:26:03.2405389Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.parameters:0 2025-12-04T09:26:03.2407170Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2706 <- wrt source file 2025-12-04T09:26:03.2409042Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_parameters:0 2025-12-04T09:26:03.2410800Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2733 <- wrt source file 2025-12-04T09:26:03.2412499Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.buffers:0 2025-12-04T09:26:03.2414213Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2760 <- wrt source file 2025-12-04T09:26:03.2416187Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_buffers:0 2025-12-04T09:26:03.2417971Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2791 <- wrt source file 2025-12-04T09:26:03.2419783Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_children:0 2025-12-04T09:26:03.2421633Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2815 <- wrt source file 2025-12-04T09:26:03.2423352Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.modules:0 2025-12-04T09:26:03.2425082Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2853 <- wrt source file 2025-12-04T09:26:03.2426888Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py::Module.named_modules:0 2025-12-04T09:26:03.2428716Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file 2025-12-04T09:26:03.2467901Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0 2025-12-04T09:26:03.2469775Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 163 <- wrt source file 2025-12-04T09:26:03.2496917Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::LayerNorm:0 2025-12-04T09:26:03.2498720Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 274 <- wrt source file 2025-12-04T09:26:03.2521159Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::GroupNorm:0 2025-12-04T09:26:03.2522862Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 369 <- wrt source file 2025-12-04T09:26:03.2528287Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/normalization.py::RMSNorm:0 2025-12-04T09:26:03.2529984Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file 2025-12-04T09:26:03.2547063Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad1d:0 2025-12-04T09:26:03.2548740Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 123 <- wrt source file 2025-12-04T09:26:03.2572659Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad2d:0 2025-12-04T09:26:03.2574362Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 189 <- wrt source file 2025-12-04T09:26:04.0238527Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::CircularPad3d:0 2025-12-04T09:26:04.0550721Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 244 <- wrt source file 2025-12-04T09:26:04.0562146Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0 2025-12-04T09:26:04.0563518Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 298 <- wrt source file 2025-12-04T09:26:04.0569948Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0 2025-12-04T09:26:04.0571307Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 355 <- wrt source file 2025-12-04T09:26:04.0596397Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0 2025-12-04T09:26:04.0598320Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 401 <- wrt source file 2025-12-04T09:26:04.0634468Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0 2025-12-04T09:26:04.0636201Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 446 <- wrt source file 2025-12-04T09:26:04.0641988Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0 2025-12-04T09:26:04.0643907Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 505 <- wrt source file 2025-12-04T09:26:04.0653764Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0 2025-12-04T09:26:04.0655515Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 565 <- wrt source file 2025-12-04T09:26:04.0660755Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0 2025-12-04T09:26:04.0662498Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 610 <- wrt source file 2025-12-04T09:26:04.0678784Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0 2025-12-04T09:26:04.0680513Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 669 <- wrt source file 2025-12-04T09:26:04.6030954Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0 2025-12-04T09:26:04.6364479Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 704 <- wrt source file 2025-12-04T09:26:04.6375301Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0 2025-12-04T09:26:04.6376614Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 762 <- wrt source file 2025-12-04T09:26:04.6383228Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0 2025-12-04T09:26:04.6384516Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 824 <- wrt source file 2025-12-04T09:26:04.6410702Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0 2025-12-04T09:26:04.6412493Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file 2025-12-04T09:26:04.6417602Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0 2025-12-04T09:26:04.6419416Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 99 <- wrt source file 2025-12-04T09:26:04.6425206Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0 2025-12-04T09:26:04.6426971Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file 2025-12-04T09:26:04.6443463Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0 2025-12-04T09:26:04.6445417Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 207 <- wrt source file 2025-12-04T09:26:04.6512248Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0 2025-12-04T09:26:04.6513926Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 291 <- wrt source file 2025-12-04T09:26:04.8648532Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0 2025-12-04T09:26:04.8715195Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 366 <- wrt source file 2025-12-04T09:26:04.8729790Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0 2025-12-04T09:26:04.8731512Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool2d:0, line 452 <- wrt source file 2025-12-04T09:26:04.8756629Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool2d:0 2025-12-04T09:26:04.8772760Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 550 <- wrt source file 2025-12-04T09:26:04.9540695Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0 2025-12-04T09:26:04.9542708Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 642 <- wrt source file 2025-12-04T09:26:04.9566068Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0 2025-12-04T09:26:04.9567740Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 738 <- wrt source file 2025-12-04T09:26:04.9610745Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0 2025-12-04T09:26:04.9612392Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 855 <- wrt source file 2025-12-04T09:26:05.1457799Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0 2025-12-04T09:26:05.1525737Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 946 <- wrt source file 2025-12-04T09:26:05.1584061Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0 2025-12-04T09:26:05.1585939Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1033 <- wrt source file 2025-12-04T09:26:05.2238374Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0 2025-12-04T09:26:05.2240159Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1156 <- wrt source file 2025-12-04T09:26:05.2249699Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool1d:0 2025-12-04T09:26:05.2251396Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1212 <- wrt source file 2025-12-04T09:26:05.2314960Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool2d:0 2025-12-04T09:26:05.2316968Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1276 <- wrt source file 2025-12-04T09:26:05.4606877Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::LPPool3d:0 2025-12-04T09:26:05.4671541Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1332 <- wrt source file 2025-12-04T09:26:05.4697034Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0 2025-12-04T09:26:05.4698820Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1367 <- wrt source file 2025-12-04T09:26:05.4708607Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0 2025-12-04T09:26:05.4710413Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1411 <- wrt source file 2025-12-04T09:26:05.4734774Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0 2025-12-04T09:26:05.4736555Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1459 <- wrt source file 2025-12-04T09:26:05.4750801Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0 2025-12-04T09:26:05.4752582Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1493 <- wrt source file 2025-12-04T09:26:05.4760836Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0 2025-12-04T09:26:05.4762625Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1533 <- wrt source file 2025-12-04T09:26:05.4783200Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0 2025-12-04T09:26:05.4784820Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::RNN:0, line 598 <- wrt source file 2025-12-04T09:26:05.4803583Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::RNN:0 2025-12-04T09:26:05.4805144Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 963 <- wrt source file 2025-12-04T09:26:05.5419139Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::LSTM:0 2025-12-04T09:26:05.5420671Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1305 <- wrt source file 2025-12-04T09:26:05.5440965Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::GRU:0 2025-12-04T09:26:05.5442741Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1561 <- wrt source file 2025-12-04T09:26:05.5456158Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::RNNCell:0 2025-12-04T09:26:05.5458096Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1683 <- wrt source file 2025-12-04T09:26:05.5468489Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::LSTMCell:0 2025-12-04T09:26:05.5470084Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1797 <- wrt source file 2025-12-04T09:26:05.5483908Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py::GRUCell:0 2025-12-04T09:26:05.5485586Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file 2025-12-04T09:26:05.5501213Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::Embedding:0 2025-12-04T09:26:05.5503023Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file 2025-12-04T09:26:05.5508047Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0 2025-12-04T09:26:05.5509838Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::EmbeddingBag:0, line 324 <- wrt source file 2025-12-04T09:26:05.5537497Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::EmbeddingBag:0 2025-12-04T09:26:05.5539295Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 523 <- wrt source file 2025-12-04T09:26:05.5546167Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0 2025-12-04T09:26:05.5548014Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 91 <- wrt source file 2025-12-04T09:26:06.3941253Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::Transformer:0 2025-12-04T09:26:06.4009611Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::Transformer.forward:0, line 267 <- wrt source file 2025-12-04T09:26:06.4011603Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::Transformer.forward:0 2025-12-04T09:26:06.4013465Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 345 <- wrt source file 2025-12-04T09:26:06.5141733Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0 2025-12-04T09:26:06.5146637Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 578 <- wrt source file 2025-12-04T09:26:06.7520478Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0 2025-12-04T09:26:06.7528448Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 702 <- wrt source file 2025-12-04T09:26:06.7853317Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0 2025-12-04T09:26:06.7855432Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 1014 <- wrt source file 2025-12-04T09:26:06.8440916Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0 2025-12-04T09:26:06.8443196Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file 2025-12-04T09:26:06.8506495Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::Upsample:0 2025-12-04T09:26:06.8508472Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 229 <- wrt source file 2025-12-04T09:26:06.8523204Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0 2025-12-04T09:26:06.8525145Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 279 <- wrt source file 2025-12-04T09:26:06.8534011Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0 2025-12-04T09:26:06.8535825Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 128 <- wrt source file 2025-12-04T09:26:06.8537640Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0 2025-12-04T09:26:06.8539538Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 644 <- wrt source file 2025-12-04T09:26:06.8541517Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0 2025-12-04T09:26:06.8543817Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1451 <- wrt source file 2025-12-04T09:26:06.8545947Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0 2025-12-04T09:26:06.8548024Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.join:0, line 1838 <- wrt source file 2025-12-04T09:26:06.8550101Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.join:0 2025-12-04T09:26:06.8552249Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 2004 <- wrt source file 2025-12-04T09:26:06.8554516Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0 2025-12-04T09:26:06.8556749Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2014 <- wrt source file 2025-12-04T09:26:06.8559017Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1 2025-12-04T09:26:06.8561303Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2049 <- wrt source file 2025-12-04T09:26:06.8563690Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0 2025-12-04T09:26:06.8566037Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_fused_optim:0, line 2107 <- wrt source file 2025-12-04T09:26:06.8568408Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_fused_optim:0 2025-12-04T09:26:06.8570041Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file 2025-12-04T09:26:06.8571572Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0 2025-12-04T09:26:06.8573019Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file 2025-12-04T09:26:06.8574284Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/init.py::skip_init:0 2025-12-04T09:26:06.8575703Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/memory_format.py::convert_conv2d_weight_memory_format:0, line 64 <- wrt source file 2025-12-04T09:26:06.8577329Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/memory_format.py::convert_conv2d_weight_memory_format:0 2025-12-04T09:26:06.8578940Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/memory_format.py::convert_conv3d_weight_memory_format:0, line 143 <- wrt source file 2025-12-04T09:26:06.8580556Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/memory_format.py::convert_conv3d_weight_memory_format:0 2025-12-04T09:26:06.8582061Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 267 <- wrt source file 2025-12-04T09:26:06.8583501Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0 2025-12-04T09:26:06.8584910Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 362 <- wrt source file 2025-12-04T09:26:06.8586362Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0 2025-12-04T09:26:06.8587769Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 593 <- wrt source file 2025-12-04T09:26:06.8589237Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0 2025-12-04T09:26:06.8590560Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::identity:0, line 852 <- wrt source file 2025-12-04T09:26:06.8591813Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::identity:0 2025-12-04T09:26:06.8593097Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 888 <- wrt source file 2025-12-04T09:26:06.8594484Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::random_unstructured:0 2025-12-04T09:26:06.8595810Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 931 <- wrt source file 2025-12-04T09:26:06.8597133Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::l1_unstructured:0 2025-12-04T09:26:06.8598434Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::random_structured:0, line 971 <- wrt source file 2025-12-04T09:26:06.8599782Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::random_structured:0 2025-12-04T09:26:06.8601355Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::ln_structured:0, line 1017 <- wrt source file 2025-12-04T09:26:06.8625691Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::ln_structured:0 2025-12-04T09:26:06.8627026Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::global_unstructured:0, line 1072 <- wrt source file 2025-12-04T09:26:06.8647290Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::global_unstructured:0 2025-12-04T09:26:06.8648637Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::custom_from_mask:0, line 1175 <- wrt source file 2025-12-04T09:26:06.8659692Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::custom_from_mask:0 2025-12-04T09:26:06.8660964Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::remove:0, line 1203 <- wrt source file 2025-12-04T09:26:06.8667750Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::remove:0 2025-12-04T09:26:06.8668963Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1231 <- wrt source file 2025-12-04T09:26:06.8678469Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/prune.py::is_pruned:0 2025-12-04T09:26:06.8679773Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pad_packed_sequence:0, line 359 <- wrt source file 2025-12-04T09:26:06.8698292Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pad_packed_sequence:0 2025-12-04T09:26:06.8699555Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 439 <- wrt source file 2025-12-04T09:26:06.8705582Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pad_sequence:0 2025-12-04T09:26:06.8706839Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 500 <- wrt source file 2025-12-04T09:26:06.8731736Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0 2025-12-04T09:26:06.8733324Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 556 <- wrt source file 2025-12-04T09:26:06.8741481Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::pack_sequence:0 2025-12-04T09:26:06.8743348Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 584 <- wrt source file 2025-12-04T09:26:06.8765062Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0 2025-12-04T09:26:06.8766751Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file 2025-12-04T09:26:06.8774590Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0 2025-12-04T09:26:06.8776391Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 347 <- wrt source file 2025-12-04T09:26:06.8783426Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0 2025-12-04T09:26:06.8785227Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 193 <- wrt source file 2025-12-04T09:26:06.8789360Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/stateless.py::functional_call:0 2025-12-04T09:26:06.8791039Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file 2025-12-04T09:26:06.8809271Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0 2025-12-04T09:26:06.8811146Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file 2025-12-04T09:26:06.8816893Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0 2025-12-04T09:26:06.8818730Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file 2025-12-04T09:26:06.8820626Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0 2025-12-04T09:26:06.8822719Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/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 2025-12-04T09:26:06.8825513Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0 2025-12-04T09:26:06.8827466Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 357 <- wrt source file 2025-12-04T09:26:06.8829100Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0 2025-12-04T09:26:06.8830754Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 483 <- wrt source file 2025-12-04T09:26:06.8832518Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0 2025-12-04T09:26:06.8834156Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 608 <- wrt source file 2025-12-04T09:26:06.8835760Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::StepLR:0 2025-12-04T09:26:06.8837358Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 695 <- wrt source file 2025-12-04T09:26:06.8839034Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0 2025-12-04T09:26:06.8840672Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 791 <- wrt source file 2025-12-04T09:26:06.8842575Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0 2025-12-04T09:26:06.8844244Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 898 <- wrt source file 2025-12-04T09:26:06.8845873Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::LinearLR:0 2025-12-04T09:26:06.8847512Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 1020 <- wrt source file 2025-12-04T09:26:06.8849228Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0 2025-12-04T09:26:06.8851106Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::SequentialLR:0, line 1097 <- wrt source file 2025-12-04T09:26:06.8852786Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::SequentialLR:0 2025-12-04T09:26:06.8854441Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0, line 1249 <- wrt source file 2025-12-04T09:26:06.8856236Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0 2025-12-04T09:26:06.8857944Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1378 <- wrt source file 2025-12-04T09:26:06.8859701Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0 2025-12-04T09:26:06.8861437Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1490 <- wrt source file 2025-12-04T09:26:06.8863205Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0 2025-12-04T09:26:06.8864865Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CyclicLR:0, line 1863 <- wrt source file 2025-12-04T09:26:06.8866484Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CyclicLR:0 2025-12-04T09:26:06.8868254Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts:0, line 2129 <- wrt source file 2025-12-04T09:26:06.8870191Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts:0 2025-12-04T09:26:06.8872145Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 2211 <- wrt source file 2025-12-04T09:26:06.8874171Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0 2025-12-04T09:26:06.8876152Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 2227 <- wrt source file 2025-12-04T09:26:06.8878188Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1 2025-12-04T09:26:06.8879983Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::OneCycleLR:0, line 2367 <- wrt source file 2025-12-04T09:26:06.8881649Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py::OneCycleLR:0 2025-12-04T09:26:06.8883535Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/optimizer.py::Optimizer.load_state_dict:0, line 900 <- wrt source file 2025-12-04T09:26:06.8885442Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/optimizer.py::Optimizer.load_state_dict:0 2025-12-04T09:26:06.8887159Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::AveragedModel:0, line 155 <- wrt source file 2025-12-04T09:26:06.8888825Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::AveragedModel:0 2025-12-04T09:26:06.8890453Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::AveragedModel:1, line 181 <- wrt source file 2025-12-04T09:26:06.8892097Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::AveragedModel:1 2025-12-04T09:26:06.8893781Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::update_bn:0, line 350 <- wrt source file 2025-12-04T09:26:06.8895372Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::update_bn:0 2025-12-04T09:26:06.8896902Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::SWALR:0, line 409 <- wrt source file 2025-12-04T09:26:06.8898492Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/swa_utils.py::SWALR:0 2025-12-04T09:26:06.8900051Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file 2025-12-04T09:26:06.8901687Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/package/glob_group.py::GlobGroup:0 2025-12-04T09:26:06.8903549Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 317 <- wrt source file 2025-12-04T09:26:06.8905628Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0 2025-12-04T09:26:06.8907443Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/profiler/profiler.py::profile:0, line 659 <- wrt source file 2025-12-04T09:26:06.8909069Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/profiler/profiler.py::profile:0 2025-12-04T09:26:06.8910809Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0, line 342 <- wrt source file 2025-12-04T09:26:06.8912736Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0 2025-12-04T09:26:06.8914517Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_comparison.py::assert_close:0, line 1477 <- wrt source file 2025-12-04T09:26:06.8959598Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_comparison.py::assert_close:0 2025-12-04T09:26:06.8960912Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_creation.py::make_tensor:0, line 114 <- wrt source file 2025-12-04T09:26:06.8962227Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_creation.py::make_tensor:0 2025-12-04T09:26:06.8963594Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::parametrize:0, line 648 <- wrt source file 2025-12-04T09:26:06.8965188Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::parametrize:0 2025-12-04T09:26:06.8966650Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0, line 769 <- wrt source file 2025-12-04T09:26:06.8968332Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0 2025-12-04T09:26:06.8969784Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0, line 858 <- wrt source file 2025-12-04T09:26:06.8971230Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0 2025-12-04T09:26:06.8972755Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py::random_symmetric_psd_matrix:0, line 4839 <- wrt source file 2025-12-04T09:26:06.8974399Z * SKIPPED: 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194 <- wrt source file 2025-12-04T09:26:06.8984121Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0 2025-12-04T09:26:06.8985629Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0, line 220 <- wrt source file 2025-12-04T09:26:06.8987208Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0 2025-12-04T09:26:06.8988893Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0, line 341 <- wrt source file 2025-12-04T09:26:06.8990706Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0 2025-12-04T09:26:06.8992505Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0, line 29 <- wrt source file 2025-12-04T09:26:06.8997856Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0 2025-12-04T09:26:06.8999426Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::register_pytree_node:0, line 159 <- wrt source file 2025-12-04T09:26:06.9000835Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::register_pytree_node:0 2025-12-04T09:26:06.9002158Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 316 <- wrt source file 2025-12-04T09:26:06.9007526Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0 2025-12-04T09:26:06.9008802Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 359 <- wrt source file 2025-12-04T09:26:06.9035541Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0 2025-12-04T09:26:06.9036846Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 396 <- wrt source file 2025-12-04T09:26:06.9041578Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0 2025-12-04T09:26:06.9043152Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 429 <- wrt source file 2025-12-04T09:26:06.9049534Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0 2025-12-04T09:26:06.9051031Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 464 <- wrt source file 2025-12-04T09:26:06.9055707Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0 2025-12-04T09:26:06.9057012Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 499 <- wrt source file 2025-12-04T09:26:06.9061976Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0 2025-12-04T09:26:06.9063251Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 536 <- wrt source file 2025-12-04T09:26:06.9069573Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::tree_map:0 2025-12-04T09:26:06.9070876Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 929 <- wrt source file 2025-12-04T09:26:06.9080811Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0 2025-12-04T09:26:06.9082154Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 308 <- wrt source file 2025-12-04T09:26:06.9095290Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::register_dataclass:0 2025-12-04T09:26:06.9096619Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::register_constant:0, line 428 <- wrt source file 2025-12-04T09:26:06.9106971Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::register_constant:0 2025-12-04T09:26:06.9108252Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1058 <- wrt source file 2025-12-04T09:26:06.9114828Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::tree_is_leaf:0 2025-12-04T09:26:06.9116052Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::tree_map:0, line 1497 <- wrt source file 2025-12-04T09:26:06.9122762Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_pytree.py::tree_map:0 2025-12-04T09:26:06.9124244Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 71 <- wrt source file 2025-12-04T09:26:06.9125850Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0 2025-12-04T09:26:06.9127508Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 382 <- wrt source file 2025-12-04T09:26:06.9129233Z * SKIPPED: 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SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0 2025-12-04T09:26:06.9139887Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py::SelectiveCheckpointContext:0, line 1257 <- wrt source file 2025-12-04T09:26:06.9141404Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py::SelectiveCheckpointContext:0 2025-12-04T09:26:06.9143228Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py::create_selective_checkpoint_contexts:0, line 1421 <- wrt source file 2025-12-04T09:26:06.9147513Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/checkpoint.py::create_selective_checkpoint_contexts:0 2025-12-04T09:26:06.9148980Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CppExtension:0, line 1247 <- wrt source file 2025-12-04T09:26:06.9150356Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CppExtension:0 2025-12-04T09:26:06.9151712Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CUDAExtension:0, line 1319 <- wrt source file 2025-12-04T09:26:06.9153079Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CUDAExtension:0 2025-12-04T09:26:06.9154433Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CUDAExtension:1, line 1397 <- wrt source file 2025-12-04T09:26:06.9155809Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::CUDAExtension:1 2025-12-04T09:26:06.9157157Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/cpp_extension.py::SyclExtension:0, line 1509 <- wrt source file 2025-12-04T09:26:06.9158530Z * SKIPPED: 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2025-12-04T09:26:06.9174795Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/throughput_benchmark.py::ThroughputBenchmark:0, line 78 <- wrt source file 2025-12-04T09:26:06.9176367Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/throughput_benchmark.py::ThroughputBenchmark:0 2025-12-04T09:26:06.9177890Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 742 <- wrt source file 2025-12-04T09:26:06.9721848Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0 2025-12-04T09:26:06.9723339Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file 2025-12-04T09:26:06.9730482Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::IterableDataset:0 2025-12-04T09:26:06.9732494Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::StackDataset:0, line 218 <- wrt source file 2025-12-04T09:26:06.9734177Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::StackDataset:0 2025-12-04T09:26:06.9735838Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::random_split:0, line 438 <- wrt source file 2025-12-04T09:26:06.9737522Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/dataset.py::random_split:0 2025-12-04T09:26:06.9739390Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/distributed.py::DistributedSampler:0, line 55 <- wrt source file 2025-12-04T09:26:06.9741229Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/distributed.py::DistributedSampler:0 2025-12-04T09:26:06.9743166Z * DOCTEST : 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/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file 2025-12-04T09:26:06.9755283Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::default_convert:0 2025-12-04T09:26:06.9756970Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file 2025-12-04T09:26:06.9760661Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::collate:0 2025-12-04T09:26:06.9762207Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 367 <- wrt source file 2025-12-04T09:26:06.9767088Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/_utils/collate.py::default_collate:0 2025-12-04T09:26:06.9768734Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0, line 97 <- wrt source file 2025-12-04T09:26:06.9770639Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0 2025-12-04T09:26:06.9772385Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 269 <- wrt source file 2025-12-04T09:26:06.9773909Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0 2025-12-04T09:26:06.9775623Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 53 <- wrt source file 2025-12-04T09:26:06.9777491Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0 2025-12-04T09:26:06.9779156Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 202 <- wrt source file 2025-12-04T09:26:06.9786814Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0 2025-12-04T09:26:06.9788519Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 90 <- wrt source file 2025-12-04T09:26:06.9790457Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0 2025-12-04T09:26:06.9792152Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file 2025-12-04T09:26:06.9816534Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0 2025-12-04T09:26:06.9818191Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 89 <- wrt source file 2025-12-04T09:26:06.9819888Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0 2025-12-04T09:26:06.9821500Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0, line 308 <- wrt source file 2025-12-04T09:26:06.9823134Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0 2025-12-04T09:26:06.9824818Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::DemultiplexerIterDataPipe:0, line 397 <- wrt source file 2025-12-04T09:26:06.9826586Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::DemultiplexerIterDataPipe:0 2025-12-04T09:26:06.9828318Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::MultiplexerIterDataPipe:0, line 615 <- wrt source file 2025-12-04T09:26:06.9830072Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::MultiplexerIterDataPipe:0 2025-12-04T09:26:06.9831748Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0, line 685 <- wrt source file 2025-12-04T09:26:06.9833448Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0 2025-12-04T09:26:06.9835114Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0, line 29 <- wrt source file 2025-12-04T09:26:06.9836844Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0 2025-12-04T09:26:06.9838684Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0, line 33 <- wrt source file 2025-12-04T09:26:06.9840429Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0 2025-12-04T09:26:06.9842099Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0, line 41 <- wrt source file 2025-12-04T09:26:06.9844201Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0 2025-12-04T09:26:06.9845882Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 102 <- wrt source file 2025-12-04T09:26:06.9847596Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0 2025-12-04T09:26:06.9849252Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::GrouperIterDataPipe:0, line 169 <- wrt source file 2025-12-04T09:26:06.9850931Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/grouping.py::GrouperIterDataPipe:0 2025-12-04T09:26:06.9852551Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0, line 37 <- wrt source file 2025-12-04T09:26:06.9854211Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0 2025-12-04T09:26:06.9855921Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0, line 24 <- wrt source file 2025-12-04T09:26:06.9857708Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0 2025-12-04T09:26:06.9859434Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file 2025-12-04T09:26:06.9861162Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0 2025-12-04T09:26:06.9862813Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0, line 36 <- wrt source file 2025-12-04T09:26:06.9864442Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0 2025-12-04T09:26:06.9866110Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file 2025-12-04T09:26:06.9868030Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0 2025-12-04T09:26:06.9869705Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file 2025-12-04T09:26:06.9871386Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0 2025-12-04T09:26:06.9873014Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 76 <- wrt source file 2025-12-04T09:26:06.9874805Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0 2025-12-04T09:26:06.9876410Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0, line 29 <- wrt source file 2025-12-04T09:26:06.9878080Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0 2025-12-04T09:26:06.9879808Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0, line 29 <- wrt source file 2025-12-04T09:26:06.9881509Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0 2025-12-04T09:26:06.9883144Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0, line 37 <- wrt source file 2025-12-04T09:26:06.9884826Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0 2025-12-04T09:26:06.9886425Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file 2025-12-04T09:26:06.9888017Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0 2025-12-04T09:26:06.9889526Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file 2025-12-04T09:26:07.6544460Z * SUCCESS: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0 2025-12-04T09:26:07.6546433Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file 2025-12-04T09:26:07.6548378Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0 2025-12-04T09:26:07.6550176Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0, line 217 <- wrt source file 2025-12-04T09:26:07.6552252Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0 2025-12-04T09:26:07.6554053Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 322 <- wrt source file 2025-12-04T09:26:07.6555917Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0 2025-12-04T09:26:07.6557845Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0, line 370 <- wrt source file 2025-12-04T09:26:07.6559682Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0 2025-12-04T09:26:07.6561603Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0, line 402 <- wrt source file 2025-12-04T09:26:07.6563187Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0 2025-12-04T09:26:07.6564805Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0, line 450 <- wrt source file 2025-12-04T09:26:07.6566799Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0 2025-12-04T09:26:07.6568533Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 489 <- wrt source file 2025-12-04T09:26:07.6570313Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0 2025-12-04T09:26:07.6572712Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 542 <- wrt source file 2025-12-04T09:26:07.6575360Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0 2025-12-04T09:26:07.6578174Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 608 <- wrt source file 2025-12-04T09:26:07.6581185Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0 2025-12-04T09:26:07.6584256Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0, line 657 <- wrt source file 2025-12-04T09:26:07.6586352Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0 2025-12-04T09:26:07.6588486Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0, line 820 <- wrt source file 2025-12-04T09:26:07.6590037Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0 2025-12-04T09:26:07.6592281Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0, line 887 <- wrt source file 2025-12-04T09:26:07.6594081Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0 2025-12-04T09:26:07.6595793Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 998 <- wrt source file 2025-12-04T09:26:07.6597659Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0 2025-12-04T09:26:07.6600011Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1072 <- wrt source file 2025-12-04T09:26:07.6602590Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0 2025-12-04T09:26:07.6604476Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1093 <- wrt source file 2025-12-04T09:26:07.6606276Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0 2025-12-04T09:26:07.6607965Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1118 <- wrt source file 2025-12-04T09:26:07.6609640Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0 2025-12-04T09:26:07.6611400Z * DOCTEST : /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1164 <- wrt source file 2025-12-04T09:26:07.6612978Z * SKIPPED: /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0 2025-12-04T09:26:07.6613789Z ============ 2025-12-04T09:26:07.6614066Z Finished doctests 2025-12-04T09:26:07.6614309Z 378 / 894 passed 2025-12-04T09:26:07.6614644Z  2025-12-04T09:26:07.6614939Z === Found 17 parse-time warnings === 2025-12-04T09:26:07.6615378Z --- Parse Warning: 1 / 17 --- 2025-12-04T09:26:07.6616851Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=368. 2025-12-04T09:26:07.6618148Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6618796Z Registers the function implementation as the fallback for the given key. 2025-12-04T09:26:07.6619269Z 2025-12-04T09:26:07.6619623Z This function only works for a library with global namespace ("_"). 2025-12-04T09:26:07.6620058Z 2025-12-04T09:26:07.6620261Z Args: 2025-12-04T09:26:07.6620702Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-12-04T09:26:07.6621242Z to register a fallthrough. 2025-12-04T09:26:07.6621832Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-12-04T09:26:07.6622482Z the dispatch key that the library was created with. 2025-12-04T09:26:07.6623179Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-12-04T09:26:07.6624036Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-12-04T09:26:07.6624598Z 2025-12-04T09:26:07.6624820Z Example:: 2025-12-04T09:26:07.6625054Z 2025-12-04T09:26:07.6625285Z >>> my_lib = Library("_", "IMPL") 2025-12-04T09:26:07.6625670Z >>> def fallback_kernel(op, *args, **kwargs): 2025-12-04T09:26:07.6626060Z >>> # Handle all autocast ops generically 2025-12-04T09:26:07.6626416Z >>> # ... 2025-12-04T09:26:07.6626750Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-12-04T09:26:07.6627113Z 2025-12-04T09:26:07.6627914Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-12-04T09:26:07.6628804Z 2025-12-04T09:26:07.6629058Z my_lib.fallback(fallback_kernel, "Autocast") 2025-12-04T09:26:07.6629388Z ^ 2025-12-04T09:26:07.6629607Z warnings.warn(msg) 2025-12-04T09:26:07.6629865Z 2025-12-04T09:26:07.6630161Z --- Parse Warning: 2 / 17 --- 2025-12-04T09:26:07.6631317Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=958. 2025-12-04T09:26:07.6632603Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6633243Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-12-04T09:26:07.6633687Z 2025-12-04T09:26:07.6633987Z Also sometimes known as a "meta kernel", "abstract impl". 2025-12-04T09:26:07.6634377Z 2025-12-04T09:26:07.6634733Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-12-04T09:26:07.6635354Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-12-04T09:26:07.6635964Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-12-04T09:26:07.6636593Z what the properties of the output Tensors are. 2025-12-04T09:26:07.6636934Z 2025-12-04T09:26:07.6637294Z The FakeTensor implementation has the same signature as the operator. 2025-12-04T09:26:07.6637890Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-12-04T09:26:07.6638457Z implementation, assume that all Tensor inputs to the operator are 2025-12-04T09:26:07.6639105Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-12-04T09:26:07.6639663Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-12-04T09:26:07.6640256Z The FakeTensor implementation must consist of only PyTorch operations 2025-12-04T09:26:07.6640821Z (and may not directly access the storage or data of any input or 2025-12-04T09:26:07.6641260Z intermediate Tensors). 2025-12-04T09:26:07.6641540Z 2025-12-04T09:26:07.6641805Z This API may be used as a decorator (see examples). 2025-12-04T09:26:07.6642175Z 2025-12-04T09:26:07.6642710Z For a detailed guide on custom ops, please see 2025-12-04T09:26:07.6643233Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-12-04T09:26:07.6643701Z 2025-12-04T09:26:07.6643903Z Args: 2025-12-04T09:26:07.6644324Z op_name: Operator name (along with the overload) or OpOverload object. 2025-12-04T09:26:07.6644824Z func: Fake tensor implementation. 2025-12-04T09:26:07.6645271Z lib (Optional[Library]): Library to register the fake tensor to. 2025-12-04T09:26:07.6645796Z allow_override: Flag controlling if we want to override an 2025-12-04T09:26:07.6646289Z existing registered fake impl. This is by default off, 2025-12-04T09:26:07.6646787Z and will error you're trying to register a fake impl to 2025-12-04T09:26:07.6647282Z an operator that already has a fake impl. This also only 2025-12-04T09:26:07.6647769Z applies if the custom operator was not created via 2025-12-04T09:26:07.6648255Z torch.library.custom_op, as overriding and existing fake 2025-12-04T09:26:07.6648704Z impl is already allowed. 2025-12-04T09:26:07.6649033Z 2025-12-04T09:26:07.6649224Z Examples: 2025-12-04T09:26:07.6649472Z >>> import torch 2025-12-04T09:26:07.6649759Z >>> import numpy as np 2025-12-04T09:26:07.6650066Z >>> from torch import Tensor 2025-12-04T09:26:07.6650380Z >>> 2025-12-04T09:26:07.6650718Z >>> # Example 1: an operator without data-dependent output shape 2025-12-04T09:26:07.6651617Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-12-04T09:26:07.6652208Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-12-04T09:26:07.6652771Z >>> raise NotImplementedError("Implementation goes here") 2025-12-04T09:26:07.6653173Z >>> 2025-12-04T09:26:07.6653476Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-12-04T09:26:07.6653883Z >>> def _(x, weight, bias): 2025-12-04T09:26:07.6654207Z >>> assert x.dim() == 2 2025-12-04T09:26:07.6654528Z >>> assert weight.dim() == 2 2025-12-04T09:26:07.6654874Z >>> assert bias.dim() == 1 2025-12-04T09:26:07.6655231Z >>> assert x.shape[1] == weight.shape[1] 2025-12-04T09:26:07.6655620Z >>> assert weight.shape[0] == bias.shape[0] 2025-12-04T09:26:07.6655997Z >>> assert x.device == weight.device 2025-12-04T09:26:07.6656337Z >>> 2025-12-04T09:26:07.6656597Z >>> return (x @ weight.t()) + bias 2025-12-04T09:26:07.6656914Z >>> 2025-12-04T09:26:07.6657233Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-12-04T09:26:07.6657848Z >>> x = torch.randn(2, 3) 2025-12-04T09:26:07.6658175Z >>> w = torch.randn(3, 3) 2025-12-04T09:26:07.6658503Z >>> b = torch.randn(3) 2025-12-04T09:26:07.6658867Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-12-04T09:26:07.6659208Z >>> 2025-12-04T09:26:07.6659454Z >>> assert y.shape == (2, 3) 2025-12-04T09:26:07.6659849Z >>> 2025-12-04T09:26:07.6660171Z >>> # Example 2: an operator with data-dependent output shape 2025-12-04T09:26:07.6660703Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-12-04T09:26:07.6661201Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-12-04T09:26:07.6661581Z >>> x_np = x.numpy(force=True) 2025-12-04T09:26:07.6661947Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-12-04T09:26:07.6662352Z >>> return torch.tensor(res, device=x.device) 2025-12-04T09:26:07.6662706Z >>> 2025-12-04T09:26:07.6663021Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-12-04T09:26:07.6663424Z >>> def _(x): 2025-12-04T09:26:07.6663751Z >>> # Number of nonzero-elements is data-dependent. 2025-12-04T09:26:07.6664191Z >>> # Since we cannot peek at the data in an fake impl, 2025-12-04T09:26:07.6664629Z >>> # we use the ctx object to construct a new symint that 2025-12-04T09:26:07.6665078Z >>> # represents the data-dependent size. 2025-12-04T09:26:07.6665461Z >>> ctx = torch.library.get_ctx() 2025-12-04T09:26:07.6665816Z >>> nnz = ctx.new_dynamic_size() 2025-12-04T09:26:07.6666170Z >>> shape = [nnz, x.dim()] 2025-12-04T09:26:07.6666558Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-12-04T09:26:07.6666948Z >>> return result 2025-12-04T09:26:07.6667227Z >>> 2025-12-04T09:26:07.6667558Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-12-04T09:26:07.6667961Z >>> 2025-12-04T09:26:07.6668208Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-12-04T09:26:07.6668710Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-12-04T09:26:07.6669226Z >>> trace.print_readable() 2025-12-04T09:26:07.6669530Z >>> 2025-12-04T09:26:07.6670087Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-12-04T09:26:07.6670550Z 2025-12-04T09:26:07.6670752Z 2025-12-04T09:26:07.6671431Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-12-04T09:26:07.6672219Z 2025-12-04T09:26:07.6672425Z _._ = None 2025-12-04T09:26:07.6672632Z ^ 2025-12-04T09:26:07.6672850Z warnings.warn(msg) 2025-12-04T09:26:07.6673109Z 2025-12-04T09:26:07.6673581Z --- Parse Warning: 3 / 17 --- 2025-12-04T09:26:07.6674796Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py line=1530. 2025-12-04T09:26:07.6676079Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6676701Z Returns the computed kernel for a given operator and dispatch key. 2025-12-04T09:26:07.6677119Z 2025-12-04T09:26:07.6677469Z This function retrieves the kernel that would be executed for a given 2025-12-04T09:26:07.6678078Z operator and dispatch key combination. The returned SafeKernelFunction 2025-12-04T09:26:07.6678644Z can be used to call the kernel in a boxed fashion. The intended use 2025-12-04T09:26:07.6679198Z case for this function is to retrieve the original kernel for a given 2025-12-04T09:26:07.6693544Z dispatch key and then register another kernel to the same dispatch key 2025-12-04T09:26:07.6694254Z that calls into the original kernel for certain cases. 2025-12-04T09:26:07.6694627Z 2025-12-04T09:26:07.6694839Z Args: 2025-12-04T09:26:07.6695193Z op: Operator name (along with the overload) or OpOverload object 2025-12-04T09:26:07.6695776Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-12-04T09:26:07.6696493Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-12-04T09:26:07.6697105Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-12-04T09:26:07.6697512Z 2025-12-04T09:26:07.6697721Z Returns: 2025-12-04T09:26:07.6698119Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-12-04T09:26:07.6698610Z call the kernel. 2025-12-04T09:26:07.6698879Z 2025-12-04T09:26:07.6699083Z Raises: 2025-12-04T09:26:07.6699379Z RuntimeError: If the operator does not exist. 2025-12-04T09:26:07.6699722Z 2025-12-04T09:26:07.6699929Z Example: 2025-12-04T09:26:07.6700192Z >>> # Get the CPU kernel for torch.add 2025-12-04T09:26:07.6700630Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-12-04T09:26:07.6701047Z >>> 2025-12-04T09:26:07.6701315Z >>> # You can also use DispatchKey enum 2025-12-04T09:26:07.6701826Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-12-04T09:26:07.6702322Z >>> 2025-12-04T09:26:07.6702581Z >>> # Or use an OpOverload directly 2025-12-04T09:26:07.6703058Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-12-04T09:26:07.6703497Z >>> 2025-12-04T09:26:07.6703858Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-12-04T09:26:07.6704343Z >>> # Get the original kernel for torch.sin 2025-12-04T09:26:07.6704810Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-12-04T09:26:07.6705252Z >>> 2025-12-04T09:26:07.6705628Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-12-04T09:26:07.6706143Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-12-04T09:26:07.6706505Z >>> if (x < 0).any(): 2025-12-04T09:26:07.6706905Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-12-04T09:26:07.6707321Z >>> else: 2025-12-04T09:26:07.6707601Z >>> return torch.zeros_like(x) 2025-12-04T09:26:07.6707935Z >>> 2025-12-04T09:26:07.6708219Z >>> lib = torch.library.Library("aten", "IMPL") 2025-12-04T09:26:07.6708749Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-12-04T09:26:07.6709359Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-12-04T09:26:07.6709891Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-12-04T09:26:07.6710311Z >>> 2025-12-04T09:26:07.6710559Z >>> # Test the conditional behavior 2025-12-04T09:26:07.6710932Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-12-04T09:26:07.6711306Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-12-04T09:26:07.6711654Z >>> torch.sin(x_positive) 2025-12-04T09:26:07.6711974Z tensor([0., 0.]) 2025-12-04T09:26:07.6712262Z >>> torch.sin(x_mixed) 2025-12-04T09:26:07.6712558Z tensor([-0.8415, 0.9093]) 2025-12-04T09:26:07.6712857Z 2025-12-04T09:26:07.6713500Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-12-04T09:26:07.6714226Z 2025-12-04T09:26:07.6714520Z which needs to be the first argument to ``kernel.call_boxed`` 2025-12-04T09:26:07.6715007Z ^ 2025-12-04T09:26:07.6715244Z warnings.warn(msg) 2025-12-04T09:26:07.6715497Z 2025-12-04T09:26:07.6715940Z --- Parse Warning: 4 / 17 --- 2025-12-04T09:26:07.6717158Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py line=70. 2025-12-04T09:26:07.6718577Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6719235Z Check if the current accelerator is available at runtime: it was build, all the 2025-12-04T09:26:07.6719860Z required drivers are available and at least one device is visible. 2025-12-04T09:26:07.6720374Z See :ref:`accelerator` for details. 2025-12-04T09:26:07.6720723Z 2025-12-04T09:26:07.6720931Z Returns: 2025-12-04T09:26:07.6721374Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-12-04T09:26:07.6721872Z 2025-12-04T09:26:07.6722253Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-12-04T09:26:07.6722919Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-12-04T09:26:07.6723589Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-12-04T09:26:07.6724132Z :ref:`multiprocessing-poison-fork-note`. 2025-12-04T09:26:07.6724614Z 2025-12-04T09:26:07.6724832Z Example:: 2025-12-04T09:26:07.6725052Z 2025-12-04T09:26:07.6725456Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:26:07.6725956Z 2025-12-04T09:26:07.6726670Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-12-04T09:26:07.6727483Z 2025-12-04T09:26:07.6727871Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:26:07.6728380Z ^ 2025-12-04T09:26:07.6728694Z warnings.warn(msg) 2025-12-04T09:26:07.6728956Z 2025-12-04T09:26:07.6729285Z --- Parse Warning: 5 / 17 --- 2025-12-04T09:26:07.6730502Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/accelerator/__init__.py line=239. 2025-12-04T09:26:07.6731858Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6732471Z Wait for all kernels in all streams on the given device to complete. 2025-12-04T09:26:07.6732902Z 2025-12-04T09:26:07.6733095Z Args: 2025-12-04T09:26:07.6733572Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-12-04T09:26:07.6734284Z the current :ref:`accelerator` device type. If not given, 2025-12-04T09:26:07.6734848Z use :func:`torch.accelerator.current_device_index` by default. 2025-12-04T09:26:07.6735267Z 2025-12-04T09:26:07.6735717Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-12-04T09:26:07.6736259Z 2025-12-04T09:26:07.6736456Z Example:: 2025-12-04T09:26:07.6736686Z 2025-12-04T09:26:07.6736946Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-12-04T09:26:07.6737484Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:26:07.6738049Z >>> start_event = torch.Event(enable_timing=True) 2025-12-04T09:26:07.6738467Z >>> end_event = torch.Event(enable_timing=True) 2025-12-04T09:26:07.6738829Z >>> start_event.record() 2025-12-04T09:26:07.6739409Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-12-04T09:26:07.6739906Z >>> sum = torch.sum(tensor) 2025-12-04T09:26:07.6740239Z >>> end_event.record() 2025-12-04T09:26:07.6740565Z >>> torch.accelerator.synchronize() 2025-12-04T09:26:07.6740996Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-12-04T09:26:07.6741448Z 2025-12-04T09:26:07.6742160Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-12-04T09:26:07.6743309Z 2025-12-04T09:26:07.6743702Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-12-04T09:26:07.6744199Z ^ 2025-12-04T09:26:07.6744527Z warnings.warn(msg) 2025-12-04T09:26:07.6744791Z 2025-12-04T09:26:07.6745130Z --- Parse Warning: 6 / 17 --- 2025-12-04T09:26:07.6746281Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py line=448. 2025-12-04T09:26:07.6747572Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6748094Z Retrieves the CUDA runtime API module. 2025-12-04T09:26:07.6748408Z 2025-12-04T09:26:07.6748609Z 2025-12-04T09:26:07.6748989Z This function initializes the CUDA runtime environment if it is not already 2025-12-04T09:26:07.6749624Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-12-04T09:26:07.6750210Z runtime API module provides access to various CUDA runtime functions. 2025-12-04T09:26:07.6750659Z 2025-12-04T09:26:07.6750861Z Args: 2025-12-04T09:26:07.6751068Z ``None`` 2025-12-04T09:26:07.6751304Z 2025-12-04T09:26:07.6751506Z Returns: 2025-12-04T09:26:07.6751790Z module: The CUDA runtime API module (_cudart). 2025-12-04T09:26:07.6752146Z 2025-12-04T09:26:07.6752344Z Raises: 2025-12-04T09:26:07.6752742Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-12-04T09:26:07.6753497Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-12-04T09:26:07.6754086Z 2025-12-04T09:26:07.6754346Z Example of CUDA operations with profiling: 2025-12-04T09:26:07.6754711Z >>> import torch 2025-12-04T09:26:07.6755025Z >>> from torch.cuda import cudart, check_error 2025-12-04T09:26:07.6755383Z >>> import os 2025-12-04T09:26:07.6755644Z >>> 2025-12-04T09:26:07.6755895Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-12-04T09:26:07.6756228Z >>> 2025-12-04T09:26:07.6756510Z >>> def perform_cuda_operations_with_streams(): 2025-12-04T09:26:07.6756892Z >>> stream = torch.cuda.Stream() 2025-12-04T09:26:07.6757254Z >>> with torch.cuda.stream(stream): 2025-12-04T09:26:07.6757639Z >>> x = torch.randn(100, 100, device='cuda') 2025-12-04T09:26:07.6758030Z >>> y = torch.randn(100, 100, device='cuda') 2025-12-04T09:26:07.6758381Z >>> z = torch.mul(x, y) 2025-12-04T09:26:07.6758706Z >>> return z 2025-12-04T09:26:07.6758979Z >>> 2025-12-04T09:26:07.6759223Z >>> torch.cuda.synchronize() 2025-12-04T09:26:07.6759591Z >>> print("====== Start nsys profiling ======") 2025-12-04T09:26:07.6759991Z >>> check_error(cudart().cudaProfilerStart()) 2025-12-04T09:26:07.6760384Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-12-04T09:26:07.6760805Z >>> result = perform_cuda_operations_with_streams() 2025-12-04T09:26:07.6761222Z >>> print("CUDA operations completed.") 2025-12-04T09:26:07.6761866Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-12-04T09:26:07.6762287Z >>> print("====== End nsys profiling ======") 2025-12-04T09:26:07.6762638Z 2025-12-04T09:26:07.6762964Z To run this example and save the profiling information, execute: 2025-12-04T09:26:07.6763675Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-12-04T09:26:07.6764478Z 2025-12-04T09:26:07.6764855Z This command profiles the CUDA operations in the provided script and saves 2025-12-04T09:26:07.6765450Z the profiling information to a file named `trace_name.prof`. 2025-12-04T09:26:07.6766013Z The `--profile-from-start off` option ensures that profiling starts only 2025-12-04T09:26:07.6766543Z after the `cudaProfilerStart` call in the script. 2025-12-04T09:26:07.6767054Z The `--csv` and `--print-summary` options format the profiling output as a 2025-12-04T09:26:07.6767547Z CSV file and print a summary, respectively. 2025-12-04T09:26:07.6768065Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-12-04T09:26:07.6768611Z overwrite of the output file if it already exists. 2025-12-04T09:26:07.6768978Z 2025-12-04T09:26:07.6769785Z 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)) 2025-12-04T09:26:07.6770695Z 2025-12-04T09:26:07.6771182Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-12-04T09:26:07.6771755Z ^ 2025-12-04T09:26:07.6771973Z warnings.warn(msg) 2025-12-04T09:26:07.6772232Z 2025-12-04T09:26:07.6772585Z --- Parse Warning: 7 / 17 --- 2025-12-04T09:26:07.6773742Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/apis.py line=39. 2025-12-04T09:26:07.6775021Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6775497Z 2025-12-04T09:26:07.6775833Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-12-04T09:26:07.6776402Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-12-04T09:26:07.6776967Z pushes the map into PyTorch operations called by ``func``, effectively 2025-12-04T09:26:07.6777425Z vectorizing those operations. 2025-12-04T09:26:07.6777720Z 2025-12-04T09:26:07.6778055Z vmap is useful for handling batch dimensions: one can write a function 2025-12-04T09:26:07.6778617Z ``func`` that runs on examples and then lift it to a function that can 2025-12-04T09:26:07.6779166Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-12-04T09:26:07.6779699Z compute batched gradients when composed with autograd. 2025-12-04T09:26:07.6780081Z 2025-12-04T09:26:07.6780282Z .. note:: 2025-12-04T09:26:07.6780607Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-12-04T09:26:07.6781059Z convenience. Use whichever one you'd like. 2025-12-04T09:26:07.6781386Z 2025-12-04T09:26:07.6781585Z Args: 2025-12-04T09:26:07.6781929Z func (function): A Python function that takes one or more arguments. 2025-12-04T09:26:07.6782381Z Must return one or more Tensors. 2025-12-04T09:26:07.6782822Z in_dims (int or nested structure): Specifies which dimension of the 2025-12-04T09:26:07.6783339Z inputs should be mapped over. ``in_dims`` should have a 2025-12-04T09:26:07.6783841Z structure like the inputs. If the ``in_dim`` for a particular 2025-12-04T09:26:07.6784350Z input is None, then that indicates there is no map dimension. 2025-12-04T09:26:07.6784764Z Default: 0. 2025-12-04T09:26:07.6785276Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-12-04T09:26:07.6785798Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-12-04T09:26:07.6786288Z it should have one element per output. Default: 0. 2025-12-04T09:26:07.6786769Z randomness (str): Specifies whether the randomness in this 2025-12-04T09:26:07.6787360Z vmap should be the same or different across batches. If 'different', 2025-12-04T09:26:07.6787908Z the randomness for each batch will be different. If 'same', the 2025-12-04T09:26:07.6788468Z randomness will be the same across batches. If 'error', any calls to 2025-12-04T09:26:07.6789042Z random functions will error. Default: 'error'. WARNING: this flag 2025-12-04T09:26:07.6789593Z only applies to random PyTorch operations and does not apply to 2025-12-04T09:26:07.6790079Z Python's random module or numpy randomness. 2025-12-04T09:26:07.6790585Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-12-04T09:26:07.6791183Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-12-04T09:26:07.6791806Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-12-04T09:26:07.6792494Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-12-04T09:26:07.6792988Z 2025-12-04T09:26:07.6793178Z Returns: 2025-12-04T09:26:07.6793506Z Returns a new "batched" function. It takes the same inputs as 2025-12-04T09:26:07.6794024Z ``func``, except each input has an extra dimension at the index 2025-12-04T09:26:07.6794539Z specified by ``in_dims``. It takes returns the same outputs as 2025-12-04T09:26:07.6795042Z ``func``, except each output has an extra dimension at the index 2025-12-04T09:26:07.6795470Z specified by ``out_dims``. 2025-12-04T09:26:07.6795767Z 2025-12-04T09:26:07.6795958Z .. warning: 2025-12-04T09:26:07.6796307Z :func:`vmap` works best with functional-style code. Please do not 2025-12-04T09:26:07.6796837Z perform any side-effects in ``func``, with the exception of 2025-12-04T09:26:07.6797393Z in-place PyTorch operations. Examples of side-effects include mutating 2025-12-04T09:26:07.6798016Z Python data structures and assigning values to variables not captured 2025-12-04T09:26:07.6798475Z in ``func``. 2025-12-04T09:26:07.6798715Z 2025-12-04T09:26:07.6799066Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-12-04T09:26:07.6799930Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-12-04T09:26:07.6800527Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-12-04T09:26:07.6800959Z 2025-12-04T09:26:07.6801194Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:26:07.6801635Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-12-04T09:26:07.6802095Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-12-04T09:26:07.6802456Z >>> batched_dot(x, y) 2025-12-04T09:26:07.6802732Z 2025-12-04T09:26:07.6803088Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-12-04T09:26:07.6803560Z model authoring experience. 2025-12-04T09:26:07.6803843Z 2025-12-04T09:26:07.6804073Z >>> batch_size, feature_size = 3, 5 2025-12-04T09:26:07.6804574Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-12-04T09:26:07.6805104Z >>> 2025-12-04T09:26:07.6805337Z >>> def model(feature_vec): 2025-12-04T09:26:07.6805667Z >>> # Very simple linear model with activation 2025-12-04T09:26:07.6806053Z >>> return feature_vec.dot(weights).relu() 2025-12-04T09:26:07.6806389Z >>> 2025-12-04T09:26:07.6806657Z >>> examples = torch.randn(batch_size, feature_size) 2025-12-04T09:26:07.6807168Z >>> result = torch.vmap(model)(examples) 2025-12-04T09:26:07.6807502Z 2025-12-04T09:26:07.6807879Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-12-04T09:26:07.6808513Z or impossible to batch. One example is higher-order gradient computation. 2025-12-04T09:26:07.6809135Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-12-04T09:26:07.6809805Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-12-04T09:26:07.6810420Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-12-04T09:26:07.6811057Z we can vectorize the whole computation, computing the Jacobian in a single 2025-12-04T09:26:07.6811667Z call to ``autograd.grad``. 2025-12-04T09:26:07.6811948Z 2025-12-04T09:26:07.6812139Z >>> # Setup 2025-12-04T09:26:07.6812371Z >>> N = 5 2025-12-04T09:26:07.6812614Z >>> f = lambda x: x**2 2025-12-04T09:26:07.6812922Z >>> x = torch.randn(N, requires_grad=True) 2025-12-04T09:26:07.6813259Z >>> y = f(x) 2025-12-04T09:26:07.6813513Z >>> I_N = torch.eye(N) 2025-12-04T09:26:07.6813779Z >>> 2025-12-04T09:26:07.6814013Z >>> # Sequential approach 2025-12-04T09:26:07.6814448Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-12-04T09:26:07.6814910Z >>> for v in I_N.unbind()] 2025-12-04T09:26:07.6815275Z >>> jacobian = torch.stack(jacobian_rows) 2025-12-04T09:26:07.6815608Z >>> 2025-12-04T09:26:07.6815842Z >>> # vectorized gradient computation 2025-12-04T09:26:07.6816180Z >>> def get_vjp(v): 2025-12-04T09:26:07.6816488Z >>> return torch.autograd.grad(y, x, v) 2025-12-04T09:26:07.6816860Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-12-04T09:26:07.6817175Z 2025-12-04T09:26:07.6817568Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-12-04T09:26:07.6818062Z 2025-12-04T09:26:07.6818270Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:26:07.6818605Z >>> batched_dot = torch.vmap( 2025-12-04T09:26:07.6818931Z ... torch.vmap(torch.dot) 2025-12-04T09:26:07.6819256Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-12-04T09:26:07.6819642Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-12-04T09:26:07.6820044Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-12-04T09:26:07.6820367Z 2025-12-04T09:26:07.6820733Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-12-04T09:26:07.6821274Z the dimension that each inputs are batched along as 2025-12-04T09:26:07.6821638Z 2025-12-04T09:26:07.6821845Z >>> torch.dot # [N], [N] -> [] 2025-12-04T09:26:07.6822297Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-12-04T09:26:07.6822791Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-12-04T09:26:07.6823124Z >>> batched_dot( 2025-12-04T09:26:07.6823379Z ... x, y 2025-12-04T09:26:07.6823730Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-12-04T09:26:07.6824124Z 2025-12-04T09:26:07.6824512Z If there are multiple inputs each of which is batched along different dimensions, 2025-12-04T09:26:07.6825132Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-12-04T09:26:07.6825556Z 2025-12-04T09:26:07.6825764Z >>> torch.dot # [D], [D] -> [] 2025-12-04T09:26:07.6826232Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-12-04T09:26:07.6826742Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-12-04T09:26:07.6827075Z >>> batched_dot( 2025-12-04T09:26:07.6827333Z ... x, y 2025-12-04T09:26:07.6827684Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-12-04T09:26:07.6828083Z 2025-12-04T09:26:07.6828533Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-12-04T09:26:07.6829029Z matching the shape of the input: 2025-12-04T09:26:07.6829317Z 2025-12-04T09:26:07.6829578Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-12-04T09:26:07.6829978Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-12-04T09:26:07.6830382Z >>> input = {"x": x, "y": y} 2025-12-04T09:26:07.6830765Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-12-04T09:26:07.6831179Z >>> batched_dot(input) 2025-12-04T09:26:07.6831453Z 2025-12-04T09:26:07.6831846Z By default, the output is batched along the first dimension. However, it can be batched 2025-12-04T09:26:07.6832399Z along any dimension by using ``out_dims`` 2025-12-04T09:26:07.6832731Z 2025-12-04T09:26:07.6832932Z >>> f = lambda x: x**2 2025-12-04T09:26:07.6833228Z >>> x = torch.randn(2, 5) 2025-12-04T09:26:07.6833564Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-12-04T09:26:07.6833924Z >>> batched_pow(x) # [5, 2] 2025-12-04T09:26:07.6834205Z 2025-12-04T09:26:07.6834628Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-12-04T09:26:07.6835157Z accept kwargs 2025-12-04T09:26:07.6835374Z 2025-12-04T09:26:07.6835595Z >>> x = torch.randn([2, 5]) 2025-12-04T09:26:07.6835907Z >>> def fn(x, scale=4.): 2025-12-04T09:26:07.6836187Z >>> return x * scale 2025-12-04T09:26:07.6836457Z >>> 2025-12-04T09:26:07.6836697Z >>> batched_pow = torch.vmap(fn) 2025-12-04T09:26:07.6837057Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-12-04T09:26:07.6837557Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-12-04T09:26:07.6838008Z 2025-12-04T09:26:07.6838215Z .. note:: 2025-12-04T09:26:07.6838586Z vmap does not provide general autobatching or handle variable-length 2025-12-04T09:26:07.6839050Z sequences out of the box. 2025-12-04T09:26:07.6839339Z 2025-12-04T09:26:07.6840005Z Original Error: IndentationError('expected an indented block after function definition on line 4', ('', 5, 1, '_._ = None\n', 5, 2)) 2025-12-04T09:26:07.6840774Z 2025-12-04T09:26:07.6840973Z _._ = None 2025-12-04T09:26:07.6841184Z ^ 2025-12-04T09:26:07.6841399Z warnings.warn(msg) 2025-12-04T09:26:07.6841657Z 2025-12-04T09:26:07.6842072Z --- Parse Warning: 8 / 17 --- 2025-12-04T09:26:07.6843590Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/apis.py line=306. 2025-12-04T09:26:07.6844977Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6845624Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-12-04T09:26:07.6846198Z input(s) specified by ``argnums``. This operator can be nested to 2025-12-04T09:26:07.6846655Z compute higher-order gradients. 2025-12-04T09:26:07.6846975Z 2025-12-04T09:26:07.6847163Z Args: 2025-12-04T09:26:07.6847516Z func (Callable): A Python function that takes one or more arguments. 2025-12-04T09:26:07.6848146Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-12-04T09:26:07.6848833Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-12-04T09:26:07.6849330Z ``(output, aux)``. 2025-12-04T09:26:07.6849824Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-12-04T09:26:07.6850453Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-12-04T09:26:07.6851283Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-12-04T09:26:07.6851813Z auxiliary objects: ``(output, aux)``. Default: False. 2025-12-04T09:26:07.6852192Z 2025-12-04T09:26:07.6852381Z Returns: 2025-12-04T09:26:07.6852825Z Function to compute gradients with respect to its inputs. By default, the output of 2025-12-04T09:26:07.6853500Z the function is the gradient tensor(s) with respect to the first argument. 2025-12-04T09:26:07.6854242Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-12-04T09:26:07.6854908Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-12-04T09:26:07.6855455Z respect to each ``argnums`` value is returned. 2025-12-04T09:26:07.6855810Z 2025-12-04T09:26:07.6856016Z Example of using ``grad``: 2025-12-04T09:26:07.6856308Z 2025-12-04T09:26:07.6856521Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6856841Z >>> from torch.func import grad 2025-12-04T09:26:07.6857168Z >>> x = torch.randn([]) 2025-12-04T09:26:07.6857508Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-12-04T09:26:07.6857889Z >>> assert torch.allclose(cos_x, x.cos()) 2025-12-04T09:26:07.6858209Z >>> 2025-12-04T09:26:07.6858456Z >>> # Second-order gradients 2025-12-04T09:26:07.6858842Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-12-04T09:26:07.6859269Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-12-04T09:26:07.6859616Z 2025-12-04T09:26:07.6859983Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-12-04T09:26:07.6860464Z 2025-12-04T09:26:07.6860683Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6861003Z >>> from torch.func import grad, vmap 2025-12-04T09:26:07.6861374Z >>> batch_size, feature_size = 3, 5 2025-12-04T09:26:07.6861701Z >>> 2025-12-04T09:26:07.6861953Z >>> def model(weights, feature_vec): 2025-12-04T09:26:07.6862337Z >>> # Very simple linear model with activation 2025-12-04T09:26:07.6862721Z >>> assert feature_vec.dim() == 1 2025-12-04T09:26:07.6863100Z >>> return feature_vec.dot(weights).relu() 2025-12-04T09:26:07.6863431Z >>> 2025-12-04T09:26:07.6863719Z >>> def compute_loss(weights, example, target): 2025-12-04T09:26:07.6864109Z >>> y = model(weights, example) 2025-12-04T09:26:07.6864477Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-12-04T09:26:07.6864838Z >>> 2025-12-04T09:26:07.6865158Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-12-04T09:26:07.6865614Z >>> examples = torch.randn(batch_size, feature_size) 2025-12-04T09:26:07.6866012Z >>> targets = torch.randn(batch_size) 2025-12-04T09:26:07.6866388Z >>> inputs = (weights, examples, targets) 2025-12-04T09:26:07.6866883Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-12-04T09:26:07.6867345Z ... *inputs 2025-12-04T09:26:07.6867609Z ... ) 2025-12-04T09:26:07.6867833Z 2025-12-04T09:26:07.6868119Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-12-04T09:26:07.6868513Z 2025-12-04T09:26:07.6868725Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6869028Z >>> from torch.func import grad 2025-12-04T09:26:07.6869373Z >>> def my_loss_func(y, y_pred): 2025-12-04T09:26:07.6869738Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-12-04T09:26:07.6870108Z >>> loss = loss_per_sample.mean() 2025-12-04T09:26:07.6870491Z >>> return loss, (y_pred, loss_per_sample) 2025-12-04T09:26:07.6870830Z >>> 2025-12-04T09:26:07.6871121Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-12-04T09:26:07.6871592Z >>> y_true = torch.rand(4) 2025-12-04T09:26:07.6871957Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-12-04T09:26:07.6872334Z >>> out = fn(y_true, y_preds) 2025-12-04T09:26:07.6872804Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-12-04T09:26:07.6873327Z 2025-12-04T09:26:07.6873547Z .. note:: 2025-12-04T09:26:07.6873852Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-12-04T09:26:07.6874237Z 2025-12-04T09:26:07.6874504Z Case 1: Using ``torch.no_grad`` inside a function: 2025-12-04T09:26:07.6874851Z 2025-12-04T09:26:07.6875069Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6875383Z >>> def f(x): 2025-12-04T09:26:07.6875688Z >>> with torch.no_grad(): 2025-12-04T09:26:07.6876008Z >>> c = x ** 2 2025-12-04T09:26:07.6876320Z >>> return x - c 2025-12-04T09:26:07.6876616Z 2025-12-04T09:26:07.6876925Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-12-04T09:26:07.6877347Z 2025-12-04T09:26:07.6877652Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-12-04T09:26:07.6878042Z 2025-12-04T09:26:07.6878257Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6878580Z >>> with torch.no_grad(): 2025-12-04T09:26:07.6878888Z >>> grad(f)(x) 2025-12-04T09:26:07.6879170Z 2025-12-04T09:26:07.6879516Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-12-04T09:26:07.6880108Z outer one. This is because ``grad`` is a "function transform": its result 2025-12-04T09:26:07.6880686Z should not depend on the result of a context manager outside of ``f``. 2025-12-04T09:26:07.6881130Z 2025-12-04T09:26:07.6881327Z 2025-12-04T09:26:07.6882000Z Original Error: IndentationError('expected an indented block after function definition on line 5', ('', 6, 1, '_._ = None\n', 6, 2)) 2025-12-04T09:26:07.6882768Z 2025-12-04T09:26:07.6882966Z _._ = None 2025-12-04T09:26:07.6883174Z ^ 2025-12-04T09:26:07.6883391Z warnings.warn(msg) 2025-12-04T09:26:07.6883647Z 2025-12-04T09:26:07.6884057Z --- Parse Warning: 9 / 17 --- 2025-12-04T09:26:07.6885447Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py line=402. 2025-12-04T09:26:07.6886874Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6887448Z Register a FakeTensor implementation for this custom op. 2025-12-04T09:26:07.6887827Z 2025-12-04T09:26:07.6888199Z This is necessary to get the operator to work efficiently with torch.compile. 2025-12-04T09:26:07.6888678Z 2025-12-04T09:26:07.6889011Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-12-04T09:26:07.6889609Z specifies the behavior of this operator on Tensors that carry no data. 2025-12-04T09:26:07.6890134Z Given some input Tensors with certain properties 2025-12-04T09:26:07.6890691Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-12-04T09:26:07.6891190Z the output Tensors are. 2025-12-04T09:26:07.6891488Z 2025-12-04T09:26:07.6891820Z Please see :func:`torch.library.register_fake` for more details. 2025-12-04T09:26:07.6892236Z 2025-12-04T09:26:07.6892435Z Args: 2025-12-04T09:26:07.6892756Z fn (Callable): The function to register as the FakeTensor 2025-12-04T09:26:07.6893148Z implementation. 2025-12-04T09:26:07.6893440Z 2025-12-04T09:26:07.6893643Z Examples: 2025-12-04T09:26:07.6894017Z >>> import torch 2025-12-04T09:26:07.6894314Z >>> import numpy as np 2025-12-04T09:26:07.6894647Z >>> from torch import Tensor 2025-12-04T09:26:07.6894966Z >>> 2025-12-04T09:26:07.6895302Z >>> # Example 1: an operator without data-dependent output shape 2025-12-04T09:26:07.6895834Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-12-04T09:26:07.6896418Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-12-04T09:26:07.6896862Z >>> return (x @ weight.t()) + bias 2025-12-04T09:26:07.6897197Z >>> 2025-12-04T09:26:07.6897460Z >>> @linear.register_fake 2025-12-04T09:26:07.6897804Z >>> def _(x, weight, bias): 2025-12-04T09:26:07.6898126Z >>> assert x.dim() == 2 2025-12-04T09:26:07.6898473Z >>> assert weight.dim() == 2 2025-12-04T09:26:07.6898837Z >>> assert bias.dim() == 1 2025-12-04T09:26:07.6899192Z >>> assert x.shape[1] == weight.shape[1] 2025-12-04T09:26:07.6899590Z >>> assert weight.shape[0] == bias.shape[0] 2025-12-04T09:26:07.6899987Z >>> assert x.device == weight.device 2025-12-04T09:26:07.6900381Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-12-04T09:26:07.6900757Z >>> 2025-12-04T09:26:07.6901016Z >>> x = torch.randn(2, 2) 2025-12-04T09:26:07.6901359Z >>> weight = torch.randn(2, 2) 2025-12-04T09:26:07.6901688Z >>> bias = torch.randn(2) 2025-12-04T09:26:07.6902057Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:26:07.6902520Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-12-04T09:26:07.6902977Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:26:07.6903508Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-12-04T09:26:07.6903992Z >>> 2025-12-04T09:26:07.6904306Z >>> # Example 2: an operator with data-dependent output shape 2025-12-04T09:26:07.6904818Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-12-04T09:26:07.6905272Z >>> def nonzero(x: Tensor) -> Tensor: 2025-12-04T09:26:07.6905638Z >>> x_np = x.cpu().numpy() 2025-12-04T09:26:07.6905996Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-12-04T09:26:07.6906400Z >>> return torch.tensor(res, device=x.device) 2025-12-04T09:26:07.6906752Z >>> 2025-12-04T09:26:07.6906999Z >>> @nonzero.register_fake 2025-12-04T09:26:07.6907319Z >>> def _(x): 2025-12-04T09:26:07.6907669Z >>> # Number of nonzero-elements is data-dependent. 2025-12-04T09:26:07.6908118Z >>> # Since we cannot peek at the data in an abstract impl, 2025-12-04T09:26:07.6908610Z >>> # we use the ctx object to construct a new symint that 2025-12-04T09:26:07.6909437Z >>> # represents the data-dependent size. 2025-12-04T09:26:07.6909994Z >>> ctx = torch.library.get_ctx() 2025-12-04T09:26:07.6910528Z >>> nnz = ctx.new_dynamic_size() 2025-12-04T09:26:07.6911118Z >>> shape = [nnz, x.dim()] 2025-12-04T09:26:07.6911696Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-12-04T09:26:07.6912302Z >>> return result 2025-12-04T09:26:07.6912796Z >>> 2025-12-04T09:26:07.6913226Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-12-04T09:26:07.6913855Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:26:07.6914500Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-12-04T09:26:07.6915170Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-12-04T09:26:07.6915578Z >>> assert torch.allclose(out, x.nonzero()) 2025-12-04T09:26:07.6915913Z 2025-12-04T09:26:07.6916122Z 2025-12-04T09:26:07.6916829Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-12-04T09:26:07.6917652Z 2025-12-04T09:26:07.6917855Z _._ = None 2025-12-04T09:26:07.6918082Z ^ 2025-12-04T09:26:07.6918292Z warnings.warn(msg) 2025-12-04T09:26:07.6918554Z 2025-12-04T09:26:07.6919001Z --- Parse Warning: 10 / 17 --- 2025-12-04T09:26:07.6920314Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/fake_profile.py line=94. 2025-12-04T09:26:07.6921772Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-12-04T09:26:07.6922265Z 2025-12-04T09:26:07.6922621Z Registers a fake kernel based on the given operator profiles. This fake 2025-12-04T09:26:07.6923240Z kernel registration will override any existing fake kernel registrations. 2025-12-04T09:26:07.6923711Z 2025-12-04T09:26:07.6924051Z The input is a dictionary mapping operator names to a set of operator 2025-12-04T09:26:07.6924755Z profiles, which we will use to generate fake kernels. The operator profiles 2025-12-04T09:26:07.6925329Z are a record of the input and output tensor metadata. Based on this 2025-12-04T09:26:07.6925921Z information we will match a given input to the recorded profile, and return 2025-12-04T09:26:07.6926539Z an output with the same metadata as in the recorded profile. If a profile 2025-12-04T09:26:07.6927040Z doesn't exist then an exception will be thrown. 2025-12-04T09:26:07.6927393Z 2025-12-04T09:26:07.6927761Z The fake kernel generation is considered unsafe because it relies on the 2025-12-04T09:26:07.6928372Z rigid, pre-defined operator profiles that do not account for potential 2025-12-04T09:26:07.6928988Z variations in output behavior. Specifically, the generated kernels assume a 2025-12-04T09:26:07.6929646Z fixed relationship between input and output ranks. However, in reality, it's 2025-12-04T09:26:07.6930297Z possible that data-dependent operations may produce outputs of different 2025-12-04T09:26:07.6930900Z ranks even when given inputs of the same rank. The generated fake kernels 2025-12-04T09:26:07.6931484Z are inflexible and unable to accommodate these nuances, making them 2025-12-04T09:26:07.6931940Z potentially unsafe. 2025-12-04T09:26:07.6932193Z 2025-12-04T09:26:07.6932381Z Args: 2025-12-04T09:26:07.6932734Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-12-04T09:26:07.6933297Z name to a set of operator profiles from which we will generate fake 2025-12-04T09:26:07.6933717Z kernels. 