2025-09-07T07:45:24.7686647Z Current runner version: '2.328.0' 2025-09-07T07:45:24.7692270Z Runner name: 'i-0b7d0f7dc0527ca9b-1001' 2025-09-07T07:45:24.7693211Z Runner group name: 'default' 2025-09-07T07:45:24.7694045Z Machine name: '32ccf0b8d8bd' 2025-09-07T07:45:24.7696499Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T07:45:24.7698427Z Contents: read 2025-09-07T07:45:24.7699087Z Metadata: read 2025-09-07T07:45:24.7699625Z ##[endgroup] 2025-09-07T07:45:24.7701760Z Secret source: Actions 2025-09-07T07:45:24.7702711Z Prepare workflow directory 2025-09-07T07:45:24.8188423Z Prepare all required actions 2025-09-07T07:45:24.8222954Z Getting action download info 2025-09-07T07:45:25.1501307Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T07:45:26.0281976Z Download action repository 'pytorch/pytorch@main' (SHA:ada43ed39c80b746b4822c92640a1882619e2795) 2025-09-07T07:45:42.4693658Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T07:45:42.8894713Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T07:45:43.2243914Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T07:45:43.8234625Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T07:45:44.2664576Z Getting action download info 2025-09-07T07:45:44.4077506Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T07:45:44.7293019Z Getting action download info 2025-09-07T07:45:44.8465553Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T07:45:45.1907708Z Getting action download info 2025-09-07T07:45:45.3066058Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T07:45:45.6694965Z Getting action download info 2025-09-07T07:45:45.8014799Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T07:45:45.8018574Z ##[group] Inputs 2025-09-07T07:45:45.8018899Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T07:45:45.8024198Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T07:45:45.8029653Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:45:45.8030488Z sync-tag: 2025-09-07T07:45:45.8031237Z timeout-minutes: 1440 2025-09-07T07:45:45.8031446Z use-gha: 2025-09-07T07:45:45.8032303Z dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T07:45:45.8033209Z s3-bucket: gha-artifacts 2025-09-07T07:45:45.8033411Z aws-role-to-assume: 2025-09-07T07:45:45.8033907Z disable-monitor: false 2025-09-07T07:45:45.8034144Z monitor-log-interval: 15 2025-09-07T07:45:45.8034382Z monitor-data-collect-interval: 4 2025-09-07T07:45:45.8034635Z ##[endgroup] 2025-09-07T07:45:45.8034950Z Complete job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T07:45:45.8492255Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T07:45:45.8492917Z with: 2025-09-07T07:45:45.8493403Z github-secret: *** 2025-09-07T07:45:45.8493925Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T07:45:45.8494555Z activate-with-label: false 2025-09-07T07:45:45.8510998Z label: with-ssh 2025-09-07T07:45:45.8511226Z remove-existing-keys: true 2025-09-07T07:45:45.8511439Z fail-silently: true 2025-09-07T07:45:45.8511988Z env: 2025-09-07T07:45:45.8512155Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:45.8512349Z ##[endgroup] 2025-09-07T07:45:45.9572995Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T07:45:45.9573783Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T07:45:45.9755709Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T07:45:45.9756052Z with: 2025-09-07T07:45:45.9756216Z no-sudo: true 2025-09-07T07:45:45.9756393Z submodules: recursive 2025-09-07T07:45:45.9756647Z fetch-depth: 0 2025-09-07T07:45:45.9756815Z env: 2025-09-07T07:45:45.9756969Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:45.9757180Z ##[endgroup] 2025-09-07T07:45:45.9831712Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:45.9832483Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:45.9851209Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:45:45.9851526Z env: 2025-09-07T07:45:45.9851690Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:45.9851887Z ##[endgroup] 2025-09-07T07:45:45.9992070Z ##[group]Run actions/checkout@v4 2025-09-07T07:45:45.9992297Z with: 2025-09-07T07:45:45.