2025-12-04T09:26:07.6933960Z 2025-12-04T09:26:07.6934168Z Examples: 2025-12-04T09:26:07.6934375Z 2025-12-04T09:26:07.6934674Z >>> # Example: Registering an op-profile from draft-export 2025-12-04T09:26:07.6935072Z >>> import torch 2025-12-04T09:26:07.6935399Z >>> from torch.export._draft_export import draft_export 2025-12-04T09:26:07.6935783Z >>> 2025-12-04T09:26:07.6936107Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-12-04T09:26:07.6936538Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-12-04T09:26:07.6936888Z >>> return x + y 2025-12-04T09:26:07.6937156Z >>> 2025-12-04T09:26:07.6937393Z >>> class M(torch.nn.Module): 2025-12-04T09:26:07.6937712Z >>> def forward(self, a, b): 2025-12-04T09:26:07.6938105Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-12-04T09:26:07.6938480Z >>> return res 2025-12-04T09:26:07.6938878Z >>> 2025-12-04T09:26:07.6939191Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-12-04T09:26:07.6939587Z >>> 2025-12-04T09:26:07.6940020Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-12-04T09:26:07.6940595Z >>> decomp = ep.run_decompositions() 2025-12-04T09:26:07.6940992Z 2025-12-04T09:26:07.6941177Z 2025-12-04T09:26:07.6941811Z Original Error: IncompleteParseError('ill-formed doctest: all parts have been processed but the doctest source is not balanced') 2025-12-04T09:26:07.6942910Z 2025-12-04T09:26:07.6943242Z warnings.warn(msg) 2025-12-04T09:26:07.6943495Z 2025-12-04T09:26:07.6943864Z --- Parse Warning: 11 / 17 --- 2025-12-04T09:26:07.6945416Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-12-04T09:26:07.6947066Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6947543Z 2025-12-04T09:26:07.6947940Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-12-04T09:26:07.6957984Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-12-04T09:26:07.6958678Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-12-04T09:26:07.6959178Z input by the user. 2025-12-04T09:26:07.6959593Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-12-04T09:26:07.6960128Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-12-04T09:26:07.6960484Z 2025-12-04T09:26:07.6960700Z Note:: 2025-12-04T09:26:07.6961166Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-12-04T09:26:07.6961720Z 2025-12-04T09:26:07.6961925Z Args: 2025-12-04T09:26:07.6962153Z model (nn.Module): 2025-12-04T09:26:07.6962556Z The model whose layers will be sparsified. The layers that needs to be 2025-12-04T09:26:07.6963180Z sparsified should be added separately using the register_layer() function 2025-12-04T09:26:07.6963697Z aggregate_fn (Optional, Callable): 2025-12-04T09:26:07.6964321Z default aggregate_fn that is used if not specified while registering the layer. 2025-12-04T09:26:07.6964886Z specifies how inputs should be aggregated over time. 2025-12-04T09:26:07.6965489Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-12-04T09:26:07.6966017Z Example 2025-12-04T09:26:07.6966336Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-12-04T09:26:07.6966772Z reduce_fn (Optional, Callable): 2025-12-04T09:26:07.6967281Z default reduce_fn that is used if not specified while registering the layer. 2025-12-04T09:26:07.6967941Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-12-04T09:26:07.6968454Z calling agg_fn() on all inputs. 2025-12-04T09:26:07.6968798Z Example 2025-12-04T09:26:07.6969187Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-12-04T09:26:07.6969628Z mask_fn (Optional, Callable): 2025-12-04T09:26:07.6970194Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-12-04T09:26:07.6970923Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-12-04T09:26:07.6971428Z register_layer(). 2025-12-04T09:26:07.6972220Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-12-04T09:26:07.6972814Z arguments. 2025-12-04T09:26:07.6973119Z features (Optional, list): 2025-12-04T09:26:07.6973473Z default selected features to sparsify. 2025-12-04T09:26:07.6974012Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-12-04T09:26:07.6974622Z For example, 2025-12-04T09:26:07.6975087Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-12-04T09:26:07.6975589Z feature_dim (Optional, int): 2025-12-04T09:26:07.6976122Z default dimension of input features. Again, features along this dim will be chosen 2025-12-04T09:26:07.6976662Z for sparsification. 2025-12-04T09:26:07.6976984Z sparse_config (Dict): 2025-12-04T09:26:07.6977433Z Default configuration for the mask_fn. This config will be passed 2025-12-04T09:26:07.6977911Z with the mask_fn() 2025-12-04T09:26:07.6978203Z 2025-12-04T09:26:07.6978409Z Example: 2025-12-04T09:26:07.6978649Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.6978932Z >>> model = SomeModel() 2025-12-04T09:26:07.6979383Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-12-04T09:26:07.6979887Z >>> # Initialize aggregate_fn 2025-12-04T09:26:07.6980205Z >>> def agg_fn(x, y): 2025-12-04T09:26:07.6980478Z >>> return x + y 2025-12-04T09:26:07.6980746Z >>> 2025-12-04T09:26:07.6980981Z >>> # Initialize reduce_fn 2025-12-04T09:26:07.6981276Z >>> def reduce_fn(x): 2025-12-04T09:26:07.6981577Z >>> return torch.mean(x, dim=0) 2025-12-04T09:26:07.6981894Z >>> 2025-12-04T09:26:07.6982113Z >>> # Initialize mask_fn 2025-12-04T09:26:07.6982411Z >>> def mask_fn(data): 2025-12-04T09:26:07.6982754Z >>> return torch.eye(data.shape).to(data.device) 2025-12-04T09:26:07.6983101Z >>> 2025-12-04T09:26:07.6983310Z >>> 2025-12-04T09:26:07.6983558Z >>> act_sparsifier.register_layer( 2025-12-04T09:26:07.6983888Z ... model.some_layer, 2025-12-04T09:26:07.6984194Z ... aggregate_fn=agg_fn, 2025-12-04T09:26:07.6984511Z ... reduce_fn=reduce_fn, 2025-12-04T09:26:07.6984823Z ... mask_fn=mask_fn, 2025-12-04T09:26:07.6985093Z ... ) 2025-12-04T09:26:07.6985310Z >>> 2025-12-04T09:26:07.6985540Z >>> # start training process 2025-12-04T09:26:07.6985837Z >>> for _ in [...]: 2025-12-04T09:26:07.6986114Z >>> # epoch starts 2025-12-04T09:26:07.6986469Z >>> # model.forward(), compute_loss() and model.backwards() 2025-12-04T09:26:07.6986853Z >>> # epoch ends 2025-12-04T09:26:07.6987134Z >>> act_sparsifier.step() 2025-12-04T09:26:07.6987461Z >>> # end training process 2025-12-04T09:26:07.6987770Z >>> sparsifier.squash_mask() 2025-12-04T09:26:07.6988072Z 2025-12-04T09:26:07.6988729Z Original Error: IndentationError("expected an indented block after 'for' statement on line 25", ('', 26, 1, '_._ = None\n', 26, 2)) 2025-12-04T09:26:07.6989473Z 2025-12-04T09:26:07.6989666Z _._ = None 2025-12-04T09:26:07.6989885Z ^ 2025-12-04T09:26:07.6990104Z warnings.warn(msg) 2025-12-04T09:26:07.6990350Z 2025-12-04T09:26:07.6990766Z --- Parse Warning: 12 / 17 --- 2025-12-04T09:26:07.6992055Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/device_mesh.py line=547. 2025-12-04T09:26:07.6993461Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.6993945Z 2025-12-04T09:26:07.6994431Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-12-04T09:26:07.6995137Z The submesh created consists of the dimensions and the communicators indicated by 2025-12-04T09:26:07.6995636Z ``mesh_dim_names`` 2025-12-04T09:26:07.6995886Z 2025-12-04T09:26:07.6996090Z Args: 2025-12-04T09:26:07.6996452Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-12-04T09:26:07.6997084Z mesh dimension of the DeviceMesh to create the submesh for. 2025-12-04T09:26:07.6997493Z Returns: 2025-12-04T09:26:07.6997721Z A :class:`DeviceMesh` object 2025-12-04T09:26:07.6998021Z 2025-12-04T09:26:07.6998441Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-12-04T09:26:07.6998965Z In the first example: 2025-12-04T09:26:07.6999412Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-12-04T09:26:07.7000070Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-12-04T09:26:07.7000700Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-12-04T09:26:07.7001287Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-12-04T09:26:07.7001886Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-12-04T09:26:07.7002490Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-12-04T09:26:07.7002936Z 2025-12-04T09:26:07.7003143Z In the second example: 2025-12-04T09:26:07.7003609Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-12-04T09:26:07.7004396Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-12-04T09:26:07.7005072Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-12-04T09:26:07.7005758Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-12-04T09:26:07.7006250Z 2025-12-04T09:26:07.7006466Z Example:: 2025-12-04T09:26:07.7006675Z 2025-12-04T09:26:07.7006899Z >>> # xdoctest: +SKIP("no rank") 2025-12-04T09:26:07.7007310Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-12-04T09:26:07.7007695Z >>> 2025-12-04T09:26:07.7008036Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-12-04T09:26:07.7008529Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-12-04T09:26:07.7009053Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-12-04T09:26:07.7009554Z >>> tp_mesh = mesh_2d["tp"] 2025-12-04T09:26:07.7009868Z >>> dp_mesh = mesh_2d["dp"] 2025-12-04T09:26:07.7010147Z >>> 2025-12-04T09:26:07.7010373Z >>> # Initialize a 3D mesh. 2025-12-04T09:26:07.7010876Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-12-04T09:26:07.7011620Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-12-04T09:26:07.7012175Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-12-04T09:26:07.7012523Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-12-04T09:26:07.7012843Z 2025-12-04T09:26:07.7013674Z 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)) 2025-12-04T09:26:07.7014633Z 2025-12-04T09:26:07.7014995Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-12-04T09:26:07.7015512Z ^ 2025-12-04T09:26:07.7015873Z warnings.warn(msg) 2025-12-04T09:26:07.7016122Z 2025-12-04T09:26:07.7016560Z --- Parse Warning: 13 / 17 --- 2025-12-04T09:26:07.7017853Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-12-04T09:26:07.7019282Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.7019817Z 2025-12-04T09:26:07.7020240Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-12-04T09:26:07.7020762Z 2025-12-04T09:26:07.7021179Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-12-04T09:26:07.7021712Z 2025-12-04T09:26:07.7022127Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-12-04T09:26:07.7022672Z will be visible to the whole process. 2025-12-04T09:26:07.7022978Z 2025-12-04T09:26:07.7023384Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-12-04T09:26:07.7023888Z 2025-12-04T09:26:07.7024115Z 1) set_up_planner - called on all ranks. 2025-12-04T09:26:07.7024483Z Signals the start of a checkpoint save. 2025-12-04T09:26:07.7024814Z 2025-12-04T09:26:07.7025044Z 2) create_local_plan - called on all ranks. 2025-12-04T09:26:07.7025603Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-12-04T09:26:07.7026117Z 2025-12-04T09:26:07.7026411Z 3) create_global_plan - called on the coordinator rank only. 2025-12-04T09:26:07.7026933Z Takes the SavePlan from all ranks and make any global decision. 2025-12-04T09:26:07.7027349Z 2025-12-04T09:26:07.7027580Z 4) finish_plan - called on all ranks. 2025-12-04T09:26:07.7028028Z This gives each rank a chance to adjust to global planning decisions. 2025-12-04T09:26:07.7028466Z 2025-12-04T09:26:07.7028743Z 5) resolve_data - called multiple times on each rank 2025-12-04T09:26:07.7029223Z Lookups a value on the `state_dict` for the storage layer to write. 2025-12-04T09:26:07.7029647Z 2025-12-04T09:26:07.7030083Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-12-04T09:26:07.7030712Z most changes can be expressed by changes in a single method. 2025-12-04T09:26:07.7031110Z 2025-12-04T09:26:07.7031351Z There are 3 usual patterns of extension: 2025-12-04T09:26:07.7031676Z 2025-12-04T09:26:07.7032045Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-12-04T09:26:07.7032683Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-12-04T09:26:07.7033135Z 2025-12-04T09:26:07.7033355Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7033738Z >>> class RenamePlanner(DefaultSavePlanner): 2025-12-04T09:26:07.7034098Z >>> def set_up_planner( 2025-12-04T09:26:07.7034372Z >>> self, 2025-12-04T09:26:07.7034640Z >>> state_dict: STATE_DICT_TYPE, 2025-12-04T09:26:07.7035001Z >>> storage_meta: Optional[StorageMeta], 2025-12-04T09:26:07.7035351Z >>> is_coordinator: bool, 2025-12-04T09:26:07.7035663Z >>> ) -> None: 2025-12-04T09:26:07.7035933Z >>> # prefix all keys with `foo_`` 2025-12-04T09:26:07.7036466Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-12-04T09:26:07.7036970Z 2025-12-04T09:26:07.7037440Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-12-04T09:26:07.7038000Z 2025-12-04T09:26:07.7038222Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7038590Z >>> class FP16Planner(DefaultSavePlanner): 2025-12-04T09:26:07.7038952Z >>> def create_local_plan(self): 2025-12-04T09:26:07.7039296Z >>> plan = super().create_local_plan() 2025-12-04T09:26:07.7039714Z >>> for p in plan: 2025-12-04T09:26:07.7040028Z >>> if p.tensor_data is not None: 2025-12-04T09:26:07.7040435Z >>> p.tensor_data.properties.dtype = torch.float16 2025-12-04T09:26:07.7040808Z >>> return plan 2025-12-04T09:26:07.7041073Z >>> 2025-12-04T09:26:07.7041374Z >>> def resolve_data(self, write_item): 2025-12-04T09:26:07.7041733Z >>> item = super().resolve_data(write_item) 2025-12-04T09:26:07.7042608Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-12-04T09:26:07.7043123Z 2025-12-04T09:26:07.7043587Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-12-04T09:26:07.7044165Z 2025-12-04T09:26:07.7044471Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7044818Z >>> from itertools import zip_longest 2025-12-04T09:26:07.7045174Z >>> from dataclasses import replace 2025-12-04T09:26:07.7045586Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-12-04T09:26:07.7046170Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-12-04T09:26:07.7046709Z >>> # This sample doesn't handle ShardedTensors 2025-12-04T09:26:07.7047103Z >>> def create_global_plan(self, all_plans): 2025-12-04T09:26:07.7047517Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-12-04T09:26:07.7047889Z >>> items_per_rank = [ 2025-12-04T09:26:07.7048233Z >>> [item for item in items if item is not None] 2025-12-04T09:26:07.7048663Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-12-04T09:26:07.7049040Z >>> ] 2025-12-04T09:26:07.7049271Z >>> all_plans = [ 2025-12-04T09:26:07.7049574Z >>> replace(plan, items=items) 2025-12-04T09:26:07.7050016Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-12-04T09:26:07.7050422Z >>> ] 2025-12-04T09:26:07.7050713Z >>> return super().create_global_plan(all_plans) 2025-12-04T09:26:07.7051067Z 2025-12-04T09:26:07.7051454Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-12-04T09:26:07.7052155Z accomplished by having each rank contribute their data items in the local plan and 2025-12-04T09:26:07.7052692Z the global planner aggregate them: 2025-12-04T09:26:07.7053002Z 2025-12-04T09:26:07.7053222Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7053618Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-12-04T09:26:07.7054042Z >>> def create_local_plan(self) -> SavePlan: 2025-12-04T09:26:07.7054413Z >>> plan = super().create_local_plan() 2025-12-04T09:26:07.7054831Z >>> return replace(plan, planner_data="per-rank-data") 2025-12-04T09:26:07.7055215Z >>> 2025-12-04T09:26:07.7055642Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-12-04T09:26:07.7056290Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-12-04T09:26:07.7056789Z >>> merged_data = [p.planner_data for p in global_plan] 2025-12-04T09:26:07.7057253Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-12-04T09:26:07.7057668Z >>> return global_plan, metadata 2025-12-04T09:26:07.7057987Z 2025-12-04T09:26:07.7058666Z Original Error: IndentationError('expected an indented block after function definition on line 3', ('', 9, 0, '_._ = None\n', 9, -1)) 2025-12-04T09:26:07.7059426Z 2025-12-04T09:26:07.7059632Z _._ = None 2025-12-04T09:26:07.7059852Z ^ 2025-12-04T09:26:07.7060060Z warnings.warn(msg) 2025-12-04T09:26:07.7060316Z 2025-12-04T09:26:07.7060689Z --- Parse Warning: 14 / 17 --- 2025-12-04T09:26:07.7062181Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-12-04T09:26:07.7063621Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.7064094Z 2025-12-04T09:26:07.7064600Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-12-04T09:26:07.7065104Z 2025-12-04T09:26:07.7065522Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-12-04T09:26:07.7066047Z 2025-12-04T09:26:07.7066446Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-12-04T09:26:07.7066991Z will be visible to the whole process. 2025-12-04T09:26:07.7067314Z 2025-12-04T09:26:07.7067721Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-12-04T09:26:07.7068222Z 2025-12-04T09:26:07.7068462Z 1) set_up_planner - called on all ranks. 2025-12-04T09:26:07.7068840Z Signals the start of loading a checkpoint. 2025-12-04T09:26:07.7069168Z 2025-12-04T09:26:07.7069409Z 2) create_local_plan - called on all ranks. 2025-12-04T09:26:07.7069962Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-12-04T09:26:07.7070466Z 2025-12-04T09:26:07.7070774Z 3) create_global_plan - called on the coordinator rank only. 2025-12-04T09:26:07.7071294Z Takes the LoadPlan from all ranks and make any global decision. 2025-12-04T09:26:07.7071698Z 2025-12-04T09:26:07.7071964Z 4) load_bytes - called multiple times on each rank 2025-12-04T09:26:07.7072416Z This is called once per non-tensor value in state_dict. 2025-12-04T09:26:07.7072498Z 2025-12-04T09:26:07.7072743Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-12-04T09:26:07.7072931Z They are called in pair for each Tensor value in state_dict. 2025-12-04T09:26:07.7073011Z 2025-12-04T09:26:07.7073344Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-12-04T09:26:07.7073535Z most changes can be expressed by changes in a single method. 2025-12-04T09:26:07.7073616Z 2025-12-04T09:26:07.7073763Z There are two usual patterns of extension: 2025-12-04T09:26:07.7073844Z 2025-12-04T09:26:07.7074122Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-12-04T09:26:07.7074389Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-12-04T09:26:07.7074625Z to keep a reference to the original state_dict as load happens in place so 2025-12-04T09:26:07.7074761Z we need to be able to perform it in place 2025-12-04T09:26:07.7074840Z 2025-12-04T09:26:07.7074955Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7075107Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-12-04T09:26:07.7075208Z >>> def set_up_planner( 2025-12-04T09:26:07.7075296Z >>> self, 2025-12-04T09:26:07.7075420Z >>> state_dict: STATE_DICT_TYPE, 2025-12-04T09:26:07.7075522Z >>> metadata: Metadata, 2025-12-04T09:26:07.7075639Z >>> is_coordinator: bool, 2025-12-04T09:26:07.7075727Z >>> ) -> None: 2025-12-04T09:26:07.7075859Z >>> self.original_state_dict = state_dict 2025-12-04T09:26:07.7076049Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-12-04T09:26:07.7076132Z >>> 2025-12-04T09:26:07.7076250Z >>> if self.flatten_sharded_tensors: 2025-12-04T09:26:07.7076416Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-12-04T09:26:07.7076496Z >>> 2025-12-04T09:26:07.7076607Z >>> if self.flatten_state_dict: 2025-12-04T09:26:07.7076805Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-12-04T09:26:07.7076945Z >>> 2025-12-04T09:26:07.7077058Z >>> self.state_dict = state_dict 2025-12-04T09:26:07.7077178Z >>> self.metadata = metadata 2025-12-04T09:26:07.7077305Z >>> self.is_coordinator = is_coordinator 2025-12-04T09:26:07.7077401Z >>> 2025-12-04T09:26:07.7077524Z >>> def load_bytes(self, read_item, value): 2025-12-04T09:26:07.7077679Z >>> # Remove the "foo_" prefix 2025-12-04T09:26:07.7078028Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-12-04T09:26:07.7078110Z 2025-12-04T09:26:07.7078192Z 2025-12-04T09:26:07.7078475Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-12-04T09:26:07.7078555Z 2025-12-04T09:26:07.7078670Z >>> # xdoctest: +SKIP("undefined vars") 2025-12-04T09:26:07.7078840Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-12-04T09:26:07.7078958Z >>> def resolve_tensor(self, read_item): 2025-12-04T09:26:07.7079109Z >>> tensor = super().resolve_tensor(read_item) 2025-12-04T09:26:07.7079256Z >>> return torch.empty_like(tensor, device="cpu") 2025-12-04T09:26:07.7079336Z >>> 2025-12-04T09:26:07.7079480Z >>> def commit_tensor(self, read_item, tensor): 2025-12-04T09:26:07.7079639Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-12-04T09:26:07.7079723Z 2025-12-04T09:26:07.7080309Z Original Error: IndentationError('expected an indented block after function definition on line 22', ('', 23, 0, '_._ = None\n', 23, -1)) 2025-12-04T09:26:07.7080388Z 2025-12-04T09:26:07.7080472Z _._ = None 2025-12-04T09:26:07.7080564Z ^ 2025-12-04T09:26:07.7080664Z warnings.warn(msg) 2025-12-04T09:26:07.7080755Z 2025-12-04T09:26:07.7080979Z --- Parse Warning: 15 / 17 --- 2025-12-04T09:26:07.7082007Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/distributed/fsdp/api.py line=295. 2025-12-04T09:26:07.7082279Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.7082360Z 2025-12-04T09:26:07.7082574Z ``FullStateDictConfig`` is a config class meant to be used with 2025-12-04T09:26:07.7082794Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-12-04T09:26:07.7083004Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-12-04T09:26:07.7083246Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-12-04T09:26:07.7083454Z is meant to be used via the :func:`state_dict_type` context manager as 2025-12-04T09:26:07.7083540Z follows: 2025-12-04T09:26:07.7083632Z 2025-12-04T09:26:07.7083764Z >>> # xdoctest: +SKIP("undefined variables") 2025-12-04T09:26:07.7084012Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-12-04T09:26:07.7084154Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-12-04T09:26:07.7084460Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-12-04T09:26:07.7084702Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-12-04T09:26:07.7084813Z >>> state = fsdp.state_dict() 2025-12-04T09:26:07.7085035Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-12-04T09:26:07.7085293Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-12-04T09:26:07.7085534Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-12-04T09:26:07.7085638Z >>> if dist.get_rank() == 0: 2025-12-04T09:26:07.7085837Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-12-04T09:26:07.7085980Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-12-04T09:26:07.7086180Z >>> model.load_state_dict(state_dict) 2025-12-04T09:26:07.7086423Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-12-04T09:26:07.7086673Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-12-04T09:26:07.7086783Z >>> fsdp = FSDP( 2025-12-04T09:26:07.7086870Z ... model, 2025-12-04T09:26:07.7087076Z ... device_id=torch.cuda.current_device(), 2025-12-04T09:26:07.7087192Z ... auto_wrap_policy=..., 2025-12-04T09:26:07.7087298Z ... sync_module_states=True, 2025-12-04T09:26:07.7087380Z ... ) 2025-12-04T09:26:07.7087614Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-12-04T09:26:07.7087697Z 2025-12-04T09:26:07.7087803Z Attributes: 2025-12-04T09:26:07.7088010Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-12-04T09:26:07.7088223Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-12-04T09:26:07.7088401Z ranks save the full state dict. (Default: ``False``) 2025-12-04T09:26:07.7088483Z 2025-12-04T09:26:07.7089014Z Original Error: IndentationError("expected an indented block after 'if' statement on line 10", ('', 11, 1, '_._ = None\n', 11, 2)) 2025-12-04T09:26:07.7089109Z 2025-12-04T09:26:07.7089196Z _._ = None 2025-12-04T09:26:07.7089279Z ^ 2025-12-04T09:26:07.7089389Z warnings.warn(msg) 2025-12-04T09:26:07.7089472Z 2025-12-04T09:26:07.7089676Z --- Parse Warning: 16 / 17 --- 2025-12-04T09:26:07.7090730Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/utils/parametrize.py line=437. 2025-12-04T09:26:07.7090990Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.7091166Z Register a parametrization to a tensor in a module. 2025-12-04T09:26:07.7091247Z 2025-12-04T09:26:07.7091540Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-12-04T09:26:07.7091842Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-12-04T09:26:07.7092123Z If the original tensor requires a gradient, the backward pass will differentiate 2025-12-04T09:26:07.7092438Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-12-04T09:26:07.7092523Z 2025-12-04T09:26:07.7092850Z The first time that a module registers a parametrization, this function will add an attribute 2025-12-04T09:26:07.7093120Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-12-04T09:26:07.7093199Z 2025-12-04T09:26:07.7093472Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-12-04T09:26:07.7093605Z ``module.parametrizations.weight``. 2025-12-04T09:26:07.7093686Z 2025-12-04T09:26:07.7093837Z The original tensor will be accessible under 2025-12-04T09:26:07.7093987Z ``module.parametrizations.weight.original``. 2025-12-04T09:26:07.7094067Z 2025-12-04T09:26:07.7094355Z Parametrizations may be concatenated by registering several parametrizations 2025-12-04T09:26:07.7094460Z on the same attribute. 2025-12-04T09:26:07.7094538Z 2025-12-04T09:26:07.7094805Z The training mode of a registered parametrization is updated on registration 2025-12-04T09:26:07.7094943Z to match the training mode of the host module 2025-12-04T09:26:07.7095034Z 2025-12-04T09:26:07.7095355Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-12-04T09:26:07.7095484Z using the context manager :func:`cached`. 2025-12-04T09:26:07.7095577Z 2025-12-04T09:26:07.7095888Z A :attr:`parametrization` may optionally implement a method with signature 2025-12-04T09:26:07.7095969Z 2025-12-04T09:26:07.7096098Z .. code-block:: python 2025-12-04T09:26:07.7096177Z 2025-12-04T09:26:07.7096399Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-12-04T09:26:07.7096492Z 2025-12-04T09:26:07.7096765Z This method is called on the unparametrized tensor when the first parametrization 2025-12-04T09:26:07.7097047Z is registered to compute the initial value of the original tensor. 2025-12-04T09:26:07.7097369Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-12-04T09:26:07.7097452Z 2025-12-04T09:26:07.7097793Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-12-04T09:26:07.7098094Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-12-04T09:26:07.7098173Z 2025-12-04T09:26:07.7098424Z It is possible for the first parametrization to depend on several inputs. 2025-12-04T09:26:07.7098674Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-12-04T09:26:07.7098928Z (see the example implementation of a ``RankOne`` parametrization below). 2025-12-04T09:26:07.7099010Z 2025-12-04T09:26:07.7099365Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-12-04T09:26:07.7099507Z with names ``original0``, ``original1``,... 2025-12-04T09:26:07.7099586Z 2025-12-04T09:26:07.7099671Z .. note:: 2025-12-04T09:26:07.7099761Z 2025-12-04T09:26:07.7100043Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-12-04T09:26:07.7100192Z once to perform a number of consistency checks. 2025-12-04T09:26:07.7100483Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-12-04T09:26:07.7100614Z and nothing will be called otherwise. 2025-12-04T09:26:07.7100708Z 2025-12-04T09:26:07.7100794Z .. note:: 2025-12-04T09:26:07.7100874Z 2025-12-04T09:26:07.7101097Z In most situations, ``right_inverse`` will be a function such that 2025-12-04T09:26:07.7101220Z ``forward(right_inverse(X)) == X`` (see 2025-12-04T09:26:07.7101531Z `right inverse `_). 2025-12-04T09:26:07.7101806Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-12-04T09:26:07.7101900Z to relax this. 2025-12-04T09:26:07.7101978Z 2025-12-04T09:26:07.7102077Z .. warning:: 2025-12-04T09:26:07.7102155Z 2025-12-04T09:26:07.7102454Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-12-04T09:26:07.7102721Z will register a number of new parameters. If such parametrization is registered 2025-12-04T09:26:07.7103004Z after the optimizer is created, these new parameters will need to be added manually 2025-12-04T09:26:07.7103218Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-12-04T09:26:07.7103296Z 2025-12-04T09:26:07.7103380Z Args: 2025-12-04T09:26:07.7103609Z module (nn.Module): module on which to register the parametrization 2025-12-04T09:26:07.7103835Z tensor_name (str): name of the parameter or buffer on which to register 2025-12-04T09:26:07.7103950Z the parametrization 2025-12-04T09:26:07.7104159Z parametrization (nn.Module): the parametrization to register 2025-12-04T09:26:07.7104252Z Keyword args: 2025-12-04T09:26:07.7104486Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-12-04T09:26:07.7104684Z may change the dtype and shape of the tensor. Default: `False` 2025-12-04T09:26:07.7105075Z Warning: the parametrization is not checked for consistency upon registration. 2025-12-04T09:26:07.7105212Z Enable this flag at your own risk. 2025-12-04T09:26:07.7105293Z 2025-12-04T09:26:07.7105376Z Raises: 2025-12-04T09:26:07.7105688Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-12-04T09:26:07.7105816Z 2025-12-04T09:26:07.7105916Z Examples: 2025-12-04T09:26:07.7106067Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-12-04T09:26:07.7106161Z >>> import torch 2025-12-04T09:26:07.7106277Z >>> import torch.nn as nn 2025-12-04T09:26:07.7106415Z >>> import torch.nn.utils.parametrize as P 2025-12-04T09:26:07.7106497Z >>> 2025-12-04T09:26:07.7106621Z >>> class Symmetric(nn.Module): 2025-12-04T09:26:07.7106725Z >>> def forward(self, X): 2025-12-04T09:26:07.7106913Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-12-04T09:26:07.7107008Z >>> 2025-12-04T09:26:07.7107126Z >>> def right_inverse(self, A): 2025-12-04T09:26:07.7107239Z >>> return A.triu() 2025-12-04T09:26:07.7107319Z >>> 2025-12-04T09:26:07.7107417Z >>> m = nn.Linear(5, 5) 2025-12-04T09:26:07.7107602Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-12-04T09:26:07.7107855Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-12-04T09:26:07.7107940Z True 2025-12-04T09:26:07.7108052Z >>> A = torch.rand(5, 5) 2025-12-04T09:26:07.7108164Z >>> A = A + A.T # A is now symmetric 2025-12-04T09:26:07.7108368Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-12-04T09:26:07.7108506Z >>> print(torch.allclose(m.weight, A)) 2025-12-04T09:26:07.7108589Z True 2025-12-04T09:26:07.7108679Z 2025-12-04T09:26:07.7108790Z >>> class RankOne(nn.Module): 2025-12-04T09:26:07.7108899Z >>> def forward(self, x, y): 2025-12-04T09:26:07.7109053Z >>> # Form a rank 1 matrix multiplying two vectors 2025-12-04T09:26:07.7109186Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-12-04T09:26:07.7109267Z >>> 2025-12-04T09:26:07.7109398Z >>> def right_inverse(self, Z): 2025-12-04T09:26:07.7109519Z >>> # Project Z onto the rank 1 matrices 2025-12-04T09:26:07.7109677Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-12-04T09:26:07.7109808Z >>> # Return rescaled singular vectors 2025-12-04T09:26:07.7109931Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-12-04T09:26:07.7110093Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-12-04T09:26:07.7110174Z >>> 2025-12-04T09:26:07.7110324Z >>> linear_rank_one = P.register_parametrization( 2025-12-04T09:26:07.7110466Z ... nn.Linear(4, 4), "weight", RankOne() 2025-12-04T09:26:07.7110550Z ... ) 2025-12-04T09:26:07.7110761Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-12-04T09:26:07.7110849Z 1 2025-12-04T09:26:07.7110953Z 2025-12-04T09:26:07.7111035Z 2025-12-04T09:26:07.7111605Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 3, 0, '_._ = None\n', 3, -1)) 2025-12-04T09:26:07.7111701Z 2025-12-04T09:26:07.7111784Z _._ = None 2025-12-04T09:26:07.7111865Z ^ 2025-12-04T09:26:07.7111976Z warnings.warn(msg) 2025-12-04T09:26:07.7112057Z 2025-12-04T09:26:07.7112274Z --- Parse Warning: 17 / 17 --- 2025-12-04T09:26:07.7113358Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/xdoctest/core.py:416: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/optim/lr_scheduler.py line=1586. 2025-12-04T09:26:07.7113616Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-12-04T09:26:07.7113814Z Reduce learning rate when a metric has stopped improving. 2025-12-04T09:26:07.7113894Z 2025-12-04T09:26:07.7114105Z Models often benefit from reducing the learning rate by a factor 2025-12-04T09:26:07.7114363Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-12-04T09:26:07.7114564Z quantity and if no improvement is seen for a 'patience' number 2025-12-04T09:26:07.7114704Z of epochs, the learning rate is reduced. 2025-12-04T09:26:07.7114787Z 2025-12-04T09:26:07.7114872Z Args: 2025-12-04T09:26:07.7115024Z optimizer (Optimizer): Wrapped optimizer. 2025-12-04T09:26:07.7115185Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-12-04T09:26:07.7115344Z be reduced when the quantity monitored has stopped 2025-12-04T09:26:07.7115529Z decreasing; in `max` mode it will be reduced when the 2025-12-04T09:26:07.7115727Z quantity monitored has stopped increasing. Default: 'min'. 2025-12-04T09:26:07.7115903Z factor (float): Factor by which the learning rate will be 2025-12-04T09:26:07.7116060Z reduced. new_lr = lr * factor. Default: 0.1. 2025-12-04T09:26:07.7116288Z patience (int): The number of allowed epochs with no improvement after 2025-12-04T09:26:07.7116434Z which the learning rate will be reduced. 2025-12-04T09:26:07.7116674Z For example, consider the case of having no patience (`patience = 0`). 2025-12-04T09:26:07.7117058Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-12-04T09:26:07.7117290Z In the second epoch, if the performance is worse than the baseline, 2025-12-04T09:26:07.7117446Z we have what is considered an intolerable epoch. 2025-12-04T09:26:07.7117735Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-12-04T09:26:07.7117906Z the learning rate is reduced at the end of this epoch. 2025-12-04T09:26:07.7118245Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-12-04T09:26:07.7118593Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-12-04T09:26:07.7118714Z the learning rate is not adjusted. 2025-12-04T09:26:07.7118811Z Default: 10. 2025-12-04T09:26:07.7119019Z threshold (float): Threshold for measuring the new optimum, 2025-12-04T09:26:07.7119181Z to only focus on significant changes. Default: 1e-4. 2025-12-04T09:26:07.7119369Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-12-04T09:26:07.7119534Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-12-04T09:26:07.7119680Z mode or best * ( 1 - threshold ) in `min` mode. 2025-12-04T09:26:07.7119847Z In `abs` mode, dynamic_threshold = best + threshold in 2025-12-04T09:26:07.7120027Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-12-04T09:26:07.7120203Z cooldown (int): Number of epochs to wait before resuming 2025-12-04T09:26:07.7120393Z normal operation after lr has been reduced. Default: 0. 2025-12-04T09:26:07.7120556Z min_lr (float or list): A scalar or a list of scalars. A 2025-12-04T09:26:07.7120731Z lower bound on the learning rate of all param groups 2025-12-04T09:26:07.7120863Z or each group respectively. Default: 0. 2025-12-04T09:26:07.7121040Z eps (float): Minimal decay applied to lr. If the difference 2025-12-04T09:26:07.7121305Z between new and old lr is smaller than eps, the update is 2025-12-04T09:26:07.7121415Z ignored. Default: 1e-8. 2025-12-04T09:26:07.7121495Z 2025-12-04T09:26:07.7121593Z Example: 2025-12-04T09:26:07.7121691Z >>> # xdoctest: +SKIP 2025-12-04T09:26:07.7121926Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-12-04T09:26:07.7122147Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-12-04T09:26:07.7122252Z >>> for epoch in range(10): 2025-12-04T09:26:07.7122359Z >>> train(...) 2025-12-04T09:26:07.7122469Z >>> val_loss = validate(...) 2025-12-04T09:26:07.7122623Z >>> # Note that step should be called after validate() 2025-12-04T09:26:07.7122751Z >>> scheduler.step(val_loss) 2025-12-04T09:26:07.7122831Z 2025-12-04T09:26:07.7123030Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-12-04T09:26:07.7123125Z 2025-12-04T09:26:07.7123570Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-12-04T09:26:07.7123651Z 2025-12-04T09:26:07.7123767Z scheduler.step(val_loss) 2025-12-04T09:26:07.7123847Z ^ 2025-12-04T09:26:07.7123956Z warnings.warn(msg) 2025-12-04T09:26:07.7124034Z 2025-12-04T09:26:07.7124153Z  2025-12-04T09:26:07.7124457Z === Found 10 run-time warnings === 2025-12-04T09:26:07.7124639Z --- Runtime Warning: 1 / 10 --- 2025-12-04T09:26:07.7124842Z example = 2025-12-04T09:26:07.7126433Z :3: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() 2025-12-04T09:26:07.7126515Z 2025-12-04T09:26:07.7126709Z --- Runtime Warning: 2 / 10 --- 2025-12-04T09:26:07.7126984Z example = 2025-12-04T09:26:07.7128432Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_tensor.py:1392: 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:1973.) 2025-12-04T09:26:07.7128567Z return super().refine_names(names) 2025-12-04T09:26:07.7128648Z 2025-12-04T09:26:07.7128840Z --- Runtime Warning: 3 / 10 --- 2025-12-04T09:26:07.7129163Z example = 2025-12-04T09:26:07.7129838Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py:275: UserWarning: Warning only once for all operators, other operators may also be overridden. 2025-12-04T09:26:07.7130177Z Overriding a previously registered kernel for the same operator and the same dispatch key 2025-12-04T09:26:07.7130383Z operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor 2025-12-04T09:26:07.7130703Z registered at /var/lib/jenkins/workspace/build/aten/src/ATen/RegisterSchema.cpp:6 2025-12-04T09:26:07.7130804Z dispatch key: CPU 2025-12-04T09:26:07.7131256Z previous kernel: registered at /var/lib/jenkins/workspace/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079 2025-12-04T09:26:07.7132340Z new kernel: registered at :1 (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/core/dispatch/OperatorEntry.cpp:208.) 2025-12-04T09:26:07.7132505Z impl_fn(self.ns, name.split("::")[-1], dispatch_key) 2025-12-04T09:26:07.7132682Z 2025-12-04T09:26:07.7132871Z --- Runtime Warning: 4 / 10 --- 2025-12-04T09:26:07.7133118Z example = 2025-12-04T09:26:07.7135135Z /opt/conda/envs/py_3.10/lib/python3.10/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.) 2025-12-04T09:26:07.7135458Z return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None) 2025-12-04T09:26:07.7135556Z 2025-12-04T09:26:07.7135740Z --- Runtime Warning: 5 / 10 --- 2025-12-04T09:26:07.7136010Z example = 2025-12-04T09:26:07.7137756Z :1: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/SparseCsrTensorImpl.cpp:53.) 2025-12-04T09:26:07.7137844Z 2025-12-04T09:26:07.7138040Z --- Runtime Warning: 6 / 10 --- 2025-12-04T09:26:07.7138362Z example = 2025-12-04T09:26:07.7140009Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/const_fold.py:314: 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 2025-12-04T09:26:07.7140179Z new_node = root_const_gm.graph.get_attr(in_node.target) 2025-12-04T09:26:07.7140261Z 2025-12-04T09:26:07.7140452Z --- Runtime Warning: 7 / 10 --- 2025-12-04T09:26:07.7140752Z example = 2025-12-04T09:26:07.7141929Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/transformer.py:144: 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) 2025-12-04T09:26:07.7142050Z self.encoder = TransformerEncoder( 2025-12-04T09:26:07.7142132Z 2025-12-04T09:26:07.7142714Z --- Runtime Warning: 8 / 10 --- 2025-12-04T09:26:07.7143065Z example = 2025-12-04T09:26:07.7144394Z :2: 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) 2025-12-04T09:26:07.7144477Z 2025-12-04T09:26:07.7144676Z --- Runtime Warning: 9 / 10 --- 2025-12-04T09:26:07.7144982Z example = 2025-12-04T09:26:07.7145850Z /opt/conda/envs/py_3.10/lib/python3.10/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`. 2025-12-04T09:26:07.7145985Z WeightNorm.apply(module, name, dim) 2025-12-04T09:26:07.7146067Z 2025-12-04T09:26:07.7146252Z --- Runtime Warning: 10 / 10 --- 2025-12-04T09:26:07.7146750Z example = 2025-12-04T09:26:07.7147618Z /opt/conda/envs/py_3.10/lib/python3.10/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`. 2025-12-04T09:26:07.7147740Z WeightNorm.apply(module, name, dim) 2025-12-04T09:26:07.7147912Z 2025-12-04T09:26:07.7148219Z === 378 passed, 516 skipped, 27 warnings in 20.76 seconds === 2025-12-04T09:26:07.7148513Z Finished doctests 1/1 ... [2025-12-04 09:26:07.664970][910.350730911], took 0.35min 2025-12-04T09:26:07.7148799Z Running inductor/test_cutlass_backend 1/1 ... [2025-12-04 09:26:07.666850][910.352621611] 2025-12-04T09:26:07.7148912Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:07.7150071Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cutlass_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:07.667247] 2025-12-04T09:26:16.2874341Z 2025-12-04T09:26:16.2875374Z 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_355dd07aecfb5228_.log 2025-12-04T09:26:16.2876243Z 2025-12-04T09:26:16.2876590Z Finished inductor/test_cutlass_backend 1/1 ... [2025-12-04 09:26:16.287282][918.973051876], took 0.14min 2025-12-04T09:26:16.2890848Z Running inductor/test_benchmark_fusion 1/1 ... [2025-12-04 09:26:16.288889][918.974660907] 2025-12-04T09:26:16.2891385Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:16.2895109Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_benchmark_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:16.289258] 2025-12-04T09:26:24.6149173Z 2025-12-04T09:26:24.6150235Z inductor/test_benchmark_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_benchmark_fusion_1.1_d1a0dcc63355e089_.log 2025-12-04T09:26:24.6151185Z Running 0 items in this shard: 2025-12-04T09:26:24.6151416Z 2025-12-04T09:26:24.6151794Z Finished inductor/test_benchmark_fusion 1/1 ... [2025-12-04 09:26:24.614728][927.300497663], took 0.14min 2025-12-04T09:26:24.6162710Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_benchmark_fusion/inductor.test_benchmark_fusion-c8188ad5f20807b0.xml 2025-12-04T09:26:24.6940718Z Running inductor/test_distributed_patterns 1/1 ... [2025-12-04 09:26:24.693723][927.379492636] 2025-12-04T09:26:24.6941315Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:24.6945670Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_distributed_patterns.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:24.694206] 2025-12-04T09:26:32.5165039Z 2025-12-04T09:26:32.5166144Z 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_69997f118b0b0afe_.log 2025-12-04T09:26:32.5167176Z Running 0 items in this shard: 2025-12-04T09:26:32.5167380Z 2025-12-04T09:26:32.5167774Z Finished inductor/test_distributed_patterns 1/1 ... [2025-12-04 09:26:32.516311][935.202080989], took 0.13min 2025-12-04T09:26:32.5179698Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_distributed_patterns/inductor.test_distributed_patterns-5e12100b8144d6ee.xml 2025-12-04T09:26:32.5924110Z Running dynamo/test_fake_distributed 1/1 ... [2025-12-04 09:26:32.592093][935.277865712] 2025-12-04T09:26:32.5924732Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:32.5927710Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_fake_distributed.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:32.592446] 2025-12-04T09:26:36.0414072Z 2025-12-04T09:26:36.0415084Z dynamo/test_fake_distributed 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fake_distributed_1.1_04459a59349a8e11_.log 2025-12-04T09:26:36.0416007Z Running 0 items in this shard: 2025-12-04T09:26:36.0416202Z 2025-12-04T09:26:36.0416550Z Finished dynamo/test_fake_distributed 1/1 ... [2025-12-04 09:26:36.041203][938.726973683], took 0.06min 2025-12-04T09:26:36.0429656Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_fake_distributed/dynamo.test_fake_distributed-4fdebebc04d1305a.xml 2025-12-04T09:26:36.0688297Z Running test_sort_and_select 1/1 ... [2025-12-04 09:26:36.068578][938.754350546] 2025-12-04T09:26:36.0688790Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:36.0691563Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_sort_and_select.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:36.068914] 2025-12-04T09:26:39.5450687Z 2025-12-04T09:26:39.5451583Z test_sort_and_select 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sort_and_select_1.1_dc7bede2f23c7701_.log 2025-12-04T09:26:39.5452403Z Running 0 items in this shard: 2025-12-04T09:26:39.5452602Z 2025-12-04T09:26:39.5452902Z Finished test_sort_and_select 1/1 ... [2025-12-04 09:26:39.544879][942.230649901], took 0.06min 2025-12-04T09:26:39.5467751Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_sort_and_select/test_sort_and_select-2037345ba52ec954.xml 2025-12-04T09:26:39.5759206Z Running test_cpp_api_parity 1/1 ... [2025-12-04 09:26:39.575664][942.261436308] 2025-12-04T09:26:39.5759706Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:39.5762854Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_api_parity.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:39.576001] 2025-12-04T09:26:49.3837225Z 2025-12-04T09:26:49.3838169Z test_cpp_api_parity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_api_parity_1.1_a42ca804bedf8aa9_.log 2025-12-04T09:26:49.3838985Z Running 0 items in this shard: 2025-12-04T09:26:49.3839183Z 2025-12-04T09:26:49.3839517Z Finished test_cpp_api_parity 1/1 ... [2025-12-04 09:26:49.383473][952.069243089], took 0.16min 2025-12-04T09:26:49.3857216Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_api_parity/test_cpp_api_parity-ecd5fbc2301ee08c.xml 2025-12-04T09:26:49.4494487Z Running test_extension_utils 1/1 ... [2025-12-04 09:26:49.449127][952.134894242] 2025-12-04T09:26:49.4495012Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:49.4498830Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_extension_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:49.449604] 2025-12-04T09:26:52.6501620Z 2025-12-04T09:26:52.6502572Z test_extension_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_extension_utils_1.1_0302fb41d66f126d_.log 2025-12-04T09:26:52.6503669Z Running 0 items in this shard: 2025-12-04T09:26:52.6503870Z 2025-12-04T09:26:52.6504180Z Finished test_extension_utils 1/1 ... [2025-12-04 09:26:52.649963][955.335733923], took 0.05min 2025-12-04T09:26:52.6522248Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_extension_utils/test_extension_utils-40a1e678aaa66b59.xml 2025-12-04T09:26:52.6891715Z Running test_show_pickle 1/1 ... [2025-12-04 09:26:52.688919][955.374691268] 2025-12-04T09:26:52.6892198Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:52.6895176Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_show_pickle.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:52.689271] 2025-12-04T09:26:55.8302216Z 2025-12-04T09:26:55.8303136Z test_show_pickle 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_show_pickle_1.1_e84938476ef436cc_.log 2025-12-04T09:26:55.8303919Z Running 0 items in this shard: 2025-12-04T09:26:55.8304116Z 2025-12-04T09:26:55.8304400Z Finished test_show_pickle 1/1 ... [2025-12-04 09:26:55.830019][958.515787858], took 0.05min 2025-12-04T09:26:55.8324077Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_show_pickle/test_show_pickle-f03a9f69282e4e9b.xml 2025-12-04T09:26:55.8633781Z Running test_torch 1/1 ... [2025-12-04 09:26:55.863179][958.548951703] 2025-12-04T09:26:55.8634236Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:26:55.8637869Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_torch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:26:55.863537] 2025-12-04T09:27:20.4213040Z 2025-12-04T09:27:20.4213950Z test_torch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_torch_1.1_7c6ae205d4193688_.log 2025-12-04T09:27:20.4251735Z Running 150 items in this shard: test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_tensoriterator_output_setup 2025-12-04T09:27:20.4288087Z 2025-12-04T09:27:20.4288336Z Finished test_torch 1/1 ... [2025-12-04 09:27:20.421191][983.106961074], took 0.41min 2025-12-04T09:27:20.4289297Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_torch/test_torch-974210a6f181dc93.xml 2025-12-04T09:27:20.5028145Z Running test_tensorexpr 1/1 ... [2025-12-04 09:27:20.502514][983.188285561] 2025-12-04T09:27:20.5028669Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:27:20.5031563Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_tensorexpr.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:27:20.502866] 2025-12-04T09:27:24.0328877Z 2025-12-04T09:27:24.0329727Z test_tensorexpr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_1.1_0a8d5a0aa00de6a7_.log 2025-12-04T09:27:24.0330566Z Running 0 items in this shard: 2025-12-04T09:27:24.0330766Z 2025-12-04T09:27:24.0331046Z Finished test_tensorexpr 1/1 ... [2025-12-04 09:27:24.032667][986.718437348], took 0.06min 2025-12-04T09:27:24.0353610Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_tensorexpr/test_tensorexpr-c99e4efcf4c409df.xml 2025-12-04T09:27:24.0632172Z Running test_utils 1/1 ... [2025-12-04 09:27:24.062898][986.748666621] 2025-12-04T09:27:24.0632650Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:27:24.0635640Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:27:24.063287] 2025-12-04T09:27:28.9567308Z 2025-12-04T09:27:28.9568514Z test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_1.1_a30fc6ac45921c3e_.log 2025-12-04T09:27:28.9596069Z Running 100 items in this shard: test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_random_seed 2025-12-04T09:27:28.9630442Z 2025-12-04T09:27:28.9630788Z Finished test_utils 1/1 ... [2025-12-04 09:27:28.956685][991.642454913], took 0.08min 2025-12-04T09:27:28.9631783Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_utils/test_utils-f382d15ed8e80aea.xml 2025-12-04T09:27:28.9956762Z Running test_namedtuple_return_api 1/1 ... [2025-12-04 09:27:28.995440][991.681211213] 2025-12-04T09:27:28.9957303Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:27:28.9960583Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:27:28.995779] 2025-12-04T09:27:32.3371035Z 2025-12-04T09:27:32.3372028Z 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_30659a9390997488_.log 2025-12-04T09:27:32.3372930Z Running 0 items in this shard: 2025-12-04T09:27:32.3373145Z 2025-12-04T09:27:32.3373463Z Finished test_namedtuple_return_api 1/1 ... [2025-12-04 09:27:32.336922][995.022693567], took 0.06min 2025-12-04T09:27:32.3398252Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_namedtuple_return_api/test_namedtuple_return_api-15ccfd05e3870a3c.xml 2025-12-04T09:27:32.3644218Z Running test_fake_tensor 1/1 ... [2025-12-04 09:27:32.364148][995.049919684] 2025-12-04T09:27:32.3645033Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:27:32.3648079Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_fake_tensor.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:27:32.364535] 2025-12-04T09:27:41.3763820Z 2025-12-04T09:27:41.3765313Z test_fake_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fake_tensor_1.1_7944c1edb36d8ae5_.log 2025-12-04T09:27:41.3798725Z Running 50 items in this shard: test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to 2025-12-04T09:27:41.3831009Z 2025-12-04T09:27:41.3831513Z Finished test_fake_tensor 1/1 ... [2025-12-04 09:27:41.376167][1004.061938683], took 0.15min 2025-12-04T09:27:41.3833382Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_fake_tensor/test_fake_tensor-974f85b07e1c6185.xml 2025-12-04T09:27:41.4453300Z Running test_multiprocessing 1/1 ... [2025-12-04 09:27:41.444990][1004.130761846] 2025-12-04T09:27:41.4454189Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:27:41.4457232Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_multiprocessing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:27:41.445383] 2025-12-04T09:33:26.1032105Z 2025-12-04T09:33:26.1033233Z test_multiprocessing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_1.1_258beab32cee769f_.log 2025-12-04T09:33:26.1070705Z Running 100 items in this shard: test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple 2025-12-04T09:33:26.1105838Z 2025-12-04T09:33:26.1106147Z Finished test_multiprocessing 1/1 ... [2025-12-04 09:33:26.103015][1348.788783932], took 5.74min 2025-12-04T09:33:26.1107289Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_multiprocessing/test_multiprocessing-3ef8309678502818.xml 2025-12-04T09:33:26.1777524Z Running test_fx 1/1 ... [2025-12-04 09:33:26.177420][1348.863191] 2025-12-04T09:33:26.1778075Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:33:26.1781192Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:33:26.177785] 2025-12-04T09:36:58.9504003Z 2025-12-04T09:36:58.9504762Z test_fx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_1.1_e512390b175137c0_.log 2025-12-04T09:36:58.9532970Z Running 100 items in this shard: test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7 2025-12-04T09:36:58.9560974Z 2025-12-04T09:36:58.9561214Z Finished test_fx 1/1 ... [2025-12-04 09:36:58.950198][1561.635967496], took 3.55min 2025-12-04T09:36:58.9562256Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_fx/test_fx-391855ef8a647be7.xml 2025-12-04T09:36:59.0437264Z Running test_autograd_fallback 1/1 ... [2025-12-04 09:36:59.043386][1561.729153591] 2025-12-04T09:36:59.0437810Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:36:59.0441429Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_autograd_fallback.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:36:59.043823] 2025-12-04T09:37:02.2950669Z 2025-12-04T09:37:02.2951655Z test_autograd_fallback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autograd_fallback_1.1_937d3734edcfa66b_.log 2025-12-04T09:37:02.2952508Z Running 0 items in this shard: 2025-12-04T09:37:02.2952707Z 2025-12-04T09:37:02.2953019Z Finished test_autograd_fallback 1/1 ... [2025-12-04 09:37:02.294838][1564.98060703], took 0.05min 2025-12-04T09:37:02.2984362Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_autograd_fallback/test_autograd_fallback-a8f4d01a3ac57092.xml 2025-12-04T09:37:02.3266368Z Running test_autocast 1/1 ... [2025-12-04 09:37:02.326237][1565.012005298] 2025-12-04T09:37:02.3266843Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:02.3269650Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_autocast.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:02.326699] 2025-12-04T09:37:05.8590746Z 2025-12-04T09:37:05.8591577Z test_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autocast_1.1_701fa20e38984ef3_.log 2025-12-04T09:37:05.8592341Z Running 0 items in this shard: 2025-12-04T09:37:05.8592541Z 2025-12-04T09:37:05.8592843Z Finished test_autocast 1/1 ... [2025-12-04 09:37:05.858870][1568.544639918], took 0.06min 2025-12-04T09:37:05.8624997Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_autocast/test_autocast-ed2ce6f56222bf6e.xml 2025-12-04T09:37:05.8913678Z Running test_python_dispatch 1/1 ... [2025-12-04 09:37:05.891138][1568.576910593] 2025-12-04T09:37:05.8914190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:05.8917912Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_python_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:05.891495] 2025-12-04T09:37:10.6414869Z 2025-12-04T09:37:10.6415805Z test_python_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_python_dispatch_1.1_a1bcd36ef1689589_.log 2025-12-04T09:37:10.6416625Z Running 0 items in this shard: 2025-12-04T09:37:10.6416877Z 2025-12-04T09:37:10.6417176Z Finished test_python_dispatch 1/1 ... [2025-12-04 09:37:10.641306][1573.327074908], took 0.08min 2025-12-04T09:37:10.6451593Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_python_dispatch/test_python_dispatch-2e2212d935e196b8.xml 2025-12-04T09:37:10.6732432Z Running test_jit_disabled 1/1 ... [2025-12-04 09:37:10.673000][1573.358772125] 2025-12-04T09:37:10.6732931Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:10.6736378Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit_disabled.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:10.673365] 2025-12-04T09:37:13.8104558Z 2025-12-04T09:37:13.8105591Z test_jit_disabled 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_disabled_1.1_be53362a1364be12_.log 2025-12-04T09:37:13.8106373Z Running 0 items in this shard: 2025-12-04T09:37:13.8106582Z 2025-12-04T09:37:13.8106873Z Finished test_jit_disabled 1/1 ... [2025-12-04 09:37:13.810250][1576.496019597], took 0.05min 2025-12-04T09:37:13.8141888Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit_disabled/test_jit_disabled-21cbf30ba6db2077.xml 2025-12-04T09:37:13.8433291Z Running test_cpp_extensions_mtia_backend 1/1 ... [2025-12-04 09:37:13.843081][1576.528853066] 2025-12-04T09:37:13.8433831Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:13.8436810Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_extensions_mtia_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:13.843434] 2025-12-04T09:37:17.0440398Z 2025-12-04T09:37:17.0441463Z test_cpp_extensions_mtia_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_mtia_backend_1.1_ccc5da7478e87015_.log 2025-12-04T09:37:17.0442682Z Running 0 items in this shard: 2025-12-04T09:37:17.0442882Z 2025-12-04T09:37:17.0443242Z Finished test_cpp_extensions_mtia_backend 1/1 ... [2025-12-04 09:37:17.043852][1579.729621091], took 0.05min 2025-12-04T09:37:17.0479666Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_extensions_mtia_backend/test_cpp_extensions_mtia_backend-58d2e57e3388b2e6.xml 2025-12-04T09:37:17.0785089Z Running functorch/test_memory_efficient_fusion 1/1 ... [2025-12-04 09:37:17.078297][1579.764069667] 2025-12-04T09:37:17.0785681Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:17.0789272Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/test_memory_efficient_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:17.078655] 2025-12-04T09:37:20.6268269Z 2025-12-04T09:37:20.6269400Z functorch/test_memory_efficient_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_memory_efficient_fusion_1.1_56b63d6fa6b0872f_.log 2025-12-04T09:37:20.6270448Z Running 0 items in this shard: 2025-12-04T09:37:20.6270649Z 2025-12-04T09:37:20.6271057Z Finished functorch/test_memory_efficient_fusion 1/1 ... [2025-12-04 09:37:20.626611][1583.312382071], took 0.06min 2025-12-04T09:37:20.6308368Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.test_memory_efficient_fusion/functorch.test_memory_efficient_fusion-30d8c5bd26f1f656.xml 2025-12-04T09:37:20.6613053Z Running test_tensor_creation_ops 1/1 ... [2025-12-04 09:37:20.661040][1583.346811127] 2025-12-04T09:37:20.6613573Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:20.6616204Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_tensor_creation_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:20.661373] 2025-12-04T09:37:24.3772655Z 2025-12-04T09:37:24.3773634Z test_tensor_creation_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensor_creation_ops_1.1_7e1c311b313b4509_.log 2025-12-04T09:37:24.3774501Z Running 0 items in this shard: 2025-12-04T09:37:24.3774714Z 2025-12-04T09:37:24.3775024Z Finished test_tensor_creation_ops 1/1 ... [2025-12-04 09:37:24.377040][1587.062810072], took 0.06min 2025-12-04T09:37:24.3813435Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_tensor_creation_ops/test_tensor_creation_ops-6337d1796146936f.xml 2025-12-04T09:37:24.4032356Z Running test_cpp_extensions_stream_and_event 1/1 ... [2025-12-04 09:37:24.402944][1587.088715972] 2025-12-04T09:37:24.4032918Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:24.4035368Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_extensions_stream_and_event.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:24.403285] 2025-12-04T09:37:27.6512464Z 2025-12-04T09:37:27.6513542Z test_cpp_extensions_stream_and_event 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_stream_and_event_1.1_67cee170ff29d84c_.log 2025-12-04T09:37:27.6514519Z Running 0 items in this shard: 2025-12-04T09:37:27.6514716Z 2025-12-04T09:37:27.6515089Z Finished test_cpp_extensions_stream_and_event 1/1 ... [2025-12-04 09:37:27.651059][1590.336829401], took 0.05min 2025-12-04T09:37:27.6555927Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_extensions_stream_and_event/test_cpp_extensions_stream_and_event-b950d631e7f281b2.xml 2025-12-04T09:37:27.6846638Z Running test_dispatch 1/1 ... [2025-12-04 09:37:27.684370][1590.370137662] 2025-12-04T09:37:27.6847118Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:27.6850385Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:27.684774] 2025-12-04T09:37:30.8853549Z 2025-12-04T09:37:30.8854418Z test_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dispatch_1.1_6056b36cc8d783ed_.log 2025-12-04T09:37:30.8855188Z Running 0 items in this shard: 2025-12-04T09:37:30.8855399Z 2025-12-04T09:37:30.8855696Z Finished test_dispatch 1/1 ... [2025-12-04 09:37:30.885141][1593.570910783], took 0.05min 2025-12-04T09:37:30.8897390Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_dispatch/test_dispatch-d5d3d22e37a1674a.xml 2025-12-04T09:37:30.9156353Z Running nn/test_convolution 1/1 ... [2025-12-04 09:37:30.915348][1593.601119679] 2025-12-04T09:37:30.9156877Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:30.9159949Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_convolution.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:30.915710] 2025-12-04T09:37:34.8694348Z 2025-12-04T09:37:34.8695297Z nn/test_convolution 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_convolution_1.1_0af20b8d5488b886_.log 2025-12-04T09:37:34.8696139Z Running 0 items in this shard: 2025-12-04T09:37:34.8696351Z 2025-12-04T09:37:34.8696652Z Finished nn/test_convolution 1/1 ... [2025-12-04 09:37:34.869229][1597.554999684], took 0.07min 2025-12-04T09:37:34.8739540Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_convolution/nn.test_convolution-c71625594b2a69e1.xml 2025-12-04T09:37:34.9017388Z Running test_cpp_extensions_jit 1/1 ... [2025-12-04 09:37:34.901485][1597.587255416] 2025-12-04T09:37:34.9017907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:34.9020988Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_extensions_jit.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:34.901846] 2025-12-04T09:37:38.7246584Z 2025-12-04T09:37:38.7247856Z test_cpp_extensions_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_jit_1.1_355315488d87f844_.log 2025-12-04T09:37:38.7248720Z Running 0 items in this shard: 2025-12-04T09:37:38.7248917Z 2025-12-04T09:37:38.7249237Z Finished test_cpp_extensions_jit 1/1 ... [2025-12-04 09:37:38.724102][1601.409873386], took 0.06min 2025-12-04T09:37:38.7290314Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_extensions_jit/test_cpp_extensions_jit-9e01630abb6815ba.xml 2025-12-04T09:37:38.7523926Z Running test_nn 1/1 ... [2025-12-04 09:37:38.752117][1601.437889083] 2025-12-04T09:37:38.7524361Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:38.7527330Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_nn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:38.752480] 2025-12-04T09:37:44.9698964Z 2025-12-04T09:37:44.9699972Z test_nn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_1.1_667926e22671f255_.log 2025-12-04T09:37:44.9700676Z Running 0 items in this shard: 2025-12-04T09:37:44.9700877Z 2025-12-04T09:37:44.9701118Z Finished test_nn 1/1 ... [2025-12-04 09:37:44.969713][1607.65548358], took 0.10min 2025-12-04T09:37:44.9748099Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_nn/test_nn-75157755530a9ef8.xml 2025-12-04T09:37:45.0873856Z Running test_multiprocessing_spawn 1/1 ... [2025-12-04 09:37:45.087077][1607.772846609] 2025-12-04T09:37:45.0874418Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:45.0878068Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_multiprocessing_spawn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:45.087466] 2025-12-04T09:37:53.3337676Z 2025-12-04T09:37:53.3338660Z test_multiprocessing_spawn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_spawn_1.1_9990875508549b91_.log 2025-12-04T09:37:53.3339567Z Running 0 items in this shard: 2025-12-04T09:37:53.3339768Z 2025-12-04T09:37:53.3340115Z Finished test_multiprocessing_spawn 1/1 ... [2025-12-04 09:37:53.333561][1616.01933211], took 0.14min 2025-12-04T09:37:53.3387223Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_multiprocessing_spawn/test_multiprocessing_spawn-1a7dbd6b88891cf7.xml 2025-12-04T09:37:53.3995539Z Running nn/test_pooling 1/1 ... [2025-12-04 09:37:53.399288][1616.085060457] 2025-12-04T09:37:53.3996057Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:53.3999330Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_pooling.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:53.399665] 2025-12-04T09:37:56.9457907Z 2025-12-04T09:37:56.9458822Z nn/test_pooling 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pooling_1.1_166129b52aec11e7_.log 2025-12-04T09:37:56.9459620Z Running 0 items in this shard: 2025-12-04T09:37:56.9459835Z 2025-12-04T09:37:56.9460117Z Finished nn/test_pooling 1/1 ... [2025-12-04 09:37:56.945618][1619.631389148], took 0.06min 2025-12-04T09:37:56.9509410Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_pooling/nn.test_pooling-76c9d78c4e1b3bdd.xml 2025-12-04T09:37:56.9817396Z Running test_cuda_trace 1/1 ... [2025-12-04 09:37:56.981514][1619.667285721] 2025-12-04T09:37:56.9817873Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:37:56.9821561Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cuda_trace.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:37:56.981873] 2025-12-04T09:38:00.1232667Z 2025-12-04T09:38:00.1233675Z test_cuda_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_trace_1.1_b35b6fc6083cce19_.log 2025-12-04T09:38:00.1234866Z Running 0 items in this shard: 2025-12-04T09:38:00.1235065Z 2025-12-04T09:38:00.1235452Z Finished test_cuda_trace 1/1 ... [2025-12-04 09:38:00.122989][1622.808760345], took 0.05min 2025-12-04T09:38:00.1287027Z Running test_native_mha 1/1 ... [2025-12-04 09:38:00.128508][1622.814280435] 2025-12-04T09:38:00.1287499Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:00.1291349Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_native_mha.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:00.128889] 2025-12-04T09:38:03.6955113Z 2025-12-04T09:38:03.6955844Z test_native_mha 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_mha_1.1_36dfb13c368883eb_.log 2025-12-04T09:38:03.6956629Z Running 0 items in this shard: 2025-12-04T09:38:03.6956842Z 2025-12-04T09:38:03.6957114Z Finished test_native_mha 1/1 ... [2025-12-04 09:38:03.695222][1626.380992124], took 0.06min 2025-12-04T09:38:03.7007098Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_native_mha/test_native_mha-dec2f7b8557e7dc0.xml 2025-12-04T09:38:03.7759778Z Running test_cuda_nvml_based_avail 1/1 ... [2025-12-04 09:38:03.775686][1626.461455884] 2025-12-04T09:38:03.7760321Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:03.7763944Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cuda_nvml_based_avail.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:03.776087] 2025-12-04T09:38:06.9173874Z 2025-12-04T09:38:06.9174862Z test_cuda_nvml_based_avail 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_nvml_based_avail_1.1_c8bcd47fd3874009_.log 2025-12-04T09:38:06.9175769Z Running 0 items in this shard: 2025-12-04T09:38:06.9175967Z 2025-12-04T09:38:06.9176294Z Finished test_cuda_nvml_based_avail 1/1 ... [2025-12-04 09:38:06.917162][1629.602931879], took 0.05min 2025-12-04T09:38:06.9230111Z Running test_mobile_optimizer 1/1 ... [2025-12-04 09:38:06.922814][1629.608586572] 2025-12-04T09:38:06.9230600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:06.9234590Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_mobile_optimizer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:06.923204] 2025-12-04T09:38:10.7503727Z 2025-12-04T09:38:10.7504758Z test_mobile_optimizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mobile_optimizer_1.1_1420e2146b046aa6_.log 2025-12-04T09:38:10.7541209Z Running 100 items in this shard: test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures 2025-12-04T09:38:10.7577325Z 2025-12-04T09:38:10.7577634Z Finished test_mobile_optimizer 1/1 ... [2025-12-04 09:38:10.750358][1633.436126652], took 0.06min 2025-12-04T09:38:10.7578772Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_mobile_optimizer/test_mobile_optimizer-caa85bae045b9638.xml 2025-12-04T09:38:10.8388746Z Running test_cuda_primary_ctx 1/1 ... [2025-12-04 09:38:10.838601][1633.524372714] 2025-12-04T09:38:10.8389255Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:10.8392811Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cuda_primary_ctx.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:10.838975] 2025-12-04T09:38:14.6040849Z 2025-12-04T09:38:14.6041806Z test_cuda_primary_ctx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_primary_ctx_1.1_3797038a5f48c12b_.log 2025-12-04T09:38:14.6044192Z Running 0 items in this shard: 2025-12-04T09:38:14.6044408Z 2025-12-04T09:38:14.6044805Z Finished test_cuda_primary_ctx 1/1 ... [2025-12-04 09:38:14.603805][1637.289574897], took 0.06min 2025-12-04T09:38:14.6098631Z Running test_reductions 1/1 ... [2025-12-04 09:38:14.609645][1637.295416815] 2025-12-04T09:38:14.6099116Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:14.6103044Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_reductions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:14.610067] 2025-12-04T09:38:19.2258038Z 2025-12-04T09:38:19.2259078Z test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_1.1_0b5b58bb8ca8c418_.log 2025-12-04T09:38:19.2259876Z Running 0 items in this shard: 2025-12-04T09:38:19.2260107Z 2025-12-04T09:38:19.2260394Z Finished test_reductions 1/1 ... [2025-12-04 09:38:19.225608][1641.911378626], took 0.08min 2025-12-04T09:38:19.2312974Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_reductions/test_reductions-03e1e53161df6506.xml 2025-12-04T09:38:19.3041792Z Running test_spectral_ops 1/1 ... [2025-12-04 09:38:19.303872][1641.98964416] 2025-12-04T09:38:19.3042511Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:19.3045927Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:19.304212] 2025-12-04T09:38:24.0841970Z 2025-12-04T09:38:24.0843336Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_b097acbabd89dab0_.log 2025-12-04T09:38:24.0844181Z Running 0 items in this shard: 2025-12-04T09:38:24.0844380Z 2025-12-04T09:38:24.0844723Z Finished test_spectral_ops 1/1 ... [2025-12-04 09:38:24.083992][1646.769761973], took 0.08min 2025-12-04T09:38:24.0899035Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_spectral_ops/test_spectral_ops-534db87a9fcffb83.xml 2025-12-04T09:38:24.1164793Z Running distributions/test_distributions 1/1 ... [2025-12-04 09:38:24.116194][1646.80196659] 2025-12-04T09:38:24.1165389Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:38:24.1168082Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:38:24.116547] 2025-12-04T09:38:28.7235563Z 2025-12-04T09:38:28.7237050Z distributions/test_distributions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_1.1_291103f76a1b8ef0_.log 2025-12-04T09:38:28.7258751Z Running 50 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample 2025-12-04T09:38:28.7279189Z 2025-12-04T09:38:28.7279562Z Finished distributions/test_distributions 1/1 ... [2025-12-04 09:38:28.723413][1651.409182166], took 0.08min 2025-12-04T09:38:28.7295140Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/distributions.test_distributions/distributions.test_distributions-f29e5a2a36bb4dfa.xml 2025-12-04T09:38:28.7594666Z Running test_autoload_disable 1/1 ... [2025-12-04 09:38:28.759191][1651.444962794] 2025-12-04T09:38:29.0908805Z Processing /var/lib/jenkins/workspace/test/cpp_extensions 2025-12-04T09:38:32.2299498Z Preparing metadata (pyproject.toml) ... [?25l- \ done 2025-12-04T09:38:32.2320975Z [?25hBuilding wheels for collected packages: torch_test_cpp_extension 2025-12-04T09:38:42.2619491Z Building wheel for torch_test_cpp_extension (pyproject.toml) ... [?25l- \ | / - \ | / - \ | done 2025-12-04T09:38:42.2887078Z [?25h Created wheel for torch_test_cpp_extension: filename=torch_test_cpp_extension-0.0.0-cp310-cp310-linux_x86_64.whl size=10079477 sha256=364b12566d0f02b5ccebf0a9a722feb644871180934c03177323dda2d0d6eaec 2025-12-04T09:38:42.2888554Z Stored in directory: /tmp/pip-ephem-wheel-cache-f1mr8xyh/wheels/2b/79/8d/635cf291e138cfea331292ca746c62b61fade208eb55a7e3a1 2025-12-04T09:38:42.2906177Z Successfully built torch_test_cpp_extension 2025-12-04T09:38:42.6579686Z Installing collected packages: torch_test_cpp_extension 2025-12-04T09:38:42.8256410Z Successfully installed torch_test_cpp_extension-0.0.0 2025-12-04T09:38:44.4687264Z W1204 09:38:44.468000 5456 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:38:45.4087235Z 2025-12-04T09:38:45.4087926Z Running tests... 2025-12-04T09:38:45.4088302Z ---------------------------------------------------------------------- 2025-12-04T09:38:45.5814572Z . 2025-12-04T09:38:45.5814902Z ---------------------------------------------------------------------- 2025-12-04T09:38:45.5815289Z Ran 1 test in 0.173s 2025-12-04T09:38:45.5815463Z 2025-12-04T09:38:45.5815545Z OK 2025-12-04T09:38:45.5815654Z 2025-12-04T09:38:45.5815773Z Generating XML reports... 2025-12-04T09:38:46.2294317Z Finished test_autoload_disable 1/1 ... [2025-12-04 09:38:46.229068][1668.914830334], took 0.29min 2025-12-04T09:38:46.2355234Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-unittest/test_autoload/TEST-TestDeviceBackendAutoload-20251204093845.xml 2025-12-04T09:38:46.3270301Z Running test_autoload_enable 1/1 ... [2025-12-04 09:38:46.326719][1669.012488818] 2025-12-04T09:38:46.6656479Z Processing /var/lib/jenkins/workspace/test/cpp_extensions 2025-12-04T09:38:49.8310642Z Preparing metadata (pyproject.toml) ... [?25l- \ done 2025-12-04T09:38:49.8360583Z [?25hBuilding wheels for collected packages: torch_test_cpp_extension 2025-12-04T09:38:59.7780637Z Building wheel for torch_test_cpp_extension (pyproject.toml) ... [?25l- \ | / - \ | / - \ | done 2025-12-04T09:38:59.8047947Z [?25h Created wheel for torch_test_cpp_extension: filename=torch_test_cpp_extension-0.0.0-cp310-cp310-linux_x86_64.whl size=10079477 sha256=dce2f22a536501ab63035bbcfbf96a95fab36ba48dee79105bd046922f3865e0 2025-12-04T09:38:59.8049467Z Stored in directory: /tmp/pip-ephem-wheel-cache-i7mr8b4f/wheels/2b/79/8d/635cf291e138cfea331292ca746c62b61fade208eb55a7e3a1 2025-12-04T09:38:59.8068167Z Successfully built torch_test_cpp_extension 2025-12-04T09:39:00.1774038Z Installing collected packages: torch_test_cpp_extension 2025-12-04T09:39:00.3531641Z Successfully installed torch_test_cpp_extension-0.0.0 2025-12-04T09:39:01.9872536Z W1204 09:39:01.986000 5641 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:39:02.9333432Z 2025-12-04T09:39:02.9334002Z Running tests... 2025-12-04T09:39:02.9334411Z ---------------------------------------------------------------------- 2025-12-04T09:39:03.1106797Z . 2025-12-04T09:39:03.1107134Z ---------------------------------------------------------------------- 2025-12-04T09:39:03.1107565Z Ran 1 test in 0.177s 2025-12-04T09:39:03.1107743Z 2025-12-04T09:39:03.1107827Z OK 2025-12-04T09:39:03.1107938Z 2025-12-04T09:39:03.1108061Z Generating XML reports... 2025-12-04T09:39:03.7202597Z Finished test_autoload_enable 1/1 ... [2025-12-04 09:39:03.719812][1686.405574316], took 0.29min 2025-12-04T09:39:03.7263584Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-unittest/test_autoload/TEST-TestDeviceBackendAutoload-20251204093902.xml 2025-12-04T09:39:03.8108521Z Running test_cpp_extensions_aot_ninja 1/1 ... [2025-12-04 09:39:03.810569][1686.496339698] 2025-12-04T09:39:04.1776697Z Processing /var/lib/jenkins/workspace/test/cpp_extensions 2025-12-04T09:39:07.3517216Z Preparing metadata (pyproject.toml) ... [?25l- \ done 2025-12-04T09:39:07.3537397Z [?25hBuilding wheels for collected packages: torch_test_cpp_extension 2025-12-04T09:39:17.7391262Z Building wheel for torch_test_cpp_extension (pyproject.toml) ... [?25l- \ | / - \ | / - \ | done 2025-12-04T09:39:17.7659975Z [?25h Created wheel for torch_test_cpp_extension: filename=torch_test_cpp_extension-0.0.0-cp310-cp310-linux_x86_64.whl size=10079605 sha256=a58d94b915ac18e368c92d7990336509793748aaf0b6e5d3f4e973fe68a6eeb4 2025-12-04T09:39:17.7661502Z Stored in directory: /tmp/pip-ephem-wheel-cache-wb78ixxl/wheels/2b/79/8d/635cf291e138cfea331292ca746c62b61fade208eb55a7e3a1 2025-12-04T09:39:17.7679307Z Successfully built torch_test_cpp_extension 2025-12-04T09:39:18.1343743Z Installing collected packages: torch_test_cpp_extension 2025-12-04T09:39:18.3058179Z Successfully installed torch_test_cpp_extension-0.0.0 2025-12-04T09:39:18.6953397Z Processing /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test 2025-12-04T09:39:20.5054392Z Preparing metadata (pyproject.toml) ... [?25l- done 2025-12-04T09:39:20.5075089Z [?25hBuilding wheels for collected packages: no_python_abi_suffix_test 2025-12-04T09:39:22.5891992Z Building wheel for no_python_abi_suffix_test (pyproject.toml) ... [?25l- \ | done 2025-12-04T09:39:22.5899075Z [?25h Created wheel for no_python_abi_suffix_test: filename=no_python_abi_suffix_test-0.0.0-cp310-cp310-linux_x86_64.whl size=2944 sha256=0c90bb9b720bf473e687b9c636d6bebd56aeb2de91d478d6b17ea95e3ca1b119 2025-12-04T09:39:22.5900731Z Stored in directory: /tmp/pip-ephem-wheel-cache-l7mvnnpn/wheels/8c/c7/11/bcf2bfbdebb3cf78b8211ac54acc945a8fdf1732548d147a80 2025-12-04T09:39:22.5919296Z Successfully built no_python_abi_suffix_test 2025-12-04T09:39:22.9596089Z Installing collected packages: no_python_abi_suffix_test 2025-12-04T09:39:22.9703008Z Successfully installed no_python_abi_suffix_test-0.0.0 2025-12-04T09:39:23.0310098Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:39:23.0314351Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_extensions_aot_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:39:23.031137] 2025-12-04T09:39:26.5570806Z 2025-12-04T09:39:26.5572068Z test_cpp_extensions_aot_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_ninja_1.1_4418ae146adcd38c_.log 2025-12-04T09:39:26.5572976Z Running 0 items in this shard: 2025-12-04T09:39:26.5573199Z 2025-12-04T09:39:26.5573531Z Finished test_cpp_extensions_aot_ninja 1/1 ... [2025-12-04 09:39:26.557035][1709.242803604], took 0.38min 2025-12-04T09:39:26.5632119Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_extensions_aot_ninja/test_cpp_extensions_aot_ninja-42e6c1b7cbbca83a.xml 2025-12-04T09:39:26.6314710Z Running test_cpp_extensions_aot_no_ninja 1/1 ... [2025-12-04 09:39:26.631123][1709.31689286] 2025-12-04T09:39:26.9666536Z Processing /var/lib/jenkins/workspace/test/cpp_extensions 2025-12-04T09:39:30.1212162Z Preparing metadata (pyproject.toml) ... [?25l- \ done 2025-12-04T09:39:30.1234121Z [?25hBuilding wheels for collected packages: torch_test_cpp_extension 2025-12-04T09:39:40.0352995Z Building wheel for torch_test_cpp_extension (pyproject.toml) ... [?25l- \ | / - \ | / - \ | done 2025-12-04T09:39:40.0619610Z [?25h Created wheel for torch_test_cpp_extension: filename=torch_test_cpp_extension-0.0.0-cp310-cp310-linux_x86_64.whl size=10079477 sha256=962b0562f846cb1b91024aacf247ffc315f926112329cee6bdfe4ad974bc8ac2 2025-12-04T09:39:40.0621091Z Stored in directory: /tmp/pip-ephem-wheel-cache-ss0m_5db/wheels/2b/79/8d/635cf291e138cfea331292ca746c62b61fade208eb55a7e3a1 2025-12-04T09:39:40.0639585Z Successfully built torch_test_cpp_extension 2025-12-04T09:39:40.4291860Z Installing collected packages: torch_test_cpp_extension 2025-12-04T09:39:40.5989125Z Successfully installed torch_test_cpp_extension-0.0.0 2025-12-04T09:39:40.9887887Z Processing /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test 2025-12-04T09:39:42.8139041Z Preparing metadata (pyproject.toml) ... [?25l- done 2025-12-04T09:39:42.8160571Z [?25hBuilding wheels for collected packages: no_python_abi_suffix_test 2025-12-04T09:39:44.8143613Z Building wheel for no_python_abi_suffix_test (pyproject.toml) ... [?25l- \ | done 2025-12-04T09:39:44.8151192Z [?25h Created wheel for no_python_abi_suffix_test: filename=no_python_abi_suffix_test-0.0.0-cp310-cp310-linux_x86_64.whl size=2944 sha256=fb3431f929bcde8a4731bd4bc65cabe4d84c551a5e7c54ffc0e77bd59fba4e19 2025-12-04T09:39:44.8152744Z Stored in directory: /tmp/pip-ephem-wheel-cache-csgbjno1/wheels/8c/c7/11/bcf2bfbdebb3cf78b8211ac54acc945a8fdf1732548d147a80 2025-12-04T09:39:44.8171966Z Successfully built no_python_abi_suffix_test 2025-12-04T09:39:45.1909188Z Installing collected packages: no_python_abi_suffix_test 2025-12-04T09:39:45.2015569Z Successfully installed no_python_abi_suffix_test-0.0.0 2025-12-04T09:39:45.2618718Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:39:45.2623245Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cpp_extensions_aot_no_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:39:45.262021] 2025-12-04T09:39:48.7683364Z 2025-12-04T09:39:48.7684533Z test_cpp_extensions_aot_no_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_no_ninja_1.1_2db7d58614af44df_.log 2025-12-04T09:39:48.7685520Z Running 0 items in this shard: 2025-12-04T09:39:48.7685766Z 2025-12-04T09:39:48.7686114Z Finished test_cpp_extensions_aot_no_ninja 1/1 ... [2025-12-04 09:39:48.768256][1731.454024679], took 0.37min 2025-12-04T09:39:48.7747474Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cpp_extensions_aot_no_ninja/test_cpp_extensions_aot_no_ninja-987df1b8de8457ae.xml 2025-12-04T09:39:48.8420948Z Running inductor/test_aot_inductor 1/1 ... [2025-12-04 09:39:48.841823][1731.527593803] 2025-12-04T09:39:48.8421497Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:39:48.8425205Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:39:48.842212] 2025-12-04T09:39:56.8851843Z 2025-12-04T09:39:56.8852856Z inductor/test_aot_inductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_1.1_b12d87def414b826_.log 2025-12-04T09:39:56.8853673Z 2025-12-04T09:39:56.8854019Z Finished inductor/test_aot_inductor 1/1 ... [2025-12-04 09:39:56.884973][1739.570743033], took 0.13min 2025-12-04T09:39:56.8918804Z Running inductor/test_torchinductor_opinfo 1/1 ... [2025-12-04 09:39:56.891673][1739.577444666] 2025-12-04T09:39:56.8919380Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:39:56.8924923Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:39:56.892067] 2025-12-04T09:40:06.0650811Z 2025-12-04T09:40:06.0651936Z inductor/test_torchinductor_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_1.1_b019b60eec17379c_.log 2025-12-04T09:40:06.0653232Z Running 0 items in this shard: 2025-12-04T09:40:06.0653445Z 2025-12-04T09:40:06.0653825Z Finished inductor/test_torchinductor_opinfo 1/1 ... [2025-12-04 09:40:06.064845][1748.750615871], took 0.15min 2025-12-04T09:40:06.0712342Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_torchinductor_opinfo/inductor.test_torchinductor_opinfo-cc6e4490a4b3c2d7.xml 2025-12-04T09:40:06.1425120Z Running inductor/test_cudagraph_trees 1/1 ... [2025-12-04 09:40:06.142217][1748.82798884] 2025-12-04T09:40:06.1425695Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:06.1429199Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cudagraph_trees.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:06.142607] 2025-12-04T09:40:13.8028041Z 2025-12-04T09:40:13.8028943Z inductor/test_cudagraph_trees 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_1.1_a309f75c4503dd76_.log 2025-12-04T09:40:13.8029769Z 2025-12-04T09:40:13.8030130Z Finished inductor/test_cudagraph_trees 1/1 ... [2025-12-04 09:40:13.802581][1756.488351977], took 0.13min 2025-12-04T09:40:13.8105201Z Running inductor/test_compile_subprocess 1/1 ... [2025-12-04 09:40:13.810345][1756.496117548] 2025-12-04T09:40:13.8105764Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:13.8109651Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:13.810692] 2025-12-04T09:40:22.0867147Z 2025-12-04T09:40:22.0868250Z inductor/test_compile_subprocess 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_1.1_994b96d79ff48e8d_.log 2025-12-04T09:40:22.0869101Z 2025-12-04T09:40:22.0869485Z Finished inductor/test_compile_subprocess 1/1 ... [2025-12-04 09:40:22.086252][1764.772023128], took 0.14min 2025-12-04T09:40:22.0933628Z Running inductor/test_native_matmul 1/1 ... [2025-12-04 09:40:22.093111][1764.778882573] 2025-12-04T09:40:22.0934168Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:22.0937572Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_native_matmul.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:22.093493] 2025-12-04T09:40:29.8459594Z 2025-12-04T09:40:29.8460663Z inductor/test_native_matmul 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_native_matmul_1.1_051ad16863ba4960_.log 2025-12-04T09:40:29.8461509Z 2025-12-04T09:40:29.8461846Z Finished inductor/test_native_matmul 1/1 ... [2025-12-04 09:40:29.845728][1772.531498386], took 0.13min 2025-12-04T09:40:29.8538180Z Running inductor/test_op_dtype_prop 1/1 ... [2025-12-04 09:40:29.853557][1772.539327809] 2025-12-04T09:40:29.8538717Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:29.8542686Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_op_dtype_prop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:29.853951] 2025-12-04T09:40:39.3223458Z 2025-12-04T09:40:39.3224476Z 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_56c57e5972d3438a_.log 2025-12-04T09:40:39.3225602Z 2025-12-04T09:40:39.3225936Z Finished inductor/test_op_dtype_prop 1/1 ... [2025-12-04 09:40:39.322108][1782.007878175], took 0.16min 2025-12-04T09:40:39.3293395Z Running inductor/test_unbacked_symints 1/1 ... [2025-12-04 09:40:39.329054][1782.014824726] 2025-12-04T09:40:39.3293986Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:39.3297479Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_unbacked_symints.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:39.329461] 2025-12-04T09:40:47.5476328Z 2025-12-04T09:40:47.5477682Z inductor/test_unbacked_symints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_unbacked_symints_1.1_0fb29ac36b7a35c3_.log 2025-12-04T09:40:47.5478720Z Running 0 items in this shard: 2025-12-04T09:40:47.5478923Z 2025-12-04T09:40:47.5479294Z Finished inductor/test_unbacked_symints 1/1 ... [2025-12-04 09:40:47.547383][1790.233153574], took 0.14min 2025-12-04T09:40:47.5540100Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_unbacked_symints/inductor.test_unbacked_symints-0db4f0bdc753de66.xml 2025-12-04T09:40:47.6231204Z Running inductor/test_padding 1/1 ... [2025-12-04 09:40:47.622781][1790.308550396] 2025-12-04T09:40:47.6231736Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:47.6234769Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_padding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:47.623188] 2025-12-04T09:40:55.6582608Z 2025-12-04T09:40:55.6583571Z inductor/test_padding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_padding_1.1_ff7252a06f789bf7_.log 2025-12-04T09:40:55.6584360Z 2025-12-04T09:40:55.6584669Z Finished inductor/test_padding 1/1 ... [2025-12-04 09:40:55.658028][1798.343797491], took 0.13min 2025-12-04T09:40:55.6655856Z Running test_varlen_attention 1/1 ... [2025-12-04 09:40:55.665361][1798.35113159] 2025-12-04T09:40:55.6656366Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:55.6660346Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_varlen_attention.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:55.665775] 2025-12-04T09:40:59.4001016Z 2025-12-04T09:40:59.4002131Z test_varlen_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_varlen_attention_1.1_a044d3976f62b133_.log 2025-12-04T09:40:59.4002990Z Running 0 items in this shard: 2025-12-04T09:40:59.4003205Z 2025-12-04T09:40:59.4003516Z Finished test_varlen_attention 1/1 ... [2025-12-04 09:40:59.399936][1802.085704903], took 0.06min 2025-12-04T09:40:59.4066888Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_varlen_attention/test_varlen_attention-4e0a4de68bfeb981.xml 2025-12-04T09:40:59.4749537Z Running test_ops_fwd_gradients 1/1 ... [2025-12-04 09:40:59.474590][1802.160358655] 2025-12-04T09:40:59.4750062Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:40:59.4753350Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:40:59.474995] 2025-12-04T09:41:04.0157773Z 2025-12-04T09:41:04.0158940Z 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_0901e1e7142e453e_.log 2025-12-04T09:41:04.0159771Z Running 0 items in this shard: 2025-12-04T09:41:04.0159993Z 2025-12-04T09:41:04.0160296Z Finished test_ops_fwd_gradients 1/1 ... [2025-12-04 09:41:04.015621][1806.701391913], took 0.08min 2025-12-04T09:41:04.0223483Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_ops_fwd_gradients/test_ops_fwd_gradients-7672b5aec71a61be.xml 2025-12-04T09:41:04.0499795Z Running test_linalg 1/1 ... [2025-12-04 09:41:04.049781][1806.735552767] 2025-12-04T09:41:04.0500245Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:04.0503581Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_linalg.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:04.050117] 2025-12-04T09:41:07.9808609Z 2025-12-04T09:41:07.9809458Z test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_1.1_cf09176a7da2f6a5_.log 2025-12-04T09:41:07.9810194Z Running 0 items in this shard: 2025-12-04T09:41:07.9810407Z 2025-12-04T09:41:07.9810670Z Finished test_linalg 1/1 ... [2025-12-04 09:41:07.980664][1810.666434208], took 0.07min 2025-12-04T09:41:07.9878984Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_linalg/test_linalg-90a14f71f0914a83.xml 2025-12-04T09:41:08.0197670Z Running inductor/test_select_algorithm 1/1 ... [2025-12-04 09:41:08.019532][1810.705303079] 2025-12-04T09:41:08.0198215Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:08.0201468Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_select_algorithm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:08.019878] 2025-12-04T09:41:15.8023024Z 2025-12-04T09:41:15.8024726Z inductor/test_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_select_algorithm_1.1_c88945ed9caf85a2_.log 2025-12-04T09:41:15.8026281Z 2025-12-04T09:41:15.8026939Z Finished inductor/test_select_algorithm 1/1 ... [2025-12-04 09:41:15.802062][1818.487832565], took 0.13min 2025-12-04T09:41:15.8099779Z Running dynamo/test_dynamic_shapes 2/2 ... [2025-12-04 09:41:15.809725][1818.495497044] 2025-12-04T09:41:15.8100681Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:15.8105998Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:15.810195] 2025-12-04T09:41:29.3566903Z 2025-12-04T09:41:29.3567893Z dynamo/test_dynamic_shapes 2/2 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_2.2_94031651875084c4_.log 2025-12-04T09:41:29.3568775Z Running 0 items in this shard: 2025-12-04T09:41:29.3568989Z 2025-12-04T09:41:29.3569318Z Finished dynamo/test_dynamic_shapes 2/2 ... [2025-12-04 09:41:29.356482][1832.042251841], took 0.23min 2025-12-04T09:41:29.3636914Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_dynamic_shapes/dynamo.test_dynamic_shapes-de37df165367e5b2.xml 2025-12-04T09:41:29.4260364Z Running inductor/test_compiled_autograd 2/2 ... [2025-12-04 09:41:29.425712][1832.111483568] 2025-12-04T09:41:29.4260931Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:29.4263844Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compiled_autograd.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:29.426086] 2025-12-04T09:41:39.9533833Z 2025-12-04T09:41:39.9534906Z inductor/test_compiled_autograd 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_autograd_2.2_bcbda6ec6dd25e25_.log 2025-12-04T09:41:39.9535883Z Running 0 items in this shard: 2025-12-04T09:41:39.9536082Z 2025-12-04T09:41:39.9536473Z Finished inductor/test_compiled_autograd 2/2 ... [2025-12-04 09:41:39.953197][1842.638967872], took 0.18min 2025-12-04T09:41:39.9604774Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_compiled_autograd/inductor.test_compiled_autograd-d8ba29f15382b2f2.xml 2025-12-04T09:41:40.0540787Z Running inductor/test_custom_lowering 1/1 ... [2025-12-04 09:41:40.053766][1842.739536539] 2025-12-04T09:41:40.0541548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:40.0545006Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_custom_lowering.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:40.054188] 2025-12-04T09:41:47.7521554Z 2025-12-04T09:41:47.7522574Z inductor/test_custom_lowering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_custom_lowering_1.1_e4f484aae237b0b3_.log 2025-12-04T09:41:47.7523499Z Running 0 items in this shard: 2025-12-04T09:41:47.7523698Z 2025-12-04T09:41:47.7524057Z Finished inductor/test_custom_lowering 1/1 ... [2025-12-04 09:41:47.751949][1850.43771656], took 0.13min 2025-12-04T09:41:47.7593678Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_custom_lowering/inductor.test_custom_lowering-805def27ecdc15d7.xml 2025-12-04T09:41:47.8337775Z Running inductor/test_perf 1/1 ... [2025-12-04 09:41:47.833506][1850.519277354] 2025-12-04T09:41:47.8338288Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:47.8341591Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_perf.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:47.833870] 2025-12-04T09:41:55.4576244Z 2025-12-04T09:41:55.4577714Z inductor/test_perf 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_perf_1.1_12a97b0d9c51df04_.log 2025-12-04T09:41:55.4579058Z 2025-12-04T09:41:55.4579597Z Finished inductor/test_perf 1/1 ... [2025-12-04 09:41:55.457347][1858.143116296], took 0.13min 2025-12-04T09:41:55.4657486Z Running inductor/test_fused_attention 1/1 ... [2025-12-04 09:41:55.465490][1858.151261604] 2025-12-04T09:41:55.4658399Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:41:55.4663022Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_fused_attention.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:41:55.465929] 2025-12-04T09:42:03.2398093Z 2025-12-04T09:42:03.2400079Z inductor/test_fused_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fused_attention_1.1_05190ddb95e10b58_.log 2025-12-04T09:42:03.2401835Z Running 0 items in this shard: 2025-12-04T09:42:03.2402218Z 2025-12-04T09:42:03.2402874Z Finished inductor/test_fused_attention 1/1 ... [2025-12-04 09:42:03.239604][1865.925374287], took 0.13min 2025-12-04T09:42:03.2474960Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_fused_attention/inductor.test_fused_attention-1172c1e07ed00a2b.xml 2025-12-04T09:42:03.3298650Z Running inductor/test_binary_folding 1/1 ... [2025-12-04 09:42:03.329567][1866.015339229] 2025-12-04T09:42:03.3299228Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:03.3302857Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:03.329968] 2025-12-04T09:42:11.3899244Z 2025-12-04T09:42:11.3900468Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_8e9dac93ea5a9db8_.log 2025-12-04T09:42:11.3901453Z Running 0 items in this shard: 2025-12-04T09:42:11.3901689Z 2025-12-04T09:42:11.3902055Z Finished inductor/test_binary_folding 1/1 ... [2025-12-04 09:42:11.389737][1874.075505014], took 0.13min 2025-12-04T09:42:11.3975328Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_binary_folding/inductor.test_binary_folding-2f6b98936661cb31.xml 2025-12-04T09:42:11.4703547Z Running inductor/test_mkldnn_pattern_matcher 1/2 ... [2025-12-04 09:42:11.470051][1874.155822982] 2025-12-04T09:42:11.4704137Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:11.4707264Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_mkldnn_pattern_matcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:11.470429] 2025-12-04T09:42:20.0623541Z 2025-12-04T09:42:20.0624803Z inductor/test_mkldnn_pattern_matcher 1/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_mkldnn_pattern_matcher_1.2_e0478c36e69283c6_.log 2025-12-04T09:42:20.0625846Z Running 0 items in this shard: 2025-12-04T09:42:20.0626043Z 2025-12-04T09:42:20.0626433Z Finished inductor/test_mkldnn_pattern_matcher 1/2 ... [2025-12-04 09:42:20.062200][1882.747967014], took 0.14min 2025-12-04T09:42:20.0700881Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_mkldnn_pattern_matcher/inductor.test_mkldnn_pattern_matcher-5f3d62578cb5fdc6.xml 2025-12-04T09:42:20.1473242Z Running inductor/test_cpu_select_algorithm 1/1 ... [2025-12-04 09:42:20.147016][1882.832787396] 2025-12-04T09:42:20.1473847Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:20.1476995Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:20.147393] 2025-12-04T09:42:28.2012159Z 2025-12-04T09:42:28.2013270Z inductor/test_cpu_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_1.1_445df20038044743_.log 2025-12-04T09:42:28.2014234Z Running 0 items in this shard: 2025-12-04T09:42:28.2014433Z 2025-12-04T09:42:28.2014792Z Finished inductor/test_cpu_select_algorithm 1/1 ... [2025-12-04 09:42:28.201010][1890.8867789], took 0.13min 2025-12-04T09:42:28.2090709Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cpu_select_algorithm/inductor.test_cpu_select_algorithm-c22f6c529f9842ea.xml 2025-12-04T09:42:28.2772051Z Running inductor/test_aot_inductor_arrayref 2/2 ... [2025-12-04 09:42:28.276894][1890.962665271] 2025-12-04T09:42:28.2772652Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:28.2775570Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor_arrayref.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:28.277245] 2025-12-04T09:42:37.0889519Z 2025-12-04T09:42:37.0890630Z inductor/test_aot_inductor_arrayref 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_arrayref_2.2_ba9d2777a725ea2f_.log 2025-12-04T09:42:37.0891638Z Running 0 items in this shard: 2025-12-04T09:42:37.0891850Z 2025-12-04T09:42:37.0892222Z Finished inductor/test_aot_inductor_arrayref 2/2 ... [2025-12-04 09:42:37.088766][1899.774534471], took 0.15min 2025-12-04T09:42:37.0971079Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_aot_inductor_arrayref/inductor.test_aot_inductor_arrayref-b20b28c4e3b26681.xml 2025-12-04T09:42:37.1754718Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-12-04 09:42:37.175114][1899.86088304] 2025-12-04T09:42:37.1755340Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:37.1758686Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:37.175559] 2025-12-04T09:42:45.1115288Z 2025-12-04T09:42:45.1116478Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_f8d0f10bd63cb229_.log 2025-12-04T09:42:45.1117424Z 2025-12-04T09:42:45.1200211Z Finished inductor/test_torchinductor_strided_blocks 1/1 ... [2025-12-04 09:42:45.111332][1907.79710277], took 0.13min 2025-12-04T09:42:45.1200989Z Running test_custom_ops 1/1 ... [2025-12-04 09:42:45.119807][1907.80557972] 2025-12-04T09:42:45.1201441Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:45.1204305Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_custom_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:45.120190] 2025-12-04T09:42:50.0063796Z 2025-12-04T09:42:50.0064648Z test_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_custom_ops_1.1_8853576b9571250c_.log 2025-12-04T09:42:50.0065418Z Running 0 items in this shard: 2025-12-04T09:42:50.0065615Z 2025-12-04T09:42:50.0065883Z Finished test_custom_ops 1/1 ... [2025-12-04 09:42:50.006211][1912.691980605], took 0.08min 2025-12-04T09:42:50.0144196Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_custom_ops/test_custom_ops-2993f82b1e5ff4cc.xml 2025-12-04T09:42:50.0800947Z Running inductor/test_multi_kernel 1/1 ... [2025-12-04 09:42:50.079797][1912.765568] 2025-12-04T09:42:50.0801495Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:50.0805357Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_multi_kernel.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:50.080235] 2025-12-04T09:42:57.8161358Z 2025-12-04T09:42:57.8162348Z inductor/test_multi_kernel 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_multi_kernel_1.1_8292eaf3d0d11e99_.log 2025-12-04T09:42:57.8163155Z 2025-12-04T09:42:57.8163486Z Finished inductor/test_multi_kernel 1/1 ... [2025-12-04 09:42:57.815900][1920.501670157], took 0.13min 2025-12-04T09:42:57.8247126Z Running inductor/test_analysis 1/1 ... [2025-12-04 09:42:57.824509][1920.5102803] 2025-12-04T09:42:57.8247621Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:42:57.8251321Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_analysis.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:42:57.824883] 2025-12-04T09:43:05.5393506Z 2025-12-04T09:43:05.5394535Z inductor/test_analysis 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_analysis_1.1_307a630719f8658f_.log 2025-12-04T09:43:05.5395395Z Running 0 items in this shard: 2025-12-04T09:43:05.5395611Z 2025-12-04T09:43:05.5395934Z Finished inductor/test_analysis 1/1 ... [2025-12-04 09:43:05.539148][1928.224918607], took 0.13min 2025-12-04T09:43:05.5475468Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_analysis/inductor.test_analysis-56b1473efa1a0732.xml 2025-12-04T09:43:05.6230877Z Running inductor/test_triton_extension_backend 1/1 ... [2025-12-04 09:43:05.622783][1928.308553929] 2025-12-04T09:43:05.6231510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:05.6234741Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_triton_extension_backend.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:05.623159] 2025-12-04T09:43:13.5854229Z 2025-12-04T09:43:13.5855987Z inductor/test_triton_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_extension_backend_1.1_2a3455676a2e2d52_.log 2025-12-04T09:43:13.5857893Z Running 0 items in this shard: 2025-12-04T09:43:13.5858298Z 2025-12-04T09:43:13.5859037Z Finished inductor/test_triton_extension_backend 1/1 ... [2025-12-04 09:43:13.585203][1936.270972764], took 0.13min 2025-12-04T09:43:13.5940302Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_triton_extension_backend/inductor.test_triton_extension_backend-9044c0c053a91cbb.xml 2025-12-04T09:43:13.6710096Z Running test_sparse_semi_structured 1/1 ... [2025-12-04 09:43:13.670696][1936.356467703] 2025-12-04T09:43:13.6710978Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:13.6715405Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:13.671131] 2025-12-04T09:43:21.4850590Z 2025-12-04T09:43:21.4851637Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_a50804d6706c3aed_.log 2025-12-04T09:43:21.4852527Z Running 0 items in this shard: 2025-12-04T09:43:21.4852727Z 2025-12-04T09:43:21.4853072Z Finished test_sparse_semi_structured 1/1 ... [2025-12-04 09:43:21.484860][1944.17062738], took 0.13min 2025-12-04T09:43:21.4934947Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_sparse_semi_structured/test_sparse_semi_structured-1097d11c113fbd71.xml 2025-12-04T09:43:21.5669018Z Running inductor/test_op_completeness 1/1 ... [2025-12-04 09:43:21.566589][1944.252360088] 2025-12-04T09:43:21.5669577Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:21.5672910Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_op_completeness.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:21.566961] 2025-12-04T09:43:25.1640196Z 2025-12-04T09:43:25.1641234Z 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_7a3c180ee5c7421f_.log 2025-12-04T09:43:25.1642172Z Running 0 items in this shard: 2025-12-04T09:43:25.1642621Z 2025-12-04T09:43:25.1642966Z Finished inductor/test_op_completeness 1/1 ... [2025-12-04 09:43:25.163823][1947.8495934], took 0.06min 2025-12-04T09:43:25.1725536Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_op_completeness/inductor.test_op_completeness-a0813fa6b23c971e.xml 2025-12-04T09:43:25.1963424Z Running inductor/test_triton_heuristics 1/1 ... [2025-12-04 09:43:25.196083][1947.881855824] 2025-12-04T09:43:25.1963988Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:25.1966814Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_triton_heuristics.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:25.196416] 2025-12-04T09:43:32.9016896Z 2025-12-04T09:43:32.9017935Z inductor/test_triton_heuristics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_heuristics_1.1_732803b60a33a90e_.log 2025-12-04T09:43:32.9018780Z 2025-12-04T09:43:32.9019175Z Finished inductor/test_triton_heuristics 1/1 ... [2025-12-04 09:43:32.901459][1955.587229131], took 0.13min 2025-12-04T09:43:32.9108558Z Running inductor/test_cutedsl_grouped_mm 1/1 ... [2025-12-04 09:43:32.910654][1955.596426625] 2025-12-04T09:43:32.9109107Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:32.9113342Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cutedsl_grouped_mm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:32.911076] 2025-12-04T09:43:36.0706546Z 2025-12-04T09:43:36.0707578Z inductor/test_cutedsl_grouped_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutedsl_grouped_mm_1.1_35fff334acb999d1_.log 2025-12-04T09:43:36.0708536Z Running 0 items in this shard: 2025-12-04T09:43:36.0708749Z 2025-12-04T09:43:36.0709142Z Finished inductor/test_cutedsl_grouped_mm 1/1 ... [2025-12-04 09:43:36.070463][1958.756233217], took 0.05min 2025-12-04T09:43:36.0794248Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cutedsl_grouped_mm/inductor.test_cutedsl_grouped_mm-d451c8bede7ab6c0.xml 2025-12-04T09:43:36.1548823Z Running inductor/test_cpp_wrapper_hipify 1/1 ... [2025-12-04 09:43:36.154643][1958.840414163] 2025-12-04T09:43:36.1549408Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:36.1553304Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cpp_wrapper_hipify.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:36.155041] 2025-12-04T09:43:39.2889353Z 2025-12-04T09:43:39.2890715Z inductor/test_cpp_wrapper_hipify 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpp_wrapper_hipify_1.1_f56faf2dff96c322_.log 2025-12-04T09:43:39.2891702Z Running 0 items in this shard: 2025-12-04T09:43:39.2891900Z 2025-12-04T09:43:39.2892276Z Finished inductor/test_cpp_wrapper_hipify 1/1 ... [2025-12-04 09:43:39.288732][1961.974502268], took 0.05min 2025-12-04T09:43:39.2976840Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cpp_wrapper_hipify/inductor.test_cpp_wrapper_hipify-c4cb02f3ada4f1c3.xml 2025-12-04T09:43:39.3385506Z Running inductor/test_template_heuristics_registry 1/1 ... [2025-12-04 09:43:39.338306][1962.024078127] 2025-12-04T09:43:39.3386140Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:39.3390071Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_template_heuristics_registry.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:39.338725] 2025-12-04T09:43:43.3852058Z 2025-12-04T09:43:43.3853369Z inductor/test_template_heuristics_registry 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_template_heuristics_registry_1.1_fa492e71a116b4ea_.log 2025-12-04T09:43:43.3854428Z Running 0 items in this shard: 2025-12-04T09:43:43.3854656Z 2025-12-04T09:43:43.3855080Z Finished inductor/test_template_heuristics_registry 1/1 ... [2025-12-04 09:43:43.384983][1966.07075339], took 0.07min 2025-12-04T09:43:43.3940880Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_template_heuristics_registry/inductor.test_template_heuristics_registry-2babd3cab23efdc7.xml 2025-12-04T09:43:43.4784996Z Running inductor/test_async_compile 1/1 ... [2025-12-04 09:43:43.478259][1966.16403044] 2025-12-04T09:43:43.4785541Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:43.4789556Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_async_compile.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:43.478671] 2025-12-04T09:43:51.2012532Z 2025-12-04T09:43:51.2013515Z inductor/test_async_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_async_compile_1.1_7c5e574630368a1a_.log 2025-12-04T09:43:51.2014459Z Running 0 items in this shard: 2025-12-04T09:43:51.2014658Z 2025-12-04T09:43:51.2015019Z Finished inductor/test_async_compile 1/1 ... [2025-12-04 09:43:51.200998][1973.886768788], took 0.13min 2025-12-04T09:43:51.2102879Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_async_compile/inductor.test_async_compile-4a22b5128bf68330.xml 2025-12-04T09:43:51.2820662Z Running inductor/test_gpu_cpp_wrapper 1/1 ... [2025-12-04 09:43:51.281781][1973.967551651] 2025-12-04T09:43:51.2821210Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:51.2824785Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_gpu_cpp_wrapper.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:51.282163] 2025-12-04T09:43:59.3699060Z 2025-12-04T09:43:59.3700092Z inductor/test_gpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_gpu_cpp_wrapper_1.1_7a567416daa0c04d_.log 2025-12-04T09:43:59.3700917Z 2025-12-04T09:43:59.3701276Z Finished inductor/test_gpu_cpp_wrapper 1/1 ... [2025-12-04 09:43:59.369679][1982.055448071], took 0.13min 2025-12-04T09:43:59.3796554Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-12-04 09:43:59.379453][1982.065225378] 2025-12-04T09:43:59.3797436Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:43:59.3801016Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:43:59.379836] 2025-12-04T09:44:09.1353470Z 2025-12-04T09:44:09.1354602Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_dd2f8597bfc1870f_.log 2025-12-04T09:44:09.1355643Z Running 0 items in this shard: 2025-12-04T09:44:09.1355844Z 2025-12-04T09:44:09.1356246Z Finished export/test_export_training_ir_to_run_decomp 1/1 ... [2025-12-04 09:44:09.135132][1991.820901683], took 0.16min 2025-12-04T09:44:09.1447343Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_export_training_ir_to_run_decomp/export.test_export_training_ir_to_run_decomp-67b47c75289e2ad4.xml 2025-12-04T09:44:09.2171480Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-12-04 09:44:09.216788][1991.902557948] 2025-12-04T09:44:09.2172030Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:09.2174681Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:09.217174] 2025-12-04T09:44:12.3622513Z 2025-12-04T09:44:12.3623550Z 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_5cb9a9b0a7d045b6_.log 2025-12-04T09:44:12.3624496Z Running 0 items in this shard: 2025-12-04T09:44:12.3624697Z 2025-12-04T09:44:12.3625089Z Finished dynamo/test_deque_reconstruct 1/1 ... [2025-12-04 09:44:12.362000][1995.047771259], took 0.05min 2025-12-04T09:44:12.3714509Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_deque_reconstruct/dynamo.test_deque_reconstruct-6bca7488932a01fc.xml 2025-12-04T09:44:12.3997070Z Running inductor/test_indexing 1/1 ... [2025-12-04 09:44:12.399455][1995.085226419] 2025-12-04T09:44:12.3997671Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:12.4000496Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:12.399787] 2025-12-04T09:44:20.1539787Z 2025-12-04T09:44:20.1540850Z inductor/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_indexing_1.1_60df8f3c6335c83d_.log 2025-12-04T09:44:20.1541852Z Running 0 items in this shard: 2025-12-04T09:44:20.1542052Z 2025-12-04T09:44:20.1542655Z Finished inductor/test_indexing 1/1 ... [2025-12-04 09:44:20.153794][2002.8395636], took 0.13min 2025-12-04T09:44:20.1634145Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_indexing/inductor.test_indexing-93fddd303ed5c06f.xml 2025-12-04T09:44:20.2356822Z Running inductor/test_inductor_annotations 1/1 ... [2025-12-04 09:44:20.235395][2002.921166059] 2025-12-04T09:44:20.2357552Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:20.2361208Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inductor_annotations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:20.235771] 2025-12-04T09:44:28.4012278Z 2025-12-04T09:44:28.4013428Z inductor/test_inductor_annotations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_annotations_1.1_abcd9c750867f8e1_.log 2025-12-04T09:44:28.4014404Z Running 0 items in this shard: 2025-12-04T09:44:28.4014615Z 2025-12-04T09:44:28.4015270Z Finished inductor/test_inductor_annotations 1/1 ... [2025-12-04 09:44:28.400999][2011.08676862], took 0.14min 2025-12-04T09:44:28.4108104Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_inductor_annotations/inductor.test_inductor_annotations-b7d9157facc90c4b.xml 2025-12-04T09:44:28.4860805Z Running inductor/test_compile_worker 1/1 ... [2025-12-04 09:44:28.485701][2011.171470876] 2025-12-04T09:44:28.4861361Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:28.4864659Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compile_worker.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:28.486124] 2025-12-04T09:44:36.3324000Z 2025-12-04T09:44:36.3325090Z inductor/test_compile_worker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_worker_1.1_e1baa8a8bddf6f43_.log 2025-12-04T09:44:36.3326048Z Running 0 items in this shard: 2025-12-04T09:44:36.3326259Z 2025-12-04T09:44:36.3326615Z Finished inductor/test_compile_worker 1/1 ... [2025-12-04 09:44:36.332212][2019.017975139], took 0.13min 2025-12-04T09:44:36.3422683Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_compile_worker/inductor.test_compile_worker-2014c305015c41eb.xml 2025-12-04T09:44:36.4196071Z Running dynamo/test_einops 1/1 ... [2025-12-04 09:44:36.419274][2019.10504404] 2025-12-04T09:44:36.4196589Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:36.4199823Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:36.419684] 2025-12-04T09:44:39.5648148Z 2025-12-04T09:44:39.5649108Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_fba5154a1742b9db_.log 2025-12-04T09:44:39.5649937Z Running 0 items in this shard: 2025-12-04T09:44:39.5650136Z 2025-12-04T09:44:39.5650427Z Finished dynamo/test_einops 1/1 ... [2025-12-04 09:44:39.564643][2022.250412204], took 0.05min 2025-12-04T09:44:39.5746915Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_einops/dynamo.test_einops-55db94cbee29eb79.xml 2025-12-04T09:44:39.6002536Z Running inductor/test_external_callables 1/1 ... [2025-12-04 09:44:39.600009][2022.285780598] 2025-12-04T09:44:39.6003116Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:39.6006630Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_external_callables.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:39.600384] 2025-12-04T09:44:43.0509481Z 2025-12-04T09:44:43.0510695Z 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_3e4b4fadd88876b8_.log 2025-12-04T09:44:43.0511673Z Running 0 items in this shard: 2025-12-04T09:44:43.0511885Z 2025-12-04T09:44:43.0512255Z Finished inductor/test_external_callables 1/1 ... [2025-12-04 09:44:43.050778][2025.7365431], took 0.06min 2025-12-04T09:44:43.0612003Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_external_callables/inductor.test_external_callables-cf7bcf79348c8c73.xml 2025-12-04T09:44:43.0883561Z Running test_testing 1/1 ... [2025-12-04 09:44:43.088140][2025.773911872] 2025-12-04T09:44:43.0884049Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:43.0887758Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_testing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:43.088514] 2025-12-04T09:44:47.8486392Z 2025-12-04T09:44:47.8487253Z test_testing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_testing_1.1_e8cd3070fa1a3f36_.log 2025-12-04T09:44:47.8488006Z Running 0 items in this shard: 2025-12-04T09:44:47.8488207Z 2025-12-04T09:44:47.8488505Z Finished test_testing 1/1 ... [2025-12-04 09:44:47.848372][2030.534142602], took 0.08min 2025-12-04T09:44:47.8588148Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_testing/test_testing-2eb647bfec900b81.xml 2025-12-04T09:44:47.8800503Z Running dynamo/test_fx_passes_pre_grad 1/1 ... [2025-12-04 09:44:47.879794][2030.565565309] 2025-12-04T09:44:47.8801092Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:47.8804294Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_fx_passes_pre_grad.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:47.880149] 2025-12-04T09:44:51.0217201Z 2025-12-04T09:44:51.0218398Z dynamo/test_fx_passes_pre_grad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_passes_pre_grad_1.1_1a906f9051cfb8e8_.log 2025-12-04T09:44:51.0219453Z Running 0 items in this shard: 2025-12-04T09:44:51.0219655Z 2025-12-04T09:44:51.0220111Z Finished dynamo/test_fx_passes_pre_grad 1/1 ... [2025-12-04 09:44:51.021466][2033.707236701], took 0.05min 2025-12-04T09:44:51.0319726Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_fx_passes_pre_grad/dynamo.test_fx_passes_pre_grad-8136b1759d6c6609.xml 2025-12-04T09:44:51.0606933Z Running export/test_strict_export_v2 1/1 ... [2025-12-04 09:44:51.060455][2033.746226401] 2025-12-04T09:44:51.0607514Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:51.0610870Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_strict_export_v2.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:51.060826] 2025-12-04T09:44:59.7292479Z 2025-12-04T09:44:59.7293576Z export/test_strict_export_v2 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_strict_export_v2_1.1_4d05e89643861dd0_.log 2025-12-04T09:44:59.7295268Z Running 0 items in this shard: 2025-12-04T09:44:59.7295528Z 2025-12-04T09:44:59.7295873Z Finished export/test_strict_export_v2 1/1 ... [2025-12-04 09:44:59.729054][2042.414823777], took 0.14min 2025-12-04T09:44:59.7396890Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_strict_export_v2/export.test_strict_export_v2-9dd6afa6d58bbe74.xml 2025-12-04T09:44:59.8128197Z Running inductor/test_flex_flash 1/1 ... [2025-12-04 09:44:59.812516][2042.498287226] 2025-12-04T09:44:59.8128733Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:44:59.8132140Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_flex_flash.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:44:59.812891] 2025-12-04T09:45:04.2845814Z 2025-12-04T09:45:04.2846787Z inductor/test_flex_flash 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_flash_1.1_7f4007b6099efe03_.log 2025-12-04T09:45:04.2847960Z Running 0 items in this shard: 2025-12-04T09:45:04.2848169Z 2025-12-04T09:45:04.2848481Z Finished inductor/test_flex_flash 1/1 ... [2025-12-04 09:45:04.284378][2046.970137313], took 0.07min 2025-12-04T09:45:04.2952880Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_flex_flash/inductor.test_flex_flash-3abfff74391cd700.xml 2025-12-04T09:45:04.3267132Z Running inductor/test_selective_lowering 1/1 ... [2025-12-04 09:45:04.326471][2047.012241884] 2025-12-04T09:45:04.3267704Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:04.3271277Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_selective_lowering.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:04.326853] 2025-12-04T09:45:11.9769872Z 2025-12-04T09:45:11.9770988Z inductor/test_selective_lowering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_selective_lowering_1.1_e256dc3d5a90600e_.log 2025-12-04T09:45:11.9771850Z 2025-12-04T09:45:11.9772217Z Finished inductor/test_selective_lowering 1/1 ... [2025-12-04 09:45:11.976718][2054.662490711], took 0.13min 2025-12-04T09:45:11.9882961Z Running inductor/test_inductor_scheduler 1/1 ... [2025-12-04 09:45:11.988020][2054.673793122] 2025-12-04T09:45:11.9883514Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:11.9886937Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inductor_scheduler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:11.988417] 2025-12-04T09:45:19.7504746Z 2025-12-04T09:45:19.7505976Z inductor/test_inductor_scheduler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_scheduler_1.1_5c6965c1df94805c_.log 2025-12-04T09:45:19.7506983Z Running 0 items in this shard: 2025-12-04T09:45:19.7507182Z 2025-12-04T09:45:19.7507556Z Finished inductor/test_inductor_scheduler 1/1 ... [2025-12-04 09:45:19.750285][2062.436056608], took 0.13min 2025-12-04T09:45:19.7612211Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_inductor_scheduler/inductor.test_inductor_scheduler-3ac7f496104b1030.xml 2025-12-04T09:45:19.8262626Z Running inductor/test_inplace_padding 1/1 ... [2025-12-04 09:45:19.825889][2062.511660589] 2025-12-04T09:45:19.8263330Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:19.8265165Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inplace_padding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:19.826230] 2025-12-04T09:45:27.7630165Z 2025-12-04T09:45:27.7631383Z 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_05a8150b0f66219f_.log 2025-12-04T09:45:27.7632212Z 2025-12-04T09:45:27.7632574Z Finished inductor/test_inplace_padding 1/1 ... [2025-12-04 09:45:27.762763][2070.448524774], took 0.13min 2025-12-04T09:45:27.7743131Z Running inductor/test_control_deps 1/1 ... [2025-12-04 09:45:27.774089][2070.459861081] 2025-12-04T09:45:27.7743921Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:27.7747562Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_control_deps.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:27.774488] 2025-12-04T09:45:35.4225842Z 2025-12-04T09:45:35.4226923Z inductor/test_control_deps 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_control_deps_1.1_88aac37330fc8047_.log 2025-12-04T09:45:35.4228039Z 2025-12-04T09:45:35.4228608Z Finished inductor/test_control_deps 1/1 ... [2025-12-04 09:45:35.422285][2078.108055963], took 0.13min 2025-12-04T09:45:35.4337720Z Running inductor/test_inplacing_pass 1/1 ... [2025-12-04 09:45:35.433543][2078.119314942] 2025-12-04T09:45:35.4338260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:35.4341622Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:35.433909] 2025-12-04T09:45:43.0999574Z 2025-12-04T09:45:43.1000656Z 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_1c2adc7a68b5f32f_.log 2025-12-04T09:45:43.1001475Z 2025-12-04T09:45:43.1001815Z Finished inductor/test_inplacing_pass 1/1 ... [2025-12-04 09:45:43.099719][2085.785489674], took 0.13min 2025-12-04T09:45:43.3455475Z Uploading artifacts took 0.23 seconds 2025-12-04T09:45:43.3459433Z Running inductor/test_profiler 1/1 ... [2025-12-04 09:45:43.345748][2086.031517944] 2025-12-04T09:45:43.3460129Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:43.3464494Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:43.346146] 2025-12-04T09:45:51.0253574Z 2025-12-04T09:45:51.0255089Z inductor/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_profiler_1.1_65732181c0c8f5a1_.log 2025-12-04T09:45:51.0256598Z 2025-12-04T09:45:51.0257185Z Finished inductor/test_profiler 1/1 ... [2025-12-04 09:45:51.025068][2093.710838573], took 0.13min 2025-12-04T09:45:51.0370540Z Running inductor/test_aot_inductor_utils 1/1 ... [2025-12-04 09:45:51.036779][2093.722551162] 2025-12-04T09:45:51.0371465Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:51.0376268Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:51.037238] 2025-12-04T09:45:58.8281592Z 2025-12-04T09:45:58.8282659Z inductor/test_aot_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_utils_1.1_bf89e0194515a1a8_.log 2025-12-04T09:45:58.8283628Z Running 0 items in this shard: 2025-12-04T09:45:58.8283841Z 2025-12-04T09:45:58.8284204Z Finished inductor/test_aot_inductor_utils 1/1 ... [2025-12-04 09:45:58.827937][2101.513705666], took 0.13min 2025-12-04T09:45:58.8391573Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_aot_inductor_utils/inductor.test_aot_inductor_utils-902a5fff04d1d335.xml 2025-12-04T09:45:58.9113036Z Running dynamo/test_cudagraphs 1/1 ... [2025-12-04 09:45:58.911036][2101.596807952] 2025-12-04T09:45:58.9113839Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:45:58.9117137Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:45:58.911406] 2025-12-04T09:46:02.1796298Z 2025-12-04T09:46:02.1797655Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_2c111bf096348e3b_.log 2025-12-04T09:46:02.1798425Z 2025-12-04T09:46:02.1798738Z Finished dynamo/test_cudagraphs 1/1 ... [2025-12-04 09:46:02.179341][2104.86511085], took 0.05min 2025-12-04T09:46:02.1910817Z Running inductor/test_custom_partitioner_fn 1/1 ... [2025-12-04 09:46:02.190852][2104.876623845] 2025-12-04T09:46:02.1911484Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:02.1915189Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_custom_partitioner_fn.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:02.191220] 2025-12-04T09:46:09.8666716Z 2025-12-04T09:46:09.8668095Z inductor/test_custom_partitioner_fn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_custom_partitioner_fn_1.1_f86cd955c06428ff_.log 2025-12-04T09:46:09.8668965Z 2025-12-04T09:46:09.8669355Z Finished inductor/test_custom_partitioner_fn 1/1 ... [2025-12-04 09:46:09.866413][2112.552181953], took 0.13min 2025-12-04T09:46:09.8782429Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-12-04 09:46:09.878004][2112.563777444] 2025-12-04T09:46:09.8783150Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:09.8786885Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:09.878397] 2025-12-04T09:46:13.5089411Z 2025-12-04T09:46:13.5091194Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_8a8cfe5967c096a8_.log 2025-12-04T09:46:13.5093060Z 2025-12-04T09:46:13.5093849Z Finished dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-12-04 09:46:13.508702][2116.194470578], took 0.06min 2025-12-04T09:46:13.5207774Z Running dynamo/test_minifier 1/1 ... [2025-12-04 09:46:13.520513][2116.206284666] 2025-12-04T09:46:13.5208620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:13.5213430Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_minifier.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:13.520970] 2025-12-04T09:46:16.9958543Z 2025-12-04T09:46:16.9960160Z dynamo/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_minifier_1.1_066853a2d1e59a19_.log 2025-12-04T09:46:16.9961783Z Running 0 items in this shard: 2025-12-04T09:46:16.9962157Z 2025-12-04T09:46:16.9962720Z Finished dynamo/test_minifier 1/1 ... [2025-12-04 09:46:16.995658][2119.681428564], took 0.06min 2025-12-04T09:46:17.0073611Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_minifier/dynamo.test_minifier-c12967bb8480eada.xml 2025-12-04T09:46:17.0858034Z Running export/test_sparse 2/2 ... [2025-12-04 09:46:17.085474][2119.771244127] 2025-12-04T09:46:17.0858858Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:17.0863367Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_sparse.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:17.085908] 2025-12-04T09:46:20.6432412Z 2025-12-04T09:46:20.6433339Z export/test_sparse 2/2 was successful, full logs can be found in artifacts with path test/test-reports/export.test_sparse_2.2_cfc7a54b5b2d025e_.log 2025-12-04T09:46:20.6434172Z Running 0 items in this shard: 2025-12-04T09:46:20.6434370Z 2025-12-04T09:46:20.6434687Z Finished export/test_sparse 2/2 ... [2025-12-04 09:46:20.643031][2123.32880185], took 0.06min 2025-12-04T09:46:20.6544215Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_sparse/export.test_sparse-ec3a9645e6b126f5.xml 2025-12-04T09:46:20.6818687Z Running test_foreach 1/1 ... [2025-12-04 09:46:20.681665][2123.36743702] 2025-12-04T09:46:20.6819159Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:20.6822953Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_foreach.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:20.682038] 2025-12-04T09:46:29.6374784Z 2025-12-04T09:46:29.6375839Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_fdce86026fadd4d3_.log 2025-12-04T09:46:29.6376594Z Running 0 items in this shard: 2025-12-04T09:46:29.6376809Z 2025-12-04T09:46:29.6377066Z Finished test_foreach 1/1 ... [2025-12-04 09:46:29.637256][2132.323025153], took 0.15min 2025-12-04T09:46:29.6487987Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_foreach/test_foreach-c371b894d86d2228.xml 2025-12-04T09:46:29.7217963Z Running xpu/test_gemm 1/1 ... [2025-12-04 09:46:29.721516][2132.407286473] 2025-12-04T09:46:29.7218422Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:29.7222487Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'xpu/test_gemm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:29.721938] 2025-12-04T09:46:33.5910799Z 2025-12-04T09:46:33.5911622Z xpu/test_gemm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_gemm_1.1_83b6b350a03063f3_.log 2025-12-04T09:46:33.5912383Z Running 0 items in this shard: 2025-12-04T09:46:33.5912583Z 2025-12-04T09:46:33.5912846Z Finished xpu/test_gemm 1/1 ... [2025-12-04 09:46:33.590875][2136.27664469], took 0.06min 2025-12-04T09:46:33.6025520Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/xpu.test_gemm/xpu.test_gemm-6326b961976d1134.xml 2025-12-04T09:46:33.6259511Z Running xpu/test_conv 1/1 ... [2025-12-04 09:46:33.625702][2136.31147368] 2025-12-04T09:46:33.6260291Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:33.6264785Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:33.626114] 2025-12-04T09:46:37.4387752Z 2025-12-04T09:46:37.4388572Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_03ea17dc74954228_.log 2025-12-04T09:46:37.4389338Z Running 0 items in this shard: 2025-12-04T09:46:37.4389541Z 2025-12-04T09:46:37.4389806Z Finished xpu/test_conv 1/1 ... [2025-12-04 09:46:37.438538][2140.124308441], took 0.06min 2025-12-04T09:46:37.4504265Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/xpu.test_conv/xpu.test_conv-3ad9537be4d7ab7d.xml 2025-12-04T09:46:37.4811129Z Running test_numpy_interop 1/1 ... [2025-12-04 09:46:37.480856][2140.16662757] 2025-12-04T09:46:37.4811644Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:37.4815109Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numpy_interop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:37.481247] 2025-12-04T09:46:40.9441314Z 2025-12-04T09:46:40.9442412Z test_numpy_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numpy_interop_1.1_69aa0a34443f370d_.log 2025-12-04T09:46:40.9443281Z Running 0 items in this shard: 2025-12-04T09:46:40.9443483Z 2025-12-04T09:46:40.9443802Z Finished test_numpy_interop 1/1 ... [2025-12-04 09:46:40.943898][2143.629668469], took 0.06min 2025-12-04T09:46:40.9559569Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numpy_interop/test_numpy_interop-c12169dbf55e5a56.xml 2025-12-04T09:46:40.9826931Z Running test_modules 1/1 ... [2025-12-04 09:46:40.982380][2143.668152454] 2025-12-04T09:46:40.9827458Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:40.9829911Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:40.982727] 2025-12-04T09:46:45.5521134Z 2025-12-04T09:46:45.5522012Z test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.1_860d0dedaa327a93_.log 2025-12-04T09:46:45.5522807Z Running 0 items in this shard: 2025-12-04T09:46:45.5523013Z 2025-12-04T09:46:45.5523299Z Finished test_modules 1/1 ... [2025-12-04 09:46:45.551848][2148.237618632], took 0.08min 2025-12-04T09:46:45.5638472Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_modules/test_modules-373404440df7c36a.xml 2025-12-04T09:46:45.5929371Z Running nn/test_packed_sequence 1/1 ... [2025-12-04 09:46:45.592722][2148.278493763] 2025-12-04T09:46:45.5929892Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:45.5933114Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:45.593050] 2025-12-04T09:46:48.7776569Z 2025-12-04T09:46:48.7786784Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_ed126ee70db1881d_.log 2025-12-04T09:46:48.7787827Z Running 0 items in this shard: 2025-12-04T09:46:48.7788044Z 2025-12-04T09:46:48.7788359Z Finished nn/test_packed_sequence 1/1 ... [2025-12-04 09:46:48.777480][2151.463249307], took 0.05min 2025-12-04T09:46:48.7896693Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_packed_sequence/nn.test_packed_sequence-37ec7141b8423303.xml 2025-12-04T09:46:48.8159071Z Running test_numa_binding 1/1 ... [2025-12-04 09:46:48.815697][2151.501469092] 2025-12-04T09:46:48.8159549Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:48.8163390Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numa_binding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:48.816063] 2025-12-04T09:46:52.0286710Z 2025-12-04T09:46:52.0287633Z test_numa_binding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numa_binding_1.1_650c91343815da18_.log 2025-12-04T09:46:52.0288420Z Running 0 items in this shard: 2025-12-04T09:46:52.0288634Z 2025-12-04T09:46:52.0288928Z Finished test_numa_binding 1/1 ... [2025-12-04 09:46:52.028443][2154.71421252], took 0.05min 2025-12-04T09:46:52.0407884Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numa_binding/test_numa_binding-536a7952028c010a.xml 2025-12-04T09:46:52.0660849Z Running test_pruning_op 1/1 ... [2025-12-04 09:46:52.065825][2154.751595805] 2025-12-04T09:46:52.0663816Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:52.0665168Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_pruning_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:52.066196] 2025-12-04T09:46:55.2694357Z 2025-12-04T09:46:55.2695257Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_6be6c9c5eb681953_.log 2025-12-04T09:46:55.2696040Z Running 0 items in this shard: 2025-12-04T09:46:55.2696273Z 2025-12-04T09:46:55.2696564Z Finished test_pruning_op 1/1 ... [2025-12-04 09:46:55.269247][2157.955016114], took 0.05min 2025-12-04T09:46:55.2816425Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_pruning_op/test_pruning_op-39e74698fd58a177.xml 2025-12-04T09:46:55.3074518Z Running test_jit_fuser_te 1/1 ... [2025-12-04 09:46:55.307197][2157.992968388] 2025-12-04T09:46:55.3075000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:46:55.3078004Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit_fuser_te.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:46:55.307537] 2025-12-04T09:47:01.1499742Z 2025-12-04T09:47:01.1500653Z test_jit_fuser_te 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_fuser_te_1.1_5f3360505fd05068_.log 2025-12-04T09:47:01.1501474Z Running 0 items in this shard: 2025-12-04T09:47:01.1501684Z 2025-12-04T09:47:01.1501956Z Finished test_jit_fuser_te 1/1 ... [2025-12-04 09:47:01.149777][2163.835547081], took 0.10min 2025-12-04T09:47:01.1624601Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit_fuser_te/test_jit_fuser_te-ff79f6a66f523d2e.xml 2025-12-04T09:47:01.1876805Z Running test_logging 1/1 ... [2025-12-04 09:47:01.187429][2163.873198942] 2025-12-04T09:47:01.1877288Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:01.1880713Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:01.187803] 2025-12-04T09:47:04.3516259Z 2025-12-04T09:47:04.3517119Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_f6d00a31f7942cb1_.log 2025-12-04T09:47:04.3517912Z Running 0 items in this shard: 2025-12-04T09:47:04.3518116Z 2025-12-04T09:47:04.3518385Z Finished test_logging 1/1 ... [2025-12-04 09:47:04.351380][2167.037150262], took 0.05min 2025-12-04T09:47:04.3639831Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_logging/test_logging-dd2f4e423ecf29bf.xml 2025-12-04T09:47:04.3901497Z Running nn/test_lazy_modules 1/1 ... [2025-12-04 09:47:04.389879][2167.075649989] 2025-12-04T09:47:04.3902287Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:04.3904830Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:04.390223] 2025-12-04T09:47:07.9808199Z 2025-12-04T09:47:07.9809280Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_104a17233fa6f358_.log 2025-12-04T09:47:07.9810119Z Running 0 items in this shard: 2025-12-04T09:47:07.9810318Z 2025-12-04T09:47:07.9810609Z Finished nn/test_lazy_modules 1/1 ... [2025-12-04 09:47:07.980638][2170.666409344], took 0.06min 2025-12-04T09:47:07.9934405Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_lazy_modules/nn.test_lazy_modules-7342adb811c18c06.xml 2025-12-04T09:47:08.0228746Z Running nn/test_pruning 1/1 ... [2025-12-04 09:47:08.022638][2170.70840878] 2025-12-04T09:47:08.0229236Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:08.0232728Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_pruning.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:08.023015] 2025-12-04T09:47:11.5813583Z 2025-12-04T09:47:11.5814457Z nn/test_pruning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pruning_1.1_315773ed86aa5c0a_.log 2025-12-04T09:47:11.5815244Z Running 0 items in this shard: 2025-12-04T09:47:11.5815444Z 2025-12-04T09:47:11.5815736Z Finished nn/test_pruning 1/1 ... [2025-12-04 09:47:11.581186][2174.26695616], took 0.06min 2025-12-04T09:47:11.5941490Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_pruning/nn.test_pruning-931e91cde801d270.xml 2025-12-04T09:47:11.6225160Z Running test_monitor 1/1 ... [2025-12-04 09:47:11.622280][2174.308050704] 2025-12-04T09:47:11.6225646Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:11.6229016Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_monitor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:11.622631] 2025-12-04T09:47:14.8052509Z 2025-12-04T09:47:14.8053402Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_01fbcb0c5e8f5478_.log 2025-12-04T09:47:14.8054159Z Running 0 items in this shard: 2025-12-04T09:47:14.8054357Z 2025-12-04T09:47:14.8054623Z Finished test_monitor 1/1 ... [2025-12-04 09:47:14.805052][2177.490823376], took 0.05min 2025-12-04T09:47:14.8180270Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_monitor/test_monitor-43898240e85e4f74.xml 2025-12-04T09:47:14.8478694Z Running test_bundled_inputs 1/1 ... [2025-12-04 09:47:14.847639][2177.533411186] 2025-12-04T09:47:14.8479217Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:14.8482206Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_bundled_inputs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:14.847978] 2025-12-04T09:47:18.0383172Z 2025-12-04T09:47:18.0384099Z test_bundled_inputs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_bundled_inputs_1.1_1cee1a7c0e1873f8_.log 2025-12-04T09:47:18.0384907Z Running 0 items in this shard: 2025-12-04T09:47:18.0385124Z 2025-12-04T09:47:18.0385700Z Finished test_bundled_inputs 1/1 ... [2025-12-04 09:47:18.038087][2180.723856422], took 0.05min 2025-12-04T09:47:18.0511832Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_bundled_inputs/test_bundled_inputs-a8e44993c222d0e8.xml 2025-12-04T09:47:18.0771524Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-12-04 09:47:18.076894][2180.762665654] 2025-12-04T09:47:18.0772316Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:18.0775693Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:18.077260] 2025-12-04T09:47:21.8410242Z 2025-12-04T09:47:21.8411392Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_b2fe9cb3470f9c77_.log 2025-12-04T09:47:21.8412402Z Running 0 items in this shard: 2025-12-04T09:47:21.8412615Z 2025-12-04T09:47:21.8413013Z Finished torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-12-04 09:47:21.840830][2184.526598799], took 0.06min 2025-12-04T09:47:21.8542909Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_numeric/torch_np.numpy_tests.core.test_numeric-d6b069297a057360.xml 2025-12-04T09:47:21.8819370Z Running torch_np/numpy_tests/core/test_multiarray 1/1 ... [2025-12-04 09:47:21.881647][2184.567419156] 2025-12-04T09:47:21.8819982Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:21.8822875Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_multiarray.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:21.882001] 2025-12-04T09:47:26.9153400Z 2025-12-04T09:47:26.9154510Z torch_np/numpy_tests/core/test_multiarray 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_multiarray_1.1_7003feca1dbb4450_.log 2025-12-04T09:47:26.9155551Z Running 0 items in this shard: 2025-12-04T09:47:26.9155774Z 2025-12-04T09:47:26.9156184Z Finished torch_np/numpy_tests/core/test_multiarray 1/1 ... [2025-12-04 09:47:26.915121][2189.600891684], took 0.08min 2025-12-04T09:47:26.9287859Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_multiarray/torch_np.numpy_tests.core.test_multiarray-97b90505824843ab.xml 2025-12-04T09:47:26.9516839Z Running test_itt 1/1 ... [2025-12-04 09:47:26.951424][2189.637196673] 2025-12-04T09:47:26.9517331Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:26.9520544Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_itt.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:26.951798] 2025-12-04T09:47:30.1191806Z 2025-12-04T09:47:30.1192652Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_89bce7f3966bdbde_.log 2025-12-04T09:47:30.1193415Z Running 0 items in this shard: 2025-12-04T09:47:30.1193617Z 2025-12-04T09:47:30.1193852Z Finished test_itt 1/1 ... [2025-12-04 09:47:30.118996][2192.804766223], took 0.05min 2025-12-04T09:47:30.1326287Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_itt/test_itt-937e9ff9c60e0c75.xml 2025-12-04T09:47:30.1584010Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-12-04 09:47:30.158158][2192.843929328] 2025-12-04T09:47:30.1584616Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:30.1588639Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:30.158529] 2025-12-04T09:47:34.4410950Z 2025-12-04T09:47:34.4412391Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_14599e8b242562a0_.log 2025-12-04T09:47:34.4413434Z Running 0 items in this shard: 2025-12-04T09:47:34.4413645Z 2025-12-04T09:47:34.4414062Z Finished torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-12-04 09:47:34.440927][2197.126695816], took 0.07min 2025-12-04T09:47:34.4547992Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_function_base/torch_np.numpy_tests.lib.test_function_base-db17e91824aca9c1.xml 2025-12-04T09:47:34.4830729Z Running test_sympy_utils 1/1 ... [2025-12-04 09:47:34.482770][2197.168542238] 2025-12-04T09:47:34.4831429Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:34.4834098Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:34.483114] 2025-12-04T09:47:38.3415052Z 2025-12-04T09:47:38.3416237Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_698985b960294b66_.log 2025-12-04T09:47:38.3417028Z Running 0 items in this shard: 2025-12-04T09:47:38.3417227Z 2025-12-04T09:47:38.3417551Z Finished test_sympy_utils 1/1 ... [2025-12-04 09:47:38.341305][2201.027075703], took 0.06min 2025-12-04T09:47:38.3553322Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_sympy_utils/test_sympy_utils-6f9529e24f4b2de2.xml 2025-12-04T09:47:38.3813190Z Running test_subclass 1/1 ... [2025-12-04 09:47:38.380954][2201.066725237] 2025-12-04T09:47:38.3813965Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:38.3815920Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_subclass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:38.381294] 2025-12-04T09:47:41.8188180Z 2025-12-04T09:47:41.8189344Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_c27aa57724d036f8_.log 2025-12-04T09:47:41.8190111Z Running 0 items in this shard: 2025-12-04T09:47:41.8190311Z 2025-12-04T09:47:41.8190627Z Finished test_subclass 1/1 ... [2025-12-04 09:47:41.818635][2204.504405932], took 0.06min 2025-12-04T09:47:41.8326922Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_subclass/test_subclass-98e305853a79bb9b.xml 2025-12-04T09:47:41.8599945Z Running test_import_stats 1/1 ... [2025-12-04 09:47:41.859743][2204.545514626] 2025-12-04T09:47:41.8600756Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:41.8603962Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_import_stats.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:41.860076] 2025-12-04T09:47:45.0311101Z 2025-12-04T09:47:45.0312326Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_f3646b1eb33f69a4_.log 2025-12-04T09:47:45.0313397Z Running 0 items in this shard: 2025-12-04T09:47:45.0313601Z 2025-12-04T09:47:45.0314041Z Finished test_import_stats 1/1 ... [2025-12-04 09:47:45.030912][2207.716682746], took 0.05min 2025-12-04T09:47:45.0452363Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_import_stats/test_import_stats-50ff956dbbdb6262.xml 2025-12-04T09:47:45.0725573Z Running functorch/test_vmap_registrations 1/1 ... [2025-12-04 09:47:45.072314][2207.758084776] 2025-12-04T09:47:45.0726253Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:45.0729611Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:45.072667] 2025-12-04T09:47:51.5587386Z 2025-12-04T09:47:51.5588739Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_124f7ff379d552fa_.log 2025-12-04T09:47:51.5589709Z Running 0 items in this shard: 2025-12-04T09:47:51.5589906Z 2025-12-04T09:47:51.5590289Z Finished functorch/test_vmap_registrations 1/1 ... [2025-12-04 09:47:51.558574][2214.244344934], took 0.11min 2025-12-04T09:47:51.5729813Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.test_vmap_registrations/functorch.test_vmap_registrations-9464f58797692f1f.xml 2025-12-04T09:47:51.6637654Z Running nn/test_parametrization 1/1 ... [2025-12-04 09:47:51.663465][2214.349236532] 2025-12-04T09:47:51.6638334Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:51.6641439Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_parametrization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:51.663820] 2025-12-04T09:47:55.2648330Z 2025-12-04T09:47:55.2652663Z nn/test_parametrization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_parametrization_1.1_f47db94c043dec7e_.log 2025-12-04T09:47:55.2653559Z Running 0 items in this shard: 2025-12-04T09:47:55.2653774Z 2025-12-04T09:47:55.2654095Z Finished nn/test_parametrization 1/1 ... [2025-12-04 09:47:55.264643][2217.950412344], took 0.06min 2025-12-04T09:47:55.2791482Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_parametrization/nn.test_parametrization-9f0ed6f18575c074.xml 2025-12-04T09:47:55.3050985Z Running test_mkldnn_fusion 1/1 ... [2025-12-04 09:47:55.304863][2217.990634861] 2025-12-04T09:47:55.3051659Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:55.3055125Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:55.305210] 2025-12-04T09:47:58.5237809Z 2025-12-04T09:47:58.5239021Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_83b78fd025da3f86_.log 2025-12-04T09:47:58.5239877Z Running 0 items in this shard: 2025-12-04T09:47:58.5240077Z 2025-12-04T09:47:58.5240373Z Finished test_mkldnn_fusion 1/1 ... [2025-12-04 09:47:58.523633][2221.209403759], took 0.05min 2025-12-04T09:47:58.5384134Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_mkldnn_fusion/test_mkldnn_fusion-e97a00128efc9dab.xml 2025-12-04T09:47:58.5634942Z Running lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:47:58.563261][2221.249032876] 2025-12-04T09:47:58.5635799Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:47:58.5639175Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:47:58.563621] 2025-12-04T09:48:03.1542499Z 2025-12-04T09:48:03.1543702Z 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_ab7fdad8bb9aa6ab_.log 2025-12-04T09:48:03.1544527Z Running 0 items in this shard: 2025-12-04T09:48:03.1544725Z 2025-12-04T09:48:03.1545016Z Finished lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:48:03.154044][2225.839813296], took 0.08min 2025-12-04T09:48:03.1585765Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-2a3f8b325a57aa57.xml 2025-12-04T09:48:03.1972865Z Running test_dynamic_shapes 1/1 ... [2025-12-04 09:48:03.197029][2225.882800606] 2025-12-04T09:48:03.1973504Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:03.1977035Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:03.197397] 2025-12-04T09:48:07.4233269Z 2025-12-04T09:48:07.4234492Z test_dynamic_shapes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dynamic_shapes_1.1_8318742e2bfbc22f_.log 2025-12-04T09:48:07.4235318Z Running 0 items in this shard: 2025-12-04T09:48:07.4235514Z 2025-12-04T09:48:07.4235814Z Finished test_dynamic_shapes 1/1 ... [2025-12-04 09:48:07.423155][2230.10892386], took 0.07min 2025-12-04T09:48:07.4381746Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_dynamic_shapes/test_dynamic_shapes-044d0760642ccb69.xml 2025-12-04T09:48:07.4614543Z Running complex_tensor/test_complex_tensor 1/1 ... [2025-12-04 09:48:07.461225][2230.146997385] 2025-12-04T09:48:07.4615203Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:07.4618742Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'complex_tensor/test_complex_tensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:07.461565] 2025-12-04T09:48:12.2293970Z 2025-12-04T09:48:12.2295313Z complex_tensor/test_complex_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/complex_tensor.test_complex_tensor_1.1_e05fcd1d37688f58_.log 2025-12-04T09:48:12.2296938Z Running 0 items in this shard: 2025-12-04T09:48:12.2297138Z 2025-12-04T09:48:12.2297541Z Finished complex_tensor/test_complex_tensor 1/1 ... [2025-12-04 09:48:12.229226][2234.914993304], took 0.08min 2025-12-04T09:48:12.2447418Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/complex_tensor.test_complex_tensor/complex_tensor.test_complex_tensor-f8157b7ec3ad54ba.xml 2025-12-04T09:48:12.2754072Z Running cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-12-04 09:48:12.275069][2234.960837524] 2025-12-04T09:48:12.2754842Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:12.2757639Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:12.275489] 2025-12-04T09:48:15.7941476Z 2025-12-04T09:48:15.7943552Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.python_agnostic_extension.test.test_python_agnostic_1.1_a63b434a4877f3ba_.log 2025-12-04T09:48:15.7944902Z Running 0 items in this shard: 2025-12-04T09:48:15.7945101Z 2025-12-04T09:48:15.7945648Z Finished cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-12-04 09:48:15.793990][2238.479757036], took 0.06min 2025-12-04T09:48:15.8096234Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/cpp_extensions.python_agnostic_extension.test.test_python_agnostic/cpp_extensions.python_agnostic_extension.test.test_python_agnostic-2b140243fbf49f96.xml 2025-12-04T09:48:15.8352577Z Running torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-12-04 09:48:15.835012][2238.52078327] 2025-12-04T09:48:15.8353180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:15.8356293Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_histograms.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:15.835348] 2025-12-04T09:48:19.1031943Z 2025-12-04T09:48:19.1033516Z torch_np/numpy_tests/lib/test_histograms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_histograms_1.1_e560d89eb2afeeea_.log 2025-12-04T09:48:19.1034552Z Running 0 items in this shard: 2025-12-04T09:48:19.1034753Z 2025-12-04T09:48:19.1035168Z Finished torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-12-04 09:48:19.103022][2241.788791627], took 0.05min 2025-12-04T09:48:19.1185077Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_histograms/torch_np.numpy_tests.lib.test_histograms-b120244cfcbb8271.xml 2025-12-04T09:48:19.1524904Z Running torch_np/test_indexing 1/1 ... [2025-12-04 09:48:19.152213][2241.837983991] 2025-12-04T09:48:19.1525436Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:19.1528901Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:19.152577] 2025-12-04T09:48:22.4245351Z 2025-12-04T09:48:22.4246315Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_677455f490517b97_.log 2025-12-04T09:48:22.4247174Z Running 0 items in this shard: 2025-12-04T09:48:22.4247369Z 2025-12-04T09:48:22.4247689Z Finished torch_np/test_indexing 1/1 ... [2025-12-04 09:48:22.424340][2245.110110107], took 0.05min 2025-12-04T09:48:22.4397885Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.test_indexing/torch_np.test_indexing-0415fb0b7bac72f9.xml 2025-12-04T09:48:22.4666548Z Running test_schema_check 1/1 ... [2025-12-04 09:48:22.466412][2245.152184087] 2025-12-04T09:48:22.4667043Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:22.4670490Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_schema_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:22.466771] 2025-12-04T09:48:27.1009999Z 2025-12-04T09:48:27.1011056Z test_schema_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_schema_check_1.1_ae81ca93a3708d76_.log 2025-12-04T09:48:27.1011856Z Running 0 items in this shard: 2025-12-04T09:48:27.1012059Z 2025-12-04T09:48:27.1012615Z Finished test_schema_check 1/1 ... [2025-12-04 09:48:27.100826][2249.786596898], took 0.08min 2025-12-04T09:48:27.1165565Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_schema_check/test_schema_check-185bfcbab1a5b045.xml 2025-12-04T09:48:27.1431193Z Running test_tensorboard 1/1 ... [2025-12-04 09:48:27.142811][2249.8285825] 2025-12-04T09:48:27.1431887Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:27.1434661Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_tensorboard.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:27.143169] 2025-12-04T09:48:30.7744430Z 2025-12-04T09:48:30.7745324Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_6c95ec853dfbd34c_.log 2025-12-04T09:48:30.7746165Z Running 0 items in this shard: 2025-12-04T09:48:30.7746366Z 2025-12-04T09:48:30.7746674Z Finished test_tensorboard 1/1 ... [2025-12-04 09:48:30.774255][2253.460023919], took 0.06min 2025-12-04T09:48:30.7903185Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_tensorboard/test_tensorboard-b30878f883d1dd8d.xml 2025-12-04T09:48:30.8157426Z Running torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-12-04 09:48:30.815504][2253.501275919] 2025-12-04T09:48:30.8158015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:30.8161475Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:30.815859] 2025-12-04T09:48:34.1125968Z 2025-12-04T09:48:34.1127116Z torch_np/numpy_tests/core/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_indexing_1.1_a84a881e7e23e941_.log 2025-12-04T09:48:34.1128140Z Running 0 items in this shard: 2025-12-04T09:48:34.1128340Z 2025-12-04T09:48:34.1128731Z Finished torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-12-04 09:48:34.112421][2256.798190536], took 0.05min 2025-12-04T09:48:34.1286234Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_indexing/torch_np.numpy_tests.core.test_indexing-89ff30a784c6ce06.xml 2025-12-04T09:48:34.1588765Z Running test_futures 1/1 ... [2025-12-04 09:48:34.158675][2256.844446844] 2025-12-04T09:48:34.1589234Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:34.1593178Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_futures.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:34.159055] 2025-12-04T09:48:37.3613740Z 2025-12-04T09:48:37.3614908Z test_futures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_futures_1.1_e54de07718cf9ca9_.log 2025-12-04T09:48:37.3615666Z Running 0 items in this shard: 2025-12-04T09:48:37.3615892Z 2025-12-04T09:48:37.3616166Z Finished test_futures 1/1 ... [2025-12-04 09:48:37.361197][2260.046966308], took 0.05min 2025-12-04T09:48:37.3776632Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_futures/test_futures-4f13964f7ebc44a1.xml 2025-12-04T09:48:37.4057920Z Running nn/test_dropout 1/1 ... [2025-12-04 09:48:37.405482][2260.091252619] 2025-12-04T09:48:37.4058682Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:37.4062179Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:37.405854] 2025-12-04T09:48:40.9055147Z 2025-12-04T09:48:40.9056334Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_0a56a29a0d7e1097_.log 2025-12-04T09:48:40.9057471Z Running 0 items in this shard: 2025-12-04T09:48:40.9057679Z 2025-12-04T09:48:40.9057960Z Finished nn/test_dropout 1/1 ... [2025-12-04 09:48:40.905268][2263.59103817], took 0.06min 2025-12-04T09:48:40.9217087Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_dropout/nn.test_dropout-860ce071afe0a033.xml 2025-12-04T09:48:40.9504959Z Running functorch/dim/test_split 1/1 ... [2025-12-04 09:48:40.950256][2263.636027585] 2025-12-04T09:48:40.9505616Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:40.9509339Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/dim/test_split.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:40.950632] 2025-12-04T09:48:44.1665643Z 2025-12-04T09:48:44.1666961Z functorch/dim/test_split 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.dim.test_split_1.1_43aeaac4f82b3b82_.log 2025-12-04T09:48:44.1667882Z Running 0 items in this shard: 2025-12-04T09:48:44.1668082Z 2025-12-04T09:48:44.1668416Z Finished functorch/dim/test_split 1/1 ... [2025-12-04 09:48:44.166367][2266.852136216], took 0.05min 2025-12-04T09:48:44.1829135Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.dim.test_split/functorch.dim.test_split-c6d4cf64608909ce.xml 2025-12-04T09:48:44.2111147Z Running torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-12-04 09:48:44.210731][2266.896500691] 2025-12-04T09:48:44.2111865Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:44.2114186Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_type_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:44.211123] 2025-12-04T09:48:47.4712133Z 2025-12-04T09:48:47.4713545Z torch_np/numpy_tests/lib/test_type_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_type_check_1.1_818b05b483c75bf7_.log 2025-12-04T09:48:47.4714559Z Running 0 items in this shard: 2025-12-04T09:48:47.4714758Z 2025-12-04T09:48:47.4715149Z Finished torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-12-04 09:48:47.471035][2270.156804655], took 0.05min 2025-12-04T09:48:47.4878724Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_type_check/torch_np.numpy_tests.lib.test_type_check-f619af4d367b2319.xml 2025-12-04T09:48:47.5180224Z Running test_jit 1/1 ... [2025-12-04 09:48:47.517703][2270.203474851] 2025-12-04T09:48:47.5180899Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:47.5183544Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:47.518061] 2025-12-04T09:48:57.1606667Z 2025-12-04T09:48:57.1607702Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_f72dfbf8fa4548a2_.log 2025-12-04T09:48:57.1608423Z Running 0 items in this shard: 2025-12-04T09:48:57.1608622Z 2025-12-04T09:48:57.1609136Z Finished test_jit 1/1 ... [2025-12-04 09:48:57.160472][2279.846242542], took 0.16min 2025-12-04T09:48:57.1772535Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit/test_jit-8e4f9e7d7689bd12.xml 2025-12-04T09:48:57.2425172Z Running test_datapipe 1/1 ... [2025-12-04 09:48:57.242240][2279.928012157] 2025-12-04T09:48:57.2425933Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:48:57.2429200Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_datapipe.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:48:57.242580] 2025-12-04T09:49:00.5902079Z 2025-12-04T09:49:00.5903214Z test_datapipe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_datapipe_1.1_88e2f574e9a2ddf0_.log 2025-12-04T09:49:00.5903991Z Running 0 items in this shard: 2025-12-04T09:49:00.5904189Z 2025-12-04T09:49:00.5904496Z Finished test_datapipe 1/1 ... [2025-12-04 09:49:00.590045][2283.275815383], took 0.06min 2025-12-04T09:49:00.6067154Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_datapipe/test_datapipe-f5883fddf023e60c.xml 2025-12-04T09:49:00.6291065Z Running test_numba_integration 1/1 ... [2025-12-04 09:49:00.628809][2283.314580864] 2025-12-04T09:49:00.6291775Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:00.6294964Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numba_integration.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:00.629161] 2025-12-04T09:49:04.1329223Z 2025-12-04T09:49:04.1330546Z test_numba_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numba_integration_1.1_2b4995b565688da3_.log 2025-12-04T09:49:04.1331399Z Running 0 items in this shard: 2025-12-04T09:49:04.1331601Z 2025-12-04T09:49:04.1331926Z Finished test_numba_integration 1/1 ... [2025-12-04 09:49:04.132700][2286.8184688], took 0.06min 2025-12-04T09:49:04.1497688Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numba_integration/test_numba_integration-dc38da8dfc6d95a6.xml 2025-12-04T09:49:04.1740283Z Running test_functional_optim 1/1 ... [2025-12-04 09:49:04.173746][2286.859517235] 2025-12-04T09:49:04.1740972Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:04.1744078Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_functional_optim.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:04.174103] 2025-12-04T09:49:07.5750928Z 2025-12-04T09:49:07.5752252Z test_functional_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functional_optim_1.1_064ea9faf583b4a5_.log 2025-12-04T09:49:07.5753081Z Running 0 items in this shard: 2025-12-04T09:49:07.5753293Z 2025-12-04T09:49:07.5753597Z Finished test_functional_optim 1/1 ... [2025-12-04 09:49:07.574926][2290.260696178], took 0.06min 2025-12-04T09:49:07.5920600Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_functional_optim/test_functional_optim-9c9e277e02bafdac.xml 2025-12-04T09:49:07.6140125Z Running test_maskedtensor 1/1 ... [2025-12-04 09:49:07.613681][2290.299452741] 2025-12-04T09:49:07.6141007Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:07.6143896Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_maskedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:07.614044] 2025-12-04T09:49:12.5000752Z 2025-12-04T09:49:12.5001961Z test_maskedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_maskedtensor_1.1_33c752bba3015c1b_.log 2025-12-04T09:49:12.5002754Z Running 0 items in this shard: 2025-12-04T09:49:12.5003244Z 2025-12-04T09:49:12.5003532Z Finished test_maskedtensor 1/1 ... [2025-12-04 09:49:12.499908][2295.185677574], took 0.08min 2025-12-04T09:49:12.5173267Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_maskedtensor/test_maskedtensor-b0e3330fefe294a4.xml 2025-12-04T09:49:12.5404783Z Running benchmark_utils/test_benchmark_utils 1/1 ... [2025-12-04 09:49:12.540166][2295.225937432] 2025-12-04T09:49:12.5405499Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:12.5408508Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'benchmark_utils/test_benchmark_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:12.540545] 2025-12-04T09:49:15.7420647Z 2025-12-04T09:49:15.7421761Z benchmark_utils/test_benchmark_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/benchmark_utils.test_benchmark_utils_1.1_4574447f9afeff2e_.log 2025-12-04T09:49:15.7422767Z Running 0 items in this shard: 2025-12-04T09:49:15.7422979Z 2025-12-04T09:49:15.7423355Z Finished benchmark_utils/test_benchmark_utils 1/1 ... [2025-12-04 09:49:15.741838][2298.427606909], took 0.05min 2025-12-04T09:49:15.7592717Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/benchmark_utils.test_benchmark_utils/benchmark_utils.test_benchmark_utils-feb04a638ad62242.xml 2025-12-04T09:49:15.7892094Z Running torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-12-04 09:49:15.788911][2298.474682596] 2025-12-04T09:49:15.7892686Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:15.7895784Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarmath.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:15.789304] 2025-12-04T09:49:19.4065844Z 2025-12-04T09:49:19.4067667Z torch_np/numpy_tests/core/test_scalarmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_2016ff632d970136_.log 2025-12-04T09:49:19.4069635Z Running 0 items in this shard: 2025-12-04T09:49:19.4070007Z 2025-12-04T09:49:19.4070779Z Finished torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-12-04 09:49:19.406392][2302.092161336], took 0.06min 2025-12-04T09:49:19.4244279Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_scalarmath/torch_np.numpy_tests.core.test_scalarmath-e7d03e034c6f9cc8.xml 2025-12-04T09:49:19.4513196Z Running test_scaled_matmul_cuda 1/1 ... [2025-12-04 09:49:19.451006][2302.136777187] 2025-12-04T09:49:19.4514029Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:19.4518628Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_scaled_matmul_cuda.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:19.451452] 2025-12-04T09:49:22.9688175Z 2025-12-04T09:49:22.9689624Z test_scaled_matmul_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_scaled_matmul_cuda_1.1_00eb159dcd220742_.log 2025-12-04T09:49:22.9691202Z Running 0 items in this shard: 2025-12-04T09:49:22.9691583Z 2025-12-04T09:49:22.9692504Z Finished test_scaled_matmul_cuda 1/1 ... [2025-12-04 09:49:22.968623][2305.654393671], took 0.06min 2025-12-04T09:49:22.9867297Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_scaled_matmul_cuda/test_scaled_matmul_cuda-cde151db5456d58b.xml 2025-12-04T09:49:23.0094867Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-12-04 09:49:23.009206][2305.69497783] 2025-12-04T09:49:23.0096309Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:23.0098233Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:23.009553] 2025-12-04T09:49:26.5127197Z 2025-12-04T09:49:26.5128328Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_ed4a11c64b627ff3_.log 2025-12-04T09:49:26.5129373Z Running 0 items in this shard: 2025-12-04T09:49:26.5129573Z 2025-12-04T09:49:26.5129967Z Finished torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-12-04 09:49:26.512512][2309.198282767], took 0.06min 2025-12-04T09:49:26.5303197Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_shape_base/torch_np.numpy_tests.core.test_shape_base-b049ed364b384cc1.xml 2025-12-04T09:49:26.5566415Z Running test_vulkan 1/1 ... [2025-12-04 09:49:26.556380][2309.242150868] 2025-12-04T09:49:26.5566882Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:26.5570343Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_vulkan.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:26.556749] 2025-12-04T09:49:29.7231659Z 2025-12-04T09:49:29.7232510Z test_vulkan 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_vulkan_1.1_135ae20429a9d5bd_.log 2025-12-04T09:49:29.7233249Z Running 0 items in this shard: 2025-12-04T09:49:29.7233499Z 2025-12-04T09:49:29.7410210Z Finished test_vulkan 1/1 ... [2025-12-04 09:49:29.722975][2312.408744786], took 0.05min 2025-12-04T09:49:29.7411203Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_vulkan/test_vulkan-def9ee5523a8dfef.xml 2025-12-04T09:49:29.7687337Z Running lazy/test_generator 1/1 ... [2025-12-04 09:49:29.768434][2312.454204958] 2025-12-04T09:49:29.7687825Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:29.7690652Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_generator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:29.768797] 2025-12-04T09:49:32.9562466Z 2025-12-04T09:49:32.9563418Z lazy/test_generator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_generator_1.1_5b69427d5e4fa2f5_.log 2025-12-04T09:49:32.9564277Z Running 0 items in this shard: 2025-12-04T09:49:32.9564473Z 2025-12-04T09:49:32.9564843Z Finished lazy/test_generator 1/1 ... [2025-12-04 09:49:32.956086][2315.641856204], took 0.05min 2025-12-04T09:49:32.9739436Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_generator/lazy.test_generator-3a7b0bc0f7b27311.xml 2025-12-04T09:49:33.0109436Z Running torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-12-04 09:49:33.010697][2315.696468197] 2025-12-04T09:49:33.0110038Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:33.0113414Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/linalg/test_linalg.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:33.011037] 2025-12-04T09:49:36.7770576Z 2025-12-04T09:49:36.7771926Z torch_np/numpy_tests/linalg/test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.linalg.test_linalg_1.1_ccbcbe960624bdd5_.log 2025-12-04T09:49:36.7772947Z Running 0 items in this shard: 2025-12-04T09:49:36.7773146Z 2025-12-04T09:49:36.7773533Z Finished torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-12-04 09:49:36.776880][2319.462649099], took 0.06min 2025-12-04T09:49:36.7948910Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.linalg.test_linalg/torch_np.numpy_tests.linalg.test_linalg-f06c6713e3f7207a.xml 2025-12-04T09:49:36.8194757Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-12-04 09:49:36.819247][2319.505019184] 2025-12-04T09:49:36.8195328Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:36.8198662Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:36.819587] 2025-12-04T09:49:40.1437512Z 2025-12-04T09:49:40.1438987Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_f6696a27a91990b0_.log 2025-12-04T09:49:40.1439992Z Running 0 items in this shard: 2025-12-04T09:49:40.1440190Z 2025-12-04T09:49:40.1440596Z Finished torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-12-04 09:49:40.143547][2322.829318294], took 0.06min 2025-12-04T09:49:40.1617596Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_dtype/torch_np.numpy_tests.core.test_dtype-e63f008fbef4fe28.xml 2025-12-04T09:49:40.1922228Z Running lazy/test_debug_util 1/1 ... [2025-12-04 09:49:40.191970][2322.877742334] 2025-12-04T09:49:40.1922768Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:40.1925806Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:40.192310] 2025-12-04T09:49:43.3682601Z 2025-12-04T09:49:43.3683694Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_74f3d3d5a079ea66_.log 2025-12-04T09:49:43.3684581Z Running 0 items in this shard: 2025-12-04T09:49:43.3684857Z 2025-12-04T09:49:43.3685152Z Finished lazy/test_debug_util 1/1 ... [2025-12-04 09:49:43.368069][2326.053840434], took 0.05min 2025-12-04T09:49:43.3865389Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_debug_util/lazy.test_debug_util-f60c31b8fc2454a3.xml 2025-12-04T09:49:43.4141145Z Running nn/test_load_state_dict 1/1 ... [2025-12-04 09:49:43.413851][2326.099623361] 2025-12-04T09:49:43.4141672Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:43.4144563Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:43.414184] 2025-12-04T09:49:46.9665406Z 2025-12-04T09:49:46.9666631Z 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_f74f27298b45b2bd_.log 2025-12-04T09:49:46.9667492Z Running 0 items in this shard: 2025-12-04T09:49:46.9667690Z 2025-12-04T09:49:46.9668014Z Finished nn/test_load_state_dict 1/1 ... [2025-12-04 09:49:46.966355][2329.652126353], took 0.06min 2025-12-04T09:49:46.9850304Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_load_state_dict/nn.test_load_state_dict-1da645d2bbad0d28.xml 2025-12-04T09:49:47.0102562Z Running nn/test_module_hooks 1/1 ... [2025-12-04 09:49:47.010002][2329.69577409] 2025-12-04T09:49:47.0103061Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:47.0105874Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_module_hooks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:47.010343] 2025-12-04T09:49:50.5841883Z 2025-12-04T09:49:50.5843143Z nn/test_module_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_module_hooks_1.1_88de1e1f5a4e9e57_.log 2025-12-04T09:49:50.5843983Z Running 0 items in this shard: 2025-12-04T09:49:50.5844183Z 2025-12-04T09:49:50.5844521Z Finished nn/test_module_hooks 1/1 ... [2025-12-04 09:49:50.583993][2333.269763514], took 0.06min 2025-12-04T09:49:50.6026380Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_module_hooks/nn.test_module_hooks-6db58748bf6dc289.xml 2025-12-04T09:49:50.6274437Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-12-04 09:49:50.627158][2333.312930855] 2025-12-04T09:49:50.6275047Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:50.6277691Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:50.627494] 2025-12-04T09:49:53.8507385Z 2025-12-04T09:49:53.8508349Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_e020bcc416350241_.log 2025-12-04T09:49:53.8509379Z Running 0 items in this shard: 2025-12-04T09:49:53.8509592Z 2025-12-04T09:49:53.8509981Z Finished torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-12-04 09:49:53.850551][2336.536320356], took 0.05min 2025-12-04T09:49:53.8694743Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_twodim_base/torch_np.numpy_tests.lib.test_twodim_base-ad341958c831b268.xml 2025-12-04T09:49:53.8972273Z Running profiler/test_memory_profiler 1/1 ... [2025-12-04 09:49:53.896951][2336.582723016] 2025-12-04T09:49:53.8972846Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:53.8976278Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'profiler/test_memory_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:53.897305] 2025-12-04T09:49:57.4392170Z 2025-12-04T09:49:57.4393225Z profiler/test_memory_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_memory_profiler_1.1_032ac1fe03a8579f_.log 2025-12-04T09:49:57.4394157Z Running 0 items in this shard: 2025-12-04T09:49:57.4394354Z 2025-12-04T09:49:57.4394703Z Finished profiler/test_memory_profiler 1/1 ... [2025-12-04 09:49:57.439027][2340.124797719], took 0.06min 2025-12-04T09:49:57.4580163Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/profiler.test_memory_profiler/profiler.test_memory_profiler-16407e21cf309b10.xml 2025-12-04T09:49:57.4816756Z Running test_jit_llga_fuser 1/1 ... [2025-12-04 09:49:57.481382][2340.167153548] 2025-12-04T09:49:57.4817259Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:49:57.4819904Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit_llga_fuser.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:49:57.481738] 2025-12-04T09:50:01.2298211Z 2025-12-04T09:50:01.2299138Z 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_624f7d61598891ff_.log 2025-12-04T09:50:01.2299954Z Running 0 items in this shard: 2025-12-04T09:50:01.2300152Z 2025-12-04T09:50:01.2300466Z Finished test_jit_llga_fuser 1/1 ... [2025-12-04 09:50:01.229630][2343.915400422], took 0.06min 2025-12-04T09:50:01.2489159Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit_llga_fuser/test_jit_llga_fuser-728d20068c0156b4.xml 2025-12-04T09:50:01.2735305Z Running test_serialization 1/1 ... [2025-12-04 09:50:01.273273][2343.959044858] 2025-12-04T09:50:01.2735807Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:01.2738693Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_serialization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:01.273619] 2025-12-04T09:50:05.3283116Z 2025-12-04T09:50:05.3284060Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_677db50f130f36e6_.log 2025-12-04T09:50:05.3284950Z Running 0 items in this shard: 2025-12-04T09:50:05.3285192Z 2025-12-04T09:50:05.3285487Z Finished test_serialization 1/1 ... [2025-12-04 09:50:05.328066][2348.013836347], took 0.07min 2025-12-04T09:50:05.3473886Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_serialization/test_serialization-e5f28919f38eb53c.xml 2025-12-04T09:50:05.3710000Z Running test_indexing 1/1 ... [2025-12-04 09:50:05.370738][2348.056509595] 2025-12-04T09:50:05.3710461Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:05.3713288Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:05.371078] 2025-12-04T09:50:08.8731474Z 2025-12-04T09:50:08.8732351Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_fc0a6a244d6c09e9_.log 2025-12-04T09:50:08.8733113Z Running 0 items in this shard: 2025-12-04T09:50:08.8733326Z 2025-12-04T09:50:08.8733587Z Finished test_indexing 1/1 ... [2025-12-04 09:50:08.872927][2351.55869878], took 0.06min 2025-12-04T09:50:08.8922635Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_indexing/test_indexing-895b06ee99d277c4.xml 2025-12-04T09:50:08.9230567Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-12-04 09:50:08.922776][2351.608547529] 2025-12-04T09:50:08.9231170Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:08.9233882Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:08.923116] 2025-12-04T09:50:12.2124400Z 2025-12-04T09:50:12.2125847Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_7492f94fec57396b_.log 2025-12-04T09:50:12.2126878Z Running 0 items in this shard: 2025-12-04T09:50:12.2127074Z 2025-12-04T09:50:12.2127472Z Finished torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-12-04 09:50:12.212238][2354.898007493], took 0.05min 2025-12-04T09:50:12.2318671Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.fft.test_pocketfft/torch_np.numpy_tests.fft.test_pocketfft-9cf68670a418eb4f.xml 2025-12-04T09:50:12.2575891Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-12-04 09:50:12.257287][2354.94305797] 2025-12-04T09:50:12.2576478Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:12.2579297Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:12.257650] 2025-12-04T09:50:15.5822738Z 2025-12-04T09:50:15.5823881Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_9f67057503aaed4d_.log 2025-12-04T09:50:15.5824937Z Running 0 items in this shard: 2025-12-04T09:50:15.5825133Z 2025-12-04T09:50:15.5825534Z Finished torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-12-04 09:50:15.582077][2358.267846938], took 0.06min 2025-12-04T09:50:15.6018673Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_shape_base_/torch_np.numpy_tests.lib.test_shape_base_-aa5884317fa90157.xml 2025-12-04T09:50:15.6260297Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-12-04 09:50:15.625764][2358.311536488] 2025-12-04T09:50:15.6260901Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:15.6264169Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:15.626105] 2025-12-04T09:50:18.8665725Z 2025-12-04T09:50:18.8666847Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_93845470efc4ea11_.log 2025-12-04T09:50:18.8667868Z Running 0 items in this shard: 2025-12-04T09:50:18.8668068Z 2025-12-04T09:50:18.8668490Z Finished torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-12-04 09:50:18.866381][2361.552150627], took 0.05min 2025-12-04T09:50:18.8862198Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_getlimits/torch_np.numpy_tests.core.test_getlimits-f8bdcf1c5611053f.xml 2025-12-04T09:50:18.9134737Z Running torch_np/test_ndarray_methods 1/1 ... [2025-12-04 09:50:18.913189][2361.598960426] 2025-12-04T09:50:18.9135292Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:18.9138506Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:18.913536] 2025-12-04T09:50:22.8768760Z 2025-12-04T09:50:22.8769902Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_8b999e4f746c878d_.log 2025-12-04T09:50:22.8771088Z Running 0 items in this shard: 2025-12-04T09:50:22.8771307Z 2025-12-04T09:50:22.8771651Z Finished torch_np/test_ndarray_methods 1/1 ... [2025-12-04 09:50:22.876689][2365.562459899], took 0.07min 2025-12-04T09:50:22.8966340Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.test_ndarray_methods/torch_np.test_ndarray_methods-299409cf03e8a6a0.xml 2025-12-04T09:50:22.9224493Z Running test_type_info 1/1 ... [2025-12-04 09:50:22.922139][2365.607910406] 2025-12-04T09:50:22.9224970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:22.9228138Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_type_info.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:22.922523] 2025-12-04T09:50:26.1849505Z 2025-12-04T09:50:26.1850460Z test_type_info 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_info_1.1_950665d747965023_.log 2025-12-04T09:50:26.1851239Z Running 0 items in this shard: 2025-12-04T09:50:26.1851438Z 2025-12-04T09:50:26.1851718Z Finished test_type_info 1/1 ... [2025-12-04 09:50:26.184779][2368.870548612], took 0.05min 2025-12-04T09:50:26.2059220Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_type_info/test_type_info-63e64e828af54c35.xml 2025-12-04T09:50:26.2325467Z Running functorch/test_aotdispatch 1/1 ... [2025-12-04 09:50:26.232202][2368.917973012] 2025-12-04T09:50:26.2326018Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:26.2329082Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:26.232595] 2025-12-04T09:50:32.6082811Z 2025-12-04T09:50:32.6083812Z functorch/test_aotdispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_1.1_bf05616288b92e61_.log 2025-12-04T09:50:32.6084791Z Running 0 items in this shard: 2025-12-04T09:50:32.6084993Z 2025-12-04T09:50:32.6085355Z Finished functorch/test_aotdispatch 1/1 ... [2025-12-04 09:50:32.608089][2375.29385819], took 0.11min 2025-12-04T09:50:32.6284079Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.test_aotdispatch/functorch.test_aotdispatch-091fe8946bcc59e2.xml 2025-12-04T09:50:32.7019438Z Running test_cuda_multigpu 1/1 ... [2025-12-04 09:50:32.701670][2375.387440498] 2025-12-04T09:50:32.7019941Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:32.7023654Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cuda_multigpu.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:32.702040] 2025-12-04T09:50:36.2022318Z 2025-12-04T09:50:36.2023211Z test_cuda_multigpu 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_multigpu_1.1_0e4a6b3e6b77d5a4_.log 2025-12-04T09:50:36.2024061Z Running 0 items in this shard: 2025-12-04T09:50:36.2024276Z 2025-12-04T09:50:36.2024558Z Finished test_cuda_multigpu 1/1 ... [2025-12-04 09:50:36.202028][2378.88779778], took 0.06min 2025-12-04T09:50:36.2229966Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cuda_multigpu/test_cuda_multigpu-00e53755d085198c.xml 2025-12-04T09:50:36.2499481Z Running test_accelerator 1/1 ... [2025-12-04 09:50:36.249692][2378.93546366] 2025-12-04T09:50:36.2500031Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:36.2503810Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_accelerator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:36.250089] 2025-12-04T09:50:39.3107213Z 2025-12-04T09:50:39.3108126Z test_accelerator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_accelerator_1.1_6164f12b8d8b68f3_.log 2025-12-04T09:50:39.3109100Z 2025-12-04T09:50:39.3109382Z Finished test_accelerator 1/1 ... [2025-12-04 09:50:39.310533][2381.996303531], took 0.05min 2025-12-04T09:50:40.9689016Z W1204 09:50:40.968000 12238 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:40.9874571Z W1204 09:50:40.986000 12236 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:41.0119956Z W1204 09:50:41.011000 12237 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:42.3191666Z Running inductor/test_aot_inductor 1/1 ... [2025-12-04 09:50:42.318728][2385.004497459] 2025-12-04T09:50:42.3192348Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:42.3194732Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:42.319168] 2025-12-04T09:50:42.3398606Z Running inductor/test_torchinductor_opinfo 1/1 ... [2025-12-04 09:50:42.339543][2385.025312063] 2025-12-04T09:50:42.3399209Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:42.3412728Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:42.339993] 2025-12-04T09:50:42.3809492Z Running inductor/test_cudagraph_trees 1/1 ... [2025-12-04 09:50:42.380568][2385.066337025] 2025-12-04T09:50:42.3810065Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:42.3813368Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cudagraph_trees.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:42.381057] 2025-12-04T09:50:50.5408274Z 2025-12-04T09:50:50.5409331Z inductor/test_cudagraph_trees 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudagraph_trees_1.1_d3d916fb71e3c465_.log 2025-12-04T09:50:50.5410193Z 2025-12-04T09:50:50.5410577Z Finished inductor/test_cudagraph_trees 1/1 ... [2025-12-04 09:50:50.540727][2393.226491441], took 0.14min 2025-12-04T09:50:52.5447018Z 2025-12-04T09:50:52.5448830Z inductor/test_aot_inductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_1.1_e967b25a251f959b_.log 2025-12-04T09:50:52.5449702Z 2025-12-04T09:50:52.5450032Z Finished inductor/test_aot_inductor 1/1 ... [2025-12-04 09:50:52.544686][2395.230453883], took 0.17min 2025-12-04T09:50:52.9868135Z W1204 09:50:52.986000 12616 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:54.3976646Z Running inductor/test_compile_subprocess 1/1 ... [2025-12-04 09:50:54.397196][2397.082965343] 2025-12-04T09:50:54.3977352Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:54.3980125Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:54.397650] 2025-12-04T09:50:54.8242782Z 2025-12-04T09:50:54.8244248Z inductor/test_torchinductor_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_1.1_f8681a15918632a2_.log 2025-12-04T09:50:54.8246094Z Running 0 items in this shard: 2025-12-04T09:50:54.8246306Z 2025-12-04T09:50:54.8246685Z Finished inductor/test_torchinductor_opinfo 1/1 ... [2025-12-04 09:50:54.824295][2397.510060808], took 0.21min 2025-12-04T09:50:54.8424923Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_torchinductor_opinfo/inductor.test_torchinductor_opinfo-90bf30935e93f416.xml 2025-12-04T09:50:55.0796185Z W1204 09:50:55.078000 12649 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:56.4941417Z Running inductor/test_native_matmul 1/1 ... [2025-12-04 09:50:56.493647][2399.179415192] 2025-12-04T09:50:56.4942008Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:56.4945530Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_native_matmul.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:56.494178] 2025-12-04T09:50:57.2895454Z W1204 09:50:57.288000 12682 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:50:58.6256067Z Running inductor/test_op_dtype_prop 1/1 ... [2025-12-04 09:50:58.625174][2401.31094287] 2025-12-04T09:50:58.6256630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:50:58.6260200Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_op_dtype_prop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:50:58.625641] 2025-12-04T09:51:02.9784753Z 2025-12-04T09:51:02.9786243Z inductor/test_compile_subprocess 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_1.1_672022d11b8c83d0_.log 2025-12-04T09:51:02.9787146Z 2025-12-04T09:51:02.9787518Z Finished inductor/test_compile_subprocess 1/1 ... [2025-12-04 09:51:02.978361][2405.664131123], took 0.14min 2025-12-04T09:51:04.9533895Z 2025-12-04T09:51:04.9535280Z inductor/test_native_matmul 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_native_matmul_1.1_defe3674c3d96c74_.log 2025-12-04T09:51:04.9536081Z 2025-12-04T09:51:04.9536479Z Finished inductor/test_native_matmul 1/1 ... [2025-12-04 09:51:04.953270][2407.639039469], took 0.14min 2025-12-04T09:51:05.3861624Z W1204 09:51:05.385000 12994 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:06.8268574Z Running inductor/test_unbacked_symints 1/1 ... [2025-12-04 09:51:06.826420][2409.512189271] 2025-12-04T09:51:06.8269200Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:06.8272521Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_unbacked_symints.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:06.826893] 2025-12-04T09:51:07.4606060Z W1204 09:51:07.459000 13027 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:08.2193317Z 2025-12-04T09:51:08.2194637Z 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_2c5c0a9c4ff220f6_.log 2025-12-04T09:51:08.2195480Z 2025-12-04T09:51:08.2196335Z Finished inductor/test_op_dtype_prop 1/1 ... [2025-12-04 09:51:08.219257][2410.905025064], took 0.16min 2025-12-04T09:51:08.8360968Z Running inductor/test_padding 1/1 ... [2025-12-04 09:51:08.835702][2411.521470686] 2025-12-04T09:51:08.8361797Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:08.8365129Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_padding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:08.836182] 2025-12-04T09:51:10.6229365Z W1204 09:51:10.622000 13076 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:12.0097232Z Running test_varlen_attention 1/1 ... [2025-12-04 09:51:12.009342][2414.695110744] 2025-12-04T09:51:12.0097774Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:12.0100541Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_varlen_attention.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:12.009768] 2025-12-04T09:51:15.4119607Z 2025-12-04T09:51:15.4120924Z inductor/test_unbacked_symints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_unbacked_symints_1.1_93d1349b094e0621_.log 2025-12-04T09:51:15.4121883Z Running 0 items in this shard: 2025-12-04T09:51:15.4122080Z 2025-12-04T09:51:15.4122458Z Finished inductor/test_unbacked_symints 1/1 ... [2025-12-04 09:51:15.411796][2418.097564419], took 0.14min 2025-12-04T09:51:15.4224923Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_unbacked_symints/inductor.test_unbacked_symints-35fe2ea9ab7b9f08.xml 2025-12-04T09:51:15.4831455Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_varlen_attention/test_varlen_attention-ebdb65ea8e6eb700.xml 2025-12-04T09:51:15.8655438Z 2025-12-04T09:51:15.8656351Z test_varlen_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_varlen_attention_1.1_8512e94bf1ce5fb2_.log 2025-12-04T09:51:15.8657193Z Running 0 items in this shard: 2025-12-04T09:51:15.8657404Z 2025-12-04T09:51:15.8657703Z Finished test_varlen_attention 1/1 ... [2025-12-04 09:51:15.865482][2418.551250542], took 0.06min 2025-12-04T09:51:17.3233386Z 2025-12-04T09:51:17.3234345Z inductor/test_padding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_padding_1.1_6d4fada3be2df107_.log 2025-12-04T09:51:17.3235126Z 2025-12-04T09:51:17.3235437Z Finished inductor/test_padding 1/1 ... [2025-12-04 09:51:17.323169][2420.008938792], took 0.14min 2025-12-04T09:51:17.8909925Z W1204 09:51:17.890000 13311 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:18.3343723Z W1204 09:51:18.333000 13327 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:19.2755433Z Running test_ops_fwd_gradients 1/1 ... [2025-12-04 09:51:19.275115][2421.960883801] 2025-12-04T09:51:19.2755972Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:19.2758930Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_ops_fwd_gradients.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:19.275577] 2025-12-04T09:51:19.7117683Z W1204 09:51:19.710000 13344 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:19.7393455Z Running test_linalg 1/1 ... [2025-12-04 09:51:19.738843][2422.424606159] 2025-12-04T09:51:19.7394530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:19.7401684Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_linalg.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:19.739680] 2025-12-04T09:51:21.1343790Z Running inductor/test_select_algorithm 1/1 ... [2025-12-04 09:51:21.133969][2423.819738095] 2025-12-04T09:51:21.1344390Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:21.1347197Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_select_algorithm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:21.134429] 2025-12-04T09:51:24.0116119Z 2025-12-04T09:51:24.0117055Z test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_linalg_1.1_d49857604e44d38b_.log 2025-12-04T09:51:24.0117829Z Running 0 items in this shard: 2025-12-04T09:51:24.0118043Z 2025-12-04T09:51:24.0118295Z Finished test_linalg 1/1 ... [2025-12-04 09:51:24.011606][2426.69737152], took 0.07min 2025-12-04T09:51:24.0277586Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_ops_fwd_gradients/test_ops_fwd_gradients-d93d0de7472bcf18.xml 2025-12-04T09:51:24.1028238Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_linalg/test_linalg-e180767c82e3d750.xml 2025-12-04T09:51:24.1811139Z 2025-12-04T09:51:24.1812349Z 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_1006e83145e84f5a_.log 2025-12-04T09:51:24.1813414Z Running 0 items in this shard: 2025-12-04T09:51:24.1813613Z 2025-12-04T09:51:24.1814044Z Finished test_ops_fwd_gradients 1/1 ... [2025-12-04 09:51:24.181054][2426.866818315], took 0.08min 2025-12-04T09:51:26.5430936Z W1204 09:51:26.542000 13428 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:26.6954191Z W1204 09:51:26.694000 13429 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:27.9468976Z Running dynamo/test_dynamic_shapes 2/2 ... [2025-12-04 09:51:27.946493][2430.632261789] 2025-12-04T09:51:27.9469565Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:27.9472735Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:27.946941] 2025-12-04T09:51:28.0928771Z Running inductor/test_compiled_autograd 2/2 ... [2025-12-04 09:51:28.092431][2430.778199193] 2025-12-04T09:51:28.0929390Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:28.0932366Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compiled_autograd.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:28.092892] 2025-12-04T09:51:29.4392391Z 2025-12-04T09:51:29.4393887Z inductor/test_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_select_algorithm_1.1_09aa4d05751eb446_.log 2025-12-04T09:51:29.4394755Z 2025-12-04T09:51:29.4395113Z Finished inductor/test_select_algorithm 1/1 ... [2025-12-04 09:51:29.439168][2432.124933998], took 0.14min 2025-12-04T09:51:31.8724069Z W1204 09:51:31.871000 13586 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:33.2548445Z Running inductor/test_custom_lowering 1/1 ... [2025-12-04 09:51:33.254428][2435.940196436] 2025-12-04T09:51:33.2549120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:33.2551610Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_custom_lowering.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:33.254853] 2025-12-04T09:51:40.6781840Z 2025-12-04T09:51:40.6783397Z inductor/test_compiled_autograd 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_autograd_2.2_f55a8a3346e1b791_.log 2025-12-04T09:51:40.6784866Z Running 0 items in this shard: 2025-12-04T09:51:40.6785215Z 2025-12-04T09:51:40.6785838Z Finished inductor/test_compiled_autograd 2/2 ... [2025-12-04 09:51:40.678052][2443.363819858], took 0.21min 2025-12-04T09:51:40.6899774Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_dynamic_shapes/dynamo.test_dynamic_shapes-f603714d34f2c63b.xml 2025-12-04T09:51:40.7628317Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_compiled_autograd/inductor.test_compiled_autograd-8426539637a5725f.xml 2025-12-04T09:51:41.6281663Z 2025-12-04T09:51:41.6283261Z inductor/test_custom_lowering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_custom_lowering_1.1_5bedb9cb72d75765_.log 2025-12-04T09:51:41.6284228Z Running 0 items in this shard: 2025-12-04T09:51:41.6284440Z 2025-12-04T09:51:41.6284841Z Finished inductor/test_custom_lowering 1/1 ... [2025-12-04 09:51:41.628094][2444.31386292], took 0.14min 2025-12-04T09:51:41.6408110Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_custom_lowering/inductor.test_custom_lowering-9dac587967a1e890.xml 2025-12-04T09:51:41.8429054Z 2025-12-04T09:51:41.8430367Z dynamo/test_dynamic_shapes 2/2 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_2.2_32f1c56b33ffbfc8_.log 2025-12-04T09:51:41.8431263Z Running 0 items in this shard: 2025-12-04T09:51:41.8431461Z 2025-12-04T09:51:41.8431788Z Finished dynamo/test_dynamic_shapes 2/2 ... [2025-12-04 09:51:41.842838][2444.528607817], took 0.23min 2025-12-04T09:51:43.1852305Z W1204 09:51:43.184000 13928 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:44.1254330Z W1204 09:51:44.124000 13944 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:44.3317653Z W1204 09:51:44.331000 13945 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:44.5463776Z Running inductor/test_perf 1/1 ... [2025-12-04 09:51:44.545942][2447.231711825] 2025-12-04T09:51:44.5464351Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:44.5467556Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_perf.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:44.546380] 2025-12-04T09:51:45.5319921Z Running inductor/test_fused_attention 1/1 ... [2025-12-04 09:51:45.531565][2448.217333346] 2025-12-04T09:51:45.5320804Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:45.5323339Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_fused_attention.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:45.531997] 2025-12-04T09:51:45.7414909Z Running inductor/test_binary_folding 1/1 ... [2025-12-04 09:51:45.741076][2448.426845855] 2025-12-04T09:51:45.7415483Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:45.7418517Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:45.741517] 2025-12-04T09:51:52.7882529Z 2025-12-04T09:51:52.7883834Z inductor/test_perf 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_perf_1.1_9c1aa55949a6a580_.log 2025-12-04T09:51:52.7884554Z 2025-12-04T09:51:52.7884893Z Finished inductor/test_perf 1/1 ... [2025-12-04 09:51:52.788096][2455.473866554], took 0.14min 2025-12-04T09:51:54.7513145Z 2025-12-04T09:51:54.7514951Z inductor/test_fused_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fused_attention_1.1_51962a550005f918_.log 2025-12-04T09:51:54.7515911Z Running 0 items in this shard: 2025-12-04T09:51:54.7516124Z 2025-12-04T09:51:54.7516475Z Finished inductor/test_fused_attention 1/1 ... [2025-12-04 09:51:54.751267][2457.437036439], took 0.15min 2025-12-04T09:51:54.7634397Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_fused_attention/inductor.test_fused_attention-828f3930656dd63c.xml 2025-12-04T09:51:55.1844657Z W1204 09:51:55.183000 14290 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:56.6132649Z Running inductor/test_mkldnn_pattern_matcher 1/2 ... [2025-12-04 09:51:56.612830][2459.29859919] 2025-12-04T09:51:56.6133450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:56.6135702Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_mkldnn_pattern_matcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:56.613261] 2025-12-04T09:51:56.6310914Z 2025-12-04T09:51:56.6312212Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_59ebffacea9a2773_.log 2025-12-04T09:51:56.6313158Z Running 0 items in this shard: 2025-12-04T09:51:56.6313375Z 2025-12-04T09:51:56.6313743Z Finished inductor/test_binary_folding 1/1 ... [2025-12-04 09:51:56.631043][2459.316813847], took 0.18min 2025-12-04T09:51:56.6437594Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_binary_folding/inductor.test_binary_folding-c2cd52c867984cde.xml 2025-12-04T09:51:57.2230067Z W1204 09:51:57.222000 14323 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:51:58.6145232Z Running inductor/test_cpu_select_algorithm 1/1 ... [2025-12-04 09:51:58.614041][2461.299809615] 2025-12-04T09:51:58.6145845Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:51:58.6148492Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:51:58.614494] 2025-12-04T09:51:59.0332406Z W1204 09:51:59.032000 14356 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:00.4297580Z Running inductor/test_aot_inductor_arrayref 2/2 ... [2025-12-04 09:52:00.429293][2463.11506184] 2025-12-04T09:52:00.4298178Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:00.4301308Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor_arrayref.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:00.429782] 2025-12-04T09:52:07.2780899Z 2025-12-04T09:52:07.2782271Z inductor/test_cpu_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_1.1_a4bfc6d665cfb171_.log 2025-12-04T09:52:07.2783308Z Running 0 items in this shard: 2025-12-04T09:52:07.2783518Z 2025-12-04T09:52:07.2783883Z Finished inductor/test_cpu_select_algorithm 1/1 ... [2025-12-04 09:52:07.278047][2469.963816289], took 0.14min 2025-12-04T09:52:07.2908406Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cpu_select_algorithm/inductor.test_cpu_select_algorithm-e286bba9c4a8de87.xml 2025-12-04T09:52:09.6170016Z W1204 09:52:09.616000 14692 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:09.8969433Z 2025-12-04T09:52:09.8971228Z inductor/test_aot_inductor_arrayref 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_arrayref_2.2_36bf806c24ed5c78_.log 2025-12-04T09:52:09.8972888Z Running 0 items in this shard: 2025-12-04T09:52:09.8973253Z 2025-12-04T09:52:09.8973909Z Finished inductor/test_aot_inductor_arrayref 2/2 ... [2025-12-04 09:52:09.896819][2472.582587467], took 0.16min 2025-12-04T09:52:09.9101031Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_aot_inductor_arrayref/inductor.test_aot_inductor_arrayref-52a392ec029450f0.xml 2025-12-04T09:52:10.9866096Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-12-04 09:52:10.986130][2473.671898302] 2025-12-04T09:52:10.9866787Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:10.9869559Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:10.986612] 2025-12-04T09:52:12.3326233Z W1204 09:52:12.331000 14752 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:13.7069990Z Running test_custom_ops 1/1 ... [2025-12-04 09:52:13.706476][2476.392245859] 2025-12-04T09:52:13.7070891Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:13.7073421Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_custom_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:13.706912] 2025-12-04T09:52:19.0105872Z 2025-12-04T09:52:19.0106881Z test_custom_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_custom_ops_1.1_6980b423371136ca_.log 2025-12-04T09:52:19.0121235Z Running 50 items in this shard: test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python, test/test_custom_ops.py::TestCustomOp::test_defined_in_python 2025-12-04T09:52:19.0135031Z 2025-12-04T09:52:19.0135313Z Finished test_custom_ops 1/1 ... [2025-12-04 09:52:19.010524][2481.696293605], took 0.09min 2025-12-04T09:52:19.0332905Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_custom_ops/test_custom_ops-bdd892d38a0ad8ec.xml 2025-12-04T09:52:19.5996885Z 2025-12-04T09:52:19.5998937Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_dffa15ee1ba91949_.log 2025-12-04T09:52:19.6000899Z 2025-12-04T09:52:19.6001732Z Finished inductor/test_torchinductor_strided_blocks 1/1 ... [2025-12-04 09:52:19.599598][2482.285367331], took 0.14min 2025-12-04T09:52:21.5331003Z W1204 09:52:21.532000 15196 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:22.0375480Z W1204 09:52:22.036000 15218 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:22.9456581Z Running inductor/test_multi_kernel 1/1 ... [2025-12-04 09:52:22.945136][2485.630904044] 2025-12-04T09:52:22.9457463Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:22.9459576Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_multi_kernel.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:22.945578] 2025-12-04T09:52:23.4983288Z Running inductor/test_analysis 1/1 ... [2025-12-04 09:52:23.497899][2486.183668058] 2025-12-04T09:52:23.4983828Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:23.4987426Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_analysis.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:23.498363] 2025-12-04T09:52:31.3558178Z 2025-12-04T09:52:31.3559848Z inductor/test_multi_kernel 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_multi_kernel_1.1_aa8ec14882844c4b_.log 2025-12-04T09:52:31.3561310Z 2025-12-04T09:52:31.3561893Z Finished inductor/test_multi_kernel 1/1 ... [2025-12-04 09:52:31.355812][2494.04157835], took 0.14min 2025-12-04T09:52:33.1798315Z 2025-12-04T09:52:33.1799360Z inductor/test_analysis 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_analysis_1.1_4918dedf24cc1ecc_.log 2025-12-04T09:52:33.1800236Z Running 0 items in this shard: 2025-12-04T09:52:33.1800453Z 2025-12-04T09:52:33.1800766Z Finished inductor/test_analysis 1/1 ... [2025-12-04 09:52:33.179712][2495.865480885], took 0.16min 2025-12-04T09:52:33.1932480Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_analysis/inductor.test_analysis-e4d76a7b65f09db8.xml 2025-12-04T09:52:33.7666357Z W1204 09:52:33.765000 15838 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:35.1628025Z Running inductor/test_triton_extension_backend 1/1 ... [2025-12-04 09:52:35.162328][2497.848096365] 2025-12-04T09:52:35.1629111Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:35.1632243Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_triton_extension_backend.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:35.162811] 2025-12-04T09:52:35.6103279Z W1204 09:52:35.609000 15903 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:37.0453157Z Running test_sparse_semi_structured 1/1 ... [2025-12-04 09:52:37.044876][2499.730640852] 2025-12-04T09:52:37.0453730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:37.0456963Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:37.045352] 2025-12-04T09:52:43.8369719Z 2025-12-04T09:52:43.8371690Z inductor/test_triton_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_extension_backend_1.1_1f89b3e633c968dc_.log 2025-12-04T09:52:43.8373819Z Running 0 items in this shard: 2025-12-04T09:52:43.8374307Z 2025-12-04T09:52:43.8375666Z Finished inductor/test_triton_extension_backend 1/1 ... [2025-12-04 09:52:43.836992][2506.522758192], took 0.14min 2025-12-04T09:52:43.8531720Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_triton_extension_backend/inductor.test_triton_extension_backend-06d98dc933747bc0.xml 2025-12-04T09:52:45.8292048Z 2025-12-04T09:52:45.8293082Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_d8a3ee7f568715f0_.log 2025-12-04T09:52:45.8293987Z Running 0 items in this shard: 2025-12-04T09:52:45.8294186Z 2025-12-04T09:52:45.8294826Z Finished test_sparse_semi_structured 1/1 ... [2025-12-04 09:52:45.829129][2508.514898715], took 0.15min 2025-12-04T09:52:45.8431874Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_sparse_semi_structured/test_sparse_semi_structured-24bac6daab65e860.xml 2025-12-04T09:52:46.3043173Z W1204 09:52:46.303000 16522 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:47.7027587Z Running inductor/test_op_completeness 1/1 ... [2025-12-04 09:52:47.702345][2510.388114204] 2025-12-04T09:52:47.7028207Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:47.7031197Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_op_completeness.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:47.702782] 2025-12-04T09:52:48.3180058Z W1204 09:52:48.317000 16587 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:49.6941903Z Running inductor/test_triton_heuristics 1/1 ... [2025-12-04 09:52:49.693775][2512.379544263] 2025-12-04T09:52:49.6942835Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:49.6946107Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_triton_heuristics.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:49.694215] 2025-12-04T09:52:51.7390057Z 2025-12-04T09:52:51.7391260Z 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_889561f7ab7408eb_.log 2025-12-04T09:52:51.7392422Z Running 0 items in this shard: 2025-12-04T09:52:51.7392660Z 2025-12-04T09:52:51.7393100Z Finished inductor/test_op_completeness 1/1 ... [2025-12-04 09:52:51.738906][2514.424673484], took 0.07min 2025-12-04T09:52:51.7533490Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_op_completeness/inductor.test_op_completeness-2a385b1e851f2d1f.xml 2025-12-04T09:52:54.2067637Z W1204 09:52:54.205000 16781 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:52:55.5784027Z Running inductor/test_cutedsl_grouped_mm 1/1 ... [2025-12-04 09:52:55.577998][2518.263766321] 2025-12-04T09:52:55.5784630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:52:55.5787096Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cutedsl_grouped_mm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:52:55.578424] 2025-12-04T09:52:58.0626054Z 2025-12-04T09:52:58.0627326Z inductor/test_triton_heuristics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_heuristics_1.1_bbaa4c298a5130f3_.log 2025-12-04T09:52:58.0628197Z 2025-12-04T09:52:58.0628567Z Finished inductor/test_triton_heuristics 1/1 ... [2025-12-04 09:52:58.062474][2520.748243604], took 0.14min 2025-12-04T09:52:59.0127743Z 2025-12-04T09:52:59.0129320Z inductor/test_cutedsl_grouped_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutedsl_grouped_mm_1.1_7235d82fb35c4d23_.log 2025-12-04T09:52:59.0130649Z Running 0 items in this shard: 2025-12-04T09:52:59.0130992Z 2025-12-04T09:52:59.0131590Z Finished inductor/test_cutedsl_grouped_mm 1/1 ... [2025-12-04 09:52:59.012712][2521.698481754], took 0.06min 2025-12-04T09:52:59.0276433Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cutedsl_grouped_mm/inductor.test_cutedsl_grouped_mm-3a2539f72a32b4c2.xml 2025-12-04T09:53:00.5569638Z W1204 09:53:00.556000 17148 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:01.4488780Z W1204 09:53:01.448000 17206 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:01.9282565Z Running inductor/test_cpp_wrapper_hipify 1/1 ... [2025-12-04 09:53:01.927808][2524.613576911] 2025-12-04T09:53:01.9283205Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:01.9286504Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_cpp_wrapper_hipify.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:01.928327] 2025-12-04T09:53:02.8827920Z Running inductor/test_template_heuristics_registry 1/1 ... [2025-12-04 09:53:02.882244][2525.568011681] 2025-12-04T09:53:02.8829134Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:02.8831555Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_template_heuristics_registry.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:02.882700] 2025-12-04T09:53:05.3419199Z 2025-12-04T09:53:05.3420757Z inductor/test_cpp_wrapper_hipify 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpp_wrapper_hipify_1.1_0f55a38baa777860_.log 2025-12-04T09:53:05.3422258Z Running 0 items in this shard: 2025-12-04T09:53:05.3422614Z 2025-12-04T09:53:05.3423413Z Finished inductor/test_cpp_wrapper_hipify 1/1 ... [2025-12-04 09:53:05.341752][2528.027519233], took 0.06min 2025-12-04T09:53:05.3563757Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_cpp_wrapper_hipify/inductor.test_cpp_wrapper_hipify-80bb8cd4545c1bd6.xml 2025-12-04T09:53:07.2538047Z 2025-12-04T09:53:07.2539418Z inductor/test_template_heuristics_registry 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_template_heuristics_registry_1.1_a6d55bf52edbc0f4_.log 2025-12-04T09:53:07.2540488Z Running 0 items in this shard: 2025-12-04T09:53:07.2540689Z 2025-12-04T09:53:07.2541139Z Finished inductor/test_template_heuristics_registry 1/1 ... [2025-12-04 09:53:07.253667][2529.939436265], took 0.07min 2025-12-04T09:53:07.2689217Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_template_heuristics_registry/inductor.test_template_heuristics_registry-80646c38d2382cff.xml 2025-12-04T09:53:07.7972884Z W1204 09:53:07.796000 17407 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:09.1911261Z Running inductor/test_async_compile 1/1 ... [2025-12-04 09:53:09.190653][2531.876422396] 2025-12-04T09:53:09.1911918Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:09.1914937Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_async_compile.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:09.191103] 2025-12-04T09:53:09.6661646Z W1204 09:53:09.665000 17521 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:11.0597908Z Running inductor/test_gpu_cpp_wrapper 1/1 ... [2025-12-04 09:53:11.059345][2533.74511362] 2025-12-04T09:53:11.0598663Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:11.0600671Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_gpu_cpp_wrapper.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:11.059774] 2025-12-04T09:53:17.7466020Z 2025-12-04T09:53:17.7467253Z inductor/test_async_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_async_compile_1.1_9a401f9b2123cb79_.log 2025-12-04T09:53:17.7468214Z Running 0 items in this shard: 2025-12-04T09:53:17.7468415Z 2025-12-04T09:53:17.7468766Z Finished inductor/test_async_compile 1/1 ... [2025-12-04 09:53:17.746492][2540.432261759], took 0.14min 2025-12-04T09:53:17.7616872Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_async_compile/inductor.test_async_compile-d7a7f53faaff1266.xml 2025-12-04T09:53:19.7741100Z 2025-12-04T09:53:19.7742175Z inductor/test_gpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_gpu_cpp_wrapper_1.1_d4d3e22ad5223ac8_.log 2025-12-04T09:53:19.7743212Z 2025-12-04T09:53:19.7743587Z Finished inductor/test_gpu_cpp_wrapper 1/1 ... [2025-12-04 09:53:19.773904][2542.459671235], took 0.15min 2025-12-04T09:53:20.2083281Z W1204 09:53:20.207000 18092 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:21.6356456Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-12-04 09:53:21.635164][2544.320932788] 2025-12-04T09:53:21.6357107Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:21.6359312Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:21.635601] 2025-12-04T09:53:22.2181895Z W1204 09:53:22.217000 18205 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:23.5665317Z Running dynamo/test_deque_reconstruct 1/1 ... [2025-12-04 09:53:23.566050][2546.25181778] 2025-12-04T09:53:23.5665907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:23.5669825Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_deque_reconstruct.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:23.566559] 2025-12-04T09:53:26.9203112Z 2025-12-04T09:53:26.9204731Z 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_e801cb6092770fb3_.log 2025-12-04T09:53:26.9206210Z Running 0 items in this shard: 2025-12-04T09:53:26.9206529Z 2025-12-04T09:53:26.9207086Z Finished dynamo/test_deque_reconstruct 1/1 ... [2025-12-04 09:53:26.920265][2549.606032323], took 0.06min 2025-12-04T09:53:26.9356599Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_deque_reconstruct/dynamo.test_deque_reconstruct-3dd27a0102c32359.xml 2025-12-04T09:53:29.3844980Z W1204 09:53:29.383000 18525 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:30.7513523Z Running inductor/test_indexing 1/1 ... [2025-12-04 09:53:30.750930][2553.436699312] 2025-12-04T09:53:30.7514114Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:30.7516958Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:30.751413] 2025-12-04T09:53:31.8547160Z 2025-12-04T09:53:31.8548976Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_9ef004d4af395d99_.log 2025-12-04T09:53:31.8550026Z Running 0 items in this shard: 2025-12-04T09:53:31.8550241Z 2025-12-04T09:53:31.8550676Z Finished export/test_export_training_ir_to_run_decomp 1/1 ... [2025-12-04 09:53:31.854645][2554.540415573], took 0.17min 2025-12-04T09:53:31.8697791Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_export_training_ir_to_run_decomp/export.test_export_training_ir_to_run_decomp-dfbb7ce1fc288a1b.xml 2025-12-04T09:53:34.2762964Z W1204 09:53:34.275000 18813 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:35.6838160Z Running inductor/test_inductor_annotations 1/1 ... [2025-12-04 09:53:35.683340][2558.369108469] 2025-12-04T09:53:35.6838777Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:35.6841611Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inductor_annotations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:35.683818] 2025-12-04T09:53:39.2605268Z 2025-12-04T09:53:39.2606542Z inductor/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_indexing_1.1_134c0437875b4d26_.log 2025-12-04T09:53:39.2607869Z Running 0 items in this shard: 2025-12-04T09:53:39.2608074Z 2025-12-04T09:53:39.2608645Z Finished inductor/test_indexing 1/1 ... [2025-12-04 09:53:39.260446][2561.946215855], took 0.14min 2025-12-04T09:53:39.2760069Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_indexing/inductor.test_indexing-2a3f17d13afa8880.xml 2025-12-04T09:53:41.7419592Z W1204 09:53:41.741000 19193 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:43.1502368Z Running inductor/test_compile_worker 1/1 ... [2025-12-04 09:53:43.149672][2565.835436782] 2025-12-04T09:53:43.1503432Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:43.1506684Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_compile_worker.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:43.150153] 2025-12-04T09:53:44.2293715Z 2025-12-04T09:53:44.2295377Z inductor/test_inductor_annotations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_annotations_1.1_09f017e275161662_.log 2025-12-04T09:53:44.2296945Z Running 0 items in this shard: 2025-12-04T09:53:44.2297295Z 2025-12-04T09:53:44.2297951Z Finished inductor/test_inductor_annotations 1/1 ... [2025-12-04 09:53:44.229253][2566.915016077], took 0.14min 2025-12-04T09:53:44.2454278Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_inductor_annotations/inductor.test_inductor_annotations-f689abcd09a6b245.xml 2025-12-04T09:53:46.6417668Z W1204 09:53:46.641000 19401 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:48.0397714Z Running dynamo/test_einops 1/1 ... [2025-12-04 09:53:48.039376][2570.725145443] 2025-12-04T09:53:48.0398244Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:48.0401083Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:48.039810] 2025-12-04T09:53:51.4638667Z 2025-12-04T09:53:51.4640115Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_72df752068205edf_.log 2025-12-04T09:53:51.4641048Z Running 0 items in this shard: 2025-12-04T09:53:51.4641246Z 2025-12-04T09:53:51.4641640Z Finished dynamo/test_einops 1/1 ... [2025-12-04 09:53:51.463769][2574.149539737], took 0.06min 2025-12-04T09:53:51.4893291Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_compile_worker/inductor.test_compile_worker-749500fbb975cff6.xml 2025-12-04T09:53:51.5618497Z 2025-12-04T09:53:51.5619831Z inductor/test_compile_worker 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_worker_1.1_6856344a13a36575_.log 2025-12-04T09:53:51.5621224Z Running 0 items in this shard: 2025-12-04T09:53:51.5621542Z 2025-12-04T09:53:51.5622033Z Finished inductor/test_compile_worker 1/1 ... [2025-12-04 09:53:51.561771][2574.247539522], took 0.14min 2025-12-04T09:53:51.5654443Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_einops/dynamo.test_einops-21b7db6425d3ac4f.xml 2025-12-04T09:53:53.9048644Z W1204 09:53:53.904000 19810 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:54.0545497Z W1204 09:53:54.053000 19811 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:53:55.2805026Z Running inductor/test_external_callables 1/1 ... [2025-12-04 09:53:55.280109][2577.965878912] 2025-12-04T09:53:55.2805628Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:55.2809375Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_external_callables.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:55.280607] 2025-12-04T09:53:55.4334218Z Running test_testing 1/1 ... [2025-12-04 09:53:55.432997][2578.118766452] 2025-12-04T09:53:55.4334872Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:53:55.4337650Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_testing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:53:55.433441] 2025-12-04T09:53:59.0498149Z 2025-12-04T09:53:59.0499665Z 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_4723ce9f1d0c3622_.log 2025-12-04T09:53:59.0500665Z Running 0 items in this shard: 2025-12-04T09:53:59.0500863Z 2025-12-04T09:53:59.0501252Z Finished inductor/test_external_callables 1/1 ... [2025-12-04 09:53:59.049708][2581.735477779], took 0.06min 2025-12-04T09:53:59.0665582Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_external_callables/inductor.test_external_callables-09de63d32c02f668.xml 2025-12-04T09:54:00.6018824Z 2025-12-04T09:54:00.6020405Z test_testing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_testing_1.1_8859fec879b62ea5_.log 2025-12-04T09:54:00.6035248Z Running 50 items in this shard: test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies, test/test_testing.py::TestImports::test_circular_dependencies 2025-12-04T09:54:00.6050306Z 2025-12-04T09:54:00.6050584Z Finished test_testing 1/1 ... [2025-12-04 09:54:00.601860][2583.287629187], took 0.09min 2025-12-04T09:54:00.6330669Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_testing/test_testing-aec75934a2a37fab.xml 2025-12-04T09:54:01.4836403Z W1204 09:54:01.482000 20139 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:02.9011491Z Running dynamo/test_fx_passes_pre_grad 1/1 ... [2025-12-04 09:54:02.900621][2585.586385446] 2025-12-04T09:54:02.9012568Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:02.9015714Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_fx_passes_pre_grad.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:02.901094] 2025-12-04T09:54:02.9953352Z W1204 09:54:02.994000 20203 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:04.3937719Z Running export/test_strict_export_v2 1/1 ... [2025-12-04 09:54:04.393367][2587.07913633] 2025-12-04T09:54:04.3938271Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:04.3941042Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_strict_export_v2.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:04.393797] 2025-12-04T09:54:06.3514236Z 2025-12-04T09:54:06.3515653Z dynamo/test_fx_passes_pre_grad 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_passes_pre_grad_1.1_d4967d25cb80b3ef_.log 2025-12-04T09:54:06.3516788Z Running 0 items in this shard: 2025-12-04T09:54:06.3517009Z 2025-12-04T09:54:06.3517593Z Finished dynamo/test_fx_passes_pre_grad 1/1 ... [2025-12-04 09:54:06.351339][2589.037108646], took 0.06min 2025-12-04T09:54:06.3682146Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_fx_passes_pre_grad/dynamo.test_fx_passes_pre_grad-dc47f978e416cac8.xml 2025-12-04T09:54:08.7350796Z W1204 09:54:08.734000 20483 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:10.1610451Z Running inductor/test_flex_flash 1/1 ... [2025-12-04 09:54:10.160572][2592.846340746] 2025-12-04T09:54:10.1611390Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:10.1615123Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_flex_flash.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:10.161080] 2025-12-04T09:54:13.7337067Z 2025-12-04T09:54:13.7338614Z export/test_strict_export_v2 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_strict_export_v2_1.1_838097c100ec3680_.log 2025-12-04T09:54:13.7339971Z Running 0 items in this shard: 2025-12-04T09:54:13.7340282Z 2025-12-04T09:54:13.7340780Z Finished export/test_strict_export_v2 1/1 ... [2025-12-04 09:54:13.733682][2596.419448599], took 0.16min 2025-12-04T09:54:13.7511132Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_strict_export_v2/export.test_strict_export_v2-dc262f99d1f3934c.xml 2025-12-04T09:54:14.9250143Z 2025-12-04T09:54:14.9251178Z inductor/test_flex_flash 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_flash_1.1_61b373f1edb19175_.log 2025-12-04T09:54:14.9252070Z Running 0 items in this shard: 2025-12-04T09:54:14.9252268Z 2025-12-04T09:54:14.9252583Z Finished inductor/test_flex_flash 1/1 ... [2025-12-04 09:54:14.924936][2597.610705833], took 0.08min 2025-12-04T09:54:14.9495134Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_flex_flash/inductor.test_flex_flash-13735eb078201b06.xml 2025-12-04T09:54:16.2059545Z W1204 09:54:16.204000 20813 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:17.3832528Z W1204 09:54:17.382000 20829 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:17.5792569Z Running inductor/test_selective_lowering 1/1 ... [2025-12-04 09:54:17.578784][2600.264553975] 2025-12-04T09:54:17.5793157Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:17.5795665Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_selective_lowering.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:17.579208] 2025-12-04T09:54:18.7759386Z Running inductor/test_inductor_scheduler 1/1 ... [2025-12-04 09:54:18.775512][2601.461278987] 2025-12-04T09:54:18.7759987Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:18.7763019Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inductor_scheduler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:18.776002] 2025-12-04T09:54:25.9762430Z 2025-12-04T09:54:25.9763716Z inductor/test_selective_lowering 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_selective_lowering_1.1_93b07e4f70177c9c_.log 2025-12-04T09:54:25.9764667Z 2025-12-04T09:54:25.9765035Z Finished inductor/test_selective_lowering 1/1 ... [2025-12-04 09:54:25.976221][2608.661988764], took 0.14min 2025-12-04T09:54:27.9031178Z 2025-12-04T09:54:27.9032503Z inductor/test_inductor_scheduler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_scheduler_1.1_5de1f937cad4f6df_.log 2025-12-04T09:54:27.9033922Z Running 0 items in this shard: 2025-12-04T09:54:27.9034249Z 2025-12-04T09:54:27.9034904Z Finished inductor/test_inductor_scheduler 1/1 ... [2025-12-04 09:54:27.903043][2610.588811395], took 0.15min 2025-12-04T09:54:27.9209861Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_inductor_scheduler/inductor.test_inductor_scheduler-da4f8b04d74b2c76.xml 2025-12-04T09:54:28.4092623Z W1204 09:54:28.408000 21491 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:29.8265864Z Running inductor/test_inplace_padding 1/1 ... [2025-12-04 09:54:29.826146][2612.511913856] 2025-12-04T09:54:29.8266469Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:29.8269658Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inplace_padding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:29.826583] 2025-12-04T09:54:30.3455205Z W1204 09:54:30.344000 21514 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:31.6885464Z Running inductor/test_control_deps 1/1 ... [2025-12-04 09:54:31.688090][2614.37385903] 2025-12-04T09:54:31.6886024Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:31.6889725Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_control_deps.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:31.688579] 2025-12-04T09:54:38.3598645Z 2025-12-04T09:54:38.3600196Z 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_42c5ded3404afcfa_.log 2025-12-04T09:54:38.3601444Z 2025-12-04T09:54:38.3602042Z Finished inductor/test_inplace_padding 1/1 ... [2025-12-04 09:54:38.359739][2621.04550004], took 0.14min 2025-12-04T09:54:39.9938472Z 2025-12-04T09:54:39.9940014Z inductor/test_control_deps 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_control_deps_1.1_1dfb9d9f24999a49_.log 2025-12-04T09:54:39.9940816Z 2025-12-04T09:54:39.9941170Z Finished inductor/test_control_deps 1/1 ... [2025-12-04 09:54:39.993692][2622.67945472], took 0.14min 2025-12-04T09:54:40.7823184Z W1204 09:54:40.781000 22133 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:42.1734172Z Running inductor/test_inplacing_pass 1/1 ... [2025-12-04 09:54:42.172885][2624.858649759] 2025-12-04T09:54:42.1734840Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:42.1736960Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:42.173372] 2025-12-04T09:54:42.4243003Z W1204 09:54:42.423000 22197 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:43.8111902Z Running inductor/test_profiler 1/1 ... [2025-12-04 09:54:43.810755][2626.496523329] 2025-12-04T09:54:43.8112627Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:43.8115238Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:43.811191] 2025-12-04T09:54:50.4702192Z 2025-12-04T09:54:50.4703664Z 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_4fc0f9f58a1be248_.log 2025-12-04T09:54:50.4704902Z 2025-12-04T09:54:50.4705519Z Finished inductor/test_inplacing_pass 1/1 ... [2025-12-04 09:54:50.470095][2633.155865067], took 0.14min 2025-12-04T09:54:52.3077694Z 2025-12-04T09:54:52.3078756Z inductor/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_profiler_1.1_30d19c62d7ed2752_.log 2025-12-04T09:54:52.3079550Z 2025-12-04T09:54:52.3079870Z Finished inductor/test_profiler 1/1 ... [2025-12-04 09:54:52.307645][2634.993408744], took 0.14min 2025-12-04T09:54:52.9257458Z W1204 09:54:52.924000 22721 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:54.3328246Z Running inductor/test_aot_inductor_utils 1/1 ... [2025-12-04 09:54:54.332405][2637.018170895] 2025-12-04T09:54:54.3328841Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:54.3332554Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_aot_inductor_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:54.332922] 2025-12-04T09:54:54.7009434Z W1204 09:54:54.700000 22834 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:54:56.1047741Z Running dynamo/test_cudagraphs 1/1 ... [2025-12-04 09:54:56.104304][2638.79007253] 2025-12-04T09:54:56.1048714Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:54:56.1051982Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:54:56.104780] 2025-12-04T09:54:59.6475283Z 2025-12-04T09:54:59.6476572Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_cf7af4759b2e340b_.log 2025-12-04T09:54:59.6477646Z 2025-12-04T09:54:59.6477970Z Finished dynamo/test_cudagraphs 1/1 ... [2025-12-04 09:54:59.647479][2642.333237751], took 0.06min 2025-12-04T09:55:02.1225326Z W1204 09:55:02.121000 23154 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:02.8182104Z 2025-12-04T09:55:02.8183419Z inductor/test_aot_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_utils_1.1_5dddfd1526d183a4_.log 2025-12-04T09:55:02.8184602Z Running 0 items in this shard: 2025-12-04T09:55:02.8184956Z 2025-12-04T09:55:02.8185425Z Finished inductor/test_aot_inductor_utils 1/1 ... [2025-12-04 09:55:02.818201][2645.503966841], took 0.14min 2025-12-04T09:55:02.8360918Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_aot_inductor_utils/inductor.test_aot_inductor_utils-c373f3e82592c7ac.xml 2025-12-04T09:55:03.5131116Z Running inductor/test_custom_partitioner_fn 1/1 ... [2025-12-04 09:55:03.512632][2646.198399453] 2025-12-04T09:55:03.5132212Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:03.5135520Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'inductor/test_custom_partitioner_fn.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:03.513132] 2025-12-04T09:55:05.2592530Z W1204 09:55:05.258000 23331 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:06.6269980Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-12-04 09:55:06.626569][2649.312338181] 2025-12-04T09:55:06.6270777Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:06.6273673Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:06.627011] 2025-12-04T09:55:10.6014851Z 2025-12-04T09:55:10.6016038Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_5e04b1e64eaf7f7d_.log 2025-12-04T09:55:10.6017021Z 2025-12-04T09:55:10.6017463Z Finished dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-12-04 09:55:10.601379][2653.28714574], took 0.07min 2025-12-04T09:55:11.9130749Z 2025-12-04T09:55:11.9131958Z inductor/test_custom_partitioner_fn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_custom_partitioner_fn_1.1_6a93f4471ee1c97f_.log 2025-12-04T09:55:11.9132838Z 2025-12-04T09:55:11.9133262Z Finished inductor/test_custom_partitioner_fn 1/1 ... [2025-12-04 09:55:11.912936][2654.598704939], took 0.14min 2025-12-04T09:55:13.0462184Z W1204 09:55:13.045000 23715 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:14.3095854Z W1204 09:55:14.308000 23777 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:14.4788194Z Running dynamo/test_minifier 1/1 ... [2025-12-04 09:55:14.478355][2657.164124459] 2025-12-04T09:55:14.4789021Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:14.4793252Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'dynamo/test_minifier.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:14.478879] 2025-12-04T09:55:15.6978994Z Running export/test_sparse 2/2 ... [2025-12-04 09:55:15.697468][2658.383236581] 2025-12-04T09:55:15.6979705Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:15.6981861Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'export/test_sparse.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:15.697884] 2025-12-04T09:55:18.1712993Z 2025-12-04T09:55:18.1714245Z dynamo/test_minifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_minifier_1.1_770ebb0192aa24c1_.log 2025-12-04T09:55:18.1715117Z Running 0 items in this shard: 2025-12-04T09:55:18.1715334Z 2025-12-04T09:55:18.1715634Z Finished dynamo/test_minifier 1/1 ... [2025-12-04 09:55:18.171306][2660.857072572], took 0.06min 2025-12-04T09:55:18.1894747Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/dynamo.test_minifier/dynamo.test_minifier-24d5c54c76b91a9c.xml 2025-12-04T09:55:19.5215431Z 2025-12-04T09:55:19.5222561Z export/test_sparse 2/2 was successful, full logs can be found in artifacts with path test/test-reports/export.test_sparse_2.2_35b56cfe94ef5e5a_.log 2025-12-04T09:55:19.5231530Z Running 0 items in this shard: 2025-12-04T09:55:19.5236733Z 2025-12-04T09:55:19.5242835Z Finished export/test_sparse 2/2 ... [2025-12-04 09:55:19.523801][2662.209566183], took 0.06min 2025-12-04T09:55:19.5470013Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/export.test_sparse/export.test_sparse-cf026e127a56a8a3.xml 2025-12-04T09:55:20.6540374Z W1204 09:55:20.653000 24069 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:21.9017537Z W1204 09:55:21.901000 24085 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:22.0551082Z Running test_foreach 1/1 ... [2025-12-04 09:55:22.054686][2664.740455086] 2025-12-04T09:55:22.0551592Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:22.0554286Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_foreach.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:22.055124] 2025-12-04T09:55:23.3244307Z Running xpu/test_gemm 1/1 ... [2025-12-04 09:55:23.324023][2666.009792146] 2025-12-04T09:55:23.3244904Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:23.3247666Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'xpu/test_gemm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:23.324495] 2025-12-04T09:55:27.5723079Z 2025-12-04T09:55:27.5724123Z xpu/test_gemm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_gemm_1.1_149ddf41512f27ed_.log 2025-12-04T09:55:27.5725101Z Running 0 items in this shard: 2025-12-04T09:55:27.5725407Z 2025-12-04T09:55:27.5725684Z Finished xpu/test_gemm 1/1 ... [2025-12-04 09:55:27.572206][2670.257977325], took 0.07min 2025-12-04T09:55:27.5911211Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/xpu.test_gemm/xpu.test_gemm-d70ce9e4565f6727.xml 2025-12-04T09:55:29.9931442Z W1204 09:55:29.992000 24516 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:31.3544728Z Running xpu/test_conv 1/1 ... [2025-12-04 09:55:31.353999][2674.039767376] 2025-12-04T09:55:31.3545424Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:31.3548958Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'xpu/test_conv.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:31.354514] 2025-12-04T09:55:31.6833203Z 2025-12-04T09:55:31.6834191Z test_foreach 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_foreach_1.1_b0c59c7b3e3cf71b_.log 2025-12-04T09:55:31.6835438Z Running 0 items in this shard: 2025-12-04T09:55:31.6835733Z 2025-12-04T09:55:31.6835995Z Finished test_foreach 1/1 ... [2025-12-04 09:55:31.683295][2674.369061348], took 0.16min 2025-12-04T09:55:31.7229233Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_foreach/test_foreach-b620f60a12c334ca.xml 2025-12-04T09:55:34.1850956Z W1204 09:55:34.184000 24709 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:35.4581126Z 2025-12-04T09:55:35.4582129Z xpu/test_conv 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_conv_1.1_158d1647a24884ba_.log 2025-12-04T09:55:35.4582903Z Running 0 items in this shard: 2025-12-04T09:55:35.4583101Z 2025-12-04T09:55:35.4583363Z Finished xpu/test_conv 1/1 ... [2025-12-04 09:55:35.458033][2678.143804153], took 0.07min 2025-12-04T09:55:35.4769859Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/xpu.test_conv/xpu.test_conv-1f89db39166eef5a.xml 2025-12-04T09:55:35.6034574Z Running test_numpy_interop 1/1 ... [2025-12-04 09:55:35.603043][2678.288811356] 2025-12-04T09:55:35.6035266Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:35.6038332Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numpy_interop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:35.603495] 2025-12-04T09:55:37.9173079Z W1204 09:55:37.916000 24890 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:39.2944997Z Running test_modules 1/1 ... [2025-12-04 09:55:39.294054][2681.979822998] 2025-12-04T09:55:39.2945507Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:39.2948559Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:39.294529] 2025-12-04T09:55:39.3641523Z 2025-12-04T09:55:39.3642712Z test_numpy_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numpy_interop_1.1_56632a59b6fcf7d9_.log 2025-12-04T09:55:39.3643542Z Running 0 items in this shard: 2025-12-04T09:55:39.3643772Z 2025-12-04T09:55:39.3644084Z Finished test_numpy_interop 1/1 ... [2025-12-04 09:55:39.363999][2682.049768378], took 0.06min 2025-12-04T09:55:39.3829909Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numpy_interop/test_numpy_interop-07b23064b377abd4.xml 2025-12-04T09:55:41.8568664Z W1204 09:55:41.856000 24984 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:43.2537435Z Running nn/test_packed_sequence 1/1 ... [2025-12-04 09:55:43.253305][2685.93907487] 2025-12-04T09:55:43.2538000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:43.2541150Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:43.253747] 2025-12-04T09:55:44.2034925Z 2025-12-04T09:55:44.2036097Z test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.1_289a575f96146297_.log 2025-12-04T09:55:44.2036858Z Running 0 items in this shard: 2025-12-04T09:55:44.2037072Z 2025-12-04T09:55:44.2037327Z Finished test_modules 1/1 ... [2025-12-04 09:55:44.203453][2686.889221865], took 0.08min 2025-12-04T09:55:44.2236792Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_modules/test_modules-06a4685e72fb43fa.xml 2025-12-04T09:55:46.6700425Z W1204 09:55:46.669000 25273 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:46.7125180Z 2025-12-04T09:55:46.7126388Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_42f52ad52fefeaed_.log 2025-12-04T09:55:46.7127497Z Running 0 items in this shard: 2025-12-04T09:55:46.7127817Z 2025-12-04T09:55:46.7128352Z Finished nn/test_packed_sequence 1/1 ... [2025-12-04 09:55:46.712464][2689.398227169], took 0.06min 2025-12-04T09:55:46.7320762Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_packed_sequence/nn.test_packed_sequence-0d67da53fa703807.xml 2025-12-04T09:55:48.0955493Z Running test_numa_binding 1/1 ... [2025-12-04 09:55:48.095169][2690.780937916] 2025-12-04T09:55:48.0956015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:48.0959499Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numa_binding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:48.095604] 2025-12-04T09:55:49.1326783Z W1204 09:55:49.131000 25339 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:50.5025433Z Running test_pruning_op 1/1 ... [2025-12-04 09:55:50.502092][2693.187861513] 2025-12-04T09:55:50.5025928Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:50.5029124Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_pruning_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:50.502591] 2025-12-04T09:55:51.6053468Z 2025-12-04T09:55:51.6054904Z test_numa_binding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numa_binding_1.1_be4560836468dfa3_.log 2025-12-04T09:55:51.6055714Z Running 0 items in this shard: 2025-12-04T09:55:51.6055913Z 2025-12-04T09:55:51.6056190Z Finished test_numa_binding 1/1 ... [2025-12-04 09:55:51.605264][2694.291034274], took 0.06min 2025-12-04T09:55:51.6258549Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numa_binding/test_numa_binding-5641d3c9c03725ce.xml 2025-12-04T09:55:53.9873403Z 2025-12-04T09:55:53.9874563Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_3c71749e47c8fcde_.log 2025-12-04T09:55:53.9875404Z Running 0 items in this shard: 2025-12-04T09:55:53.9875604Z 2025-12-04T09:55:53.9875888Z Finished test_pruning_op 1/1 ... [2025-12-04 09:55:53.987314][2696.673080049], took 0.06min 2025-12-04T09:55:54.0112401Z W1204 09:55:54.010000 25534 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:54.0234731Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_pruning_op/test_pruning_op-536a115ec88db560.xml 2025-12-04T09:55:55.4193253Z Running test_jit_fuser_te 1/1 ... [2025-12-04 09:55:55.418911][2698.104680066] 2025-12-04T09:55:55.4194215Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:55.4196728Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit_fuser_te.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:55.419342] 2025-12-04T09:55:56.4349081Z W1204 09:55:56.434000 25647 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:55:57.7831810Z Running test_logging 1/1 ... [2025-12-04 09:55:57.782704][2700.468472011] 2025-12-04T09:55:57.7832684Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:55:57.7835692Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:55:57.783140] 2025-12-04T09:56:01.1437868Z 2025-12-04T09:56:01.1438797Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_b75b80ee6576f5aa_.log 2025-12-04T09:56:01.1439556Z Running 0 items in this shard: 2025-12-04T09:56:01.1439777Z 2025-12-04T09:56:01.1440065Z Finished test_logging 1/1 ... [2025-12-04 09:56:01.143772][2703.829536317], took 0.06min 2025-12-04T09:56:01.1641990Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_logging/test_logging-32407c1d89ea4825.xml 2025-12-04T09:56:03.1201030Z 2025-12-04T09:56:03.1202251Z test_jit_fuser_te 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_fuser_te_1.1_8e7f041c9c177e4d_.log 2025-12-04T09:56:03.1250578Z Running 150 items in this shard: test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserStatic::test_torch_to, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_inlined_optimized_graph, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check, test/test_jit_fuser_te.py::TestTEFuserDynamic::test_skip_grad_in_check 2025-12-04T09:56:03.1295745Z 2025-12-04T09:56:03.1296023Z Finished test_jit_fuser_te 1/1 ... [2025-12-04 09:56:03.120450][2705.806216076], took 0.13min 2025-12-04T09:56:03.1409821Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit_fuser_te/test_jit_fuser_te-f1e30e4a142755a8.xml 2025-12-04T09:56:03.5872424Z W1204 09:56:03.586000 25989 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:04.9964883Z Running nn/test_lazy_modules 1/1 ... [2025-12-04 09:56:04.996030][2707.681799436] 2025-12-04T09:56:04.9965749Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:04.9969935Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:04.996547] 2025-12-04T09:56:05.5690911Z W1204 09:56:05.568000 26018 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:06.9603775Z Running nn/test_pruning 1/1 ... [2025-12-04 09:56:06.959909][2709.645675865] 2025-12-04T09:56:06.9604445Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:06.9609662Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_pruning.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:06.960402] 2025-12-04T09:56:08.8901799Z 2025-12-04T09:56:08.8902947Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_5695e2c312af1a72_.log 2025-12-04T09:56:08.8903890Z Running 0 items in this shard: 2025-12-04T09:56:08.8904209Z 2025-12-04T09:56:08.8904517Z Finished nn/test_lazy_modules 1/1 ... [2025-12-04 09:56:08.890056][2711.575827291], took 0.06min 2025-12-04T09:56:08.9105552Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_lazy_modules/nn.test_lazy_modules-f0a15d2ee1b4cfc5.xml 2025-12-04T09:56:10.8005747Z 2025-12-04T09:56:10.8007231Z nn/test_pruning 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pruning_1.1_23015a09208fc244_.log 2025-12-04T09:56:10.8008621Z Running 0 items in this shard: 2025-12-04T09:56:10.8008969Z 2025-12-04T09:56:10.8009463Z Finished nn/test_pruning 1/1 ... [2025-12-04 09:56:10.800426][2713.486195877], took 0.06min 2025-12-04T09:56:10.8211992Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_pruning/nn.test_pruning-facd5adb85832e59.xml 2025-12-04T09:56:11.3475482Z W1204 09:56:11.346000 26261 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:12.7594590Z Running test_monitor 1/1 ... [2025-12-04 09:56:12.759042][2715.444810823] 2025-12-04T09:56:12.7595095Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:12.7598005Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_monitor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:12.759494] 2025-12-04T09:56:13.3646806Z W1204 09:56:13.363000 26368 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:14.7407416Z Running test_bundled_inputs 1/1 ... [2025-12-04 09:56:14.740317][2717.426085879] 2025-12-04T09:56:14.7408259Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:14.7411390Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_bundled_inputs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:14.740800] 2025-12-04T09:56:16.2016934Z 2025-12-04T09:56:16.2018224Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_0aa23cd893c2f876_.log 2025-12-04T09:56:16.2018990Z Running 0 items in this shard: 2025-12-04T09:56:16.2019340Z 2025-12-04T09:56:16.2019602Z Finished test_monitor 1/1 ... [2025-12-04 09:56:16.201582][2718.887349638], took 0.06min 2025-12-04T09:56:16.2230563Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_monitor/test_monitor-217bd9764e6f99f8.xml 2025-12-04T09:56:18.3139953Z 2025-12-04T09:56:18.3141043Z test_bundled_inputs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_bundled_inputs_1.1_27e9f61c704dc51d_.log 2025-12-04T09:56:18.3141883Z Running 0 items in this shard: 2025-12-04T09:56:18.3142082Z 2025-12-04T09:56:18.3142607Z Finished test_bundled_inputs 1/1 ... [2025-12-04 09:56:18.313880][2720.999649706], took 0.06min 2025-12-04T09:56:18.3350437Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_bundled_inputs/test_bundled_inputs-392758be939dfbd2.xml 2025-12-04T09:56:18.6107623Z W1204 09:56:18.610000 26569 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:20.1082011Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-12-04 09:56:20.107717][2722.793484871] 2025-12-04T09:56:20.1083065Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:20.1085966Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:20.108181] 2025-12-04T09:56:20.7599629Z W1204 09:56:20.759000 26634 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:22.1220496Z Running torch_np/numpy_tests/core/test_multiarray 1/1 ... [2025-12-04 09:56:22.121564][2724.807333225] 2025-12-04T09:56:22.1221541Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:22.1225084Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_multiarray.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:22.122086] 2025-12-04T09:56:24.2112108Z 2025-12-04T09:56:24.2113723Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_db05759f977fd0c8_.log 2025-12-04T09:56:24.2115264Z Running 0 items in this shard: 2025-12-04T09:56:24.2115623Z 2025-12-04T09:56:24.2116257Z Finished torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-12-04 09:56:24.211085][2726.896854396], took 0.07min 2025-12-04T09:56:24.2331841Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_numeric/torch_np.numpy_tests.core.test_numeric-b9e3ab0aef0e9a51.xml 2025-12-04T09:56:26.6049625Z W1204 09:56:26.604000 26913 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:27.4820329Z 2025-12-04T09:56:27.4822189Z torch_np/numpy_tests/core/test_multiarray 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_multiarray_1.1_c2caf71f9d9dec6b_.log 2025-12-04T09:56:27.4823262Z Running 0 items in this shard: 2025-12-04T09:56:27.4823463Z 2025-12-04T09:56:27.4823875Z Finished torch_np/numpy_tests/core/test_multiarray 1/1 ... [2025-12-04 09:56:27.481896][2730.16766577], took 0.09min 2025-12-04T09:56:27.5037605Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_multiarray/torch_np.numpy_tests.core.test_multiarray-f4690cafe9a000f5.xml 2025-12-04T09:56:27.9875289Z Running test_itt 1/1 ... [2025-12-04 09:56:27.987120][2730.672888154] 2025-12-04T09:56:27.9876006Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:27.9880086Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_itt.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:27.987631] 2025-12-04T09:56:29.9478084Z W1204 09:56:29.947000 26991 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:31.3043671Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-12-04 09:56:31.303838][2733.989607017] 2025-12-04T09:56:31.3044892Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:31.3048254Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:31.304395] 2025-12-04T09:56:31.3501614Z 2025-12-04T09:56:31.3502864Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_7b40395800656001_.log 2025-12-04T09:56:31.3504165Z Running 0 items in this shard: 2025-12-04T09:56:31.3504510Z 2025-12-04T09:56:31.3504887Z Finished test_itt 1/1 ... [2025-12-04 09:56:31.350120][2734.035887415], took 0.06min 2025-12-04T09:56:31.3855080Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_itt/test_itt-b37ed021ce55eb04.xml 2025-12-04T09:56:33.8274939Z W1204 09:56:33.826000 27184 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:35.1777846Z Running test_sympy_utils 1/1 ... [2025-12-04 09:56:35.177376][2737.863144049] 2025-12-04T09:56:35.1778364Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:35.1781336Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:35.177824] 2025-12-04T09:56:35.9914039Z 2025-12-04T09:56:35.9915552Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_8354a9f17cc9ef9b_.log 2025-12-04T09:56:35.9916601Z Running 0 items in this shard: 2025-12-04T09:56:35.9916815Z 2025-12-04T09:56:35.9917233Z Finished torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-12-04 09:56:35.991363][2738.67712439], took 0.08min 2025-12-04T09:56:36.0139237Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_function_base/torch_np.numpy_tests.lib.test_function_base-4e388136ab96b1af.xml 2025-12-04T09:56:38.3898304Z W1204 09:56:38.389000 27362 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:39.3095037Z 2025-12-04T09:56:39.3096643Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_dea07f0e6c9ba0b4_.log 2025-12-04T09:56:39.3097462Z Running 0 items in this shard: 2025-12-04T09:56:39.3097661Z 2025-12-04T09:56:39.3097933Z Finished test_sympy_utils 1/1 ... [2025-12-04 09:56:39.309449][2741.995210193], took 0.07min 2025-12-04T09:56:39.3316829Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_sympy_utils/test_sympy_utils-52025b80792f8166.xml 2025-12-04T09:56:39.7569958Z Running test_subclass 1/1 ... [2025-12-04 09:56:39.756524][2742.442292006] 2025-12-04T09:56:39.7570485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:39.7574495Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_subclass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:39.757041] 2025-12-04T09:56:41.8027772Z W1204 09:56:41.802000 27525 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:43.2192463Z Running test_import_stats 1/1 ... [2025-12-04 09:56:43.218852][2745.904620372] 2025-12-04T09:56:43.2192984Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:43.2196387Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_import_stats.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:43.219336] 2025-12-04T09:56:43.4672868Z 2025-12-04T09:56:43.4674105Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_5bc8ce7b44048195_.log 2025-12-04T09:56:43.4675281Z Running 0 items in this shard: 2025-12-04T09:56:43.4675576Z 2025-12-04T09:56:43.4675987Z Finished test_subclass 1/1 ... [2025-12-04 09:56:43.467221][2746.152990547], took 0.06min 2025-12-04T09:56:43.5043659Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_subclass/test_subclass-43269ef057ead224.xml 2025-12-04T09:56:45.8689770Z W1204 09:56:45.868000 27670 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:46.6793624Z 2025-12-04T09:56:46.6795062Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_d220e1ce342f91f1_.log 2025-12-04T09:56:46.6795873Z Running 0 items in this shard: 2025-12-04T09:56:46.6796082Z 2025-12-04T09:56:46.6796377Z Finished test_import_stats 1/1 ... [2025-12-04 09:56:46.679193][2749.364961593], took 0.06min 2025-12-04T09:56:46.7021196Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_import_stats/test_import_stats-7cd0431b43338c2c.xml 2025-12-04T09:56:47.2521933Z Running functorch/test_vmap_registrations 1/1 ... [2025-12-04 09:56:47.251672][2749.937441386] 2025-12-04T09:56:47.2522672Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:47.2524230Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:47.252098] 2025-12-04T09:56:49.1783660Z W1204 09:56:49.177000 27833 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:50.5292653Z Running nn/test_parametrization 1/1 ... [2025-12-04 09:56:50.528833][2753.214602411] 2025-12-04T09:56:50.5293639Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:50.5296940Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_parametrization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:50.529276] 2025-12-04T09:56:54.0459576Z 2025-12-04T09:56:54.0460627Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_2f81d0c0ee65cca1_.log 2025-12-04T09:56:54.0461968Z Running 0 items in this shard: 2025-12-04T09:56:54.0462165Z 2025-12-04T09:56:54.0462538Z Finished functorch/test_vmap_registrations 1/1 ... [2025-12-04 09:56:54.045772][2756.731542408], took 0.11min 2025-12-04T09:56:54.0838950Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.test_vmap_registrations/functorch.test_vmap_registrations-90a23accc9c4a4d1.xml 2025-12-04T09:56:54.1530004Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_parametrization/nn.test_parametrization-dd2b55c44478dcef.xml 2025-12-04T09:56:54.5265306Z 2025-12-04T09:56:54.5266362Z nn/test_parametrization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_parametrization_1.1_ab59b4b48a3d7588_.log 2025-12-04T09:56:54.5300643Z Running 50 items in this shard: test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True, test/nn/test_parametrization.py::TestNNParametrization::test_caching_parametrization_with_transfer_parametrizations_and_params_swap_True 2025-12-04T09:56:54.5334031Z 2025-12-04T09:56:54.5334373Z Finished nn/test_parametrization 1/1 ... [2025-12-04 09:56:54.526630][2757.212394858], took 0.07min 2025-12-04T09:56:56.5664963Z W1204 09:56:56.565000 28075 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:57.0668068Z W1204 09:56:57.066000 28160 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:56:57.9200680Z Running test_mkldnn_fusion 1/1 ... [2025-12-04 09:56:57.919681][2760.605449834] 2025-12-04T09:56:57.9201196Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:57.9204307Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:57.920116] 2025-12-04T09:56:58.4865757Z Running lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:56:58.486174][2761.171942044] 2025-12-04T09:56:58.4866297Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:56:58.4869287Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:56:58.486633] 2025-12-04T09:57:03.5186226Z 2025-12-04T09:57:03.5187271Z 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_5f8762cddb7a8ff2_.log 2025-12-04T09:57:03.5188084Z Running 0 items in this shard: 2025-12-04T09:57:03.5188295Z 2025-12-04T09:57:03.5188624Z Finished lazy/test_ts_opinfo 1/1 ... [2025-12-04 09:57:03.518424][2766.204186665], took 0.08min 2025-12-04T09:57:03.5307234Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-01446018fcaea56c.xml 2025-12-04T09:57:07.1468546Z W1204 09:57:07.145000 28453 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:57:09.2336755Z Running test_dynamic_shapes 1/1 ... [2025-12-04 09:57:09.233219][2771.918981536] 2025-12-04T09:57:09.2337415Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:57:09.2344567Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:57:09.233976] 2025-12-04T09:57:29.9150674Z 2025-12-04T09:57:29.9152077Z PRINTING LOG FILE of test_dynamic_shapes 1/1 (test/test-reports/test_dynamic_shapes_1.1_219280898da3781a_.log) 2025-12-04T09:57:29.9154050Z W1204 09:57:13.433000 28614 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:57:29.9156114Z Test results will be stored in test-reports/python-pytest/test_dynamic_shapes/test_dynamic_shapes-9130874f01345cb0.xml 2025-12-04T09:57:29.9157531Z ============================= test session starts ============================== 2025-12-04T09:57:29.9158698Z platform linux -- Python 3.10.14, pytest-7.3.2, pluggy-1.6.0 -- /opt/conda/envs/py_3.10/bin/python 2025-12-04T09:57:29.9235684Z cachedir: .pytest_cache 2025-12-04T09:57:29.9237060Z hypothesis profile 'pytorch_ci' -> database=None, max_examples=50, derandomize=True, suppress_health_check=[HealthCheck.too_slow] 2025-12-04T09:57:29.9238460Z rootdir: /var/lib/jenkins/workspace 2025-12-04T09:57:29.9239046Z configfile: pytest.ini 2025-12-04T09:57:29.9241672Z plugins: hypothesis-6.56.4, cpp-2.3.0, flakefinder-1.1.0, rerunfailures-14.0, subtests-0.13.1, xdist-3.3.1, xdoctest-1.3.0, typeguard-4.3.0 2025-12-04T09:57:29.9243468Z collecting ... collected 378 items 2025-12-04T09:57:29.9244160Z stepcurrent: Cannot find last run test, not skipping 2025-12-04T09:57:29.9278545Z Running 50 items in this shard: test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs, test/test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:29.9311862Z 2025-12-04T09:57:29.9312321Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [10.9788s] [ 2%] 2025-12-04T09:57:29.9313332Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0398s] [ 2%] 2025-12-04T09:57:29.9314486Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0478s] [ 2%] 2025-12-04T09:57:29.9315535Z 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test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0676s] [ 2%] 2025-12-04T09:57:29.9359041Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0669s] [ 2%] 2025-12-04T09:57:29.9360017Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0589s] [ 2%] 2025-12-04T09:57:29.9360994Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0488s] [ 2%] 2025-12-04T09:57:29.9361969Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0182s] [ 2%] 2025-12-04T09:57:29.9363268Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0320s] [ 2%] 2025-12-04T09:57:29.9364801Z test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs FAILED [0.0300s] [ 2%] 2025-12-04T09:57:29.9365602Z 2025-12-04T09:57:29.9365851Z =================================== FAILURES =================================== 2025-12-04T09:57:29.9366764Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9367797Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9368742Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9370020Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9374893Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9379775Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9381266Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9382832Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9384410Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9386184Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9387828Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9389489Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9391243Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9392794Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9394334Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9395874Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9397496Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9399111Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9400729Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9402368Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9404015Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9405773Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9407342Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9408934Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9410531Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9412124Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9413643Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9415141Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9416493Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9417779Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9419040Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9420417Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9421970Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9424371Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9426965Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9428886Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9431599Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9434301Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9437644Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9440952Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9443176Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:29.9445480Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9448775Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9453045Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9459167Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9461520Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:29.9463491Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:29.9465856Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:29.9468169Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:29.9470519Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:29.9473467Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9477287Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9479635Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9481029Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:29.9482546Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9483575Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9484497Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9485890Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9490624Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9495244Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9496731Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9498215Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9499735Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9501266Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9502871Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9504471Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9506027Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9507553Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9509087Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9510589Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9512193Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9513674Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9514826Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9515985Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9517161Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9518341Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9519445Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9520756Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9521884Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9523015Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9524171Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9525659Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9527016Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9528270Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9529556Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9530921Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9532411Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9534745Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9537258Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9539184Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9541638Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9545413Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9549737Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9613321Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9615438Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:29.9617349Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9619823Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9623255Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9626371Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9628235Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:29.9629690Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:29.9631400Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:29.9633104Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:29.9634831Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:29.9636991Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9639543Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9641244Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9642513Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:29.9643494Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9644250Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9644977Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9645902Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9649419Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9652813Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9653881Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9654983Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9656067Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9657262Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9658433Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9659601Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9660768Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9661867Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9662971Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9664804Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9665922Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9667064Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9668220Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9669371Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9670528Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9671696Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9672811Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9673925Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9675027Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9676129Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9677214Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9678265Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9679200Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9680100Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9680995Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9681948Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9683024Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9684795Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9686584Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9687980Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9689819Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9692014Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9695238Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9698352Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9700220Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:29.9702129Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9704533Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9707699Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9710769Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9712588Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:29.9714717Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:29.9717151Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:29.9719434Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:29.9721791Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:29.9724812Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9728500Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9730907Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9732293Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:29.9733846Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9734967Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9735896Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9737149Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9741864Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9746937Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9748430Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9749930Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9751429Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9752959Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9754574Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9756243Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9757759Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9759259Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9760771Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9762253Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9763813Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9765486Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9767052Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9768614Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9770214Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9771828Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9773368Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9775271Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9776800Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9778344Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9780056Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9781513Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9782807Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9784067Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9785463Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9786848Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9788324Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9790647Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9792891Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9794327Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9796150Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9798445Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9801735Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9804980Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9806879Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:29.9809224Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9812522Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9816956Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9821075Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9823545Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:29.9825505Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:29.9827855Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:29.9830150Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:29.9832480Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:29.9835395Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9838876Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9841182Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9842870Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:29.9844203Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9845315Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9846270Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9847543Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9852263Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9856867Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9858331Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9859835Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9861337Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9863197Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9864796Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9866365Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9868069Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9869586Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9871124Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9872597Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9874186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9875756Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9877325Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9878523Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9879693Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9880862Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9881974Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9883083Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9884201Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9885411Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9886506Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9887546Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9888492Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9889389Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9890277Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9891242Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9892308Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9894001Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9895792Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9897159Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9899099Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9901305Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9904510Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9907615Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9909486Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:29.9911362Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:29.9913807Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9916942Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9920027Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:29.9921756Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:29.9923202Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:29.9924986Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:29.9926691Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:29.9928429Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:29.9930593Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9933200Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:29.9934896Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9935906Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:29.9936923Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:29.9937658Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:29.9938323Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:29.9939239Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:29.9942969Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:29.9946432Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:29.9947857Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:29.9949337Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:29.9950859Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:29.9952386Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:29.9954001Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:29.9955608Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9957136Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:29.9958641Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:29.9960155Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:29.9961655Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:29.9963230Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:29.9964958Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9966528Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:29.9968076Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9969681Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:29.9971283Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9972801Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:29.9974632Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9976175Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:29.9977700Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:29.9979353Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:29.9980800Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:29.9982103Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:29.9983347Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:29.9984589Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:29.9985888Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:29.9987365Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:29.9989666Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:29.9992134Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:29.9994031Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:29.9996459Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:29.9999430Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0003622Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0007972Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0010553Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0013139Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0016456Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0019816Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0022926Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0024758Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0026211Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0028287Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0030890Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0033556Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0036874Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0040838Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0043763Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0045356Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0046860Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0047975Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0048979Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0050363Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0055783Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0061081Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0062721Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0064412Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0066090Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0068115Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0069920Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0071713Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0073537Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0075222Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0076921Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0078611Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0080361Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0082118Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0083881Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0085718Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0087522Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0089326Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0091030Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0092764Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0094470Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0096180Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0097857Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0099477Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0100898Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0102285Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0103674Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0105150Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0106809Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0109419Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0112189Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0114235Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0116965Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0120368Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0125437Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0130218Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0133100Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0136019Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0139755Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0144933Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0149690Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0152390Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0154630Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0157298Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0159892Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0162557Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0165962Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0170176Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0172837Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0174371Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0175992Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0177107Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0178126Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0179496Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0184890Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0190221Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0191877Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0193581Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0195260Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0196949Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0198756Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0200570Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0201963Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0203471Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0205083Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0206594Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0208141Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0209707Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0211264Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0212826Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0214423Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0216032Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0217767Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0219336Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0220848Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0222004Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0223249Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0224303Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0225241Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0226146Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0227046Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0228012Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0229071Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0230769Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0232558Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0233945Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0235719Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0237914Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0241046Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0244407Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0246335Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0248234Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0250664Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0253963Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0257076Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0258909Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0260353Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0262101Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0263802Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0265522Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0267684Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0270236Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0271938Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0272951Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0273902Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0274633Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0275299Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0276210Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0279687Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0283345Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0284971Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0286592Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0288214Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0289993Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0291727Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0293450Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0295248Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0296826Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0298460Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0300085Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0301764Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0303458Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0305126Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0306835Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0308562Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0310269Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0311936Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0313570Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0315221Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0316429Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0317531Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0318603Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0319712Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0320807Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0321905Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0323037Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0324298Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0326195Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0328183Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0329803Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0332106Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0334466Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0337691Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0340800Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0343074Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0344964Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0347414Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0350587Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0353698Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0355440Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0356882Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0358608Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0360317Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0362061Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0364224Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0367021Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0368720Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0369717Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0370800Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0371536Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0372188Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0373099Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0376606Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0380012Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0381078Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0382175Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0383267Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0384366Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0385700Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0386871Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0387961Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0389059Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0390160Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0391252Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0392382Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0393524Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0394657Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0395801Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0396957Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0398123Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0399306Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0400420Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0401518Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0402625Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0403830Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0404917Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0405866Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0406766Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0407670Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0408621Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0409697Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0411394Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0413165Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0414550Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0416295Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0418482Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0421608Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0424721Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0426600Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0428506Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0430927Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0434132Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0437213Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0439018Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0440451Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0442182Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0444114Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0445886Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0448045Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0450603Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0452302Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0453301Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0454272Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0455000Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0455670Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0456569Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0460040Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0463424Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0464493Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0465593Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0466804Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0468289Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0469743Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0471195Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0472654Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0474013Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0475380Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0476728Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0478132Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0479545Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0480959Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0482378Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0483810Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0485329Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0486695Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0488075Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0489438Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0490817Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0492157Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0493457Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0494619Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0495680Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0496594Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0497571Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0498636Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0500338Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0502122Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0503494Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0505388Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0507588Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0510787Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0513884Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0515745Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0517644Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0526205Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0529385Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0532473Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0534207Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0535693Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0537417Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0539111Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0540842Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0543261Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0545953Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0547671Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0548674Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0549687Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0550426Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0551088Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0552015Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0555489Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0558931Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0560106Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0561199Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0562301Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0563397Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0564658Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0565824Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0566919Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0568020Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0569125Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0570212Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0571364Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0572501Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0573639Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0574770Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0575938Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0577106Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0578287Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0579381Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0580481Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0581586Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0582697Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0583723Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0584670Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0585570Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0586464Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0587418Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0588484Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0590188Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0592013Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0593382Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0595154Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0597361Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0600494Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0603612Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0605552Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0607457Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0609878Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0613110Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0616185Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0617961Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0619404Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0621157Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0622847Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0624574Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0626810Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0629412Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0630782Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0631585Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0632360Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0632956Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0633508Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0634236Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0636993Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0639696Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0640560Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0641445Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0642771Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0644485Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0646319Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0680328Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0682326Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0684038Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0685801Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0687488Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0689240Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0691025Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0692760Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0694525Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0696510Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0698295Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0700090Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0701799Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0703504Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0705230Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0706848Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0708466Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0709896Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0711286Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0712661Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0714112Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0715724Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0718338Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0721106Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0723266Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0726305Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0729694Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0734585Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0739415Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0742574Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0745581Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0749489Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0754398Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0759211Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0761931Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0764156Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0766985Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0769590Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0772309Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0775622Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0780477Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0783138Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0784697Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0786211Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0787314Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0788346Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0789745Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0795045Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0800256Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0802018Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0803722Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0805524Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0807216Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0808997Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0810804Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0812479Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0814186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0815883Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0817578Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0819327Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0821044Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0822799Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0824551Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0826336Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0828081Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0829926Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0831656Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0833360Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0835035Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0836766Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0838387Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0839859Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0841216Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0842883Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0844386Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0846101Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0848717Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0851638Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0853811Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0856491Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0859834Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0864614Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0869419Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0872329Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.0875239Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0878993Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0884094Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0889014Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0891789Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.0894001Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.0896711Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.0899349Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.0902051Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.0905462Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0909351Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.0911947Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0913503Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.0914970Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.0916088Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.0917109Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.0918500Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.0923891Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.0929227Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.0930859Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.0932527Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.0934366Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.0936030Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.0937825Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.0939656Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0941416Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.0943422Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.0945121Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.0946761Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.0948532Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.0950267Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0952017Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.0953784Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0955722Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.0957536Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0959250Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.0960949Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0962676Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.0964421Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.0966159Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.0967777Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.0969211Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.0970632Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.0972026Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.0973499Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.0975147Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.0977717Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.0980498Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.0982609Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.0985503Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.0988918Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.0993783Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.0998538Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1001421Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1004305Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1008211Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1013068Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1017863Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1020538Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1022783Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1025420Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1027999Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1030633Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1033981Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1038076Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1040636Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1042190Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1044014Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1045177Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1046183Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1047567Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1052962Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1058244Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1060085Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1061805Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1063521Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1065180Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1066964Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1068794Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1070482Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1072186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1073874Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1075594Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1077327Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1079038Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1080770Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1082549Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1084380Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1086255Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1088126Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1089588Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1091008Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1092821Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1094579Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1096355Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1097867Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1099296Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1100750Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1102318Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1104048Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1106732Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1109348Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1111292Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1113778Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1116871Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1121288Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1125748Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1128390Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1131045Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1134466Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1139064Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1143764Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1146386Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1148449Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1150908Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1153330Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1155803Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1159042Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1162678Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1165250Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1166716Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1168120Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1168966Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1169662Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1170613Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1174231Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1177810Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1178877Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1179989Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1181267Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1182375Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1183544Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1184721Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1185862Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1186962Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1188047Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1189140Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1190281Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1191417Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1192538Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1193676Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1194889Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1196051Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1197150Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1198262Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1199364Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1200464Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1201533Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1202577Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1203513Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1204403Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1205396Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1206362Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1207430Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1209126Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1210897Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1212276Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1214102Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1216302Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1219498Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1222582Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1224439Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1226341Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1228836Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1231988Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1235082Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1236816Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1238251Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1239991Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1241690Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1243650Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1245848Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1248504Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1250194Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1251208Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1252220Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1252959Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1253620Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1254539Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1258022Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1261433Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1262557Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1263647Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1264766Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1265870Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1267044Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1268199Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1269299Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1270397Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1271503Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1272582Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1273712Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1274847Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1275977Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1277102Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1278266Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1279423Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1280591Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1281690Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1282795Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1283930Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1285061Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1286091Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1287033Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1287931Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1288815Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1289776Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1290851Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1292545Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1294394Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1295762Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1297517Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1299711Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1302830Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1305933Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1307801Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1309691Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1312132Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1315329Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1318204Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1319618Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1320968Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1322340Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1323692Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1325127Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1326886Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1328909Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1330261Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1331299Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1332313Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1332908Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1333442Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1334186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1336934Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1339628Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1340484Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1341355Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1342580Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1343763Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1344939Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1346154Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1347246Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1348355Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1349468Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1350558Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1351705Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1352850Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1353992Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1355135Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1356368Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1357540Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1358658Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1359761Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1360877Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1362000Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1363086Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1364149Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1365163Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1366070Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1366982Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1367943Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1369028Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1370749Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1372546Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1373924Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1375768Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1377982Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1381163Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1384292Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1386180Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1388081Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1390565Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1393756Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1396867Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1398626Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1400082Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1401832Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1403524Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1405310Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1407474Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1410095Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1411794Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1412801Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1413796Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1414529Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1415193Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1416098Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1419616Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1423022Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1424128Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1425240Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1426335Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1427436Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1428607Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1429785Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1430866Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1431971Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1433070Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1434169Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1435296Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1436449Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1437592Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1438741Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1439901Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1441082Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1442529Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1443657Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1444801Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1445978Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1447070Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1448128Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1449073Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1449975Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1450885Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1451845Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1452930Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1454641Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1456493Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1457875Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1460666Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1464121Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1468852Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1473618Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1476529Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1479456Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1483221Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1488318Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1493125Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1495838Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1498071Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1500706Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1503251Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1505862Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1509227Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1513151Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1515780Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1517334Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1518849Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1519983Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1521000Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1522371Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1527855Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1533053Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1534689Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1536389Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1538171Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1539825Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1541627Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1543748Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1545373Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1547059Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1548719Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1550382Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1552122Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1553847Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1555597Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1557356Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1559283Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1561044Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1562769Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1564457Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1566256Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1567947Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1569668Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1571244Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1572680Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1574054Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1575444Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1576937Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1578621Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1581229Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1583986Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1586101Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1588936Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1592311Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1597165Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1601887Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1604821Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1607743Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1611521Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1616330Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1621043Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1623702Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1625921Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1628547Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1631121Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1633780Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1637105Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1641173Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1644141Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1645774Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1647366Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1648490Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1649493Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1650909Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1656291Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1661508Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1663291Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1664978Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1666705Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1668363Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1670176Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1671978Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1673675Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1675320Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1677018Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1678699Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1680425Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1682164Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1683907Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1685739Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1687540Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1689312Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1691235Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1692975Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1694683Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1696452Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1698120Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1699753Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1701198Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1702586Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1703953Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1705422Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1707048Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1709655Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1712472Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1714628Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1717360Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1720711Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1725596Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1730334Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1733201Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1736087Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1739805Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1745075Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1749839Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1752614Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1754797Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1757497Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1760198Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1763270Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1767056Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1771219Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1774006Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1775678Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1777349Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1778665Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1779815Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1781449Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1786992Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1792424Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1794339Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1796171Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1798108Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1800009Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1801950Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1803925Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1820875Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1822652Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1824339Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1826017Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1827747Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1829523Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1831306Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1833063Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1834985Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1836805Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1838491Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1840202Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1841882Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1843973Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1845673Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1847287Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1848727Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1850084Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1851466Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1852973Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1854629Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1857238Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1859989Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1862118Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1865049Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1868375Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1873232Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1877989Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1880838Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1883747Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1887751Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1892635Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1897387Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1899633Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.1901308Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.1903344Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.1905448Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.1907183Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.1909349Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1911993Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.1913696Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1914713Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.1915716Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.1916440Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.1917116Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.1918036Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.1921549Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.1925021Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.1926140Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.1927232Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.1928346Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.1929444Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.1930604Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.1931784Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1932880Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.1933984Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.1935070Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.1936176Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.1937324Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.1938459Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1939578Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.1940717Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1941894Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.1943306Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1944551Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.1945669Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1946778Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.1947940Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.1949003Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.1950052Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.1951001Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.1951903Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.1952794Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.1953753Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.1954831Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.1956680Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.1959468Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.1961603Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.1964327Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.1967797Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1972705Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1977556Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1980447Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.1983384Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.1987143Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1992185Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1997061Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.1999859Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2002065Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2004847Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2007449Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2010115Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2013569Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2017518Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2020161Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2021731Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2023210Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2024319Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2025320Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2026716Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2032147Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2037492Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2039149Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2040828Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2042978Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2044428Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2046277Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2048132Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2049798Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2051497Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2053161Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2054837Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2056597Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2058339Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2060081Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2061803Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2063687Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2065479Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2067198Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2068890Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2070594Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2072267Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2073921Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2075526Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2076982Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2078361Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2079777Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2081242Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2082880Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2085549Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2088308Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2090426Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2093271Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2096634Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2101513Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2106309Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2109217Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2112121Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2116063Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2120921Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2125805Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2128481Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2130713Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2133154Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2135768Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2138425Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2141751Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2146185Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2148800Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2150350Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2151901Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2153015Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2154027Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2155407Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2160766Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2166148Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2167874Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2169557Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2171260Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2172936Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2174736Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2176541Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2178219Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2179913Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2181605Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2183294Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2185046Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2186760Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2188516Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2190278Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2192083Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2193869Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2195691Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2197397Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2199105Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2200862Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2202519Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2204123Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2205651Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2207034Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2208412Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2209893Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2211549Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2214177Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2216999Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2218839Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2220882Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2223411Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2226738Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2230427Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2232546Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2234473Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2236906Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2240199Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2243548Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2245468Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2246916Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2248662Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2250358Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2252093Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2254315Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2256874Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2258583Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2259589Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2260558Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2261286Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2261958Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2262853Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2267352Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2272133Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2273651Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2275205Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2276991Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2278554Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2280215Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2281999Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2283534Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2285198Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2286756Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2288314Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2289915Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2291533Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2293150Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2294765Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2296500Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2298119Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2299712Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2301291Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2302848Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2304430Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2305940Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2307436Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2308762Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2310046Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2311313Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2312711Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2314210Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2316579Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2319093Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2321027Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2323666Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2326867Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2331380Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2335486Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2337424Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2339387Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2342096Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2345640Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2349804Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2352201Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2354146Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2356518Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2358846Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2361199Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2364137Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2367976Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2370309Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2371693Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2373099Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2374130Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2375049Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2376300Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2380113Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2380732Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2381535Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2382189Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2382854Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2383485Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2384219Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2384884Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2385513Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2386184Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2386822Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2387459Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2388152Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2388782Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2389507Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2390132Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2390865Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2391537Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2392331Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2392986Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2393667Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2394359Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2394987Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2395602Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2396098Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2396631Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2397127Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2397752Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2398369Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2399845Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2400680Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2401611Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2402897Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2404407Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2407085Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2408602Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2409458Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2410970Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2412566Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2415101Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2416235Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2416765Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2417588Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2418366Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2419137Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2419948Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2421187Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2422406Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2422756Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2423264Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2423563Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2423832Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2424102Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2424601Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2428160Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2428783Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2429449Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2430100Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2430860Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2431535Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2432286Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2433013Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2433660Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2434319Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2434973Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2435618Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2436351Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2437005Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2437728Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2438399Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2439230Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2439892Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2440591Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2441225Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2441903Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2442823Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2443465Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2444084Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2444643Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2445221Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2445699Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2446341Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2446991Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2448491Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2449266Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2450207Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2451748Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2453291Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2455915Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2457455Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2458304Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2459853Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2461578Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2464122Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2465641Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2466343Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2467436Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2468522Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2469581Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2470665Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2472344Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2474126Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2474645Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2475400Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2475842Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2476208Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2476561Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2477288Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2481146Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2481804Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2482524Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2483192Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2483851Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2484583Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2485370Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2486023Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2486692Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2487355Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2488005Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2488688Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2489397Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2490078Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2490810Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2491464Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2492339Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2492998Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2493856Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2494537Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2495204Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2495935Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2496568Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2497201Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2497700Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2498232Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2498596Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2499060Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2499540Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2500651Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2501255Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2501971Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2502928Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2504098Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2506107Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2507238Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2507854Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2508982Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2510130Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2512037Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2513139Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2513665Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2514469Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2515231Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2516009Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2516794Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2518039Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2519221Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2519577Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2520070Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2520366Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2520648Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2520896Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2521404Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2524243Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2524784Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2525245Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2525715Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2526253Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2526715Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2527260Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2527754Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2528207Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2528691Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2529144Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2529620Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2530118Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2530581Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2531100Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2531559Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2532162Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2532624Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2533101Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2533576Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2534047Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2534521Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2534963Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2535396Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2535753Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2536139Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2536475Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2536935Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2537382Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2538473Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2539018Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2539766Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2540685Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2541799Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2543920Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2545031Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2545652Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2546767Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2548042Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2549887Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2551001Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2551477Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2552292Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2553085Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2553853Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2554654Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2555844Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2557127Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2557470Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2558083Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2558380Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2558640Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2558902Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2559397Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2562234Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2562674Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2563186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2563662Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2564126Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2564656Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2565195Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2565679Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2566135Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2566614Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2567092Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2567553Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2568075Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2568541Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2569044Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2569520Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2570054Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2570533Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2571067Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2571531Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2572023Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2572513Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2572961Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2573394Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2573741Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2574147Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2574488Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2574945Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2575399Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2576472Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2577061Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2577744Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2578673Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2579793Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2581640Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2582747Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2583371Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2584486Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2585632Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2587526Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2588645Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2589129Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2589927Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2590703Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2591467Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2592268Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2593504Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2594710Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2595057Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2595551Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2595858Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2596119Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2596375Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2596865Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2599696Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2600151Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2600611Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2601090Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2601601Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2602074Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2602610Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2603122Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2603583Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2604050Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2604575Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2605041Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2605545Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2606022Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2606527Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2607004Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2607571Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2608048Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2608811Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2609483Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2610129Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2610894Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2611510Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2612155Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2612646Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2613193Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2613703Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2614328Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2614977Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2616443Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2617293Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2618370Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2619612Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2621159Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2623736Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2625384Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2626342Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2627883Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2629563Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2632062Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2633631Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2634289Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2635352Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2636517Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2637583Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2638672Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2640329Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2642127Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2643019Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2643864Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2644297Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2644789Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2645152Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2645853Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2649703Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2650335Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2651230Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2651887Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2652551Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2653193Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2653940Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2654581Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2655214Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2655880Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2656584Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2657246Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2657923Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2658570Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2659291Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2659936Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2660694Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2661342Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2662213Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2662874Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2663533Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2664247Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2664859Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2665470Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2665975Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2666519Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2667013Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2667632Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2668263Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2669726Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2670554Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2671502Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2672751Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2674356Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2676847Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2678371Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2679235Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2680820Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2682523Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2685296Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2686905Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2687589Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2688432Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2689227Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2690027Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2690848Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2692136Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2693389Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2693747Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2694394Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2694694Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2694978Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2695227Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2695724Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2698579Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2699027Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2699503Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2699980Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2700525Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2700993Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2701534Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2702049Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2702507Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2703068Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2703694Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2704326Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2705025Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2705670Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2706356Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2707011Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2707853Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2708511Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2709184Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2709835Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2710418Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2711045Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2711671Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2712263Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2712746Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2713307Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2713776Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2714415Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2715037Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2716500Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2717259Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2718315Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2719585Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2721087Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2723619Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2725246Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2726103Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2727602Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2729262Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2731727Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2733220Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2733875Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2734953Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2736010Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2737034Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2738142Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2739750Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2741508Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2741988Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2743171Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2743606Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2743985Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2744357Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2745040Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2748850Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2749499Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2750328Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2750981Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2751612Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2752271Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2753017Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2753660Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2754292Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2754954Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2755596Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2756212Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2756905Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2757548Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2758231Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2758894Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2759647Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2760293Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2761222Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2761873Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2762549Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2763270Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2763889Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2764595Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2765096Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2765653Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2766113Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2766740Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2767371Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2768827Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2769679Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2770610Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2771862Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2773301Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2775168Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2776298Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2776915Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2778051Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2779208Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2781161Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2782313Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2782811Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2783618Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2784399Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2785161Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2785957Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2787214Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2788404Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2788767Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2789265Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2789575Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2789842Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2790090Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2790599Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2793441Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2793903Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2794363Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2794834Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2795374Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2795842Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2796398Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2796893Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2797350Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2797837Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2798297Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2798778Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2799283Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2799741Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2800256Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2800716Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2801302Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2801764Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2802243Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2802717Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2803186Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2803666Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2804109Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2804626Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2804985Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2805369Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2805722Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2806170Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2806617Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2807702Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2808240Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2808993Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2809907Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2811027Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2812884Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2813993Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2814604Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2815718Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2816979Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2818820Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2819927Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2820403Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2821217Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2821989Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2822761Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2823561Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2824759Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2826019Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2826366Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2826905Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2827200Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2827472Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2827718Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2828209Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2831055Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2831501Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2832004Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2832472Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2832946Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2833405Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2833941Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2834417Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2834869Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2835353Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2835807Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2836277Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2836792Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2837251Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2837882Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2838516Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2839250Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2839908Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2840719Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2841394Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2842043Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2843007Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2843652Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2844271Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2844879Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2845420Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2845902Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2846523Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2847141Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2848622Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2849560Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2850489Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2851735Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2853237Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2855736Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2857228Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2858088Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2859615Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2861201Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2863904Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2865482Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2866134Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2867210Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2868274Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2869319Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2870406Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2872102Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2873716Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2874203Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2874888Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2875311Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2875672Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2876050Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2876735Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2880540Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2881172Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2881805Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2882467Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2883221Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2894437Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2895222Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2896059Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2896696Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2897353Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2898006Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2898662Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2899389Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2900039Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2900737Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2901406Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2902252Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2902936Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2903605Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2904256Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2904933Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2905582Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2906211Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2906820Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2907312Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2907790Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2908131Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2908600Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2909055Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2910143Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2910708Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2911489Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2912426Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2913551Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2915476Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2916607Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2917241Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2918507Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2920320Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2923171Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2924973Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2925728Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2926969Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2928152Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2929330Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2930567Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2932416Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2934400Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2934937Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2935742Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2936202Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2936598Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2936985Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2937746Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.2942113Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.2943154Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.2943862Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.2944602Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.2945310Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.2946022Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.2946847Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.2947566Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2948268Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.2948986Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.2949698Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.2950418Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.2951195Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.2951918Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2952690Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.2953413Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2954236Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.2954951Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2955900Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.2956623Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2957375Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.2958157Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.2958839Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.2959526Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.2960050Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.2960638Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.2961179Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2961871Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.2962584Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.2964260Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.2965279Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.2966327Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.2967740Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.2969487Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2972324Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2974049Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2974986Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.2976708Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.2978495Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2981489Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2983249Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.2983994Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.2985223Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.2986407Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.2987608Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.2988834Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.2990771Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2992622Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.2993158Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.2993919Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.2994366Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.2994782Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.2995150Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.2995925Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3000289Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3000990Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3001698Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3002414Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3003242Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3003955Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3004834Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3005445Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3006142Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3006885Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3007588Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3008320Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3009093Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3009789Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3010579Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3011295Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3012188Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3012891Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3013628Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3014357Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3015089Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3015822Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3016495Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3017162Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3017701Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3018292Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3018825Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3019515Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3020212Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3021870Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3022696Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3023852Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3025269Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3027021Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3029921Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3031626Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3032585Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3034309Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3036168Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3039005Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3040706Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3041435Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3042957Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3044140Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3045376Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3046593Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3048434Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3050496Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3051031Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3051861Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3052312Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3052733Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3053107Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3053860Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3058251Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3059037Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3059757Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3060475Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3061201Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3061916Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3062730Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3063465Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3064167Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3064887Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3065613Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3066338Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3067121Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3067831Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3068599Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3069334Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3070158Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3070885Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3071760Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3072485Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3073238Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3073999Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3074703Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3075367Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3075894Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3076502Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3077022Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3077725Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3078421Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3080074Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3080988Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3082039Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3083461Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3085289Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3088154Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3089863Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3090824Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3092291Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3093840Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3096446Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3098023Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3098676Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3099753Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3100808Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3101835Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3102929Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3104638Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3106250Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3106724Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3107393Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3107814Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3108188Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3108561Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3109230Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3112552Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3113025Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3113488Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3113979Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3114537Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3115019Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3115557Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3116059Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3116534Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3117004Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3117473Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3117932Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3118442Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3118915Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3119423Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3119897Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3120466Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3120927Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3121423Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3121884Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3122365Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3122830Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3123274Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3123715Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3124057Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3124460Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3124891Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3125340Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3125804Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3126883Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3127435Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3128174Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3129088Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3130217Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3132087Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3133208Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3133831Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3134954Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3136168Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3137999Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3139105Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3139584Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3140405Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3141173Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3141936Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3142991Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3144195Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3145536Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3145884Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3146435Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3146729Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3146993Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3147261Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3147758Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3150621Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3151146Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3151619Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3152089Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3152549Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3153029Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3153563Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3154049Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3154508Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3154976Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3155449Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3155913Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3156432Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3156899Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3157404Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3157879Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3158418Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3158896Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3159433Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3159897Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3160384Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3160877Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3161339Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3161766Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3162109Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3162505Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3162851Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3163318Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3163774Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3164917Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3165506Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3166187Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3167122Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3168240Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3170088Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3171554Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3172441Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3174118Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3175860Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3178779Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3180484Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3181216Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3182398Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3183556Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3184683Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3185865Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3188669Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3190492Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3191031Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3191753Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3192196Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3192575Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3192931Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3193668Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3197910Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3198605Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3199272Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3199980Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3200791Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3201483Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3202283Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3203078Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3203612Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3204082Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3204630Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3205122Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3205632Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3206107Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3206616Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3207189Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3207832Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3208380Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3208962Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3209498Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3210038Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3210603Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3211121Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3211631Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3212026Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3212467Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3212862Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3213314Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3213787Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3214869Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3215460Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3216422Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3217516Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3218838Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3221065Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3222224Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3222842Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3223973Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3225189Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3227052Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3228164Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3228642Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3229448Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3230229Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3230993Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3231800Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3233003Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3234281Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3234627Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3235169Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3235466Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3235730Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3235990Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3236484Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3239305Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3239785Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3240245Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3240732Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3241197Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3241674Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3242461Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3242931Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3243407Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3243878Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3244359Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3244886Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3245393Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3245877Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3246382Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3246864Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3247400Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3248007Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3248498Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3248961Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3249451Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3249963Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3250410Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3250856Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3251208Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3251610Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3251955Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3252402Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3252871Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3253945Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3254553Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3255225Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3256151Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3257262Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3259111Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3260229Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3260839Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3261965Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3263126Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3265045Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3266172Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3266664Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3267464Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3268236Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3268996Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3269791Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3271027Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3272222Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3272580Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3273072Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3273377Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3273638Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3273890Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3274402Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3277255Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3277712Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3278170Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3278655Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3279169Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3279633Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3280184Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3280679Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3281144Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3281613Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3282073Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3282546Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3283053Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3283529Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3284034Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3284582Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3285130Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3285604Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3286093Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3286558Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3287031Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3287512Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3287958Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3288406Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3288754Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3289140Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3289497Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3289947Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3290412Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3291495Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3292035Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3292782Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3293701Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3294830Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3296685Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3297806Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3298415Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3299541Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3300723Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3302582Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3303694Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3304175Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3304992Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3305762Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3306539Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3307337Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3308550Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3309804Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3310166Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3310693Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3310988Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3311257Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3311501Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3311993Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3314812Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3315285Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3315758Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3316232Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3316703Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3317162Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3317701Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3318177Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3318631Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3319109Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3319564Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3320027Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3320542Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3321002Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3321517Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3321977Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3322509Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3323052Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3323524Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3323994Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3324468Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3325011Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3325467Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3325896Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3326254Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3326642Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3326981Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3327443Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3327892Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3328990Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3329563Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3330238Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3331160Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3332270Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3334135Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3335243Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3335863Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3336977Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3338151Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3340061Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3341196Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3341674Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3342810Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3343583Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3344351Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3345152Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3346424Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3347621Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3347966Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3348475Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3348769Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3349031Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3349291Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3349783Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3352965Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3353521Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3354100Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3354786Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3355354Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3355941Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3356606Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3357249Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3357815Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3358401Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3358986Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3359563Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3360203Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3360781Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3361404Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3362036Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3362697Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3363292Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3363884Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3364461Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3365124Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3365693Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3366259Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3366794Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3367223Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3367719Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3368144Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3368701Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3369277Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3370606Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3371294Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3372223Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3373381Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3374764Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3377113Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3378493Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3379256Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3380573Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3381789Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3383643Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3384743Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3385233Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3386039Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3386819Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3387586Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3388395Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3389644Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3390837Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3391193Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3391717Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3392029Z ________________ TestUnbacked.test_do_not_guard_unbacked_inputs ________________ 2025-12-04T09:57:30.3392287Z [XPASS(strict)] https://github.com/pytorch/pytorch/issues/163785 2025-12-04T09:57:30.3392531Z ----------------------------- Captured stderr call ----------------------------- 2025-12-04T09:57:30.3393034Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] Python shape guard function: 2025-12-04T09:57:30.3395839Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def ___make_guard_fn(IsNonOverlappingAndDenseIndicator, cast_symbool_to_symint_guardless, math, torch, ___check_type_id, ___check_obj_id, ___odict_getitem, ___key_to_id, ___dict_version, ___dict_contains, ___tuple_iterator_len, ___normalize_range_iter, ___tuple_iterator_getitem, ___dataclass_fields, ___namedtuple_fields, ___get_torch_function_mode_stack_at, ___get_current_stream, __math_isnan, __numpy_isnan, inf, __load_module, utils_device, device, ___from_numpy, ___as_tensor, inspect): 2025-12-04T09:57:30.3396324Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] def guard(L): 2025-12-04T09:57:30.3396786Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var0 = L['a'] 2025-12-04T09:57:30.3397271Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var1 = _var0.size 2025-12-04T09:57:30.3397731Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var2 = _var1() 2025-12-04T09:57:30.3398188Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var3 = _var2[1] 2025-12-04T09:57:30.3398734Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var0.stride()[0] == _var3): 2025-12-04T09:57:30.3399196Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3399661Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var4 = L['b'] 2025-12-04T09:57:30.3400130Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var5 = _var4.size 2025-12-04T09:57:30.3400593Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var6 = _var5() 2025-12-04T09:57:30.3401068Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] _var7 = _var2[0] 2025-12-04T09:57:30.3401572Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[0] == _var7): 2025-12-04T09:57:30.3402044Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3402550Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var6[1] == _var3): 2025-12-04T09:57:30.3403006Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3403552Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (_var4.stride()[0] == _var3): 2025-12-04T09:57:30.3404068Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3404626Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var7): 2025-12-04T09:57:30.3405085Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3405560Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] if not (0 <= _var3): 2025-12-04T09:57:30.3406067Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return False 2025-12-04T09:57:30.3406506Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return True 2025-12-04T09:57:30.3406951Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] return guard 2025-12-04T09:57:30.3407292Z V1204 09:57:25.792000 28614 site-packages/torch/_dynamo/guards.py:1786] [0/0] [__guards] 2025-12-04T09:57:30.3407679Z V1204 09:57:25.793000 28614 site-packages/torch/_dynamo/guards.py:3990] [0/0] [__guards] GUARDS: 2025-12-04T09:57:30.3408031Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3408476Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] TREE_GUARD_MANAGER: 2025-12-04T09:57:30.3408942Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- RootGuardManager 2025-12-04T09:57:30.3410015Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- LAMBDA_GUARD: torch._functorch.aot_autograd.utils.top_saved_tensors_hooks ids == None # _dynamo/output_graph.py:808 in init_ambient_guards 2025-12-04T09:57:30.3410617Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GLOBAL_STATE: ___check_global_state() 2025-12-04T09:57:30.3411310Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- TORCH_FUNCTION_MODE_STACK: ___check_torch_function_mode_stack() 2025-12-04T09:57:30.3412229Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- DEFAULT_DEVICE: utils_device.CURRENT_DEVICE == None # _dynamo/output_graph.py:795 in init_ambient_guards 2025-12-04T09:57:30.3413361Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['a'], accessed_by=FrameLocalsGuardAccessor(key='a', framelocals_idx=0), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3415206Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['a'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3416325Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['a'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3416941Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING: check_no_aliasing(L['a'], L['b']) 2025-12-04T09:57:30.3418064Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | +- GuardManager: source=L['b'], accessed_by=FrameLocalsGuardAccessor(key='b', framelocals_idx=1), type=, tag_safe=(True, False) 2025-12-04T09:57:30.3419216Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TYPE_MATCH: ___check_type_id(L['b'], 93884895593984) # # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3421142Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- TENSOR_MATCH: check_tensor(L['b'], Tensor, DispatchKeySet(CPU, BackendSelect, ADInplaceOrView, AutogradCPU), torch.float32, device=None, requires_grad=False, size=[None, None], stride=[None, 1]) # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3422269Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_HASATTR: hasattr(L['b'], '_dynamo_dynamic_indices') == False # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func 2025-12-04T09:57:30.3422746Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] | | +- NO_TENSOR_ALIASING 2025-12-04T09:57:30.3423565Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['a'].stride()[0] == L['a'].size()[1] # (unknown source L['a'].stride()[0], please file a bug) 2025-12-04T09:57:30.3424333Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[0] == L['a'].size()[0] # (unknown source L['b'].size()[0], please file a bug) 2025-12-04T09:57:30.3425179Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].size()[1] == L['a'].size()[1] # (unknown source L['b'].size()[1], please file a bug) 2025-12-04T09:57:30.3426035Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: L['b'].stride()[0] == L['a'].size()[1] # (unknown source L['b'].stride()[0], please file a bug) 2025-12-04T09:57:30.3427485Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[0] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3428762Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] +- LAMBDA_GUARD: 0 <= L['a'].size()[1] # a.expand(b.shape) # ar/lib/jenkins/workspace/test/test_dynamic_shapes.py:3403 in func (_dynamo/variables/builder.py:3686 in ) 2025-12-04T09:57:30.3429173Z V1204 09:57:25.794000 28614 site-packages/torch/_dynamo/guards.py:3698] [0/0] [__guards] 2025-12-04T09:57:30.3429698Z V1204 09:57:25.828000 28614 site-packages/torch/_dynamo/guards.py:3734] [0/0] [__guards] Guard eval latency = 65.49 us 2025-12-04T09:57:30.3430557Z - generated xml file: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_dynamic_shapes/test_dynamic_shapes-9130874f01345cb0.xml - 2025-12-04T09:57:30.3430832Z =========================== short test summary info ============================ 2025-12-04T09:57:30.3431284Z FAILED [10.9788s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3431721Z FAILED [0.0398s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3432128Z FAILED [0.0478s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3432495Z FAILED [0.0653s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3432868Z FAILED [0.0277s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3433232Z FAILED [0.0449s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3433594Z FAILED [0.0643s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3433970Z FAILED [0.0250s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3434331Z FAILED [0.0639s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3434704Z FAILED [0.0651s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3435165Z FAILED [0.0410s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3435535Z FAILED [0.0412s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3435911Z FAILED [0.0614s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3436326Z FAILED [0.0644s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3436701Z FAILED [0.0445s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3437060Z FAILED [0.0570s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3437416Z FAILED [0.0639s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3437786Z FAILED [0.0646s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3438146Z FAILED [0.0595s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3438503Z FAILED [0.0626s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3438872Z FAILED [0.0440s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3439228Z FAILED [0.0627s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3439598Z FAILED [0.0247s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3439957Z FAILED [0.0590s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3440351Z FAILED [0.0648s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3440719Z FAILED [0.0334s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3441077Z FAILED [0.0251s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3441449Z FAILED [0.0798s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3441807Z FAILED [0.0628s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3442161Z FAILED [0.0635s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3442768Z FAILED [0.0299s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3443126Z FAILED [0.0152s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3443486Z FAILED [0.0509s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3443855Z FAILED [0.0204s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3444213Z FAILED [0.0150s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3444638Z FAILED [0.0485s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3445000Z FAILED [0.0527s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3445357Z FAILED [0.0170s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3445727Z FAILED [0.0161s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3446085Z FAILED [0.0494s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3446454Z FAILED [0.0584s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3446808Z FAILED [0.0649s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3447165Z FAILED [0.0788s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3447537Z FAILED [0.0676s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3448015Z FAILED [0.0669s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3448372Z FAILED [0.0589s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3448739Z FAILED [0.0488s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3449095Z FAILED [0.0182s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3449512Z FAILED [0.0320s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3449868Z FAILED [0.0300s] test_dynamic_shapes.py::TestUnbacked::test_do_not_guard_unbacked_inputs 2025-12-04T09:57:30.3450044Z ============================= 50 failed in 14.62s ============================== 2025-12-04T09:57:30.3450054Z 2025-12-04T09:57:30.3450605Z FINISHED PRINTING LOG FILE of test_dynamic_shapes 1/1 (test/test-reports/test_dynamic_shapes_1.1_219280898da3781a_.log) 2025-12-04T09:57:30.3450612Z 2025-12-04T09:57:30.3450970Z Finished test_dynamic_shapes 1/1 ... [2025-12-04 09:57:29.919549][2792.605311612], took 0.34min 2025-12-04T09:57:30.3451876Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_dynamic_shapes/test_dynamic_shapes-9130874f01345cb0.xml 2025-12-04T09:57:30.4827686Z Uploading logs for 57117865590 to S3 2025-12-04T09:57:30.5383199Z Uploading artifacts took 0.46 seconds 2025-12-04T09:57:33.0258593Z test_dynamic_shapes 1/1 failed! 2025-12-04T09:57:33.0259687Z W1204 09:57:33.025000 29312 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:57:34.7772759Z Running complex_tensor/test_complex_tensor 1/1 ... [2025-12-04 09:57:34.776829][2797.462597263] 2025-12-04T09:57:34.7773782Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:57:34.7776803Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'complex_tensor/test_complex_tensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:57:34.777312] 2025-12-04T09:57:41.4656378Z 2025-12-04T09:57:41.4658058Z complex_tensor/test_complex_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/complex_tensor.test_complex_tensor_1.1_f3f4b7818c829843_.log 2025-12-04T09:57:41.4659093Z Running 0 items in this shard: 2025-12-04T09:57:41.4659290Z 2025-12-04T09:57:41.4659655Z Finished complex_tensor/test_complex_tensor 1/1 ... [2025-12-04 09:57:41.465514][2804.151281394], took 0.11min 2025-12-04T09:57:41.5085056Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/complex_tensor.test_complex_tensor/complex_tensor.test_complex_tensor-107cb6bee9143c17.xml 2025-12-04T09:57:45.0024679Z W1204 09:57:45.001000 29694 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:57:47.0463008Z Running cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-12-04 09:57:47.045674][2809.731435192] 2025-12-04T09:57:47.0464355Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:57:47.0470181Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:57:47.046441] 2025-12-04T09:57:52.7843552Z 2025-12-04T09:57:52.7845338Z cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.python_agnostic_extension.test.test_python_agnostic_1.1_39951704a3cb7fed_.log 2025-12-04T09:57:52.7847004Z Running 0 items in this shard: 2025-12-04T09:57:52.7847206Z 2025-12-04T09:57:52.7849021Z Finished cpp_extensions/python_agnostic_extension/test/test_python_agnostic 1/1 ... [2025-12-04 09:57:52.784212][2815.469982478], took 0.10min 2025-12-04T09:57:52.8193160Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/cpp_extensions.python_agnostic_extension.test.test_python_agnostic/cpp_extensions.python_agnostic_extension.test.test_python_agnostic-2457e41ea4926c14.xml 2025-12-04T09:57:55.4047125Z W1204 09:57:55.403000 29971 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:57:56.8425144Z Running torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-12-04 09:57:56.841933][2819.527698758] 2025-12-04T09:57:56.8426251Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:57:56.8429879Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_histograms.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:57:56.842536] 2025-12-04T09:58:01.5383910Z 2025-12-04T09:58:01.5385680Z torch_np/numpy_tests/lib/test_histograms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_histograms_1.1_3adf396fd9fb3f9c_.log 2025-12-04T09:58:01.5387146Z Running 0 items in this shard: 2025-12-04T09:58:01.5387393Z 2025-12-04T09:58:01.5387889Z Finished torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-12-04 09:58:01.538122][2824.223881911], took 0.08min 2025-12-04T09:58:01.5944490Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_histograms/torch_np.numpy_tests.lib.test_histograms-20cca9059bef54f9.xml 2025-12-04T09:58:04.5571990Z W1204 09:58:04.556000 30197 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:06.0134524Z Running torch_np/test_indexing 1/1 ... [2025-12-04 09:58:06.012904][2828.698670513] 2025-12-04T09:58:06.0135555Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:06.0140085Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:06.013495] 2025-12-04T09:58:10.3483541Z 2025-12-04T09:58:10.3484761Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_34bcddd435707a18_.log 2025-12-04T09:58:10.3485859Z Running 0 items in this shard: 2025-12-04T09:58:10.3486106Z 2025-12-04T09:58:10.3486501Z Finished torch_np/test_indexing 1/1 ... [2025-12-04 09:58:10.348175][2833.03394258], took 0.07min 2025-12-04T09:58:10.3866294Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.test_indexing/torch_np.test_indexing-b82ac6db81972033.xml 2025-12-04T09:58:13.0150906Z W1204 09:58:13.014000 30471 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:14.4949491Z Running test_schema_check 1/1 ... [2025-12-04 09:58:14.494447][2837.180211916] 2025-12-04T09:58:14.4950335Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:14.4954657Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_schema_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:14.495022] 2025-12-04T09:58:21.2762650Z 2025-12-04T09:58:21.2764478Z test_schema_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_schema_check_1.1_bea28b9d43642611_.log 2025-12-04T09:58:21.2765438Z Running 0 items in this shard: 2025-12-04T09:58:21.2765639Z 2025-12-04T09:58:21.2765921Z Finished test_schema_check 1/1 ... [2025-12-04 09:58:21.276188][2843.961953153], took 0.11min 2025-12-04T09:58:21.3194234Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_schema_check/test_schema_check-1c8257b65e8eb08c.xml 2025-12-04T09:58:24.3684000Z W1204 09:58:24.367000 30850 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:25.8286290Z Running test_tensorboard 1/1 ... [2025-12-04 09:58:25.828024][2848.513786165] 2025-12-04T09:58:25.8287196Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:25.8292096Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_tensorboard.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:25.828693] 2025-12-04T09:58:31.6416143Z 2025-12-04T09:58:31.6417256Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_bf6505e94fb1cc80_.log 2025-12-04T09:58:31.6421348Z Running 0 items in this shard: 2025-12-04T09:58:31.6421650Z 2025-12-04T09:58:31.6422044Z Finished test_tensorboard 1/1 ... [2025-12-04 09:58:31.641994][2854.327759055], took 0.10min 2025-12-04T09:58:31.6843051Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_tensorboard/test_tensorboard-1460c07cf339b412.xml 2025-12-04T09:58:34.5744975Z W1204 09:58:34.573000 31130 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:36.0293917Z Running torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-12-04 09:58:36.028930][2858.714695244] 2025-12-04T09:58:36.0294693Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:36.0298328Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:36.029466] 2025-12-04T09:58:41.1436010Z 2025-12-04T09:58:41.1438628Z torch_np/numpy_tests/core/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_indexing_1.1_826a2b6884e8b2aa_.log 2025-12-04T09:58:41.1460545Z Running 0 items in this shard: 2025-12-04T09:58:41.1461038Z 2025-12-04T09:58:41.1461673Z Finished torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-12-04 09:58:41.143457][2863.829225126], took 0.09min 2025-12-04T09:58:41.1822508Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_indexing/torch_np.numpy_tests.core.test_indexing-7e03f69a1360e65f.xml 2025-12-04T09:58:44.5146564Z W1204 09:58:44.513000 31356 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:46.5578434Z Running test_futures 1/1 ... [2025-12-04 09:58:46.557318][2869.243081823] 2025-12-04T09:58:46.5579402Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:46.5584766Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_futures.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:46.558003] 2025-12-04T09:58:51.4932127Z 2025-12-04T09:58:51.4939116Z test_futures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_futures_1.1_aa601c296c65312a_.log 2025-12-04T09:58:51.4940389Z Running 0 items in this shard: 2025-12-04T09:58:51.4941165Z 2025-12-04T09:58:51.4941638Z Finished test_futures 1/1 ... [2025-12-04 09:58:51.493084][2874.178852495], took 0.08min 2025-12-04T09:58:51.5308685Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_futures/test_futures-1017cf1de2ccf58e.xml 2025-12-04T09:58:54.4069700Z W1204 09:58:54.405000 31678 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:58:56.0517705Z Running nn/test_dropout 1/1 ... [2025-12-04 09:58:56.051216][2878.736983671] 2025-12-04T09:58:56.0518586Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:58:56.0522193Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:58:56.051828] 2025-12-04T09:59:00.0435243Z 2025-12-04T09:59:00.0436518Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_65153bf5e3344d62_.log 2025-12-04T09:59:00.0437694Z Running 0 items in this shard: 2025-12-04T09:59:00.0438000Z 2025-12-04T09:59:00.0438464Z Finished nn/test_dropout 1/1 ... [2025-12-04 09:59:00.043372][2882.729137514], took 0.07min 2025-12-04T09:59:00.1088158Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_dropout/nn.test_dropout-de5823ec20debaf9.xml 2025-12-04T09:59:02.6882567Z W1204 09:59:02.687000 31856 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:59:04.1328983Z Running functorch/dim/test_split 1/1 ... [2025-12-04 09:59:04.132378][2886.818146539] 2025-12-04T09:59:04.1330011Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:59:04.1333797Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/dim/test_split.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:59:04.132928] 2025-12-04T09:59:09.1496295Z 2025-12-04T09:59:09.1497821Z functorch/dim/test_split 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.dim.test_split_1.1_f3a20a6873586fbb_.log 2025-12-04T09:59:09.1499195Z Running 0 items in this shard: 2025-12-04T09:59:09.1499549Z 2025-12-04T09:59:09.1500034Z Finished functorch/dim/test_split 1/1 ... [2025-12-04 09:59:09.149547][2891.835309876], took 0.08min 2025-12-04T09:59:09.1992923Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.dim.test_split/functorch.dim.test_split-81021214eacd2449.xml 2025-12-04T09:59:12.8834803Z W1204 09:59:12.882000 32130 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:59:14.9780746Z Running torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-12-04 09:59:14.977458][2897.663219975] 2025-12-04T09:59:14.9781848Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:59:14.9786876Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_type_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:59:14.978190] 2025-12-04T09:59:19.9481437Z 2025-12-04T09:59:19.9484068Z torch_np/numpy_tests/lib/test_type_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_type_check_1.1_47ae53818915337d_.log 2025-12-04T09:59:19.9486181Z Running 0 items in this shard: 2025-12-04T09:59:19.9486555Z 2025-12-04T09:59:19.9487862Z Finished torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-12-04 09:59:19.933213][2902.618975895], took 0.08min 2025-12-04T09:59:19.9746802Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_type_check/torch_np.numpy_tests.lib.test_type_check-96f46193e07f5269.xml 2025-12-04T09:59:23.1052577Z W1204 09:59:23.104000 32452 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:59:24.5519120Z Running test_jit 1/1 ... [2025-12-04 09:59:24.551466][2907.237233411] 2025-12-04T09:59:24.5519729Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:59:24.5524235Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:59:24.551988] 2025-12-04T09:59:37.0187645Z 2025-12-04T09:59:37.0189254Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_e70b422516fd456e_.log 2025-12-04T09:59:37.0343997Z Running 450 items in this shard: test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_rand, test/test_jit.py::TestScript::test_requires_grad_loop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_method_overloading, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_list, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_optional_tensor, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, test/test_jit.py::TestScript::test_prim_grad_undefined, 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test/test_jit.py::TestScript::test_requires_grad_loop, test/test_jit.py::TestScript::test_requires_grad_loop, test/test_jit.py::TestScript::test_requires_grad_loop, test/test_jit.py::TestScript::test_requires_grad_loop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, 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test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_as_tensor_shape_prop, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_requires_grad, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses, test/test_jit.py::TestScript::test_tensor_subclasses 2025-12-04T09:59:37.0498728Z 2025-12-04T09:59:37.0499193Z Finished test_jit 1/1 ... [2025-12-04 09:59:37.019707][2919.705472939], took 0.21min 2025-12-04T09:59:37.0679129Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit/test_jit-025bb63857fd4d60.xml 2025-12-04T09:59:40.4128305Z W1204 09:59:40.411000 32927 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:59:42.5180213Z Running test_datapipe 1/1 ... [2025-12-04 09:59:42.517531][2925.203297944] 2025-12-04T09:59:42.5181199Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:59:42.5184253Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_datapipe.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:59:42.518028] 2025-12-04T09:59:47.8420866Z 2025-12-04T09:59:47.8422509Z test_datapipe 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_datapipe_1.1_503e91b9c4fcebfa_.log 2025-12-04T09:59:47.8428185Z Running 0 items in this shard: 2025-12-04T09:59:47.8428619Z 2025-12-04T09:59:47.8429158Z Finished test_datapipe 1/1 ... [2025-12-04 09:59:47.841950][2930.527714247], took 0.09min 2025-12-04T09:59:47.8835653Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_datapipe/test_datapipe-5effc8cea6cf6f99.xml 2025-12-04T09:59:51.1189313Z W1204 09:59:51.118000 33159 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T09:59:52.8578924Z Running test_numba_integration 1/1 ... [2025-12-04 09:59:52.857345][2935.543113042] 2025-12-04T09:59:52.8580297Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T09:59:52.8584278Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_numba_integration.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 09:59:52.857905] 2025-12-04T09:59:57.1879436Z 2025-12-04T09:59:57.1880606Z test_numba_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numba_integration_1.1_90bdf13849f1d969_.log 2025-12-04T09:59:57.1881685Z Running 0 items in this shard: 2025-12-04T09:59:57.1881979Z 2025-12-04T09:59:57.1882416Z Finished test_numba_integration 1/1 ... [2025-12-04 09:59:57.187864][2939.873632703], took 0.07min 2025-12-04T09:59:57.2301025Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_numba_integration/test_numba_integration-be60f3f30f9e1f05.xml 2025-12-04T10:00:00.4146363Z W1204 10:00:00.413000 33481 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:02.4849560Z Running test_functional_optim 1/1 ... [2025-12-04 10:00:02.484414][2945.170175961] 2025-12-04T10:00:02.4850641Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:02.4855499Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_functional_optim.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:02.485154] 2025-12-04T10:00:07.8434182Z 2025-12-04T10:00:07.8435744Z test_functional_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functional_optim_1.1_0f62784fdea41441_.log 2025-12-04T10:00:07.8437161Z Running 0 items in this shard: 2025-12-04T10:00:07.8437485Z 2025-12-04T10:00:07.8438014Z Finished test_functional_optim 1/1 ... [2025-12-04 10:00:07.843414][2950.52917844], took 0.09min 2025-12-04T10:00:07.8874257Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_functional_optim/test_functional_optim-aa39444b668bd3f3.xml 2025-12-04T10:00:10.8875448Z W1204 10:00:10.886000 33755 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:12.3128152Z Running test_maskedtensor 1/1 ... [2025-12-04 10:00:12.312387][2954.998155444] 2025-12-04T10:00:12.3128686Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:12.3131151Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_maskedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:12.312838] 2025-12-04T10:00:18.7761336Z 2025-12-04T10:00:18.7762379Z test_maskedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_maskedtensor_1.1_c7a0c47d0808565f_.log 2025-12-04T10:00:18.7763393Z Running 0 items in this shard: 2025-12-04T10:00:18.7763639Z 2025-12-04T10:00:18.7764036Z Finished test_maskedtensor 1/1 ... [2025-12-04 10:00:18.775919][2961.46168597], took 0.11min 2025-12-04T10:00:18.8163332Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_maskedtensor/test_maskedtensor-3b0272d68f77585d.xml 2025-12-04T10:00:21.6355720Z W1204 10:00:21.634000 33996 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:23.5571150Z Running benchmark_utils/test_benchmark_utils 1/1 ... [2025-12-04 10:00:23.556578][2966.242345669] 2025-12-04T10:00:23.5572208Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:23.5577216Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'benchmark_utils/test_benchmark_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:23.557212] 2025-12-04T10:00:27.7088629Z 2025-12-04T10:00:27.7090514Z benchmark_utils/test_benchmark_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/benchmark_utils.test_benchmark_utils_1.1_8019f83b061ba50b_.log 2025-12-04T10:00:27.7091943Z Running 0 items in this shard: 2025-12-04T10:00:27.7092191Z 2025-12-04T10:00:27.7092661Z Finished benchmark_utils/test_benchmark_utils 1/1 ... [2025-12-04 10:00:27.708843][2970.394610117], took 0.07min 2025-12-04T10:00:27.7519631Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/benchmark_utils.test_benchmark_utils/benchmark_utils.test_benchmark_utils-c04370840d43d314.xml 2025-12-04T10:00:30.8541303Z W1204 10:00:30.852000 34270 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:32.8319992Z Running torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-12-04 10:00:32.831443][2975.517212143] 2025-12-04T10:00:32.8323595Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:32.8326053Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarmath.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:32.832072] 2025-12-04T10:00:38.4548200Z 2025-12-04T10:00:38.4549572Z torch_np/numpy_tests/core/test_scalarmath 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_e051ca28a0227856_.log 2025-12-04T10:00:38.4553791Z Running 0 items in this shard: 2025-12-04T10:00:38.4554052Z 2025-12-04T10:00:38.4554556Z Finished torch_np/numpy_tests/core/test_scalarmath 1/1 ... [2025-12-04 10:00:38.454925][2981.140689094], took 0.09min 2025-12-04T10:00:38.4956213Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_scalarmath/torch_np.numpy_tests.core.test_scalarmath-9de46dbc35372756.xml 2025-12-04T10:00:41.1803590Z W1204 10:00:41.179000 34592 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:42.8509196Z Running test_scaled_matmul_cuda 1/1 ... [2025-12-04 10:00:42.850235][2985.536000578] 2025-12-04T10:00:42.8510154Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:42.8514376Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_scaled_matmul_cuda.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:42.850892] 2025-12-04T10:00:47.4743902Z 2025-12-04T10:00:47.4745476Z test_scaled_matmul_cuda 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_scaled_matmul_cuda_1.1_30284178f3646ead_.log 2025-12-04T10:00:47.4747147Z Running 0 items in this shard: 2025-12-04T10:00:47.4747520Z 2025-12-04T10:00:47.4751285Z Finished test_scaled_matmul_cuda 1/1 ... [2025-12-04 10:00:47.474338][2990.160100966], took 0.08min 2025-12-04T10:00:47.5414645Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_scaled_matmul_cuda/test_scaled_matmul_cuda-7674c0d35ef02878.xml 2025-12-04T10:00:50.4531364Z W1204 10:00:50.452000 34818 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:00:51.9252891Z Running torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-12-04 10:00:51.924702][2994.610465989] 2025-12-04T10:00:51.9253749Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:00:51.9266242Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_shape_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:00:51.925219] 2025-12-04T10:00:57.5035661Z 2025-12-04T10:00:57.5037753Z torch_np/numpy_tests/core/test_shape_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_3e3b4c87ac632f4e_.log 2025-12-04T10:00:57.5040274Z Running 0 items in this shard: 2025-12-04T10:00:57.5040807Z 2025-12-04T10:00:57.5041615Z Finished torch_np/numpy_tests/core/test_shape_base 1/1 ... [2025-12-04 10:00:57.503494][3000.189258571], took 0.09min 2025-12-04T10:00:57.5552917Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_shape_base/torch_np.numpy_tests.core.test_shape_base-ddc876438d2fd5b1.xml 2025-12-04T10:01:01.1401506Z W1204 10:01:01.139000 35092 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:03.0833246Z Running test_vulkan 1/1 ... [2025-12-04 10:01:03.082712][3005.768477305] 2025-12-04T10:01:03.0834239Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:03.0838553Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_vulkan.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:03.083354] 2025-12-04T10:01:07.5461816Z 2025-12-04T10:01:07.5463143Z test_vulkan 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_vulkan_1.1_408879c888321153_.log 2025-12-04T10:01:07.5464349Z Running 0 items in this shard: 2025-12-04T10:01:07.5464607Z 2025-12-04T10:01:07.5464940Z Finished test_vulkan 1/1 ... [2025-12-04 10:01:07.546013][3010.231780066], took 0.07min 2025-12-04T10:01:07.5926730Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_vulkan/test_vulkan-7a7044ee2a09055f.xml 2025-12-04T10:01:10.6825444Z W1204 10:01:10.681000 35318 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:12.7881251Z Running lazy/test_generator 1/1 ... [2025-12-04 10:01:12.787658][3015.473425191] 2025-12-04T10:01:12.7881923Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:12.7885347Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_generator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:12.788193] 2025-12-04T10:01:17.0196973Z 2025-12-04T10:01:17.0198637Z lazy/test_generator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_generator_1.1_8987ab354a3f1ee4_.log 2025-12-04T10:01:17.0199973Z Running 0 items in this shard: 2025-12-04T10:01:17.0200217Z 2025-12-04T10:01:17.0200584Z Finished lazy/test_generator 1/1 ... [2025-12-04 10:01:17.019548][3019.705312613], took 0.07min 2025-12-04T10:01:17.0686204Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_generator/lazy.test_generator-fff901907fbc9755.xml 2025-12-04T10:01:20.0864192Z W1204 10:01:20.085000 35592 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:22.1103325Z Running torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-12-04 10:01:22.109784][3024.795546048] 2025-12-04T10:01:22.1104423Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:22.1109788Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/linalg/test_linalg.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:22.110564] 2025-12-04T10:01:28.0894499Z 2025-12-04T10:01:28.0896549Z torch_np/numpy_tests/linalg/test_linalg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.linalg.test_linalg_1.1_b6d6e049344086bd_.log 2025-12-04T10:01:28.0899053Z Running 0 items in this shard: 2025-12-04T10:01:28.0899634Z 2025-12-04T10:01:28.0900662Z Finished torch_np/numpy_tests/linalg/test_linalg 1/1 ... [2025-12-04 10:01:28.089420][3030.775185556], took 0.10min 2025-12-04T10:01:28.1462140Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.linalg.test_linalg/torch_np.numpy_tests.linalg.test_linalg-c0da762e414f52a2.xml 2025-12-04T10:01:31.3252150Z W1204 10:01:31.324000 35914 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:32.7818784Z Running torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-12-04 10:01:32.781251][3035.467018517] 2025-12-04T10:01:32.7819902Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:32.7821858Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_dtype.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:32.781817] 2025-12-04T10:01:37.4309029Z 2025-12-04T10:01:37.4310622Z torch_np/numpy_tests/core/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_5a421ca6009dc335_.log 2025-12-04T10:01:37.4312133Z Running 0 items in this shard: 2025-12-04T10:01:37.4312420Z 2025-12-04T10:01:37.4313052Z Finished torch_np/numpy_tests/core/test_dtype 1/1 ... [2025-12-04 10:01:37.430896][3040.116662411], took 0.08min 2025-12-04T10:01:37.4704740Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_dtype/torch_np.numpy_tests.core.test_dtype-218749d02183c001.xml 2025-12-04T10:01:40.5320987Z W1204 10:01:40.531000 36140 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:41.9772304Z Running lazy/test_debug_util 1/1 ... [2025-12-04 10:01:41.976666][3044.662433964] 2025-12-04T10:01:41.9773257Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:41.9776661Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'lazy/test_debug_util.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:41.977260] 2025-12-04T10:01:45.7357483Z 2025-12-04T10:01:45.7359030Z lazy/test_debug_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_debug_util_1.1_51af2840cafd543b_.log 2025-12-04T10:01:45.7360527Z Running 0 items in this shard: 2025-12-04T10:01:45.7360902Z 2025-12-04T10:01:45.7361401Z Finished lazy/test_debug_util 1/1 ... [2025-12-04 10:01:45.735450][3048.421214829], took 0.06min 2025-12-04T10:01:45.7815772Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/lazy.test_debug_util/lazy.test_debug_util-c6b9e9e154ba55cf.xml 2025-12-04T10:01:48.3867536Z W1204 10:01:48.385000 36414 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:01:49.8336053Z Running nn/test_load_state_dict 1/1 ... [2025-12-04 10:01:49.833062][3052.518830133] 2025-12-04T10:01:49.8337049Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:01:49.8340144Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_load_state_dict.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:01:49.833558] 2025-12-04T10:01:55.0088100Z 2025-12-04T10:01:55.0089654Z 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_bfd0315ce6718fac_.log 2025-12-04T10:01:55.0091229Z Running 0 items in this shard: 2025-12-04T10:01:55.0091583Z 2025-12-04T10:01:55.0092147Z Finished nn/test_load_state_dict 1/1 ... [2025-12-04 10:01:55.008893][3057.694656929], took 0.09min 2025-12-04T10:01:55.0581256Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_load_state_dict/nn.test_load_state_dict-fa5c919d018e833d.xml 2025-12-04T10:01:58.4899127Z W1204 10:01:58.489000 36640 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:00.4103599Z Running nn/test_module_hooks 1/1 ... [2025-12-04 10:02:00.409798][3063.095565472] 2025-12-04T10:02:00.4104281Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:00.4106998Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'nn/test_module_hooks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:00.410358] 2025-12-04T10:02:04.7583909Z 2025-12-04T10:02:04.7585051Z nn/test_module_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_module_hooks_1.1_22cc15a5d5ba56c9_.log 2025-12-04T10:02:04.7586118Z Running 0 items in this shard: 2025-12-04T10:02:04.7586363Z 2025-12-04T10:02:04.7586890Z Finished nn/test_module_hooks 1/1 ... [2025-12-04 10:02:04.758255][3067.444024193], took 0.07min 2025-12-04T10:02:04.8048311Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/nn.test_module_hooks/nn.test_module_hooks-44018fc21ad27c25.xml 2025-12-04T10:02:07.3783422Z W1204 10:02:07.377000 36959 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:09.4529366Z Running torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-12-04 10:02:09.452244][3072.138005659] 2025-12-04T10:02:09.4530944Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:09.4538577Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_twodim_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:09.453162] 2025-12-04T10:02:13.6277447Z 2025-12-04T10:02:13.6279154Z torch_np/numpy_tests/lib/test_twodim_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_b49816f4c927ad4e_.log 2025-12-04T10:02:13.6280880Z Running 0 items in this shard: 2025-12-04T10:02:13.6281301Z 2025-12-04T10:02:13.6282015Z Finished torch_np/numpy_tests/lib/test_twodim_base 1/1 ... [2025-12-04 10:02:13.627565][3076.313332429], took 0.07min 2025-12-04T10:02:13.6722949Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_twodim_base/torch_np.numpy_tests.lib.test_twodim_base-76a6ba8da1dfdef2.xml 2025-12-04T10:02:16.8383025Z W1204 10:02:16.837000 37140 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:19.0001427Z Running profiler/test_memory_profiler 1/1 ... [2025-12-04 10:02:18.999511][3081.685272304] 2025-12-04T10:02:19.0002424Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:19.0008476Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'profiler/test_memory_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:19.000277] 2025-12-04T10:02:24.0609574Z 2025-12-04T10:02:24.0611491Z profiler/test_memory_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_memory_profiler_1.1_12782556f96a4357_.log 2025-12-04T10:02:24.0655794Z Running 50 items in this shard: test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none, test/profiler/test_memory_profiler.py::TestIdentifyGradients::test_extract_gradients_from_optimizer_set_to_none 2025-12-04T10:02:24.0696468Z 2025-12-04T10:02:24.0696983Z Finished profiler/test_memory_profiler 1/1 ... [2025-12-04 10:02:24.061212][3086.746976198], took 0.08min 2025-12-04T10:02:24.1163808Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/profiler.test_memory_profiler/profiler.test_memory_profiler-c1112dc01a5c8cca.xml 2025-12-04T10:02:26.8984503Z W1204 10:02:26.897000 37462 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:28.3876421Z Running test_jit_llga_fuser 1/1 ... [2025-12-04 10:02:28.387137][3091.072905068] 2025-12-04T10:02:28.3877706Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:28.3880474Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_jit_llga_fuser.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:28.387657] 2025-12-04T10:02:33.2894437Z 2025-12-04T10:02:33.2895696Z 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_7185d0aa18cc6b19_.log 2025-12-04T10:02:33.2897113Z Running 0 items in this shard: 2025-12-04T10:02:33.2897493Z 2025-12-04T10:02:33.2898083Z Finished test_jit_llga_fuser 1/1 ... [2025-12-04 10:02:33.289164][3095.974933831], took 0.08min 2025-12-04T10:02:33.3691716Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_jit_llga_fuser/test_jit_llga_fuser-e429552ca5b5fcd7.xml 2025-12-04T10:02:36.1647241Z W1204 10:02:36.163000 37736 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:37.6091427Z Running test_serialization 1/1 ... [2025-12-04 10:02:37.608668][3100.294436282] 2025-12-04T10:02:37.6092286Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:37.6096214Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_serialization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:37.609193] 2025-12-04T10:02:43.8133764Z 2025-12-04T10:02:43.8134902Z test_serialization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_serialization_1.1_65a0b74e19f6b8f0_.log 2025-12-04T10:02:43.8135930Z Running 0 items in this shard: 2025-12-04T10:02:43.8136206Z 2025-12-04T10:02:43.8136584Z Finished test_serialization 1/1 ... [2025-12-04 10:02:43.813180][3106.49894868], took 0.10min 2025-12-04T10:02:43.8639232Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_serialization/test_serialization-d2041315058edfef.xml 2025-12-04T10:02:47.1821029Z W1204 10:02:47.180000 37962 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:49.2056547Z Running test_indexing 1/1 ... [2025-12-04 10:02:49.205032][3111.890793481] 2025-12-04T10:02:49.2057428Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:49.2063256Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:49.205787] 2025-12-04T10:02:53.3076542Z 2025-12-04T10:02:53.3077897Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_6c4181e7d893b016_.log 2025-12-04T10:02:53.3085727Z Running 0 items in this shard: 2025-12-04T10:02:53.3086131Z 2025-12-04T10:02:53.3086541Z Finished test_indexing 1/1 ... [2025-12-04 10:02:53.307460][3115.993224251], took 0.07min 2025-12-04T10:02:53.3592862Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_indexing/test_indexing-0e4ad769a08d78c4.xml 2025-12-04T10:02:56.4917499Z W1204 10:02:56.490000 38236 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:02:58.5239770Z Running torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-12-04 10:02:58.523484][3121.209247564] 2025-12-04T10:02:58.5240576Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:02:58.5245870Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/fft/test_pocketfft.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:02:58.524190] 2025-12-04T10:03:02.8604650Z 2025-12-04T10:03:02.8606935Z torch_np/numpy_tests/fft/test_pocketfft 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_600a6814c728f072_.log 2025-12-04T10:03:02.8608901Z Running 0 items in this shard: 2025-12-04T10:03:02.8609272Z 2025-12-04T10:03:02.8609879Z Finished torch_np/numpy_tests/fft/test_pocketfft 1/1 ... [2025-12-04 10:03:02.860358][3125.546124621], took 0.07min 2025-12-04T10:03:02.9220348Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.fft.test_pocketfft/torch_np.numpy_tests.fft.test_pocketfft-021e07e8099446cf.xml 2025-12-04T10:03:05.8620078Z W1204 10:03:05.861000 38558 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:07.9273192Z Running torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-12-04 10:03:07.926819][3130.612587495] 2025-12-04T10:03:07.9273979Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:07.9276549Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_shape_base_.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:07.927334] 2025-12-04T10:03:12.4320964Z 2025-12-04T10:03:12.4322701Z torch_np/numpy_tests/lib/test_shape_base_ 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_e3365dae8d2f29c4_.log 2025-12-04T10:03:12.4323741Z Running 0 items in this shard: 2025-12-04T10:03:12.4323950Z 2025-12-04T10:03:12.4324338Z Finished torch_np/numpy_tests/lib/test_shape_base_ 1/1 ... [2025-12-04 10:03:12.431979][3135.117746135], took 0.08min 2025-12-04T10:03:12.4827193Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.lib.test_shape_base_/torch_np.numpy_tests.lib.test_shape_base_-1d6390d2f83bcdd6.xml 2025-12-04T10:03:15.4557605Z W1204 10:03:15.454000 38784 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:17.1865468Z Running torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-12-04 10:03:17.186082][3139.871846742] 2025-12-04T10:03:17.1866589Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:17.1871769Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/numpy_tests/core/test_getlimits.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:17.186725] 2025-12-04T10:03:22.2920762Z 2025-12-04T10:03:22.2923041Z torch_np/numpy_tests/core/test_getlimits 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_e335fb57b40ee9ee_.log 2025-12-04T10:03:22.2928098Z Running 0 items in this shard: 2025-12-04T10:03:22.2928649Z 2025-12-04T10:03:22.2931958Z Finished torch_np/numpy_tests/core/test_getlimits 1/1 ... [2025-12-04 10:03:22.292730][3144.978481897], took 0.09min 2025-12-04T10:03:22.3618545Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.numpy_tests.core.test_getlimits/torch_np.numpy_tests.core.test_getlimits-ff786bd6cbe35951.xml 2025-12-04T10:03:25.7432623Z W1204 10:03:25.741000 39058 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:27.1907557Z Running torch_np/test_ndarray_methods 1/1 ... [2025-12-04 10:03:27.190200][3149.875965118] 2025-12-04T10:03:27.1908496Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:27.1912956Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'torch_np/test_ndarray_methods.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:27.190800] 2025-12-04T10:03:31.5724831Z 2025-12-04T10:03:31.5726093Z torch_np/test_ndarray_methods 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ndarray_methods_1.1_265bd46742f62cb6_.log 2025-12-04T10:03:31.5727279Z Running 0 items in this shard: 2025-12-04T10:03:31.5727525Z 2025-12-04T10:03:31.5727950Z Finished torch_np/test_ndarray_methods 1/1 ... [2025-12-04 10:03:31.572418][3154.258185342], took 0.07min 2025-12-04T10:03:31.6461104Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/torch_np.test_ndarray_methods/torch_np.test_ndarray_methods-3519d6855a82bbb7.xml 2025-12-04T10:03:35.0213950Z W1204 10:03:35.020000 39284 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:37.1878207Z Running test_type_info 1/1 ... [2025-12-04 10:03:37.187293][3159.873061026] 2025-12-04T10:03:37.1879133Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:37.1884769Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_type_info.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:37.188011] 2025-12-04T10:03:42.3154806Z 2025-12-04T10:03:42.3155882Z test_type_info 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_info_1.1_39c211b0985af73c_.log 2025-12-04T10:03:42.3156868Z Running 0 items in this shard: 2025-12-04T10:03:42.3157123Z 2025-12-04T10:03:42.3157446Z Finished test_type_info 1/1 ... [2025-12-04 10:03:42.315342][3165.001108878], took 0.09min 2025-12-04T10:03:42.3660633Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_type_info/test_type_info-683e374dcd17cadf.xml 2025-12-04T10:03:45.0743888Z W1204 10:03:45.073000 39600 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:46.5337127Z Running functorch/test_aotdispatch 1/1 ... [2025-12-04 10:03:46.532965][3169.218728189] 2025-12-04T10:03:46.5338180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:46.5345689Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:46.533647] 2025-12-04T10:03:55.4780432Z 2025-12-04T10:03:55.4781928Z functorch/test_aotdispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_1.1_b2bcab15ed6a5c47_.log 2025-12-04T10:03:55.4783481Z Running 0 items in this shard: 2025-12-04T10:03:55.4783808Z 2025-12-04T10:03:55.4784291Z Finished functorch/test_aotdispatch 1/1 ... [2025-12-04 10:03:55.478050][3178.163811358], took 0.15min 2025-12-04T10:03:55.5418906Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/functorch.test_aotdispatch/functorch.test_aotdispatch-f5a83df3b7571f46.xml 2025-12-04T10:03:58.5527466Z W1204 10:03:58.551000 39943 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:03:59.9968428Z Running test_cuda_multigpu 1/1 ... [2025-12-04 10:03:59.996302][3182.682068924] 2025-12-04T10:03:59.9969764Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:03:59.9974385Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_cuda_multigpu.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:03:59.996907] 2025-12-04T10:04:04.0585084Z 2025-12-04T10:04:04.0588197Z test_cuda_multigpu 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_multigpu_1.1_50fd7763a220f5eb_.log 2025-12-04T10:04:04.0589603Z Running 0 items in this shard: 2025-12-04T10:04:04.0589921Z 2025-12-04T10:04:04.0590478Z Finished test_cuda_multigpu 1/1 ... [2025-12-04 10:04:04.058437][3186.74420014], took 0.07min 2025-12-04T10:04:04.0927580Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_cuda_multigpu/test_cuda_multigpu-d9cc7bfc0d859f57.xml 2025-12-04T10:04:07.0841825Z W1204 10:04:07.083000 40217 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:04:09.0748191Z Running test_accelerator 1/1 ... [2025-12-04 10:04:09.074272][3191.760040942] 2025-12-04T10:04:09.0748837Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:04:09.0752888Z Executing ['/opt/conda/envs/py_3.10/bin/python', '-bb', 'test_accelerator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '--flake-finder', '--flake-runs=50', '--import-slow-tests', '--import-disabled-tests', '--rerun-disabled-tests'] ... [2025-12-04 10:04:09.074728] 2025-12-04T10:04:13.0417090Z 2025-12-04T10:04:13.0418576Z test_accelerator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_accelerator_1.1_333efbcf6b8912fa_.log 2025-12-04T10:04:13.0419925Z 2025-12-04T10:04:13.0420658Z Finished test_accelerator 1/1 ... [2025-12-04 10:04:13.041518][3195.727284682], took 0.07min 2025-12-04T10:04:16.5350346Z W1204 10:04:16.533000 40527 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:14:13.2381749Z 2025-12-04T10:14:13.2383567Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_992a0a8639eb791c_.log 2025-12-04T10:14:13.2401210Z Running 50 items in this shard: test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops 2025-12-04T10:14:13.2419882Z 2025-12-04T10:14:13.2420183Z Finished test_mkldnn_fusion 1/1 ... [2025-12-04 10:14:13.238156][3795.923925895], took 17.26min 2025-12-04T10:14:13.2622308Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_mkldnn_fusion/test_mkldnn_fusion-f9a4a203c128bdfe.xml 2025-12-04T10:14:15.6011251Z W1204 10:14:15.600000 54428 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:26:23.5725025Z 2025-12-04T10:26:23.5726321Z inductor/test_mkldnn_pattern_matcher 1/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_mkldnn_pattern_matcher_1.2_d029b9dcecb3c3f2_.log 2025-12-04T10:26:23.5756958Z Running 50 items in this shard: test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True, test/inductor/test_mkldnn_pattern_matcher.py::TestPatternMatcher::test_qlinear_add_cpu_use_relu_False_is_qat_False_is_dynamic_True 2025-12-04T10:26:23.5786120Z 2025-12-04T10:26:23.5786505Z Finished inductor/test_mkldnn_pattern_matcher 1/2 ... [2025-12-04 10:26:23.572534][4526.25830229], took 34.45min 2025-12-04T10:26:23.5861828Z Parsing testcases for test report: /var/lib/jenkins/workspace/test/test-reports/python-pytest/inductor.test_mkldnn_pattern_matcher/inductor.test_mkldnn_pattern_matcher-e22bba77341f13e2.xml 2025-12-04T10:26:24.0403645Z Uploading artifacts took 0.33 seconds 2025-12-04T10:26:24.7864880Z Running test batch 'tests to run' cost 3667.8 seconds 2025-12-04T10:26:24.7879104Z Emitting td_test_failure_stats_v2 2025-12-04T10:26:24.7882609Z Writing 1 documents to S3 ossci-raw-job-status/ossci_uploaded_metrics/td_test_failure_stats_v2_1764843984_af7a47acd0fb11f0ad7e0242ac110002 2025-12-04T10:26:24.8938519Z Done! Finish writing document to S3 ossci-raw-job-status/ossci_uploaded_metrics/td_test_failure_stats_v2_1764843984_af7a47acd0fb11f0ad7e0242ac110002 2025-12-04T10:26:24.8957444Z Emitting td_test_failure_stats_v2 2025-12-04T10:26:24.8960017Z Writing 1 documents to S3 ossci-raw-job-status/ossci_uploaded_metrics/td_test_failure_stats_v2_1764843984_af8ab628d0fb11f0ad7e0242ac110002 2025-12-04T10:26:24.9344786Z Done! Finish writing document to S3 ossci-raw-job-status/ossci_uploaded_metrics/td_test_failure_stats_v2_1764843984_af8ab628d0fb11f0ad7e0242ac110002 2025-12-04T10:26:24.9345694Z test_ci_sanity_check_fail 1/1 failed! 2025-12-04T10:26:24.9346182Z test_dynamic_shapes 1/1 failed! 2025-12-04T10:26:26.0794670Z 2025-12-04T10:26:26.0795246Z real 61m14.713s 2025-12-04T10:26:26.0795671Z user 200m26.781s 2025-12-04T10:26:26.0795900Z sys 55m30.848s 2025-12-04T10:26:26.0796141Z + assert_git_not_dirty 2025-12-04T10:26:26.0796612Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *rocm* ]] 2025-12-04T10:26:26.0797043Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *xla* ]] 2025-12-04T10:26:26.0801626Z ++ git status --porcelain 2025-12-04T10:26:26.0802960Z ++ grep -v '?? third_party' 2025-12-04T10:27:02.7818764Z ++ true 2025-12-04T10:27:02.7819123Z + git_status= 2025-12-04T10:27:02.7821554Z + [[ -n '' ]] 2025-12-04T10:27:02.7821877Z + test_aten 2025-12-04T10:27:02.7822326Z + echo 'Running ATen tests with pytorch lib' 2025-12-04T10:27:02.7822697Z Running ATen tests with pytorch lib 2025-12-04T10:27:02.7823009Z + [[ -n '' ]] 2025-12-04T10:27:02.7823271Z + echo 'Running test with the build folder' 2025-12-04T10:27:02.7823613Z Running test with the build folder 2025-12-04T10:27:02.7823941Z + TEST_BASE_DIR=build/bin 2025-12-04T10:27:02.7825225Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10_cuda.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10d_cuda_test.so build/bin 2025-12-04T10:27:02.7852915Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libcaffe2_nvrtc.so build/bin 2025-12-04T10:27:02.7865467Z + ln -sf '/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libmkldnn*' build/bin 2025-12-04T10:27:02.7878754Z + ln -sf '/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libnccl*' build/bin 2025-12-04T10:27:02.7903887Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cuda_linalg.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_nvshmem.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorchbind_test.so build/bin 2025-12-04T10:27:02.7914232Z + ls build/bin 2025-12-04T10:27:02.7955428Z BackoffTest 2025-12-04T10:27:02.7955680Z CppSignature_test 2025-12-04T10:27:02.7955934Z Dict_test 2025-12-04T10:27:02.7956238Z Dimname_test 2025-12-04T10:27:02.7956454Z FileStoreTest 2025-12-04T10:27:02.7956699Z HashStoreTest 2025-12-04T10:27:02.7957053Z IListRef_test 2025-12-04T10:27:02.7957369Z KernelFunction_test 2025-12-04T10:27:02.7957795Z List_test 2025-12-04T10:27:02.7958129Z MaybeOwned_test 2025-12-04T10:27:02.7958376Z NamedTensor_test 2025-12-04T10:27:02.7958843Z ProcessGroupGlooAsyncTest 2025-12-04T10:27:02.7959290Z ProcessGroupGlooTest 2025-12-04T10:27:02.7959624Z ProcessGroupMPITest 2025-12-04T10:27:02.7959958Z ProcessGroupNCCLErrorsTest 2025-12-04T10:27:02.7960397Z ProcessGroupNCCLTest 2025-12-04T10:27:02.7960834Z StorageUtils_test 2025-12-04T10:27:02.7961329Z TCPStoreTest 2025-12-04T10:27:02.7961579Z apply_utils_test 2025-12-04T10:27:02.7961796Z atest 2025-12-04T10:27:02.7962018Z backend_fallback_test 2025-12-04T10:27:02.7962310Z basic 2025-12-04T10:27:02.7962522Z broadcast_test 2025-12-04T10:27:02.7962771Z c10_AllocatorConfig_test 2025-12-04T10:27:02.7963030Z c10_ArrayRef_test 2025-12-04T10:27:02.7963270Z c10_Bitset_test 2025-12-04T10:27:02.7963747Z c10_CompileTimeFunctionPointer_test 2025-12-04T10:27:02.7964178Z c10_ConstexprCrc_test 2025-12-04T10:27:02.7964456Z c10_DeadlockDetection_test 2025-12-04T10:27:02.7964826Z c10_DeviceGuard_test 2025-12-04T10:27:02.7965064Z c10_Device_test 2025-12-04T10:27:02.7965307Z c10_DispatchKeySet_test 2025-12-04T10:27:02.7965575Z c10_Enumerate_test 2025-12-04T10:27:02.7965798Z c10_Half_test 2025-12-04T10:27:02.7966124Z c10_InlineDeviceGuard_test 2025-12-04T10:27:02.7966421Z c10_InlineStreamGuard_test 2025-12-04T10:27:02.7966691Z c10_IntrusiveList_test 2025-12-04T10:27:02.7966958Z c10_LeftRight_test 2025-12-04T10:27:02.7967210Z c10_NetworkFlow_test 2025-12-04T10:27:02.7967459Z c10_Scalar_test 2025-12-04T10:27:02.7967681Z c10_Semaphore_test 2025-12-04T10:27:02.7967930Z c10_SizesAndStrides_test 2025-12-04T10:27:02.7968204Z c10_StreamGuard_test 2025-12-04T10:27:02.7968444Z c10_SymInt_test 2025-12-04T10:27:02.7968684Z c10_Synchronized_test 2025-12-04T10:27:02.7968948Z c10_ThreadLocal_test 2025-12-04T10:27:02.7969196Z c10_TypeIndex_test 2025-12-04T10:27:02.7969445Z c10_accumulate_test 2025-12-04T10:27:02.7969690Z c10_bfloat16_test 2025-12-04T10:27:02.7969913Z c10_bit_cast_test 2025-12-04T10:27:02.7970168Z c10_complex_math_test 2025-12-04T10:27:02.7970425Z c10_complex_test 2025-12-04T10:27:02.7970647Z c10_cow_test 2025-12-04T10:27:02.7970903Z c10_cuda_CUDAAssertionsTest_1_var_test 2025-12-04T10:27:02.7971271Z c10_cuda_CUDAAssertionsTest_catches_stream 2025-12-04T10:27:02.7971721Z c10_cuda_CUDAAssertionsTest_catches_thread_and_block_and_device 2025-12-04T10:27:02.7972199Z c10_cuda_CUDAAssertionsTest_from_2_processes 2025-12-04T10:27:02.7972744Z c10_cuda_CUDAAssertionsTest_multiple_writes_from_blocks_and_threads 2025-12-04T10:27:02.7973307Z c10_cuda_CUDAAssertionsTest_multiple_writes_from_multiple_blocks 2025-12-04T10:27:02.7973845Z c10_cuda_CUDAAssertionsTest_multiple_writes_from_same_block 2025-12-04T10:27:02.7974256Z c10_cuda_CUDATest 2025-12-04T10:27:02.7974498Z c10_error_test 2025-12-04T10:27:02.7974726Z c10_exception_test 2025-12-04T10:27:02.7974968Z c10_flags_test 2025-12-04T10:27:02.7975205Z c10_generic_math_test 2025-12-04T10:27:02.7975460Z c10_intrusive_ptr_benchmark 2025-12-04T10:27:02.7975751Z c10_intrusive_ptr_test 2025-12-04T10:27:02.7976009Z c10_irange_test 2025-12-04T10:27:02.7976230Z c10_lazy_test 2025-12-04T10:27:02.7976456Z c10_logging_test 2025-12-04T10:27:02.7976692Z c10_nofatal_test 2025-12-04T10:27:02.7976913Z c10_optional_test 2025-12-04T10:27:02.7977169Z c10_ordered_preserving_dict_test 2025-12-04T10:27:02.7977466Z c10_registry_test 2025-12-04T10:27:02.7977691Z c10_small_vector_test 2025-12-04T10:27:02.7977941Z c10_ssize_test 2025-12-04T10:27:02.7978169Z c10_string_util_test 2025-12-04T10:27:02.7978407Z c10_string_view_test 2025-12-04T10:27:02.7978654Z c10_tempfile_test 2025-12-04T10:27:02.7978896Z c10_typeid_test 2025-12-04T10:27:02.7979119Z cpu_allocator_test 2025-12-04T10:27:02.7979361Z cpu_generator_test 2025-12-04T10:27:02.7979617Z cpu_profiling_allocator_test 2025-12-04T10:27:02.7979900Z cpu_rng_test 2025-12-04T10:27:02.7980152Z cuda_allocatorTraceTracker_test 2025-12-04T10:27:02.7980456Z cuda_allocator_test 2025-12-04T10:27:02.7980712Z cuda_apply_test 2025-12-04T10:27:02.7980941Z cuda_atomic_ops_test 2025-12-04T10:27:02.7981215Z cuda_caching_host_allocator_test 2025-12-04T10:27:02.7981522Z cuda_complex_math_test 2025-12-04T10:27:02.7981771Z cuda_complex_test 2025-12-04T10:27:02.7982008Z cuda_cub_test 2025-12-04T10:27:02.7982246Z cuda_cublas_handle_pool_test 2025-12-04T10:27:02.7982516Z cuda_cudnn_test 2025-12-04T10:27:02.7982749Z cuda_device_test 2025-12-04T10:27:02.7982996Z cuda_distributions_test 2025-12-04T10:27:02.7983255Z cuda_dlconvertor_test 2025-12-04T10:27:02.7983508Z cuda_event_test 2025-12-04T10:27:02.7983753Z cuda_exchange_device_test 2025-12-04T10:27:02.7984017Z cuda_generator_test 2025-12-04T10:27:02.7984266Z cuda_half_test 2025-12-04T10:27:02.7984508Z cuda_integer_divider_test 2025-12-04T10:27:02.7984768Z cuda_optional_test 2025-12-04T10:27:02.7985117Z cuda_packedtensoraccessor_test 2025-12-04T10:27:02.7985439Z cuda_reportMemoryUsage_test 2025-12-04T10:27:02.7985716Z cuda_stream_test 2025-12-04T10:27:02.7985963Z cuda_vectorized_test 2025-12-04T10:27:02.7986220Z dlconvertor_test 2025-12-04T10:27:02.7986451Z example_allreduce 2025-12-04T10:27:02.7986704Z extension_backend_test 2025-12-04T10:27:02.7986997Z half_test 2025-12-04T10:27:02.7987206Z inline_container_test 2025-12-04T10:27:02.7987453Z ivalue_test 2025-12-04T10:27:02.7987685Z kernel_function_legacy_test 2025-12-04T10:27:02.7987973Z kernel_function_test 2025-12-04T10:27:02.7988225Z kernel_lambda_legacy_test 2025-12-04T10:27:02.7988500Z kernel_lambda_test 2025-12-04T10:27:02.7988751Z kernel_stackbased_test 2025-12-04T10:27:02.7988994Z lazy_tensor_test 2025-12-04T10:27:02.7989229Z legacy_vmap_test 2025-12-04T10:27:02.7989481Z libc10.so 2025-12-04T10:27:02.7989889Z libc10_cuda.so 2025-12-04T10:27:02.7990173Z libc10d_cuda_test.so 2025-12-04T10:27:02.7990433Z libcaffe2_nvrtc.so 2025-12-04T10:27:02.7990654Z 'libmkldnn*' 2025-12-04T10:27:02.7990876Z 'libnccl*' 2025-12-04T10:27:02.7991088Z libtorch.so 2025-12-04T10:27:02.7991298Z libtorch_cpu.so 2025-12-04T10:27:02.7991535Z libtorch_cuda.so 2025-12-04T10:27:02.7991777Z libtorch_cuda_linalg.so 2025-12-04T10:27:02.7992041Z libtorch_global_deps.so 2025-12-04T10:27:02.7992313Z libtorch_nvshmem.so 2025-12-04T10:27:02.7992568Z libtorch_python.so 2025-12-04T10:27:02.7992859Z libtorchbind_test.so 2025-12-04T10:27:02.7993200Z make_boxed_from_unboxed_functor_test 2025-12-04T10:27:02.7993518Z math_kernel_test 2025-12-04T10:27:02.7993811Z memory_format_test 2025-12-04T10:27:02.7994065Z memory_overlapping_test 2025-12-04T10:27:02.7994339Z mobile_memory_cleanup 2025-12-04T10:27:02.7994576Z native_test 2025-12-04T10:27:02.7994799Z op_allowlist_test 2025-12-04T10:27:02.7995043Z op_registration_test 2025-12-04T10:27:02.7995287Z operator_name_test 2025-12-04T10:27:02.7995528Z operators_test 2025-12-04T10:27:02.7995781Z packedtensoraccessor_test 2025-12-04T10:27:02.7996065Z parallel_benchmark 2025-12-04T10:27:02.7996289Z pow_test 2025-12-04T10:27:02.7996501Z protoc 2025-12-04T10:27:02.7996715Z protoc-3.13.0.0 2025-12-04T10:27:02.7996942Z quantized_test 2025-12-04T10:27:02.7997180Z reduce_ops_test 2025-12-04T10:27:02.7997433Z reportMemoryUsage_test 2025-12-04T10:27:02.7997692Z scalar_tensor_test 2025-12-04T10:27:02.7997932Z scalar_test 2025-12-04T10:27:02.7998172Z stride_properties_test 2025-12-04T10:27:02.7998428Z tensor_iterator_test 2025-12-04T10:27:02.7998689Z test_aoti_abi_check 2025-12-04T10:27:02.7998939Z test_api 2025-12-04T10:27:02.7999140Z test_cpp_rpc 2025-12-04T10:27:02.7999373Z test_dist_autograd 2025-12-04T10:27:02.7999611Z test_jit 2025-12-04T10:27:02.7999806Z test_lazy 2025-12-04T10:27:02.8000019Z test_parallel 2025-12-04T10:27:02.8000247Z test_vec_half_AVX2 2025-12-04T10:27:02.8000477Z test_vec_half_AVX512 2025-12-04T10:27:02.8000729Z test_vec_half_DEFAULT 2025-12-04T10:27:02.8000986Z thread_init_test 2025-12-04T10:27:02.8001210Z torch_shm_manager 2025-12-04T10:27:02.8001442Z type_ptr_test 2025-12-04T10:27:02.8001660Z type_test 2025-12-04T10:27:02.8001866Z undefined_tensor_test 2025-12-04T10:27:02.8002125Z vec_test_all_types_AVX2 2025-12-04T10:27:02.8002398Z vec_test_all_types_AVX512 2025-12-04T10:27:02.8002666Z vec_test_all_types_DEFAULT 2025-12-04T10:27:02.8002952Z verify_api_visibility 2025-12-04T10:27:02.8003202Z weakref_test 2025-12-04T10:27:02.8003511Z wrapdim_test 2025-12-04T10:27:02.8003883Z xla_tensor_test 2025-12-04T10:27:02.8004170Z + aten/tools/run_tests.sh build/bin 2025-12-04T10:27:02.8004482Z + set -e 2025-12-04T10:27:02.8004875Z ++ dirname aten/tools/run_tests.sh 2025-12-04T10:27:02.8005361Z + VALGRIND_SUP=/var/lib/jenkins/workspace/aten/tools/valgrind.sup 2025-12-04T10:27:02.8005820Z + export CPP_TESTS_DIR=build/bin 2025-12-04T10:27:02.8006117Z + CPP_TESTS_DIR=build/bin 2025-12-04T10:27:02.8006386Z + VALGRIND=ON 2025-12-04T10:27:02.8008445Z + python test/run_test.py --cpp --verbose -i cpp/basic cpp/atest cpp/scalar_test cpp/broadcast_test cpp/wrapdim_test cpp/apply_utils_test cpp/dlconvertor_test cpp/native_test cpp/scalar_tensor_test cpp/undefined_tensor_test cpp/extension_backend_test cpp/lazy_tensor_test cpp/tensor_iterator_test cpp/Dimname_test cpp/Dict_test cpp/NamedTensor_test cpp/cpu_generator_test cpp/legacy_vmap_test cpp/operators_test 2025-12-04T10:27:04.3967445Z W1204 10:27:04.396000 78369 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:07.8693369Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:27:07.8797044Z Found test times from artifacts 2025-12-04T10:27:07.9195678Z Found test times from artifacts 2025-12-04T10:27:07.9208147Z Running all tests 2025-12-04T10:27:07.9213167Z Running parallel tests on 3 processes 2025-12-04T10:27:07.9215176Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:27:07.9215539Z Serial tests (0): 2025-12-04T10:27:07.9215786Z Parallel tests (19): 2025-12-04T10:27:07.9216051Z cpp/Dict_test 1/1 2025-12-04T10:27:07.9216316Z cpp/Dimname_test 1/1 2025-12-04T10:27:07.9216587Z cpp/NamedTensor_test 1/1 2025-12-04T10:27:07.9216886Z cpp/apply_utils_test 1/1 2025-12-04T10:27:07.9217166Z cpp/atest 1/1 2025-12-04T10:27:07.9217399Z cpp/basic 1/1 2025-12-04T10:27:07.9217647Z cpp/broadcast_test 1/1 2025-12-04T10:27:07.9217935Z cpp/cpu_generator_test 1/1 2025-12-04T10:27:07.9218220Z cpp/dlconvertor_test 1/1 2025-12-04T10:27:07.9218754Z cpp/extension_backend_test 1/1 2025-12-04T10:27:07.9219074Z cpp/lazy_tensor_test 1/1 2025-12-04T10:27:07.9219354Z cpp/legacy_vmap_test 1/1 2025-12-04T10:27:07.9219641Z cpp/native_test 1/1 2025-12-04T10:27:07.9220091Z cpp/operators_test 1/1 2025-12-04T10:27:07.9220383Z cpp/scalar_tensor_test 1/1 2025-12-04T10:27:07.9220662Z cpp/scalar_test 1/1 2025-12-04T10:27:07.9220953Z cpp/tensor_iterator_test 1/1 2025-12-04T10:27:07.9221557Z cpp/undefined_tensor_test 1/1 2025-12-04T10:27:07.9221861Z cpp/wrapdim_test 1/1 2025-12-04T10:27:07.9222142Z Name: excluded (est. time: 0.0min) 2025-12-04T10:27:07.9222448Z Serial tests (0): 2025-12-04T10:27:07.9222682Z Parallel tests (0): 2025-12-04T10:27:07.9223076Z Running cpp/Dict_test 1/1 ... [2025-12-04 10:27:07.921869][4570.60764203] 2025-12-04T10:27:07.9223543Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:07.9223946Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:07.9224533Z Finished cpp/Dict_test 1/1 ... [2025-12-04 10:27:07.922044][4570.607819468], took 0.00min 2025-12-04T10:27:08.5038856Z Uploading artifacts took 0.55 seconds 2025-12-04T10:27:08.5039401Z Running cpp/Dimname_test 1/1 ... [2025-12-04 10:27:08.503629][4571.189400976] 2025-12-04T10:27:08.5039874Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.5040299Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.5040934Z Finished cpp/Dimname_test 1/1 ... [2025-12-04 10:27:08.503791][4571.189566154], took 0.00min 2025-12-04T10:27:08.5354156Z Running cpp/NamedTensor_test 1/1 ... [2025-12-04 10:27:08.535158][4571.220928803] 2025-12-04T10:27:08.5355143Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.5355941Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.5356591Z Finished cpp/NamedTensor_test 1/1 ... [2025-12-04 10:27:08.535322][4571.221096563], took 0.00min 2025-12-04T10:27:08.5660825Z Running cpp/apply_utils_test 1/1 ... [2025-12-04 10:27:08.565830][4571.251603279] 2025-12-04T10:27:08.5661844Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.5662378Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.5662993Z Finished cpp/apply_utils_test 1/1 ... [2025-12-04 10:27:08.565983][4571.25175765], took 0.00min 2025-12-04T10:27:08.5965592Z Running cpp/atest 1/1 ... [2025-12-04 10:27:08.596317][4571.282090859] 2025-12-04T10:27:08.5966792Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.5967392Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.5968186Z Finished cpp/atest 1/1 ... [2025-12-04 10:27:08.596469][4571.282236496], took 0.00min 2025-12-04T10:27:08.6267087Z Running cpp/basic 1/1 ... [2025-12-04 10:27:08.626416][4571.312189404] 2025-12-04T10:27:08.6267935Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.6268370Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.6268946Z Finished cpp/basic 1/1 ... [2025-12-04 10:27:08.626573][4571.312343322], took 0.00min 2025-12-04T10:27:08.6568664Z Running cpp/broadcast_test 1/1 ... [2025-12-04 10:27:08.656655][4571.342428866] 2025-12-04T10:27:08.6569405Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.6570177Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.6571013Z Finished cpp/broadcast_test 1/1 ... [2025-12-04 10:27:08.656818][4571.342593038], took 0.00min 2025-12-04T10:27:08.6868542Z Running cpp/cpu_generator_test 1/1 ... [2025-12-04 10:27:08.686603][4571.372376438] 2025-12-04T10:27:08.6876171Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.6876873Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.6877511Z Finished cpp/cpu_generator_test 1/1 ... [2025-12-04 10:27:08.686760][4571.372530628], took 0.00min 2025-12-04T10:27:08.7171565Z Running cpp/dlconvertor_test 1/1 ... [2025-12-04 10:27:08.716922][4571.402695546] 2025-12-04T10:27:08.7172504Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.7173301Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.7174073Z Finished cpp/dlconvertor_test 1/1 ... [2025-12-04 10:27:08.717081][4571.402854846], took 0.00min 2025-12-04T10:27:08.7473357Z Running cpp/extension_backend_test 1/1 ... [2025-12-04 10:27:08.747033][4571.432805145] 2025-12-04T10:27:08.7474104Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.7474529Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.7475187Z Finished cpp/extension_backend_test 1/1 ... [2025-12-04 10:27:08.747191][4571.432964959], took 0.00min 2025-12-04T10:27:08.7774598Z Running cpp/lazy_tensor_test 1/1 ... [2025-12-04 10:27:08.777210][4571.462983286] 2025-12-04T10:27:08.7775577Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.7776073Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.7776684Z Finished cpp/lazy_tensor_test 1/1 ... [2025-12-04 10:27:08.777383][4571.463157358], took 0.00min 2025-12-04T10:27:08.8075169Z Running cpp/legacy_vmap_test 1/1 ... [2025-12-04 10:27:08.807261][4571.493034509] 2025-12-04T10:27:08.8076171Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.8076588Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.8077205Z Finished cpp/legacy_vmap_test 1/1 ... [2025-12-04 10:27:08.807415][4571.49318601], took 0.00min 2025-12-04T10:27:08.8377397Z Running cpp/native_test 1/1 ... [2025-12-04 10:27:08.837485][4571.523259067] 2025-12-04T10:27:08.8378332Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.8378844Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.8379441Z Finished cpp/native_test 1/1 ... [2025-12-04 10:27:08.837642][4571.523412372], took 0.00min 2025-12-04T10:27:08.8677689Z Running cpp/operators_test 1/1 ... [2025-12-04 10:27:08.867522][4571.553295928] 2025-12-04T10:27:08.8678648Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.8679178Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.8679794Z Finished cpp/operators_test 1/1 ... [2025-12-04 10:27:08.867684][4571.553459064], took 0.00min 2025-12-04T10:27:08.8978695Z Running cpp/scalar_tensor_test 1/1 ... [2025-12-04 10:27:08.897653][4571.583426699] 2025-12-04T10:27:08.8979490Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.8980262Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.8981098Z Finished cpp/scalar_tensor_test 1/1 ... [2025-12-04 10:27:08.897814][4571.583588781], took 0.00min 2025-12-04T10:27:08.9277115Z Running cpp/scalar_test 1/1 ... [2025-12-04 10:27:08.927457][4571.613230938] 2025-12-04T10:27:08.9278021Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.9278446Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.9279136Z Finished cpp/scalar_test 1/1 ... [2025-12-04 10:27:08.927609][4571.613383537], took 0.00min 2025-12-04T10:27:08.9578181Z Running cpp/tensor_iterator_test 1/1 ... [2025-12-04 10:27:08.957575][4571.643348284] 2025-12-04T10:27:08.9579192Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.9579825Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.9580464Z Finished cpp/tensor_iterator_test 1/1 ... [2025-12-04 10:27:08.957733][4571.643508333], took 0.00min 2025-12-04T10:27:08.9877911Z Running cpp/undefined_tensor_test 1/1 ... [2025-12-04 10:27:08.987548][4571.673321941] 2025-12-04T10:27:08.9878960Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:08.9879565Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:08.9880215Z Finished cpp/undefined_tensor_test 1/1 ... [2025-12-04 10:27:08.987700][4571.673474672], took 0.00min 2025-12-04T10:27:09.0178323Z Running cpp/wrapdim_test 1/1 ... [2025-12-04 10:27:09.017546][4571.703319577] 2025-12-04T10:27:09.0179184Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:09.0179614Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:09.0180215Z Finished cpp/wrapdim_test 1/1 ... [2025-12-04 10:27:09.017693][4571.703467817], took 0.00min 2025-12-04T10:27:10.7395594Z W1204 10:27:10.738000 78393 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:10.7397019Z W1204 10:27:10.739000 78394 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:10.7562128Z W1204 10:27:10.755000 78395 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:12.0840024Z Running cpp/Dict_test 1/1 ... [2025-12-04 10:27:12.083539][4574.769308649] 2025-12-04T10:27:12.0840548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:12.0841155Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:12.0853178Z Finished cpp/Dict_test 1/1 ... [2025-12-04 10:27:12.083728][4574.769502972], took 0.00min 2025-12-04T10:27:12.0854429Z Running cpp/Dimname_test 1/1 ... [2025-12-04 10:27:12.085062][4574.770831345] 2025-12-04T10:27:12.0855382Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:12.0856220Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:12.0857456Z Finished cpp/Dimname_test 1/1 ... [2025-12-04 10:27:12.085249][4574.771023811], took 0.00min 2025-12-04T10:27:12.1083100Z Running cpp/NamedTensor_test 1/1 ... [2025-12-04 10:27:12.107918][4574.793686951] 2025-12-04T10:27:12.1084187Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:12.1085057Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:12.1086350Z Finished cpp/NamedTensor_test 1/1 ... [2025-12-04 10:27:12.108110][4574.793885035], took 0.00min 2025-12-04T10:27:14.5349177Z W1204 10:27:14.534000 78448 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:14.5447681Z W1204 10:27:14.544000 78449 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:14.5808320Z W1204 10:27:14.580000 78447 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:15.8768076Z Running cpp/apply_utils_test 1/1 ... [2025-12-04 10:27:15.876339][4578.562108538] 2025-12-04T10:27:15.8768998Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:15.8769716Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:15.8771163Z Finished cpp/apply_utils_test 1/1 ... [2025-12-04 10:27:15.876540][4578.56231341], took 0.00min 2025-12-04T10:27:15.9126633Z Running cpp/atest 1/1 ... [2025-12-04 10:27:15.912253][4578.598019371] 2025-12-04T10:27:15.9127477Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:15.9128218Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:15.9129495Z Finished cpp/atest 1/1 ... [2025-12-04 10:27:15.912571][4578.598341014], took 0.00min 2025-12-04T10:27:15.9380053Z Running cpp/basic 1/1 ... [2025-12-04 10:27:15.937620][4578.623389045] 2025-12-04T10:27:15.9380824Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:15.9381591Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:15.9382596Z Finished cpp/basic 1/1 ... [2025-12-04 10:27:15.937815][4578.623589429], took 0.00min 2025-12-04T10:27:18.3292368Z W1204 10:27:18.328000 78498 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:18.3940876Z W1204 10:27:18.393000 78500 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:18.4169293Z W1204 10:27:18.416000 78499 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:19.6632972Z Running cpp/broadcast_test 1/1 ... [2025-12-04 10:27:19.662873][4582.348642384] 2025-12-04T10:27:19.6633555Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:19.6633972Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:19.6634840Z Finished cpp/broadcast_test 1/1 ... [2025-12-04 10:27:19.663108][4582.34888118], took 0.00min 2025-12-04T10:27:19.7348419Z Running cpp/cpu_generator_test 1/1 ... [2025-12-04 10:27:19.734498][4582.420266295] 2025-12-04T10:27:19.7348948Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:19.7775644Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:19.7776342Z Finished cpp/cpu_generator_test 1/1 ... [2025-12-04 10:27:19.734697][4582.420471693], took 0.00min 2025-12-04T10:27:19.7777037Z Running cpp/dlconvertor_test 1/1 ... [2025-12-04 10:27:19.777182][4582.462951044] 2025-12-04T10:27:19.7777535Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:19.7777966Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:19.7778601Z Finished cpp/dlconvertor_test 1/1 ... [2025-12-04 10:27:19.777423][4582.463191086], took 0.00min 2025-12-04T10:27:22.1587442Z W1204 10:27:22.158000 78549 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:22.1714936Z W1204 10:27:22.170000 78550 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:22.2342891Z W1204 10:27:22.233000 78551 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:23.5054125Z Running cpp/extension_backend_test 1/1 ... [2025-12-04 10:27:23.504923][4586.19069272] 2025-12-04T10:27:23.5054695Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:23.5055109Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:23.5055768Z Finished cpp/extension_backend_test 1/1 ... [2025-12-04 10:27:23.505116][4586.19089085], took 0.00min 2025-12-04T10:27:23.5061305Z Running cpp/lazy_tensor_test 1/1 ... [2025-12-04 10:27:23.505850][4586.191619999] 2025-12-04T10:27:23.5061842Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:23.5062375Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:23.5063007Z Finished cpp/lazy_tensor_test 1/1 ... [2025-12-04 10:27:23.506030][4586.191805321], took 0.00min 2025-12-04T10:27:23.5980814Z Running cpp/legacy_vmap_test 1/1 ... [2025-12-04 10:27:23.597719][4586.283488558] 2025-12-04T10:27:23.5981765Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:23.5982528Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:23.5983983Z Finished cpp/legacy_vmap_test 1/1 ... [2025-12-04 10:27:23.597913][4586.283687503], took 0.00min 2025-12-04T10:27:25.9918915Z W1204 10:27:25.991000 78601 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:26.0276500Z W1204 10:27:26.026000 78600 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:26.1017657Z W1204 10:27:26.101000 78602 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:27.3611809Z Running cpp/native_test 1/1 ... [2025-12-04 10:27:27.360734][4590.046502023] 2025-12-04T10:27:27.3612345Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:27.3612773Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:27.3613366Z Finished cpp/native_test 1/1 ... [2025-12-04 10:27:27.360931][4590.046705616], took 0.00min 2025-12-04T10:27:27.4041148Z Running cpp/operators_test 1/1 ... [2025-12-04 10:27:27.403742][4590.089510661] 2025-12-04T10:27:27.4041705Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:27.4042117Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:27.4042982Z Finished cpp/operators_test 1/1 ... [2025-12-04 10:27:27.403994][4590.089766914], took 0.00min 2025-12-04T10:27:27.4562605Z Running cpp/scalar_tensor_test 1/1 ... [2025-12-04 10:27:27.455879][4590.141648546] 2025-12-04T10:27:27.4563136Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:27.4563550Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:27.4564419Z Finished cpp/scalar_tensor_test 1/1 ... [2025-12-04 10:27:27.456127][4590.141899515], took 0.00min 2025-12-04T10:27:29.9382144Z W1204 10:27:29.937000 78651 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:29.9754405Z W1204 10:27:29.974000 78652 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:30.0114225Z W1204 10:27:30.010000 78653 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:31.3116055Z Running cpp/scalar_test 1/1 ... [2025-12-04 10:27:31.311155][4593.996923545] 2025-12-04T10:27:31.3116624Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:31.3117034Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:31.3117639Z Finished cpp/scalar_test 1/1 ... [2025-12-04 10:27:31.311378][4593.99714588], took 0.00min 2025-12-04T10:27:31.3586092Z Running cpp/tensor_iterator_test 1/1 ... [2025-12-04 10:27:31.358249][4594.044017206] 2025-12-04T10:27:31.3586726Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:31.3587132Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:31.3587778Z Finished cpp/tensor_iterator_test 1/1 ... [2025-12-04 10:27:31.358498][4594.044270398], took 0.00min 2025-12-04T10:27:31.3778365Z Running cpp/undefined_tensor_test 1/1 ... [2025-12-04 10:27:31.377443][4594.063212373] 2025-12-04T10:27:31.3779042Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:31.3779462Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:31.3780119Z Finished cpp/undefined_tensor_test 1/1 ... [2025-12-04 10:27:31.377640][4594.063414283], took 0.00min 2025-12-04T10:27:33.8183515Z W1204 10:27:33.817000 78702 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:33.8341631Z W1204 10:27:33.833000 78703 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:33.8603859Z W1204 10:27:33.859000 78704 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:35.1948110Z Running cpp/wrapdim_test 1/1 ... [2025-12-04 10:27:35.194343][4597.880112311] 2025-12-04T10:27:35.1949211Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:35.1949694Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:35.1950581Z Finished cpp/wrapdim_test 1/1 ... [2025-12-04 10:27:35.194577][4597.880351375], took 0.00min 2025-12-04T10:27:36.0305660Z Running test batch 'tests to run' cost 28.11 seconds 2025-12-04T10:27:36.7690857Z + run_if_exists tensor_interop_test 2025-12-04T10:27:36.7691358Z + local test_name=tensor_interop_test 2025-12-04T10:27:36.7691708Z + [[ -x build/bin/tensor_interop_test ]] 2025-12-04T10:27:36.7692110Z + echo 'Warning: tensor_interop_test does not exist.' 2025-12-04T10:27:36.7692550Z Warning: tensor_interop_test does not exist. 2025-12-04T10:27:36.7692903Z + run_if_exists cudnn_test 2025-12-04T10:27:36.7693176Z + local test_name=cudnn_test 2025-12-04T10:27:36.7693477Z + [[ -x build/bin/cudnn_test ]] 2025-12-04T10:27:36.7693798Z + echo 'Warning: cudnn_test does not exist.' 2025-12-04T10:27:36.7694136Z Warning: cudnn_test does not exist. 2025-12-04T10:27:36.7694478Z + run_if_exists cuda_generator_test 2025-12-04T10:27:36.7694806Z + local test_name=cuda_generator_test 2025-12-04T10:27:36.7695144Z + [[ -x build/bin/cuda_generator_test ]] 2025-12-04T10:27:36.7695616Z + python test/run_test.py --cpp --verbose -i cpp/cuda_generator_test 2025-12-04T10:27:38.3774376Z W1204 10:27:38.376000 78753 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:41.9381839Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:27:41.9485699Z Found test times from artifacts 2025-12-04T10:27:41.9889005Z Found test times from artifacts 2025-12-04T10:27:41.9901680Z Running all tests 2025-12-04T10:27:41.9905847Z Running parallel tests on 3 processes 2025-12-04T10:27:41.9906212Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:27:41.9906532Z Serial tests (0): 2025-12-04T10:27:41.9906790Z Parallel tests (1): 2025-12-04T10:27:41.9907095Z cpp/cuda_generator_test 1/1 2025-12-04T10:27:41.9907495Z Name: excluded (est. time: 0.0min) 2025-12-04T10:27:41.9907807Z Serial tests (0): 2025-12-04T10:27:41.9908193Z Parallel tests (0): 2025-12-04T10:27:41.9908707Z Running cpp/cuda_generator_test 1/1 ... [2025-12-04 10:27:41.990622][4604.676395591] 2025-12-04T10:27:41.9909232Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:41.9909788Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:41.9910430Z Finished cpp/cuda_generator_test 1/1 ... [2025-12-04 10:27:41.990814][4604.676585622], took 0.00min 2025-12-04T10:27:42.5226078Z Uploading artifacts took 0.50 seconds 2025-12-04T10:27:44.2340481Z W1204 10:27:44.233000 78779 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:44.2419208Z W1204 10:27:44.241000 78777 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:44.2474951Z W1204 10:27:44.246000 78778 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:45.5979581Z Running cpp/cuda_generator_test 1/1 ... [2025-12-04 10:27:45.597520][4608.283289961] 2025-12-04T10:27:45.5980150Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:45.5980607Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:45.5981246Z Finished cpp/cuda_generator_test 1/1 ... [2025-12-04 10:27:45.597708][4608.283483265], took 0.00min 2025-12-04T10:27:46.3840838Z Running test batch 'tests to run' cost 4.39 seconds 2025-12-04T10:27:47.0763491Z + run_if_exists apply_test 2025-12-04T10:27:47.0763865Z + local test_name=apply_test 2025-12-04T10:27:47.0764175Z + [[ -x build/bin/apply_test ]] 2025-12-04T10:27:47.0764508Z + echo 'Warning: apply_test does not exist.' 2025-12-04T10:27:47.0764925Z Warning: apply_test does not exist. 2025-12-04T10:27:47.0765249Z + run_if_exists stream_test 2025-12-04T10:27:47.0765895Z + local test_name=stream_test 2025-12-04T10:27:47.0766200Z + [[ -x build/bin/stream_test ]] 2025-12-04T10:27:47.0766529Z + echo 'Warning: stream_test does not exist.' 2025-12-04T10:27:47.0766880Z Warning: stream_test does not exist. 2025-12-04T10:27:47.0767209Z + run_if_exists cuda_half_test 2025-12-04T10:27:47.0767514Z + local test_name=cuda_half_test 2025-12-04T10:27:47.0767872Z + [[ -x build/bin/cuda_half_test ]] 2025-12-04T10:27:47.0768298Z + python test/run_test.py --cpp --verbose -i cpp/cuda_half_test 2025-12-04T10:27:48.6583843Z W1204 10:27:48.657000 78831 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:52.0972571Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:27:52.1077000Z Found test times from artifacts 2025-12-04T10:27:52.1477694Z Found test times from artifacts 2025-12-04T10:27:52.1489900Z Running all tests 2025-12-04T10:27:52.1492863Z Running parallel tests on 3 processes 2025-12-04T10:27:52.1493224Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:27:52.1493545Z Serial tests (0): 2025-12-04T10:27:52.1493807Z Parallel tests (1): 2025-12-04T10:27:52.1494060Z cpp/cuda_half_test 1/1 2025-12-04T10:27:52.1494354Z Name: excluded (est. time: 0.0min) 2025-12-04T10:27:52.1494669Z Serial tests (0): 2025-12-04T10:27:52.1494903Z Parallel tests (0): 2025-12-04T10:27:52.1495674Z Running cpp/cuda_half_test 1/1 ... [2025-12-04 10:27:52.149347][4614.835121223] 2025-12-04T10:27:52.1496472Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:52.1497064Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:52.1497674Z Finished cpp/cuda_half_test 1/1 ... [2025-12-04 10:27:52.149510][4614.83528492], took 0.00min 2025-12-04T10:27:52.7130906Z Uploading artifacts took 0.53 seconds 2025-12-04T10:27:54.3703404Z W1204 10:27:54.369000 78855 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:54.3860608Z W1204 10:27:54.385000 78856 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:54.4062195Z W1204 10:27:54.405000 78857 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:27:55.7275766Z Running cpp/cuda_half_test 1/1 ... [2025-12-04 10:27:55.727118][4618.412887754] 2025-12-04T10:27:55.7276310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:27:55.7276735Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:27:55.7277367Z Finished cpp/cuda_half_test 1/1 ... [2025-12-04 10:27:55.727341][4618.413115085], took 0.00min 2025-12-04T10:27:56.5509365Z Running test batch 'tests to run' cost 4.4 seconds 2025-12-04T10:27:57.2788887Z + run_if_exists cuda_vectorized_test 2025-12-04T10:27:57.2789373Z + local test_name=cuda_vectorized_test 2025-12-04T10:27:57.2790723Z + [[ -x build/bin/cuda_vectorized_test ]] 2025-12-04T10:27:57.2791254Z + python test/run_test.py --cpp --verbose -i cpp/cuda_vectorized_test 2025-12-04T10:27:58.8858342Z W1204 10:27:58.885000 78909 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:02.4061174Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:02.4164984Z Found test times from artifacts 2025-12-04T10:28:02.4563154Z Found test times from artifacts 2025-12-04T10:28:02.4574955Z Running all tests 2025-12-04T10:28:02.4578769Z Running parallel tests on 3 processes 2025-12-04T10:28:02.4579190Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:02.4579508Z Serial tests (0): 2025-12-04T10:28:02.4579765Z Parallel tests (1): 2025-12-04T10:28:02.4580176Z cpp/cuda_vectorized_test 1/1 2025-12-04T10:28:02.4580481Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:02.4581299Z Serial tests (0): 2025-12-04T10:28:02.4581565Z Parallel tests (0): 2025-12-04T10:28:02.4582167Z Running cpp/cuda_vectorized_test 1/1 ... [2025-12-04 10:28:02.457861][4625.143634965] 2025-12-04T10:28:02.4582695Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:02.4583121Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:02.4583824Z Finished cpp/cuda_vectorized_test 1/1 ... [2025-12-04 10:28:02.458015][4625.143790545], took 0.00min 2025-12-04T10:28:03.0343989Z Uploading artifacts took 0.55 seconds 2025-12-04T10:28:04.6793937Z W1204 10:28:04.678000 78934 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:04.6817473Z W1204 10:28:04.681000 78933 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:04.7385135Z W1204 10:28:04.737000 78935 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:06.0328358Z Running cpp/cuda_vectorized_test 1/1 ... [2025-12-04 10:28:06.032412][4628.718181391] 2025-12-04T10:28:06.0329101Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:06.0329706Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:06.0330533Z Finished cpp/cuda_vectorized_test 1/1 ... [2025-12-04 10:28:06.032648][4628.718421793], took 0.00min 2025-12-04T10:28:06.8757908Z Running test batch 'tests to run' cost 4.42 seconds 2025-12-04T10:28:07.6167937Z + run_if_exists cuda_distributions_test 2025-12-04T10:28:07.6168607Z + local test_name=cuda_distributions_test 2025-12-04T10:28:07.6169002Z + [[ -x build/bin/cuda_distributions_test ]] 2025-12-04T10:28:07.6169498Z + python test/run_test.py --cpp --verbose -i cpp/cuda_distributions_test 2025-12-04T10:28:09.2351171Z W1204 10:28:09.234000 78987 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:12.7949431Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:12.8053706Z Found test times from artifacts 2025-12-04T10:28:12.8453708Z Found test times from artifacts 2025-12-04T10:28:12.8465865Z Running all tests 2025-12-04T10:28:12.8469199Z Running parallel tests on 3 processes 2025-12-04T10:28:12.8469578Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:12.8469899Z Serial tests (0): 2025-12-04T10:28:12.8470152Z Parallel tests (1): 2025-12-04T10:28:12.8470419Z cpp/cuda_distributions_test 1/1 2025-12-04T10:28:12.8470916Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:12.8471281Z Serial tests (0): 2025-12-04T10:28:12.8471525Z Parallel tests (0): 2025-12-04T10:28:12.8471985Z Running cpp/cuda_distributions_test 1/1 ... [2025-12-04 10:28:12.846947][4635.532720951] 2025-12-04T10:28:12.8472735Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:12.8473173Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:12.8473825Z Finished cpp/cuda_distributions_test 1/1 ... [2025-12-04 10:28:12.847107][4635.532882385], took 0.00min 2025-12-04T10:28:13.3753212Z Uploading artifacts took 0.50 seconds 2025-12-04T10:28:15.0659091Z W1204 10:28:15.065000 79012 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:15.0666021Z W1204 10:28:15.066000 79011 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:15.1071267Z W1204 10:28:15.106000 79013 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:16.4173562Z Running cpp/cuda_distributions_test 1/1 ... [2025-12-04 10:28:16.416877][4639.102645685] 2025-12-04T10:28:16.4174504Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:16.4175181Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:16.4176677Z Finished cpp/cuda_distributions_test 1/1 ... [2025-12-04 10:28:16.417070][4639.102845115], took 0.00min 2025-12-04T10:28:17.2190260Z Running test batch 'tests to run' cost 4.37 seconds 2025-12-04T10:28:17.9086053Z + run_if_exists cuda_optional_test 2025-12-04T10:28:17.9086462Z + local test_name=cuda_optional_test 2025-12-04T10:28:17.9086799Z + [[ -x build/bin/cuda_optional_test ]] 2025-12-04T10:28:17.9087517Z + python test/run_test.py --cpp --verbose -i cpp/cuda_optional_test 2025-12-04T10:28:19.4971469Z W1204 10:28:19.496000 79065 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:22.9733611Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:22.9837944Z Found test times from artifacts 2025-12-04T10:28:23.0239213Z Found test times from artifacts 2025-12-04T10:28:23.0251703Z Running all tests 2025-12-04T10:28:23.0254973Z Running parallel tests on 3 processes 2025-12-04T10:28:23.0255348Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:23.0255673Z Serial tests (0): 2025-12-04T10:28:23.0255929Z Parallel tests (1): 2025-12-04T10:28:23.0256260Z cpp/cuda_optional_test 1/1 2025-12-04T10:28:23.0256579Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:23.0256885Z Serial tests (0): 2025-12-04T10:28:23.0257290Z Parallel tests (0): 2025-12-04T10:28:23.0257757Z Running cpp/cuda_optional_test 1/1 ... [2025-12-04 10:28:23.025519][4645.711292858] 2025-12-04T10:28:23.0258419Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:23.0259131Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:23.0259883Z Finished cpp/cuda_optional_test 1/1 ... [2025-12-04 10:28:23.025675][4645.711450685], took 0.00min 2025-12-04T10:28:23.5678201Z Uploading artifacts took 0.51 seconds 2025-12-04T10:28:25.2311945Z W1204 10:28:25.230000 79090 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:25.2347804Z W1204 10:28:25.234000 79089 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:25.2798625Z W1204 10:28:25.279000 79091 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:26.5777357Z Running cpp/cuda_optional_test 1/1 ... [2025-12-04 10:28:26.577338][4649.263106608] 2025-12-04T10:28:26.5777924Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:26.5778367Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:26.5779008Z Finished cpp/cuda_optional_test 1/1 ... [2025-12-04 10:28:26.577572][4649.2633455], took 0.00min 2025-12-04T10:28:27.3904759Z Running test batch 'tests to run' cost 4.36 seconds 2025-12-04T10:28:28.0824325Z + run_if_exists cuda_tensor_interop_test 2025-12-04T10:28:28.0824747Z + local test_name=cuda_tensor_interop_test 2025-12-04T10:28:28.0825284Z + [[ -x build/bin/cuda_tensor_interop_test ]] 2025-12-04T10:28:28.0825716Z + echo 'Warning: cuda_tensor_interop_test does not exist.' 2025-12-04T10:28:28.0826281Z Warning: cuda_tensor_interop_test does not exist. 2025-12-04T10:28:28.0826760Z + run_if_exists cuda_complex_test 2025-12-04T10:28:28.0827085Z + local test_name=cuda_complex_test 2025-12-04T10:28:28.0827573Z + [[ -x build/bin/cuda_complex_test ]] 2025-12-04T10:28:28.0828015Z + python test/run_test.py --cpp --verbose -i cpp/cuda_complex_test 2025-12-04T10:28:29.6849068Z W1204 10:28:29.684000 79143 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:33.1596026Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:33.1699553Z Found test times from artifacts 2025-12-04T10:28:33.2099146Z Found test times from artifacts 2025-12-04T10:28:33.2111650Z Running all tests 2025-12-04T10:28:33.2115782Z Running parallel tests on 3 processes 2025-12-04T10:28:33.2116170Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:33.2116673Z Serial tests (0): 2025-12-04T10:28:33.2117132Z Parallel tests (1): 2025-12-04T10:28:33.2117408Z cpp/cuda_complex_test 1/1 2025-12-04T10:28:33.2117719Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:33.2118485Z Serial tests (0): 2025-12-04T10:28:33.2118728Z Parallel tests (0): 2025-12-04T10:28:33.2119152Z Running cpp/cuda_complex_test 1/1 ... [2025-12-04 10:28:33.211561][4655.89733511] 2025-12-04T10:28:33.2119646Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:33.2120056Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:33.2120678Z Finished cpp/cuda_complex_test 1/1 ... [2025-12-04 10:28:33.211749][4655.897520777], took 0.00min 2025-12-04T10:28:33.7459827Z Uploading artifacts took 0.50 seconds 2025-12-04T10:28:35.4243118Z W1204 10:28:35.423000 79168 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:35.4344540Z W1204 10:28:35.433000 79169 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:35.4369892Z W1204 10:28:35.436000 79167 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:36.7803642Z Running cpp/cuda_complex_test 1/1 ... [2025-12-04 10:28:36.779874][4659.465643446] 2025-12-04T10:28:36.7804452Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:36.7805305Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:36.7806760Z Finished cpp/cuda_complex_test 1/1 ... [2025-12-04 10:28:36.780067][4659.465842346], took 0.00min 2025-12-04T10:28:37.5667016Z Running test batch 'tests to run' cost 4.35 seconds 2025-12-04T10:28:38.2923285Z + run_if_exists cuda_complex_math_test 2025-12-04T10:28:38.2923807Z + local test_name=cuda_complex_math_test 2025-12-04T10:28:38.2924212Z + [[ -x build/bin/cuda_complex_math_test ]] 2025-12-04T10:28:38.2924863Z + python test/run_test.py --cpp --verbose -i cpp/cuda_complex_math_test 2025-12-04T10:28:39.8633643Z W1204 10:28:39.862000 79221 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:43.2950418Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:43.3053357Z Found test times from artifacts 2025-12-04T10:28:43.3453864Z Found test times from artifacts 2025-12-04T10:28:43.3466426Z Running all tests 2025-12-04T10:28:43.3469226Z Running parallel tests on 3 processes 2025-12-04T10:28:43.3470083Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:43.3470463Z Serial tests (0): 2025-12-04T10:28:43.3470764Z Parallel tests (1): 2025-12-04T10:28:43.3471156Z cpp/cuda_complex_math_test 1/1 2025-12-04T10:28:43.3471480Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:43.3471978Z Serial tests (0): 2025-12-04T10:28:43.3472268Z Parallel tests (0): 2025-12-04T10:28:43.3472900Z Running cpp/cuda_complex_math_test 1/1 ... [2025-12-04 10:28:43.346969][4666.032743] 2025-12-04T10:28:43.3473583Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:43.3473991Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:43.3474820Z Finished cpp/cuda_complex_math_test 1/1 ... [2025-12-04 10:28:43.347126][4666.03290205], took 0.00min 2025-12-04T10:28:43.8901155Z Uploading artifacts took 0.51 seconds 2025-12-04T10:28:45.5673235Z W1204 10:28:45.566000 79246 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:45.5889117Z W1204 10:28:45.588000 79247 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:45.5964469Z W1204 10:28:45.595000 79245 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:46.9302977Z Running cpp/cuda_complex_math_test 1/1 ... [2025-12-04 10:28:46.929880][4669.615648964] 2025-12-04T10:28:46.9303548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:46.9303980Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:46.9304627Z Finished cpp/cuda_complex_math_test 1/1 ... [2025-12-04 10:28:46.930102][4669.615875346], took 0.00min 2025-12-04T10:28:47.7389181Z Running test batch 'tests to run' cost 4.39 seconds 2025-12-04T10:28:48.4939980Z + run_if_exists cuda_cub_test 2025-12-04T10:28:48.4940347Z + local test_name=cuda_cub_test 2025-12-04T10:28:48.4940698Z + [[ -x build/bin/cuda_cub_test ]] 2025-12-04T10:28:48.4941126Z + python test/run_test.py --cpp --verbose -i cpp/cuda_cub_test 2025-12-04T10:28:50.0896416Z W1204 10:28:50.088000 79299 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:53.5629739Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:28:53.5734144Z Found test times from artifacts 2025-12-04T10:28:53.6135845Z Found test times from artifacts 2025-12-04T10:28:53.6148894Z Running all tests 2025-12-04T10:28:53.6152806Z Running parallel tests on 3 processes 2025-12-04T10:28:53.6153243Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:28:53.6153736Z Serial tests (0): 2025-12-04T10:28:53.6153992Z Parallel tests (1): 2025-12-04T10:28:53.6154261Z cpp/cuda_cub_test 1/1 2025-12-04T10:28:53.6154536Z Name: excluded (est. time: 0.0min) 2025-12-04T10:28:53.6155207Z Serial tests (0): 2025-12-04T10:28:53.6155463Z Parallel tests (0): 2025-12-04T10:28:53.6155856Z Running cpp/cuda_cub_test 1/1 ... [2025-12-04 10:28:53.615297][4676.301070341] 2025-12-04T10:28:53.6156335Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:53.6156750Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:53.6157360Z Finished cpp/cuda_cub_test 1/1 ... [2025-12-04 10:28:53.615464][4676.301239699], took 0.00min 2025-12-04T10:28:54.1207335Z Uploading artifacts took 0.47 seconds 2025-12-04T10:28:55.7926430Z W1204 10:28:55.791000 79324 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:55.8100037Z W1204 10:28:55.809000 79323 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:55.8128810Z W1204 10:28:55.812000 79325 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:28:57.1717244Z Running cpp/cuda_cub_test 1/1 ... [2025-12-04 10:28:57.171261][4679.857029987] 2025-12-04T10:28:57.1718178Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:28:57.1718897Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:28:57.1719952Z Finished cpp/cuda_cub_test 1/1 ... [2025-12-04 10:28:57.171455][4679.857229079], took 0.00min 2025-12-04T10:28:57.9609700Z Running test batch 'tests to run' cost 4.35 seconds 2025-12-04T10:28:58.6715078Z + run_if_exists cuda_atomic_ops_test 2025-12-04T10:28:58.6715491Z + local test_name=cuda_atomic_ops_test 2025-12-04T10:28:58.6715838Z + [[ -x build/bin/cuda_atomic_ops_test ]] 2025-12-04T10:28:58.6716311Z + python test/run_test.py --cpp --verbose -i cpp/cuda_atomic_ops_test 2025-12-04T10:29:00.2672140Z W1204 10:29:00.266000 79377 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:03.7200062Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:29:03.7303563Z Found test times from artifacts 2025-12-04T10:29:03.7702586Z Found test times from artifacts 2025-12-04T10:29:03.7715446Z Running all tests 2025-12-04T10:29:03.7718632Z Running parallel tests on 3 processes 2025-12-04T10:29:03.7719408Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:29:03.7719887Z Serial tests (0): 2025-12-04T10:29:03.7720139Z Parallel tests (1): 2025-12-04T10:29:03.7720414Z cpp/cuda_atomic_ops_test 1/1 2025-12-04T10:29:03.7720872Z Name: excluded (est. time: 0.0min) 2025-12-04T10:29:03.7721164Z Serial tests (0): 2025-12-04T10:29:03.7721554Z Parallel tests (0): 2025-12-04T10:29:03.7722309Z Running cpp/cuda_atomic_ops_test 1/1 ... [2025-12-04 10:29:03.771930][4686.457703669] 2025-12-04T10:29:03.7722811Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:29:03.7723234Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:29:03.7723881Z Finished cpp/cuda_atomic_ops_test 1/1 ... [2025-12-04 10:29:03.772092][4686.457868002], took 0.00min 2025-12-04T10:29:04.3097815Z Uploading artifacts took 0.51 seconds 2025-12-04T10:29:05.9702505Z W1204 10:29:05.969000 79403 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:05.9737935Z W1204 10:29:05.973000 79401 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:05.9754309Z W1204 10:29:05.974000 79402 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:07.3186639Z Running cpp/cuda_atomic_ops_test 1/1 ... [2025-12-04 10:29:07.318236][4690.004005152] 2025-12-04T10:29:07.3187225Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:29:07.3187638Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:29:07.3188275Z Finished cpp/cuda_atomic_ops_test 1/1 ... [2025-12-04 10:29:07.318428][4690.004202841], took 0.00min 2025-12-04T10:29:08.1190231Z Running test batch 'tests to run' cost 4.35 seconds 2025-12-04T10:29:08.8663184Z + run_if_exists cuda_allocator_test 2025-12-04T10:29:08.8663597Z + local test_name=cuda_allocator_test 2025-12-04T10:29:08.8663956Z + [[ -x build/bin/cuda_allocator_test ]] 2025-12-04T10:29:08.8664437Z + python test/run_test.py --cpp --verbose -i cpp/cuda_allocator_test 2025-12-04T10:29:10.4784148Z W1204 10:29:10.477000 79455 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:14.0971468Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:29:14.1075156Z Found test times from artifacts 2025-12-04T10:29:14.1474256Z Found test times from artifacts 2025-12-04T10:29:14.1486902Z Running all tests 2025-12-04T10:29:14.1490936Z Running parallel tests on 3 processes 2025-12-04T10:29:14.1491628Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:29:14.1492027Z Serial tests (0): 2025-12-04T10:29:14.1492468Z Parallel tests (1): 2025-12-04T10:29:14.1492904Z cpp/cuda_allocator_test 1/1 2025-12-04T10:29:14.1493418Z Name: excluded (est. time: 0.0min) 2025-12-04T10:29:14.1493729Z Serial tests (0): 2025-12-04T10:29:14.1493983Z Parallel tests (0): 2025-12-04T10:29:14.1494424Z Running cpp/cuda_allocator_test 1/1 ... [2025-12-04 10:29:14.149073][4696.834846581] 2025-12-04T10:29:14.1494938Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:29:14.1495357Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:29:14.1495987Z Finished cpp/cuda_allocator_test 1/1 ... [2025-12-04 10:29:14.149233][4696.835008044], took 0.00min 2025-12-04T10:29:14.7072993Z Uploading artifacts took 0.53 seconds 2025-12-04T10:29:16.3981984Z W1204 10:29:16.397000 79479 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:16.4113679Z W1204 10:29:16.410000 79481 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:16.4124058Z W1204 10:29:16.411000 79480 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:29:17.7763305Z Running cpp/cuda_allocator_test 1/1 ... [2025-12-04 10:29:17.775858][4700.461628117] 2025-12-04T10:29:17.7763891Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:29:17.7764312Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:29:17.7765028Z Finished cpp/cuda_allocator_test 1/1 ... [2025-12-04 10:29:17.776046][4700.461821548], took 0.00min 2025-12-04T10:29:18.5715905Z Running test batch 'tests to run' cost 4.42 seconds 2025-12-04T10:29:19.3257523Z + '[' ON == ON ']' 2025-12-04T10:29:19.3258388Z + valgrind --suppressions=/var/lib/jenkins/workspace/aten/tools/valgrind.sup --error-exitcode=1 build/bin/basic '--gtest_filter=-*CUDA' 2025-12-04T10:29:19.3521919Z ==79533== Memcheck, a memory error detector 2025-12-04T10:29:19.3522444Z ==79533== Copyright (C) 2002-2022, and GNU GPL'd, by Julian Seward et al. 2025-12-04T10:29:19.3523070Z ==79533== Using Valgrind-3.20.0 and LibVEX; rerun with -h for copyright info 2025-12-04T10:29:19.3523599Z ==79533== Command: build/bin/basic --gtest_filter=-*CUDA 2025-12-04T10:29:19.3524000Z ==79533== 2025-12-04T10:29:19.7148756Z ==79533== Warning: set address range perms: large range [0x4a9b000, 0x18f32000) (defined) 2025-12-04T10:29:19.7150002Z ==79533== Warning: set address range perms: large range [0x599f000, 0x160b8000) (defined) 2025-12-04T10:29:25.0241282Z ==79533== Warning: set address range perms: large range [0x2c52d000, 0x3e071000) (noaccess) 2025-12-04T10:29:25.0242069Z ==79533== Warning: set address range perms: large range [0x2c600000, 0x3df44000) (defined) 2025-12-04T10:29:25.0717517Z ==79533== Warning: set address range perms: large range [0x2d61d000, 0x3df44000) (defined) 2025-12-04T10:29:25.5536101Z ==79533== Warning: set address range perms: large range [0x65bcf000, 0x8bc50000) (noaccess) 2025-12-04T10:29:25.5537175Z ==79533== Warning: set address range perms: large range [0x65c00000, 0x8ba81000) (defined) 2025-12-04T10:30:26.7126020Z Running main() from /var/lib/jenkins/workspace/third_party/googletest/googletest/src/gtest_main.cc 2025-12-04T10:30:26.7446086Z Note: Google Test filter = -*CUDA 2025-12-04T10:30:26.7525335Z [==========] Running 6 tests from 1 test suite. 2025-12-04T10:30:26.7544060Z [----------] Global test environment set-up. 2025-12-04T10:30:26.7609876Z [----------] 6 tests from BasicTest 2025-12-04T10:30:26.7636630Z [ RUN ] BasicTest.BasicTestCPU 2025-12-04T10:30:28.8371358Z 1490 ms 2025-12-04T10:30:28.9420015Z 58 ms 2025-12-04T10:30:29.0801241Z 100 ms 2025-12-04T10:30:31.9536129Z [ OK ] BasicTest.BasicTestCPU (5187 ms) 2025-12-04T10:30:31.9730057Z [ RUN ] BasicTest.BasicTestHalfCPU 2025-12-04T10:30:32.7078251Z 690 ms 2025-12-04T10:30:32.7598133Z 47 ms 2025-12-04T10:30:32.8270163Z 65 ms 2025-12-04T10:30:32.8813900Z [ OK ] BasicTest.BasicTestHalfCPU (908 ms) 2025-12-04T10:30:32.8815672Z [ RUN ] BasicTest.FactoryMethodsTest 2025-12-04T10:30:32.9224038Z [ OK ] BasicTest.FactoryMethodsTest (40 ms) 2025-12-04T10:30:32.9226274Z [ RUN ] BasicTest.BasicStdTestCPU 2025-12-04T10:30:32.9657692Z Simple example: called once 2025-12-04T10:30:33.1019355Z throw: call_once will retry 2025-12-04T10:30:33.1045444Z throw: call_once will retry 2025-12-04T10:30:33.1468512Z Didn't throw, call_once will not attempt again 2025-12-04T10:30:33.1493063Z [ OK ] BasicTest.BasicStdTestCPU (226 ms) 2025-12-04T10:30:33.1493466Z [ RUN ] BasicTest.TestForBlobResizeCPU 2025-12-04T10:30:33.1700151Z [ OK ] BasicTest.TestForBlobResizeCPU (20 ms) 2025-12-04T10:30:33.1700624Z [ RUN ] BasicTest.TestForBlobStridesResizeCPU 2025-12-04T10:30:33.1745781Z [ OK ] BasicTest.TestForBlobStridesResizeCPU (4 ms) 2025-12-04T10:30:33.1767379Z [----------] 6 tests from BasicTest (6412 ms total) 2025-12-04T10:30:33.1767642Z 2025-12-04T10:30:33.1781444Z [----------] Global test environment tear-down 2025-12-04T10:30:33.1807829Z [==========] 6 tests from 1 test suite ran. (6440 ms total) 2025-12-04T10:30:33.1821869Z [ PASSED ] 6 tests. 2025-12-04T10:30:35.9569162Z ==79533== 2025-12-04T10:30:35.9575946Z ==79533== HEAP SUMMARY: 2025-12-04T10:30:35.9576910Z ==79533== in use at exit: 1,022,944 bytes in 6,494 blocks 2025-12-04T10:30:35.9577633Z ==79533== total heap usage: 901,229 allocs, 894,735 frees, 224,415,569 bytes allocated 2025-12-04T10:30:35.9578537Z ==79533== 2025-12-04T10:30:39.1610069Z ==79533== LEAK SUMMARY: 2025-12-04T10:30:39.1610437Z ==79533== definitely lost: 0 bytes in 0 blocks 2025-12-04T10:30:39.1611119Z ==79533== indirectly lost: 0 bytes in 0 blocks 2025-12-04T10:30:39.1611520Z ==79533== possibly lost: 74,176 bytes in 9 blocks 2025-12-04T10:30:39.1611933Z ==79533== still reachable: 948,768 bytes in 6,485 blocks 2025-12-04T10:30:39.1612370Z ==79533== suppressed: 0 bytes in 0 blocks 2025-12-04T10:30:39.1612843Z ==79533== Rerun with --leak-check=full to see details of leaked memory 2025-12-04T10:30:39.1613260Z ==79533== 2025-12-04T10:30:39.1613598Z ==79533== For lists of detected and suppressed errors, rerun with: -s 2025-12-04T10:30:39.1614168Z ==79533== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 0 from 0) 2025-12-04T10:30:39.2641372Z + [[ -x build/bin/tensor_interop_test ]] 2025-12-04T10:30:39.2644038Z + [[ -n '' ]] 2025-12-04T10:30:39.2644292Z + assert_git_not_dirty 2025-12-04T10:30:39.2644658Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *rocm* ]] 2025-12-04T10:30:39.2645066Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *xla* ]] 2025-12-04T10:30:39.2651410Z ++ git status --porcelain 2025-12-04T10:30:39.2652640Z ++ grep -v '?? third_party' 2025-12-04T10:30:39.5728995Z ++ true 2025-12-04T10:30:39.5730672Z + git_status= 2025-12-04T10:30:39.5730924Z + [[ -n '' ]] 2025-12-04T10:30:39.5731616Z + test_libtorch 1 2025-12-04T10:30:39.5732979Z + local SHARD=1 2025-12-04T10:30:39.5733238Z + [[ nogpu_AVX512 != \s\l\o\w ]] 2025-12-04T10:30:39.5733571Z + echo 'Testing libtorch' 2025-12-04T10:30:39.5733834Z Testing libtorch 2025-12-04T10:30:39.5734684Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libbackend_with_compiler.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5747088Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libjitbackend_test.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5759752Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libcaffe2_nvrtc.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5773611Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10_cuda.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libc10d_cuda_test.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5787636Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libshm /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libshm.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libshm_windows /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5802930Z + ln -sf /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_cuda_linalg.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_nvshmem.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libtorchbind_test.so /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5814982Z + ln -sf '/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib/libnvfuser*' /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5826958Z + export CPP_TESTS_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5827637Z + CPP_TESTS_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-12-04T10:30:39.5828118Z + [[ -z 1 ]] 2025-12-04T10:30:39.5828350Z + [[ 1 == \1 ]] 2025-12-04T10:30:39.5828572Z + test_libtorch_api 2025-12-04T10:30:39.5828904Z + MNIST_DIR=/var/lib/jenkins/workspace/test/cpp/api/mnist 2025-12-04T10:30:39.5829569Z + python tools/download_mnist.py --quiet -d /var/lib/jenkins/workspace/test/cpp/api/mnist 2025-12-04T10:30:39.6313438Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz ... 2025-12-04T10:30:39.9955812Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz ... 2025-12-04T10:30:40.0402463Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz ... 2025-12-04T10:30:40.1322975Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz ... 2025-12-04T10:30:40.1775390Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *asan* ]] 2025-12-04T10:30:40.1775923Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *slow-gradcheck* ]] 2025-12-04T10:30:40.1776339Z + OMP_NUM_THREADS=2 2025-12-04T10:30:40.1776749Z + TORCH_CPP_TEST_MNIST_PATH=/var/lib/jenkins/workspace/test/cpp/api/mnist 2025-12-04T10:30:40.1777383Z + python test/run_test.py --cpp --verbose -i cpp/test_api -k 'not IMethodTest' 2025-12-04T10:30:41.7129586Z W1204 10:30:41.712000 79707 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:30:45.0779197Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-12-04T10:30:45.0883768Z Found test times from artifacts 2025-12-04T10:30:45.1288619Z Found test times from artifacts 2025-12-04T10:30:45.1303069Z Running all tests 2025-12-04T10:30:45.1306630Z Running parallel tests on 3 processes 2025-12-04T10:30:45.1306995Z Name: tests to run (est. time: 0.0min) 2025-12-04T10:30:45.1307332Z Serial tests (0): 2025-12-04T10:30:45.1307582Z Parallel tests (1): 2025-12-04T10:30:45.1307841Z cpp/test_api 1/1 2025-12-04T10:30:45.1308099Z Name: excluded (est. time: 0.0min) 2025-12-04T10:30:45.1308400Z Serial tests (0): 2025-12-04T10:30:45.1308648Z Parallel tests (0): 2025-12-04T10:30:45.1312871Z Running cpp/test_api 1/1 ... [2025-12-04 10:30:45.131082][4787.816853836] 2025-12-04T10:30:45.1313614Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:30:45.1314319Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:30:45.1314904Z Finished cpp/test_api 1/1 ... [2025-12-04 10:30:45.131290][4787.817064443], took 0.00min 2025-12-04T10:30:45.6417177Z Uploading artifacts took 0.48 seconds 2025-12-04T10:30:47.2741718Z W1204 10:30:47.273000 79718 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:30:47.2743372Z W1204 10:30:47.273000 79719 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:30:47.2824370Z W1204 10:30:47.281000 79717 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:30:48.6254870Z Running cpp/test_api 1/1 ... [2025-12-04 10:30:48.625066][4791.310835067] 2025-12-04T10:30:48.6255379Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-12-04T10:30:48.6255816Z Skipping C++ tests when running under RERUN_DISABLED_TESTS mode 2025-12-04T10:30:48.6256402Z Finished cpp/test_api 1/1 ... [2025-12-04 10:30:48.625287][4791.311061722], took 0.00min 2025-12-04T10:30:49.4078967Z Running test batch 'tests to run' cost 4.28 seconds 2025-12-04T10:30:50.0872243Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *android* ]] 2025-12-04T10:30:50.0872747Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *cuda* ]] 2025-12-04T10:30:50.0873109Z + [[ -z 1 ]] 2025-12-04T10:30:50.0873335Z + [[ 1 == \2 ]] 2025-12-04T10:30:50.0873576Z + assert_git_not_dirty 2025-12-04T10:30:50.0874169Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *rocm* ]] 2025-12-04T10:30:50.0874596Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 != *xla* ]] 2025-12-04T10:30:50.0879519Z ++ git status --porcelain 2025-12-04T10:30:50.0880586Z ++ grep -v '?? third_party' 2025-12-04T10:30:50.3954859Z ++ true 2025-12-04T10:30:50.3955157Z + git_status= 2025-12-04T10:30:50.3955417Z + [[ -n '' ]] 2025-12-04T10:30:50.3955983Z + [[ linux-jammy-cuda13.0-py3.10-gcc11 == *xpu* ]] 2025-12-04T10:30:50.3957525Z + sccache_epilogue 2025-12-04T10:30:50.3957821Z + echo '::group::Sccache Compilation Log' 2025-12-04T10:30:50.3958475Z ##[group]Sccache Compilation Log 2025-12-04T10:30:50.3958862Z + echo '=================== sccache compilation log ===================' 2025-12-04T10:30:50.3959304Z =================== sccache compilation log =================== 2025-12-04T10:30:50.3959983Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log 2025-12-04T10:30:50.4096185Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ===========' 2025-12-04T10:30:50.4096933Z =========== If your build fails, please take a look at the log above for possible reasons =========== 2025-12-04T10:30:50.4097461Z + sccache --show-stats 2025-12-04T10:30:50.4130033Z Compile requests 2751 2025-12-04T10:30:50.4130462Z Compile requests executed 64 2025-12-04T10:30:50.4130832Z Cache hits 21 2025-12-04T10:30:50.4131254Z Cache hits (C/C++) 21 2025-12-04T10:30:50.4131586Z Cache misses 43 2025-12-04T10:30:50.4132022Z Cache misses (C/C++) 43 2025-12-04T10:30:50.4132365Z Cache hits rate 32.81 % 2025-12-04T10:30:50.4132710Z Cache hits rate (C/C++) 32.81 % 2025-12-04T10:30:50.4133034Z Cache timeouts 0 2025-12-04T10:30:50.4133368Z Cache read errors 0 2025-12-04T10:30:50.4133709Z Forced recaches 0 2025-12-04T10:30:50.4134069Z Cache write errors 0 2025-12-04T10:30:50.4134486Z Cache errors 0 2025-12-04T10:30:50.4134815Z Compilations 43 2025-12-04T10:30:50.4135139Z Compilation failures 0 2025-12-04T10:30:50.4135485Z Non-cacheable compilations 0 2025-12-04T10:30:50.4135830Z Non-cacheable calls 2 2025-12-04T10:30:50.4136176Z Non-compilation calls 2685 2025-12-04T10:30:50.4136515Z Unsupported compiler calls 0 2025-12-04T10:30:50.4136865Z Average cache write 0.045 s 2025-12-04T10:30:50.4137211Z Average compiler 14.131 s 2025-12-04T10:30:50.4137543Z Average cache read hit 0.101 s 2025-12-04T10:30:50.4137896Z Failed distributed compilations 0 2025-12-04T10:30:50.4138134Z 2025-12-04T10:30:50.4138246Z Non-cacheable reasons: 2025-12-04T10:30:50.4138504Z -E 2 2025-12-04T10:30:50.4138736Z 2025-12-04T10:30:50.4138991Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-12-04T10:30:50.4139477Z Version (client) 0.10.0 2025-12-04T10:30:50.4139799Z + sccache --stop-server 2025-12-04T10:30:50.4157132Z Stopping sccache server... 2025-12-04T10:30:50.4161050Z Compile requests 2751 2025-12-04T10:30:50.4161504Z Compile requests executed 64 2025-12-04T10:30:50.4161835Z Cache hits 21 2025-12-04T10:30:50.4162165Z Cache hits (C/C++) 21 2025-12-04T10:30:50.4162489Z Cache misses 43 2025-12-04T10:30:50.4162820Z Cache misses (C/C++) 43 2025-12-04T10:30:50.4163145Z Cache hits rate 32.81 % 2025-12-04T10:30:50.4163487Z Cache hits rate (C/C++) 32.81 % 2025-12-04T10:30:50.4163824Z Cache timeouts 0 2025-12-04T10:30:50.4164142Z Cache read errors 0 2025-12-04T10:30:50.4164728Z Forced recaches 0 2025-12-04T10:30:50.4165071Z Cache write errors 0 2025-12-04T10:30:50.4165391Z Cache errors 0 2025-12-04T10:30:50.4165719Z Compilations 43 2025-12-04T10:30:50.4166053Z Compilation failures 0 2025-12-04T10:30:50.4166390Z Non-cacheable compilations 0 2025-12-04T10:30:50.4166787Z Non-cacheable calls 2 2025-12-04T10:30:50.4167132Z Non-compilation calls 2685 2025-12-04T10:30:50.4167478Z Unsupported compiler calls 0 2025-12-04T10:30:50.4167818Z Average cache write 0.045 s 2025-12-04T10:30:50.4168172Z Average compiler 14.131 s 2025-12-04T10:30:50.4168540Z Average cache read hit 0.101 s 2025-12-04T10:30:50.4168978Z Failed distributed compilations 0 2025-12-04T10:30:50.4169226Z 2025-12-04T10:30:50.4169324Z Non-cacheable reasons: 2025-12-04T10:30:50.4169594Z -E 2 2025-12-04T10:30:50.4169817Z 2025-12-04T10:30:50.4170082Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-12-04T10:30:50.4170554Z Version (client) 0.10.0 2025-12-04T10:30:50.4170891Z + echo ::endgroup:: 2025-12-04T10:30:50.4171381Z ##[endgroup] 2025-12-04T10:30:50.4171614Z + cleanup_workspace 2025-12-04T10:30:50.4172131Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.' 2025-12-04T10:30:50.4172979Z sudo may print the following warning message that can be ignored. The chown command will still run. 2025-12-04T10:30:50.4173720Z + echo ' sudo: setrlimit(RLIMIT_STACK): Operation not permitted' 2025-12-04T10:30:50.4174211Z sudo: setrlimit(RLIMIT_STACK): Operation not permitted 2025-12-04T10:30:50.4174778Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42' 2025-12-04T10:30:50.4175419Z For more details refer to https://github.com/sudo-project/sudo/issues/42 2025-12-04T10:30:50.4175936Z + sudo chown -R 1000 /var/lib/jenkins/workspace 2025-12-04T10:30:51.0990330Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main 2025-12-04T10:30:51.0990850Z with: 2025-12-04T10:30:51.0991115Z benchmark-results-dir: test/test-reports 2025-12-04T10:30:51.0991461Z dry-run: false 2025-12-04T10:30:51.0991692Z schema-version: v3 2025-12-04T10:30:51.0992180Z github-token: *** 2025-12-04T10:30:51.0992422Z env: 2025-12-04T10:30:51.0992650Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:51.0992921Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:51.0993406Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:51.0993952Z ##[endgroup] 2025-12-04T10:30:51.1012566Z ##[group]Run set -eux 2025-12-04T10:30:51.1012866Z set -eux 2025-12-04T10:30:51.1013103Z  2025-12-04T10:30:51.1013316Z if [[ -n "" ]]; then 2025-12-04T10:30:51.1013604Z  source "" 2025-12-04T10:30:51.1013849Z fi 2025-12-04T10:30:51.1014290Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-12-04T10:30:51.1014807Z  2025-12-04T10:30:51.1015034Z DEVICE_NAME="" 2025-12-04T10:30:51.1015309Z DEVICE_TYPE="" 2025-12-04T10:30:51.1015567Z  2025-12-04T10:30:51.1015795Z if command -v nvidia-smi; then 2025-12-04T10:30:51.1016284Z  # NB: I'm using PyTorch here to get the device name, however, it needs to 2025-12-04T10:30:51.1016921Z  # install the correct version of PyTorch manually for now. Any PyTorch 2025-12-04T10:30:51.1017497Z  # version is fine, I just use 2.7.1 to satify PYPIDEP linter 2025-12-04T10:30:51.1017958Z  python3 -mpip install torch==2.7.1 2025-12-04T10:30:51.1018326Z elif command -v rocminfo; then 2025-12-04T10:30:51.1018797Z  # NB: Installing torch on ROCm runner with pip here causes CI to fail 2025-12-04T10:30:51.1019389Z  # with a memoryview is too large error only on MI300 runners. Is pip 2025-12-04T10:30:51.1020000Z  # version on ROCm runner there too old? As a workaround, let's use the 2025-12-04T10:30:51.1020528Z  # GPU device name coming from rocminfo instead 2025-12-04T10:30:51.1020899Z  DEVICE_NAME=rocm 2025-12-04T10:30:51.1021415Z  DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs) 2025-12-04T10:30:51.1022055Z fi 2025-12-04T10:30:51.1022274Z  2025-12-04T10:30:51.1022543Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV 2025-12-04T10:30:51.1022988Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-12-04T10:30:51.1032639Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:51.1033034Z env: 2025-12-04T10:30:51.1033260Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:51.1033542Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:51.1034011Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:51.1034561Z ##[endgroup] 2025-12-04T10:30:51.1071020Z + [[ -n '' ]] 2025-12-04T10:30:51.1071651Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-12-04T10:30:51.3549602Z Defaulting to user installation because normal site-packages is not writeable 2025-12-04T10:30:52.5220681Z Collecting boto3==1.35.33 2025-12-04T10:30:52.5408040Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-12-04T10:30:52.8790171Z Collecting psutil==7.0.0 2025-12-04T10:30:52.8838907Z 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) 2025-12-04T10:30:52.9150124Z Collecting pynvml==12.0.0 2025-12-04T10:30:52.9196836Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-12-04T10:30:54.1524679Z Collecting botocore<1.36.0,>=1.35.33 2025-12-04T10:30:54.1567457Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-12-04T10:30:54.3616308Z Collecting s3transfer<0.11.0,>=0.10.0 2025-12-04T10:30:54.3658777Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-12-04T10:30:54.3704351Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.33) (0.10.0) 2025-12-04T10:30:54.4150513Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-12-04T10:30:54.4188323Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-12-04T10:30:54.4282507Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.25.10) 2025-12-04T10:30:54.4289815Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1) 2025-12-04T10:30:54.5860437Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.15.0) 2025-12-04T10:30:54.7226833Z Installing collected packages: botocore, s3transfer, nvidia-ml-py, pynvml, psutil, boto3 2025-12-04T10:30:55.2507817Z Attempting uninstall: nvidia-ml-py 2025-12-04T10:30:55.2509530Z Found existing installation: nvidia-ml-py 11.525.84 2025-12-04T10:30:55.2524087Z Uninstalling nvidia-ml-py-11.525.84: 2025-12-04T10:30:55.2721007Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-12-04T10:30:55.3338402Z Attempting uninstall: psutil 2025-12-04T10:30:55.3339199Z Found existing installation: psutil 5.9.8 2025-12-04T10:30:55.3414379Z Uninstalling psutil-5.9.8: 2025-12-04T10:30:55.3421061Z Successfully uninstalled psutil-5.9.8 2025-12-04T10:30:55.5146813Z Successfully installed boto3-1.35.33 botocore-1.35.99 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4 2025-12-04T10:30:55.6280934Z + DEVICE_NAME= 2025-12-04T10:30:55.6281390Z + DEVICE_TYPE= 2025-12-04T10:30:55.6281769Z + command -v nvidia-smi 2025-12-04T10:30:55.6282251Z + command -v rocminfo 2025-12-04T10:30:55.6282695Z + echo DEVICE_NAME= 2025-12-04T10:30:55.6283068Z + echo DEVICE_TYPE= 2025-12-04T10:30:55.6307534Z ##[group]Run set -eux 2025-12-04T10:30:55.6307805Z set -eux 2025-12-04T10:30:55.6308041Z  2025-12-04T10:30:55.6308292Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-12-04T10:30:55.6308658Z  echo "Missing github-token input" 2025-12-04T10:30:55.6309001Z  exit 1 2025-12-04T10:30:55.6309325Z fi 2025-12-04T10:30:55.6316511Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:55.6316919Z env: 2025-12-04T10:30:55.6317148Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:55.6317433Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:55.6317918Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:55.6318461Z DEVICE_NAME: 2025-12-04T10:30:55.6318696Z DEVICE_TYPE: 2025-12-04T10:30:55.6319145Z GITHUB_TOKEN: *** 2025-12-04T10:30:55.6319393Z ##[endgroup] 2025-12-04T10:30:55.6350906Z + [[ -z *** ]] 2025-12-04T10:30:55.6393749Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-12-04T10:30:55.6394215Z with: 2025-12-04T10:30:55.6394584Z github-token: *** 2025-12-04T10:30:55.6394808Z env: 2025-12-04T10:30:55.6395029Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:55.6395311Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:55.6395779Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:55.6396325Z DEVICE_NAME: 2025-12-04T10:30:55.6396557Z DEVICE_TYPE: 2025-12-04T10:30:55.6396789Z ##[endgroup] 2025-12-04T10:30:55.6411446Z ##[group]Run set -eux 2025-12-04T10:30:55.6411780Z set -eux 2025-12-04T10:30:55.6412026Z  2025-12-04T10:30:55.6412541Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-12-04T10:30:55.6418362Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:55.6418767Z env: 2025-12-04T10:30:55.6418996Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:55.6419267Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:55.6419897Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:55.6420442Z DEVICE_NAME: 2025-12-04T10:30:55.6420681Z DEVICE_TYPE: 2025-12-04T10:30:55.6421199Z GITHUB_TOKEN: *** 2025-12-04T10:30:55.6421448Z ##[endgroup] 2025-12-04T10:30:55.6448139Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 19922826259 i-0ed9e7c329090f0b0 2025-12-04T10:30:58.5571639Z setting job-id=57117865590 2025-12-04T10:30:58.5572354Z setting job-name=linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T10:30:58.5696648Z ##[group]Run set -eux 2025-12-04T10:30:58.5697142Z set -eux 2025-12-04T10:30:58.5697512Z  2025-12-04T10:30:58.5697866Z if [[ -n "" ]]; then 2025-12-04T10:30:58.5698354Z  source "" 2025-12-04T10:30:58.5698756Z fi 2025-12-04T10:30:58.5699131Z  2025-12-04T10:30:58.5699870Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-12-04T10:30:58.5700895Z  --schema-version "${SCHEMA_VERSION}" \ 2025-12-04T10:30:58.5701557Z  --repo "${REPO}" \ 2025-12-04T10:30:58.5702120Z  --head-branch "${HEAD_BRANCH}" \ 2025-12-04T10:30:58.5702774Z  --head-sha "${HEAD_SHA}" \ 2025-12-04T10:30:58.5703411Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-12-04T10:30:58.5704092Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-12-04T10:30:58.5704717Z  --job-id "${JOB_ID}" \ 2025-12-04T10:30:58.5705222Z  --job-name "${JOB_NAME}" 2025-12-04T10:30:58.5714233Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.5714962Z env: 2025-12-04T10:30:58.5715335Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.5715831Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.5716713Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.5717649Z DEVICE_NAME: 2025-12-04T10:30:58.5718047Z DEVICE_TYPE: 2025-12-04T10:30:58.5718460Z SCHEMA_VERSION: v3 2025-12-04T10:30:58.5718937Z REPO: pytorch/pytorch 2025-12-04T10:30:58.5719418Z HEAD_BRANCH: refs/heads/main 2025-12-04T10:30:58.5720048Z HEAD_SHA: ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 2025-12-04T10:30:58.5720891Z WORKFLOW_RUN_ID: 19922826259 2025-12-04T10:30:58.5721371Z RUN_ATTEMPT: 1 2025-12-04T10:30:58.5721764Z JOB_ID: 57117865590 2025-12-04T10:30:58.5722741Z JOB_NAME: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T10:30:58.5723838Z ##[endgroup] 2025-12-04T10:30:58.5755941Z + [[ -n '' ]] 2025-12-04T10:30:58.5758315Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32 --workflow-id 19922826259 --run-attempt 1 --job-id 57117865590 --job-name 'linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests)' 2025-12-04T10:30:58.6094348Z ##[group]Run set -eux 2025-12-04T10:30:58.6094637Z set -eux 2025-12-04T10:30:58.6094887Z  2025-12-04T10:30:58.6095100Z if [[ -n "" ]]; then 2025-12-04T10:30:58.6095424Z  source "" 2025-12-04T10:30:58.6095672Z fi 2025-12-04T10:30:58.6095875Z  2025-12-04T10:30:58.6096401Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-12-04T10:30:58.6102741Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.6103141Z env: 2025-12-04T10:30:58.6103362Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.6103652Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.6104135Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.6104803Z DEVICE_NAME: 2025-12-04T10:30:58.6105041Z DEVICE_TYPE: 2025-12-04T10:30:58.6105270Z ##[endgroup] 2025-12-04T10:30:58.6132495Z + [[ -n '' ]] 2025-12-04T10:30:58.6133392Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-12-04T10:30:58.6570130Z INFO:root:Fail to import torch to get the device name 2025-12-04T10:30:58.6697763Z ##[group]Run set -eux 2025-12-04T10:30:58.6698183Z set -eux 2025-12-04T10:30:58.6698573Z  2025-12-04T10:30:58.6698950Z # TODO (huydhn): Implement this part 2025-12-04T10:30:58.6699597Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-12-04T10:30:58.6706045Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.6706451Z env: 2025-12-04T10:30:58.6706667Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.6706950Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.6707452Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.6707996Z DEVICE_NAME: 2025-12-04T10:30:58.6708219Z DEVICE_TYPE: 2025-12-04T10:30:58.6708447Z ##[endgroup] 2025-12-04T10:30:58.6734715Z + echo 'dependencies={}' 2025-12-04T10:30:58.6756134Z ##[group]Run set -eux 2025-12-04T10:30:58.6756436Z set -eux 2025-12-04T10:30:58.6756674Z  2025-12-04T10:30:58.6756901Z if [[ -n "" ]]; then 2025-12-04T10:30:58.6757171Z  source "" 2025-12-04T10:30:58.6757419Z fi 2025-12-04T10:30:58.6757641Z  2025-12-04T10:30:58.6757899Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-12-04T10:30:58.6758368Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-12-04T10:30:58.6758888Z  # We don't want the job to fail if the directory doesn't exist 2025-12-04T10:30:58.6759314Z  exit 0 2025-12-04T10:30:58.6759532Z fi 2025-12-04T10:30:58.6759745Z  2025-12-04T10:30:58.6760000Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-12-04T10:30:58.6760500Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-12-04T10:30:58.6761102Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-12-04T10:30:58.6761649Z  --metadata "${BENCHMARK_METADATA}" \ 2025-12-04T10:30:58.6762028Z  --runners "${RUNNER_INFO}" \ 2025-12-04T10:30:58.6762386Z  --dependencies "${DEPENDENCIES}" \ 2025-12-04T10:30:58.6762741Z  --dry-run 2025-12-04T10:30:58.6762998Z else 2025-12-04T10:30:58.6763387Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-12-04T10:30:58.6763978Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-12-04T10:30:58.6764430Z  --metadata "${BENCHMARK_METADATA}" \ 2025-12-04T10:30:58.6764918Z  --runners "${RUNNER_INFO}" \ 2025-12-04T10:30:58.6765275Z  --dependencies "${DEPENDENCIES}" 2025-12-04T10:30:58.6765614Z fi 2025-12-04T10:30:58.6771485Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.6771880Z env: 2025-12-04T10:30:58.6772104Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.6772389Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.6772867Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.6773411Z DEVICE_NAME: 2025-12-04T10:30:58.6773644Z DEVICE_TYPE: 2025-12-04T10:30:58.6773978Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-12-04T10:30:58.6774317Z DRY_RUN: false 2025-12-04T10:30:58.6775990Z BENCHMARK_METADATA: {"timestamp": 1764844258, "schema_version": "v3", "name": "linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32", "workflow_id": 19922826259, "run_attempt": 1, "job_id": 57117865590} 2025-12-04T10:30:58.6777996Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 16, "avail_mem_in_gb": 30, "extra_info": {"hostname": "ip-10-0-5-68.ec2.internal"}, "name": "", "type": ""}] 2025-12-04T10:30:58.6778688Z DEPENDENCIES: {} 2025-12-04T10:30:58.6778916Z ##[endgroup] 2025-12-04T10:30:58.6805095Z + [[ -n '' ]] 2025-12-04T10:30:58.6805371Z + [[ ! -d test/test-reports ]] 2025-12-04T10:30:58.6805677Z + [[ false == \t\r\u\e ]] 2025-12-04T10:30:58.6808842Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1764844258, "schema_version": "v3", "name": "linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "ffd9b0fb4355e97af82fc42cf185c3ffa0fc0a32", "workflow_id": 19922826259, "run_attempt": 1, "job_id": 57117865590}' --runners '[{"cpu_info": "x86_64", "cpu_count": 16, "avail_mem_in_gb": 30, "extra_info": {"hostname": "ip-10-0-5-68.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}' 2025-12-04T10:30:58.8421195Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'lazy/test_ts_opinfo'}], 'excluded': []} from test/test-reports/td_exclusions-146706d8459f532627ae.json is not a benchmark record, skipping 2025-12-04T10:30:58.8423068Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8510280Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'inductor/test_aot_inductor'}, {'test_file': 'inductor/test_torchinductor'}, {'test_file': 'inductor/test_torchinductor_dynamic_shapes'}, {'test_file': 'inductor/test_torchinductor_codegen_dynamic_shapes'}, {'test_file': 'inductor/test_kernel_benchmark'}, {'test_file': 'inductor/test_torchinductor_opinfo'}, {'test_file': 'inductor/test_pattern_matcher'}, {'test_file': 'inductor/test_cuda_repro'}, {'test_file': 'inductor/test_cudagraph_trees'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'dynamo/test_repros'}, {'test_file': 'inductor/test_flex_attention'}, {'test_file': 'inductor/test_cuda_select_algorithm'}, {'test_file': 'inductor/test_compile_subprocess'}, {'test_file': 'inductor/test_flex_decoding'}, {'test_file': 'inductor/test_deterministic'}, {'test_file': 'export/test_retraceability'}, {'test_file': 'inductor/test_fp8'}, {'test_file': 'dynamo/test_model_output'}, {'test_file': 'inductor/test_triton_kernels'}, {'test_file': 'inductor/test_extension_backend'}, {'test_file': 'inductor/test_native_matmul'}, {'test_file': 'inductor/test_loop_ordering'}, {'test_file': 'export/test_serdes'}, {'test_file': 'dynamo/test_regional_inductor'}, {'test_file': 'dynamo/test_fx_graph_runnable'}, {'test_file': 'dynamo/test_backends'}, {'test_file': 'inductor/test_aot_inductor_package'}, {'test_file': 'inductor/test_decompose_mem_bound_mm'}, {'test_file': 'inductor/test_op_dtype_prop'}, {'test_file': 'inductor/test_online_softmax'}, {'test_file': 'inductor/test_memory'}, {'test_file': 'dynamo/test_streams'}, {'test_file': 'inductor/test_unbacked_symints'}, {'test_file': 'inductor/test_scatter_optimization'}, {'test_file': 'inductor/test_mix_order_reduction'}, {'test_file': 'inductor/test_padding'}, {'test_file': 'dynamo/test_aot_compile'}, {'test_file': 'dynamo/test_sets'}, {'test_file': 'dynamo/test_wrap_inductor_compiled_regions'}, {'test_file': 'dynamo/test_callback'}, {'test_file': 'dynamo/test_compiler_bisector'}, {'test_file': 'inductor/test_custom_op_autotune'}, {'test_file': 'inductor/test_cudagraph_trees_expandable_segments'}, {'test_file': 'dynamo/test_decorators'}, {'test_file': 'test_privateuseone_python_backend'}, {'test_file': 'inductor/test_collective_autotuning'}, {'test_file': 'test_varlen_attention'}, {'test_file': 'test_cuda'}, {'test_file': 'test_transformers'}, {'test_file': 'test_matmul_cuda'}, {'test_file': 'test_autograd'}, {'test_file': 'test_sparse'}, {'test_file': 'higher_order_ops/test_local_map'}, {'test_file': 'test_dataloader'}, {'test_file': 'higher_order_ops/test_invoke_subgraph'}, {'test_file': 'test_decomp'}, {'test_file': 'test_ci_sanity_check_fail'}, {'test_file': 'test_ops_fwd_gradients'}, {'test_file': 'test_meta'}, {'test_file': 'test_ops_jit'}, {'test_file': 'test_ops_gradients'}, {'test_file': 'test_nestedtensor'}, {'test_file': 'test_linalg'}, {'test_file': 'test_cuda_expandable_segments'}, {'test_file': 'test_public_bindings'}, {'test_file': 'test_ops'}, {'test_file': 'functorch/test_dims'}, {'test_file': 'test_sparse_csr'}, {'test_file': 'functorch/test_ops'}, {'test_file': 'functorch/test_vmap'}, {'test_file': 'test_overrides'}, {'test_file': 'test_torchfuzz_repros'}, {'test_file': 'inductor/test_max_autotune'}, {'test_file': 'doctests'}, {'test_file': 'inductor/test_select_algorithm'}, {'test_file': 'inductor/test_group_batch_fusion'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'inductor/test_cpu_repro'}, {'test_file': 'inductor/test_smoke'}, {'test_file': 'dynamo/test_after_aot'}, {'test_file': 'inductor/test_snode_runtime'}, {'test_file': 'inductor/test_minifier'}, {'test_file': 'inductor/test_compiled_autograd'}, {'test_file': 'inductor/test_custom_lowering'}, {'test_file': 'inductor/test_perf'}, {'test_file': 'inductor/test_fused_attention'}, {'test_file': 'inductor/test_binary_folding'}, {'test_file': 'inductor/test_mkldnn_pattern_matcher'}, {'test_file': 'inductor/test_inductor_freezing'}, {'test_file': 'inductor/test_layout_optim'}, {'test_file': 'dynamo/test_unspec'}, {'test_file': 'dynamo/test_higher_order_ops'}, {'test_file': 'inductor/test_mmdecomp'}, {'test_file': 'dynamo/test_ctx_manager'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 'dynamo/test_misc'}, {'test_file': 'inductor/test_cpu_select_algorithm'}, {'test_file': 'inductor/test_aot_inductor_arrayref'}, {'test_file': 'inductor/test_cpu_cpp_wrapper'}, {'test_file': 'inductor/test_cutlass_backend'}, {'test_file': 'inductor/test_triton_cpu_backend'}, {'test_file': 'inductor/test_torchinductor_strided_blocks'}, {'test_file': 'test_custom_ops'}, {'test_file': 'test_content_store'}, {'test_file': 'inductor/test_halide'}, {'test_file': 'inductor/test_multi_kernel'}, {'test_file': 'inductor/test_analysis'}, {'test_file': 'inductor/test_pad_mm'}, {'test_file': 'inductor/test_triton_syntax'}, {'test_file': 'inductor/test_triton_extension_backend'}, {'test_file': 'test_sparse_semi_structured'}, {'test_file': 'inductor/test_op_completeness'}, {'test_file': 'inductor/test_subgraph_choice'}, {'test_file': 'inductor/test_b2b_gemm'}, {'test_file': 'inductor/test_triton_heuristics'}, {'test_file': 'inductor/test_cutedsl_grouped_mm'}, {'test_file': 'inductor/test_cpp_wrapper_hipify'}, {'test_file': 'inductor/test_ck_backend'}, {'test_file': 'inductor/test_inductor_utils'}, {'test_file': 'inductor/test_template_heuristics_registry'}, {'test_file': 'inductor/test_async_compile'}, {'test_file': 'inductor/test_gpu_cpp_wrapper'}, {'test_file': 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{'test_file': 'higher_order_ops/test_invoke_quant'}, {'test_file': 'torch_np/test_basic'}, {'test_file': 'test_jiterator'}, {'test_file': 'test_native_functions'}, {'test_file': 'test_typing'}, {'test_file': 'higher_order_ops/test_with_effects'}, {'test_file': 'test_weak'}, {'test_file': 'test_complex'}, {'test_file': 'test_optim'}, {'test_file': 'lazy/test_functionalization'}, {'test_file': 'torch_np/test_random'}, {'test_file': 'nn/test_multihead_attention'}, {'test_file': 'test_legacy_vmap'}, {'test_file': 'lazy/test_bindings'}, {'test_file': 'xpu/test_conv'}, {'test_file': 'test_utils'}, {'test_file': 'test_pytree'}, {'test_file': 'test_namedtuple_return_api'}, {'test_file': 'profiler/test_record_function'}, {'test_file': 'test_compile_benchmark_util'}, {'test_file': 'test_set_default_mobile_cpu_allocator'}, {'test_file': 'test_fake_tensor'}, {'test_file': 'test_stateless'}, {'test_file': 'functorch/test_ac'}, {'test_file': 'test_binary_ufuncs'}, {'test_file': 'higher_order_ops/test_print'}, {'test_file': 'test_per_overload_api'}, {'test_file': 'torch_np/numpy_tests/core/test_einsum'}, {'test_file': 'test_multiprocessing'}, {'test_file': 'test_out_dtype_op'}, {'test_file': 'torch_np/test_ufuncs_basic'}, {'test_file': 'lazy/test_step_closures'}, {'test_file': 'functorch/dim/test_getsetitem'}, {'test_file': 'test_fx'}, {'test_file': 'test_numpy_interop'}, {'test_file': 'profiler/test_cpp_thread'}, {'test_file': 'test_hub'}, {'test_file': 'test_segment_reductions'}, {'test_file': 'test_opaque_obj_v2'}, {'test_file': 'test_autograd_fallback'}, {'test_file': 'test_type_hints'}, {'test_file': 'functorch/test_aot_joint_with_descriptors'}, {'test_file': 'test_functionalization_of_rng_ops'}, {'test_file': 'test_fx_reinplace_pass'}, {'test_file': 'functorch/test_control_flow'}, {'test_file': 'test_modules'}, {'test_file': 'nn/test_packed_sequence'}, {'test_file': 'test_numa_binding'}, {'test_file': 'test_pruning_op'}, {'test_file': 'test_jit_fuser_te'}, {'test_file': 'test_autocast'}, {'test_file': 'test_logging'}, {'test_file': 'test_python_dispatch'}, {'test_file': 'nn/test_lazy_modules'}, {'test_file': 'nn/test_pruning'}, {'test_file': 'test_monitor'}, {'test_file': 'test_cuda_sanitizer'}, {'test_file': 'test_bundled_inputs'}, {'test_file': 'torch_np/numpy_tests/core/test_numeric'}, {'test_file': 'torch_np/numpy_tests/core/test_multiarray'}, {'test_file': 'test_itt'}, {'test_file': 'torch_np/numpy_tests/lib/test_function_base'}, {'test_file': 'test_masked'}, {'test_file': 'test_sympy_utils'}, {'test_file': 'test_jit_disabled'}, {'test_file': 'test_subclass'}, {'test_file': 'test_import_stats'}, {'test_file': 'functorch/test_vmap_registrations'}, {'test_file': 'nn/test_parametrization'}, {'test_file': 'test_mkldnn_fusion'}, {'test_file': 'test_cpp_extensions_mtia_backend'}, {'test_file': 'lazy/test_ts_opinfo'}, {'test_file': 'test_dynamic_shapes'}, {'test_file': 'complex_tensor/test_complex_tensor'}, {'test_file': 'optim/test_lrscheduler'}, {'test_file': 'optim/test_swa_utils'}, {'test_file': 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic'}, {'test_file': 'functorch/test_memory_efficient_fusion'}, {'test_file': 'torch_np/numpy_tests/lib/test_histograms'}, {'test_file': 'torch_np/test_indexing'}, {'test_file': 'test_schema_check'}, {'test_file': 'test_tensorboard'}, {'test_file': 'torch_np/numpy_tests/core/test_indexing'}, {'test_file': 'test_futures'}, {'test_file': 'test_tensor_creation_ops'}, {'test_file': 'nn/test_dropout'}, {'test_file': 'functorch/dim/test_split'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'cpp_extensions/test_libtorch_agnostic'}, {'test_file': 'test_cpp_extensions_stream_and_event'}, {'test_file': 'profiler/test_execution_trace'}, {'test_file': 'test_jit'}, {'test_file': 'test_dispatch'}, {'test_file': 'test_datapipe'}, {'test_file': 'test_numba_integration'}, {'test_file': 'test_functional_optim'}, {'test_file': 'test_maskedtensor'}, {'test_file': 'benchmark_utils/test_benchmark_utils'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarmath'}, {'test_file': 'test_scaled_matmul_cuda'}, {'test_file': 'torch_np/numpy_tests/core/test_shape_base'}, {'test_file': 'test_vulkan'}, {'test_file': 'lazy/test_generator'}, {'test_file': 'nn/test_convolution'}, {'test_file': 'torch_np/numpy_tests/linalg/test_linalg'}, {'test_file': 'torch_np/numpy_tests/core/test_dtype'}, {'test_file': 'lazy/test_debug_util'}, {'test_file': 'nn/test_load_state_dict'}, {'test_file': 'test_shape_ops'}, {'test_file': 'nn/test_module_hooks'}, {'test_file': 'torch_np/numpy_tests/lib/test_twodim_base'}, {'test_file': 'profiler/test_memory_profiler'}, {'test_file': 'test_jit_llga_fuser'}, {'test_file': 'test_serialization'}, {'test_file': 'optim/test_optim'}, {'test_file': 'test_indexing'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'test_cpp_extensions_jit'}, {'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'test_view_ops'}, {'test_file': 'test_type_info'}, {'test_file': 'functorch/test_aotdispatch'}, {'test_file': 'test_nn'}, {'test_file': 'torch_np/numpy_tests/core/test_dlpack'}, {'test_file': 'test_multiprocessing_spawn'}, {'test_file': 'test_scatter_gather_ops'}, {'test_file': 'test_cuda_multigpu'}, {'test_file': 'test_mkldnn'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'test_jit_autocast'}, {'test_file': 'nn/test_pooling'}, {'test_file': 'nn/test_embedding'}, {'test_file': 'test_unary_ufuncs'}, {'test_file': 'test_xnnpack_integration'}, {'test_file': 'test_cuda_trace'}, {'test_file': 'test_native_mha'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'test_cuda_nvml_based_avail'}, {'test_file': 'test_function_schema'}, {'test_file': 'test_accelerator'}, {'test_file': 'nn/test_init'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_methods'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'test_mobile_optimizer'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'test_type_promotion'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'test_cuda_primary_ctx'}, {'test_file': 'profiler/test_profiler_tree'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'test_dlpack'}, {'test_file': 'profiler/test_torch_tidy'}, {'test_file': 'lazy/test_reuse_ir'}, {'test_file': 'test_functional_autograd_benchmark'}, {'test_file': 'test_reductions'}, {'test_file': 'torch_np/test_reductions'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'test_prims'}, {'test_file': 'test_spectral_ops'}, {'test_file': 'profiler/test_python_tracer'}, {'test_file': 'cpp_extensions/libtorch_agnostic_2_10_extension/test_version_compatibility'}, {'test_file': 'distributions/test_distributions'}, {'test_file': 'test_autoload_disable'}, {'test_file': 'test_autoload_enable'}, {'test_file': 'test_cpp_extensions_aot_ninja'}, {'test_file': 'test_cpp_extensions_aot_no_ninja'}], 'excluded': []} from test/test-reports/td_exclusions-eea907dd31fc5aadcc4e.json is not a benchmark record, skipping 2025-12-04T10:30:58.8595548Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8597374Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_generator_test'}], 'excluded': []} from test/test-reports/td_exclusions-e4e6102ac983ffda7968.json is not a benchmark record, skipping 2025-12-04T10:30:58.8599182Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8600976Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_half_test'}], 'excluded': []} from test/test-reports/td_exclusions-6e4ac912b047286c7c26.json is not a benchmark record, skipping 2025-12-04T10:30:58.8602745Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8604612Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_vectorized_test'}], 'excluded': []} from test/test-reports/td_exclusions-a8da18053105513f7f10.json is not a benchmark record, skipping 2025-12-04T10:30:58.8606406Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8608229Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_distributions_test'}], 'excluded': []} from test/test-reports/td_exclusions-b4b9be0582579e8e15b8.json is not a benchmark record, skipping 2025-12-04T10:30:58.8610050Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8611849Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_optional_test'}], 'excluded': []} from test/test-reports/td_exclusions-8ddf2b128a723189eafc.json is not a benchmark record, skipping 2025-12-04T10:30:58.8613701Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8615496Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_complex_test'}], 'excluded': []} from test/test-reports/td_exclusions-b2a75114f84a639f10e5.json is not a benchmark record, skipping 2025-12-04T10:30:58.8617264Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8621457Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/Dict_test'}, {'test_file': 'cpp/Dimname_test'}, {'test_file': 'cpp/NamedTensor_test'}, {'test_file': 'cpp/apply_utils_test'}, {'test_file': 'cpp/atest'}, {'test_file': 'cpp/basic'}, {'test_file': 'cpp/broadcast_test'}, {'test_file': 'cpp/cpu_generator_test'}, {'test_file': 'cpp/dlconvertor_test'}, {'test_file': 'cpp/extension_backend_test'}, {'test_file': 'cpp/lazy_tensor_test'}, {'test_file': 'cpp/legacy_vmap_test'}, {'test_file': 'cpp/native_test'}, {'test_file': 'cpp/operators_test'}, {'test_file': 'cpp/scalar_tensor_test'}, {'test_file': 'cpp/scalar_test'}, {'test_file': 'cpp/tensor_iterator_test'}, {'test_file': 'cpp/undefined_tensor_test'}, {'test_file': 'cpp/wrapdim_test'}], 'excluded': []} from test/test-reports/td_exclusions-dbbb709d436c6897c23e.json is not a benchmark record, skipping 2025-12-04T10:30:58.8625692Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8627565Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_complex_math_test'}], 'excluded': []} from test/test-reports/td_exclusions-85433f398f5980e5157f.json is not a benchmark record, skipping 2025-12-04T10:30:58.8629368Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8631122Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_cub_test'}], 'excluded': []} from test/test-reports/td_exclusions-0218fcb143bf4edd5736.json is not a benchmark record, skipping 2025-12-04T10:30:58.8632881Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8634674Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_atomic_ops_test'}], 'excluded': []} from test/test-reports/td_exclusions-ee9a3bb24ab368cfc328.json is not a benchmark record, skipping 2025-12-04T10:30:58.8647232Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8649086Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/cuda_allocator_test'}], 'excluded': []} from test/test-reports/td_exclusions-3d7104b62205ae2b48bd.json is not a benchmark record, skipping 2025-12-04T10:30:58.8650909Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8652656Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/test_api'}], 'excluded': []} from test/test-reports/td_exclusions-06de77a1ab0f4c1aaa1d.json is not a benchmark record, skipping 2025-12-04T10:30:58.8654406Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-12-04T10:30:58.8690680Z ##[group]Run cat test/**/*_toprint.log || true 2025-12-04T10:30:58.8691471Z cat test/**/*_toprint.log || true 2025-12-04T10:30:58.8697576Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.8697966Z env: 2025-12-04T10:30:58.8698202Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.8698487Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.8698956Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.8699497Z DEVICE_NAME: 2025-12-04T10:30:58.8699735Z DEVICE_TYPE: 2025-12-04T10:30:58.8699957Z ##[endgroup] 2025-12-04T10:30:58.8797639Z W1204 09:25:33.868000 2048 site-packages/torch/utils/cpp_extension.py:118] No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda' 2025-12-04T10:30:58.8798756Z Test results will be stored in test-reports/python-pytest/test_ci_sanity_check_fail/test_ci_sanity_check_fail-05f200249794d09c.xml 2025-12-04T10:30:58.8799771Z ============================= test session starts ============================== 2025-12-04T10:30:58.8800400Z platform linux -- Python 3.10.14, pytest-7.3.2, pluggy-1.6.0 -- /opt/conda/envs/py_3.10/bin/python 2025-12-04T10:30:58.8800964Z cachedir: .pytest_cache 2025-12-04T10:30:58.8801624Z hypothesis profile 'pytorch_ci' -> database=None, max_examples=50, derandomize=True, suppress_health_check=[HealthCheck.too_slow] 2025-12-04T10:30:58.8802423Z rootdir: /var/lib/jenkins/workspace 2025-12-04T10:30:58.8802749Z configfile: pytest.ini 2025-12-04T10:30:58.8803432Z plugins: hypothesis-6.56.4, cpp-2.3.0, flakefinder-1.1.0, rerunfailures-14.0, subtests-0.13.1, xdist-3.3.1, xdoctest-1.3.0, typeguard-4.3.0 2025-12-04T10:30:58.8804178Z collecting ... collected 2 items 2025-12-04T10:30:58.8804589Z stepcurrent: Cannot find last run test, not skipping 2025-12-04T10:30:58.8804994Z Running 0 items in this shard: 2025-12-04T10:30:58.8805192Z 2025-12-04T10:30:58.8805871Z - generated xml file: /var/lib/jenkins/workspace/test/test-reports/python-pytest/test_ci_sanity_check_fail/test_ci_sanity_check_fail-05f200249794d09c.xml - 2025-12-04T10:30:58.8806799Z ============================ no tests ran in 0.01s ============================= 2025-12-04T10:30:58.8841882Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-12-04T10:30:58.8842575Z kill "$MONITOR_SCRIPT_PID" 2025-12-04T10:30:58.8848445Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:58.8848838Z env: 2025-12-04T10:30:58.8849067Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:58.8849349Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:58.8849818Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:58.8850354Z DEVICE_NAME: 2025-12-04T10:30:58.8850591Z DEVICE_TYPE: 2025-12-04T10:30:58.8850821Z MONITOR_SCRIPT_PID: 44656 2025-12-04T10:30:58.8851097Z ##[endgroup] 2025-12-04T10:30:58.8876781Z /home/ec2-user/actions-runner/_work/_temp/124661ed-de74-4d52-8646-5516ffaea4bc.sh: line 1: kill: (44656) - No such process 2025-12-04T10:30:58.8887157Z ##[error]Process completed with exit code 1. 2025-12-04T10:30:58.9036083Z Prepare all required actions 2025-12-04T10:30:58.9036525Z Getting action download info 2025-12-04T10:30:59.0868928Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-12-04T10:30:59.3083354Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-12-04T10:30:59.8202625Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-12-04T10:30:59.8203183Z with: 2025-12-04T10:30:59.8203666Z file-suffix: test-nogpu_AVX512-1-3-linux.4xlarge_57117865590 2025-12-04T10:30:59.8204315Z s3-bucket: gha-artifacts 2025-12-04T10:30:59.8204791Z env: 2025-12-04T10:30:59.8205122Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:59.8205540Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:59.8206275Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:59.8207078Z DEVICE_NAME: 2025-12-04T10:30:59.8207422Z DEVICE_TYPE: 2025-12-04T10:30:59.8207966Z ##[endgroup] 2025-12-04T10:30:59.8243296Z ##[group]Run # Remove any previous test jsons if they exist 2025-12-04T10:30:59.8244016Z # Remove any previous test jsons if they exist 2025-12-04T10:30:59.8244677Z rm -f test-jsons-*.zip 2025-12-04T10:30:59.8245362Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-12-04T10:30:59.8253675Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:59.8254263Z env: 2025-12-04T10:30:59.8254591Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:59.8255010Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:59.8255720Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:59.8256552Z DEVICE_NAME: 2025-12-04T10:30:59.8256890Z DEVICE_TYPE: 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test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_8354a9f17cc9ef9b_.log (deflated 50%) 2025-12-04T10:30:59.9790044Z adding: test/test-reports/functorch.test_vmap_registrations_1.1_2f81d0c0ee65cca1_.log (deflated 48%) 2025-12-04T10:30:59.9790867Z adding: test/test-reports/lazy.test_ts_opinfo_1.1_5f8762cddb7a8ff2_.log (deflated 46%) 2025-12-04T10:30:59.9791579Z adding: test/test-reports/test_dynamic_shapes_1.1_219280898da3781a_.log (deflated 99%) 2025-12-04T10:30:59.9792375Z adding: test/test-reports/complex_tensor.test_complex_tensor_1.1_f3f4b7818c829843_.log (deflated 57%) 2025-12-04T10:30:59.9793404Z adding: test/test-reports/cpp_extensions.python_agnostic_extension.test.test_python_agnostic_1.1_39951704a3cb7fed_.log (deflated 53%) 2025-12-04T10:30:59.9794491Z adding: test/test-reports/torch_np.numpy_tests.lib.test_histograms_1.1_3adf396fd9fb3f9c_.log (deflated 49%) 2025-12-04T10:30:59.9795313Z adding: test/test-reports/torch_np.test_indexing_1.1_34bcddd435707a18_.log (deflated 47%) 2025-12-04T10:30:59.9796135Z adding: test/test-reports/torch_np.numpy_tests.core.test_indexing_1.1_826a2b6884e8b2aa_.log (deflated 49%) 2025-12-04T10:30:59.9796980Z adding: test/test-reports/functorch.dim.test_split_1.1_f3a20a6873586fbb_.log (deflated 47%) 2025-12-04T10:30:59.9797809Z adding: test/test-reports/torch_np.numpy_tests.lib.test_type_check_1.1_47ae53818915337d_.log (deflated 49%) 2025-12-04T10:30:59.9798627Z adding: test/test-reports/test_numba_integration_1.1_90bdf13849f1d969_.log (deflated 47%) 2025-12-04T10:30:59.9799370Z adding: test/test-reports/test_functional_optim_1.1_0f62784fdea41441_.log (deflated 47%) 2025-12-04T10:30:59.9800195Z adding: test/test-reports/benchmark_utils.test_benchmark_utils_1.1_8019f83b061ba50b_.log (deflated 49%) 2025-12-04T10:30:59.9801091Z adding: test/test-reports/torch_np.numpy_tests.core.test_scalarmath_1.1_e051ca28a0227856_.log (deflated 49%) 2025-12-04T10:30:59.9801955Z adding: test/test-reports/test_scaled_matmul_cuda_1.1_30284178f3646ead_.log (deflated 47%) 2025-12-04T10:30:59.9802789Z adding: test/test-reports/torch_np.numpy_tests.core.test_shape_base_1.1_3e3b4c87ac632f4e_.log (deflated 49%) 2025-12-04T10:30:59.9803604Z adding: test/test-reports/lazy.test_generator_1.1_8987ab354a3f1ee4_.log (deflated 46%) 2025-12-04T10:30:59.9804410Z adding: test/test-reports/torch_np.numpy_tests.linalg.test_linalg_1.1_b6d6e049344086bd_.log (deflated 49%) 2025-12-04T10:30:59.9805371Z adding: test/test-reports/torch_np.numpy_tests.core.test_dtype_1.1_5a421ca6009dc335_.log (deflated 49%) 2025-12-04T10:30:59.9806171Z adding: test/test-reports/lazy.test_debug_util_1.1_51af2840cafd543b_.log (deflated 47%) 2025-12-04T10:30:59.9806909Z adding: test/test-reports/nn.test_load_state_dict_1.1_bfd0315ce6718fac_.log (deflated 47%) 2025-12-04T10:30:59.9807632Z adding: test/test-reports/nn.test_module_hooks_1.1_22cc15a5d5ba56c9_.log (deflated 47%) 2025-12-04T10:30:59.9808452Z adding: test/test-reports/torch_np.numpy_tests.lib.test_twodim_base_1.1_b49816f4c927ad4e_.log (deflated 49%) 2025-12-04T10:30:59.9809328Z adding: test/test-reports/profiler.test_memory_profiler_1.1_12782556f96a4357_.log (deflated 95%) 2025-12-04T10:30:59.9810093Z adding: test/test-reports/test_jit_llga_fuser_1.1_7185d0aa18cc6b19_.log (deflated 46%) 2025-12-04T10:30:59.9810885Z adding: test/test-reports/torch_np.numpy_tests.fft.test_pocketfft_1.1_600a6814c728f072_.log (deflated 49%) 2025-12-04T10:30:59.9811789Z adding: test/test-reports/torch_np.numpy_tests.lib.test_shape_base__1.1_e3365dae8d2f29c4_.log (deflated 49%) 2025-12-04T10:30:59.9812814Z adding: test/test-reports/torch_np.numpy_tests.core.test_getlimits_1.1_e335fb57b40ee9ee_.log (deflated 49%) 2025-12-04T10:30:59.9813685Z adding: test/test-reports/torch_np.test_ndarray_methods_1.1_265bd46742f62cb6_.log (deflated 48%) 2025-12-04T10:30:59.9814492Z adding: test/test-reports/functorch.test_aotdispatch_1.1_b2bcab15ed6a5c47_.log (deflated 49%) 2025-12-04T10:30:59.9815357Z adding: test/test-reports/inductor.test_mkldnn_pattern_matcher_1.2_d029b9dcecb3c3f2_.log (deflated 93%) 2025-12-04T10:30:59.9836566Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-12-04T10:30:59.9837256Z # Remove any previous debugging artifacts if they exist 2025-12-04T10:30:59.9837667Z rm -f debug-*.zip 2025-12-04T10:30:59.9837951Z if [ -d 'test/debug' ]; then 2025-12-04T10:30:59.9838316Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-12-04T10:30:59.9838680Z fi 2025-12-04T10:30:59.9845122Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:30:59.9845509Z env: 2025-12-04T10:30:59.9845720Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:59.9846053Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:59.9846517Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:59.9847038Z DEVICE_NAME: 2025-12-04T10:30:59.9847254Z DEVICE_TYPE: 2025-12-04T10:30:59.9847570Z FILE_SUFFIX: test-nogpu_AVX512-1-3-linux.4xlarge_57117865590 2025-12-04T10:30:59.9847959Z ##[endgroup] 2025-12-04T10:30:59.9931447Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-12-04T10:30:59.9931784Z with: 2025-12-04T10:30:59.9932011Z s3-bucket: gha-artifacts 2025-12-04T10:30:59.9932354Z s3-prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:30:59.9932711Z retention-days: 14 2025-12-04T10:30:59.9932975Z if-no-files-found: warn 2025-12-04T10:30:59.9933255Z path: test-jsons-*.zip 2025-12-04T10:30:59.9933509Z name: artifact 2025-12-04T10:30:59.9933746Z region: us-east-1 2025-12-04T10:30:59.9933982Z env: 2025-12-04T10:30:59.9934187Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:30:59.9934534Z HAS_NVIDIA_GPU: false 2025-12-04T10:30:59.9935047Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:30:59.9935644Z DEVICE_NAME: 2025-12-04T10:30:59.9935863Z DEVICE_TYPE: 2025-12-04T10:30:59.9936193Z ##[endgroup] 2025-12-04T10:31:00.3578940Z NOTE: s3-prefix specified, ignoring name parameter 2025-12-04T10:31:00.3579448Z With the provided path, there will be 1 file uploaded 2025-12-04T10:31:00.3579932Z Uploading to s3 prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:00.3628763Z Starting upload of test-jsons-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:00.5016063Z Finished upload of test-jsons-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:00.5228842Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-12-04T10:31:00.5229186Z with: 2025-12-04T10:31:00.5229415Z s3-bucket: gha-artifacts 2025-12-04T10:31:00.5229758Z s3-prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:00.5230138Z retention-days: 14 2025-12-04T10:31:00.5230403Z if-no-files-found: error 2025-12-04T10:31:00.5230694Z path: test-reports-*.zip 2025-12-04T10:31:00.5230956Z name: artifact 2025-12-04T10:31:00.5231194Z region: us-east-1 2025-12-04T10:31:00.5231440Z env: 2025-12-04T10:31:00.5231643Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:00.5231919Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:00.5232403Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:00.5232944Z DEVICE_NAME: 2025-12-04T10:31:00.5233162Z DEVICE_TYPE: 2025-12-04T10:31:00.5233391Z ##[endgroup] 2025-12-04T10:31:00.8840276Z NOTE: s3-prefix specified, ignoring name parameter 2025-12-04T10:31:00.8840766Z With the provided path, there will be 1 file uploaded 2025-12-04T10:31:00.8841258Z Uploading to s3 prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:00.8890060Z Starting upload of test-reports-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:01.0319494Z Finished upload of test-reports-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:01.0508932Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-12-04T10:31:01.0509288Z with: 2025-12-04T10:31:01.0509520Z s3-bucket: gha-artifacts 2025-12-04T10:31:01.0509855Z s3-prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:01.0510228Z retention-days: 14 2025-12-04T10:31:01.0510497Z if-no-files-found: ignore 2025-12-04T10:31:01.0510766Z path: logs-*.zip 2025-12-04T10:31:01.0511012Z name: artifact 2025-12-04T10:31:01.0511252Z region: us-east-1 2025-12-04T10:31:01.0511474Z env: 2025-12-04T10:31:01.0511693Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:01.0511972Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:01.0512437Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:01.0512978Z DEVICE_NAME: 2025-12-04T10:31:01.0513209Z DEVICE_TYPE: 2025-12-04T10:31:01.0513425Z ##[endgroup] 2025-12-04T10:31:01.3901700Z NOTE: s3-prefix specified, ignoring name parameter 2025-12-04T10:31:01.3902700Z With the provided path, there will be 1 file uploaded 2025-12-04T10:31:01.3903183Z Uploading to s3 prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:01.3951489Z Starting upload of logs-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:01.4986600Z Finished upload of logs-test-nogpu_AVX512-1-3-linux.4xlarge_57117865590.zip 2025-12-04T10:31:01.5176825Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-12-04T10:31:01.5177173Z with: 2025-12-04T10:31:01.5177406Z s3-bucket: gha-artifacts 2025-12-04T10:31:01.5177749Z s3-prefix: pytorch/pytorch/19922826259/1/artifact 2025-12-04T10:31:01.5178109Z retention-days: 14 2025-12-04T10:31:01.5188559Z if-no-files-found: ignore 2025-12-04T10:31:01.5188868Z path: debug-*.zip 2025-12-04T10:31:01.5189100Z name: artifact 2025-12-04T10:31:01.5189339Z region: us-east-1 2025-12-04T10:31:01.5189580Z env: 2025-12-04T10:31:01.5189787Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:01.5190101Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:01.5190591Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:01.5191138Z DEVICE_NAME: 2025-12-04T10:31:01.5191358Z DEVICE_TYPE: 2025-12-04T10:31:01.5191721Z ##[endgroup] 2025-12-04T10:31:01.8474960Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-12-04T10:31:01.8671259Z ##[group]Run # shellcheck disable=SC2156 2025-12-04T10:31:01.8671662Z # shellcheck disable=SC2156 2025-12-04T10:31:01.8672280Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-12-04T10:31:01.8678673Z shell: /usr/bin/bash -e {0} 2025-12-04T10:31:01.8678971Z env: 2025-12-04T10:31:01.8679200Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:01.8679469Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:01.8679955Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:01.8680504Z DEVICE_NAME: 2025-12-04T10:31:01.8680740Z DEVICE_TYPE: 2025-12-04T10:31:01.8680957Z ##[endgroup] 2025-12-04T10:31:02.2073556Z Prepare all required actions 2025-12-04T10:31:02.2074002Z Getting action download info 2025-12-04T10:31:02.3799705Z Download action repository 'actions/setup-python@v6' (SHA:83679a892e2d95755f2dac6acb0bfd1e9ac5d548) 2025-12-04T10:31:02.7691811Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-12-04T10:31:02.7692200Z with: 2025-12-04T10:31:02.7692426Z job_id: 57117865590 2025-12-04T10:31:02.7692968Z job_name: linux-jammy-cuda13.0-py3.10-gcc11 / test (nogpu_AVX512, 1, 3, linux.4xlarge, rerun_disabled_tests) 2025-12-04T10:31:02.7693587Z workflow_name: periodic 2025-12-04T10:31:02.7693860Z workflow_run_id: 19922826259 2025-12-04T10:31:02.7694148Z workflow_attempt: 1 2025-12-04T10:31:02.7694402Z env: 2025-12-04T10:31:02.7694606Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:02.7694885Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:02.7695367Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:02.7695954Z DEVICE_NAME: 2025-12-04T10:31:02.7696176Z DEVICE_TYPE: 2025-12-04T10:31:02.7696402Z ##[endgroup] 2025-12-04T10:31:02.7735107Z ##[group]Run actions/setup-python@v6 2025-12-04T10:31:02.7735447Z with: 2025-12-04T10:31:02.7735675Z python-version: 3.10 2025-12-04T10:31:02.7735930Z check-latest: false 2025-12-04T10:31:02.7736416Z token: *** 2025-12-04T10:31:02.7736665Z update-environment: true 2025-12-04T10:31:02.7736966Z allow-prereleases: false 2025-12-04T10:31:02.7737242Z freethreaded: false 2025-12-04T10:31:02.7737500Z env: 2025-12-04T10:31:02.7737721Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:02.7737988Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:02.7738469Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:02.7739010Z DEVICE_NAME: 2025-12-04T10:31:02.7739229Z DEVICE_TYPE: 2025-12-04T10:31:02.7739458Z ##[endgroup] 2025-12-04T10:31:03.2502389Z ##[group]Installed versions 2025-12-04T10:31:03.2511759Z Version 3.10 was not found in the local cache 2025-12-04T10:31:03.2800816Z (node:127559) [DEP0040] DeprecationWarning: The `punycode` module is deprecated. Please use a userland alternative instead. 2025-12-04T10:31:03.2801688Z (Use `node --trace-deprecation ...` to show where the warning was created) 2025-12-04T10:31:03.6491042Z ##[error]The version '3.10' with architecture 'x64' was not found for this operating system. The list of all available versions can be found here: https://raw.githubusercontent.com/actions/python-versions/main/versions-manifest.json 2025-12-04T10:31:03.6668014Z ##[group]Run pytorch/test-infra/.github/actions/teardown-linux@main 2025-12-04T10:31:03.6668470Z with: 2025-12-04T10:31:03.6668683Z env: 2025-12-04T10:31:03.6668902Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:03.6669175Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:03.6669655Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:03.6670209Z DEVICE_NAME: 2025-12-04T10:31:03.6670446Z DEVICE_TYPE: 2025-12-04T10:31:03.6670661Z ##[endgroup] 2025-12-04T10:31:03.6686631Z ##[group]Run set -eou pipefail 2025-12-04T10:31:03.6686950Z set -eou pipefail 2025-12-04T10:31:03.6687316Z  2025-12-04T10:31:03.6687707Z echo "Holding runner for 2 hours until all ssh sessions have logged out" 2025-12-04T10:31:03.6688212Z for _ in $(seq 1440); do 2025-12-04T10:31:03.6688554Z  # Break if no ssh session exists anymore 2025-12-04T10:31:03.6688929Z  if [ "$(who)" = "" ]; then 2025-12-04T10:31:03.6689286Z  break 2025-12-04T10:31:03.6689538Z  fi 2025-12-04T10:31:03.6689771Z  echo "." 2025-12-04T10:31:03.6690023Z  sleep 5 2025-12-04T10:31:03.6690256Z done 2025-12-04T10:31:03.6696184Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:31:03.6696585Z env: 2025-12-04T10:31:03.6696804Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:03.6697085Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:03.6697567Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:03.6698093Z DEVICE_NAME: 2025-12-04T10:31:03.6698332Z DEVICE_TYPE: 2025-12-04T10:31:03.6698562Z ##[endgroup] 2025-12-04T10:31:03.6725061Z Holding runner for 2 hours until all ssh sessions have logged out 2025-12-04T10:31:03.6801183Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-12-04T10:31:03.6801784Z # ignore expansion of "docker ps -q" since it could be empty 2025-12-04T10:31:03.6802283Z # shellcheck disable=SC2046 2025-12-04T10:31:03.6802858Z docker stop $(docker ps -q) || true 2025-12-04T10:31:03.6803223Z # Prune all of the docker images 2025-12-04T10:31:03.6803579Z docker system prune -af 2025-12-04T10:31:03.6809485Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-12-04T10:31:03.6809887Z env: 2025-12-04T10:31:03.6810113Z GIT_DEFAULT_BRANCH: main 2025-12-04T10:31:03.6810398Z HAS_NVIDIA_GPU: false 2025-12-04T10:31:03.6810866Z DOCKER_CONTAINER_ID: 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:03.6811417Z DEVICE_NAME: 2025-12-04T10:31:03.6811655Z DEVICE_TYPE: 2025-12-04T10:31:03.6811874Z ##[endgroup] 2025-12-04T10:31:14.4077503Z 40bac2ce78e3 2025-12-04T10:31:14.8389159Z Deleted Containers: 2025-12-04T10:31:14.8389628Z 40bac2ce78e35df38693665694c2bb5dfba5cbb427e1c5e6c7d655271343ae81 2025-12-04T10:31:14.8390010Z 2025-12-04T10:31:20.3211331Z Deleted Images: 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2025-12-04T10:31:20.3460750Z Post job cleanup. 2025-12-04T10:31:20.4889578Z (node:127657) [DEP0040] DeprecationWarning: The `punycode` module is deprecated. Please use a userland alternative instead. 2025-12-04T10:31:20.4891115Z (Use `node --trace-deprecation ...` to show where the warning was created) 2025-12-04T10:31:20.5041434Z Post job cleanup. 2025-12-04T10:31:20.5088799Z Post job cleanup. 2025-12-04T10:31:20.6142405Z [command]/usr/bin/git version 2025-12-04T10:31:20.6182894Z git version 2.50.1 2025-12-04T10:31:20.6219051Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/3e03885d-30bf-4192-ac0e-d91809d97928/.gitconfig' 2025-12-04T10:31:20.6229027Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/3e03885d-30bf-4192-ac0e-d91809d97928' before making global git config changes 2025-12-04T10:31:20.6230113Z Adding repository directory to the temporary git global config as a safe directory 2025-12-04T10:31:20.6235390Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-12-04T10:31:20.6277638Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-12-04T10:31:20.6317362Z [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' || :" 2025-12-04T10:31:20.6670230Z Entering 'android/libs/fbjni' 2025-12-04T10:31:20.6734235Z Entering 'third_party/FP16' 2025-12-04T10:31:20.6802759Z Entering 'third_party/FXdiv' 2025-12-04T10:31:20.6867371Z Entering 'third_party/NNPACK' 2025-12-04T10:31:20.6932489Z Entering 'third_party/NVTX' 2025-12-04T10:31:20.6997755Z Entering 'third_party/VulkanMemoryAllocator' 2025-12-04T10:31:20.7062744Z Entering 'third_party/XNNPACK' 2025-12-04T10:31:20.7143391Z Entering 'third_party/aiter' 2025-12-04T10:31:20.7207983Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-12-04T10:31:20.7280245Z Entering 'third_party/benchmark' 2025-12-04T10:31:20.7347018Z Entering 'third_party/composable_kernel' 2025-12-04T10:31:20.7420336Z Entering 'third_party/cpp-httplib' 2025-12-04T10:31:20.7484952Z Entering 'third_party/cpuinfo' 2025-12-04T10:31:20.7552198Z Entering 'third_party/cudnn_frontend' 2025-12-04T10:31:20.7616145Z Entering 'third_party/cutlass' 2025-12-04T10:31:20.7691562Z Entering 'third_party/fbgemm' 2025-12-04T10:31:20.7759086Z Entering 'third_party/fbgemm/external/asmjit' 2025-12-04T10:31:20.7822188Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-12-04T10:31:20.7895661Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-12-04T10:31:20.7960627Z Entering 'third_party/fbgemm/external/cutlass' 2025-12-04T10:31:20.8034108Z Entering 'third_party/fbgemm/external/googletest' 2025-12-04T10:31:20.8097039Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-12-04T10:31:20.8159677Z Entering 'third_party/fbgemm/external/json' 2025-12-04T10:31:20.8225713Z Entering 'third_party/flash-attention' 2025-12-04T10:31:20.8292264Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-12-04T10:31:20.8362802Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-12-04T10:31:20.8435587Z Entering 'third_party/flatbuffers' 2025-12-04T10:31:20.8502325Z Entering 'third_party/fmt' 2025-12-04T10:31:20.8568536Z Entering 'third_party/gemmlowp/gemmlowp' 2025-12-04T10:31:20.8632999Z Entering 'third_party/gloo' 2025-12-04T10:31:20.8698404Z Entering 'third_party/googletest' 2025-12-04T10:31:20.8763130Z Entering 'third_party/ideep' 2025-12-04T10:31:20.8827743Z Entering 'third_party/ideep/mkl-dnn' 2025-12-04T10:31:20.8899005Z Entering 'third_party/ittapi' 2025-12-04T10:31:20.8964922Z Entering 'third_party/kineto' 2025-12-04T10:31:20.9028277Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-12-04T10:31:20.9093494Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-12-04T10:31:20.9159312Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-12-04T10:31:20.9222608Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-12-04T10:31:20.9286776Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-12-04T10:31:20.9350631Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-12-04T10:31:20.9415626Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-12-04T10:31:20.9479149Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-12-04T10:31:20.9543954Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-12-04T10:31:20.9609241Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-12-04T10:31:20.9672654Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp' 2025-12-04T10:31:20.9735757Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T10:31:20.9801123Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T10:31:20.9869211Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-12-04T10:31:20.9932939Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-12-04T10:31:20.9998038Z Entering 'third_party/kleidiai' 2025-12-04T10:31:21.0063072Z Entering 'third_party/mimalloc' 2025-12-04T10:31:21.0128644Z Entering 'third_party/nlohmann' 2025-12-04T10:31:21.0193863Z Entering 'third_party/onnx' 2025-12-04T10:31:21.0276571Z Entering 'third_party/onnx/third_party/pybind11' 2025-12-04T10:31:21.0343211Z Entering 'third_party/opentelemetry-cpp' 2025-12-04T10:31:21.0408356Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-12-04T10:31:21.0471159Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-12-04T10:31:21.0536267Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-12-04T10:31:21.0598337Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-12-04T10:31:21.0662299Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-12-04T10:31:21.0724392Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-12-04T10:31:21.0787084Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-12-04T10:31:21.0850507Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T10:31:21.0914259Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T10:31:21.0979192Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-12-04T10:31:21.1064995Z Entering 'third_party/pocketfft' 2025-12-04T10:31:21.1129800Z Entering 'third_party/protobuf' 2025-12-04T10:31:21.1196015Z Entering 'third_party/protobuf/third_party/benchmark' 2025-12-04T10:31:21.1259515Z Entering 'third_party/protobuf/third_party/googletest' 2025-12-04T10:31:21.1323564Z Entering 'third_party/psimd' 2025-12-04T10:31:21.1389653Z Entering 'third_party/pthreadpool' 2025-12-04T10:31:21.1454176Z Entering 'third_party/pybind11' 2025-12-04T10:31:21.1518090Z Entering 'third_party/python-peachpy' 2025-12-04T10:31:21.1582126Z Entering 'third_party/sleef' 2025-12-04T10:31:21.1646268Z Entering 'third_party/tensorpipe' 2025-12-04T10:31:21.1709722Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-12-04T10:31:21.1772007Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-12-04T10:31:21.1834238Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-12-04T10:31:21.1897998Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-12-04T10:31:21.1960621Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-12-04T10:31:21.2045576Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-12-04T10:31:21.2068320Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2077721Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-12-04T10:31:21.2109894Z [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' || :" 2025-12-04T10:31:21.2451100Z Entering 'android/libs/fbjni' 2025-12-04T10:31:21.2494872Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2535078Z Entering 'third_party/FP16' 2025-12-04T10:31:21.2579233Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2616275Z Entering 'third_party/FXdiv' 2025-12-04T10:31:21.2661972Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2700846Z Entering 'third_party/NNPACK' 2025-12-04T10:31:21.2745208Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2782598Z Entering 'third_party/NVTX' 2025-12-04T10:31:21.2827082Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2866174Z Entering 'third_party/VulkanMemoryAllocator' 2025-12-04T10:31:21.2909533Z http.https://github.com/.extraheader 2025-12-04T10:31:21.2947810Z Entering 'third_party/XNNPACK' 2025-12-04T10:31:21.2990619Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3043889Z Entering 'third_party/aiter' 2025-12-04T10:31:21.3087372Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3125313Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-12-04T10:31:21.3168714Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3216519Z Entering 'third_party/benchmark' 2025-12-04T10:31:21.3260590Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3298599Z Entering 'third_party/composable_kernel' 2025-12-04T10:31:21.3344436Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3390698Z Entering 'third_party/cpp-httplib' 2025-12-04T10:31:21.3436699Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3475512Z Entering 'third_party/cpuinfo' 2025-12-04T10:31:21.3519301Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3557833Z Entering 'third_party/cudnn_frontend' 2025-12-04T10:31:21.3601306Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3639167Z Entering 'third_party/cutlass' 2025-12-04T10:31:21.3682513Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3731996Z Entering 'third_party/fbgemm' 2025-12-04T10:31:21.3776322Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3816274Z Entering 'third_party/fbgemm/external/asmjit' 2025-12-04T10:31:21.3860601Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3898573Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-12-04T10:31:21.3941423Z http.https://github.com/.extraheader 2025-12-04T10:31:21.3988291Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-12-04T10:31:21.4031377Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4070556Z Entering 'third_party/fbgemm/external/cutlass' 2025-12-04T10:31:21.4114086Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4161999Z Entering 'third_party/fbgemm/external/googletest' 2025-12-04T10:31:21.4205016Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4243535Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-12-04T10:31:21.4286028Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4323174Z Entering 'third_party/fbgemm/external/json' 2025-12-04T10:31:21.4366630Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4409049Z Entering 'third_party/flash-attention' 2025-12-04T10:31:21.4453997Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4492652Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-12-04T10:31:21.4535882Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4581041Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-12-04T10:31:21.4624265Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4672236Z Entering 'third_party/flatbuffers' 2025-12-04T10:31:21.4716608Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4758074Z Entering 'third_party/fmt' 2025-12-04T10:31:21.4801970Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4839395Z Entering 'third_party/gemmlowp/gemmlowp' 2025-12-04T10:31:21.4884878Z http.https://github.com/.extraheader 2025-12-04T10:31:21.4923552Z Entering 'third_party/gloo' 2025-12-04T10:31:21.4968632Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5007603Z Entering 'third_party/googletest' 2025-12-04T10:31:21.5051892Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5089939Z Entering 'third_party/ideep' 2025-12-04T10:31:21.5133325Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5172555Z Entering 'third_party/ideep/mkl-dnn' 2025-12-04T10:31:21.5215356Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5261643Z Entering 'third_party/ittapi' 2025-12-04T10:31:21.5305999Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5344651Z Entering 'third_party/kineto' 2025-12-04T10:31:21.5390868Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5429389Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-12-04T10:31:21.5473492Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5512601Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-12-04T10:31:21.5556244Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5595660Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-12-04T10:31:21.5639505Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5679558Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-12-04T10:31:21.5722789Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5761106Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-12-04T10:31:21.5805370Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5842910Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-12-04T10:31:21.5886108Z http.https://github.com/.extraheader 2025-12-04T10:31:21.5926606Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-12-04T10:31:21.5969981Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6008533Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-12-04T10:31:21.6052626Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6090677Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-12-04T10:31:21.6134325Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6175273Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-12-04T10:31:21.6218709Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6259075Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp' 2025-12-04T10:31:21.6302262Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6339962Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T10:31:21.6384660Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6425682Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T10:31:21.6469601Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6512332Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-12-04T10:31:21.6555283Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6592862Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-12-04T10:31:21.6635943Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6676359Z Entering 'third_party/kleidiai' 2025-12-04T10:31:21.6722165Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6760826Z Entering 'third_party/mimalloc' 2025-12-04T10:31:21.6805644Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6843570Z Entering 'third_party/nlohmann' 2025-12-04T10:31:21.6886813Z http.https://github.com/.extraheader 2025-12-04T10:31:21.6925146Z Entering 'third_party/onnx' 2025-12-04T10:31:21.6971173Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7025102Z Entering 'third_party/onnx/third_party/pybind11' 2025-12-04T10:31:21.7069042Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7108324Z Entering 'third_party/opentelemetry-cpp' 2025-12-04T10:31:21.7152311Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7190534Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-12-04T10:31:21.7233583Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7272416Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-12-04T10:31:21.7314671Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7352426Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-12-04T10:31:21.7394956Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7431631Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-12-04T10:31:21.7474628Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7513102Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-12-04T10:31:21.7555903Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7592632Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-12-04T10:31:21.7634978Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7672101Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-12-04T10:31:21.7715267Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7751988Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-12-04T10:31:21.7794347Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7833151Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-12-04T10:31:21.7876859Z http.https://github.com/.extraheader 2025-12-04T10:31:21.7915911Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-12-04T10:31:21.7958811Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8019805Z Entering 'third_party/pocketfft' 2025-12-04T10:31:21.8064894Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8102174Z Entering 'third_party/protobuf' 2025-12-04T10:31:21.8146851Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8186695Z Entering 'third_party/protobuf/third_party/benchmark' 2025-12-04T10:31:21.8230340Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8267985Z Entering 'third_party/protobuf/third_party/googletest' 2025-12-04T10:31:21.8310794Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8351444Z Entering 'third_party/psimd' 2025-12-04T10:31:21.8395110Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8431738Z Entering 'third_party/pthreadpool' 2025-12-04T10:31:21.8478665Z http.https://github.com/.extraheader 2025-12-04T10:31:21.8516384Z Entering 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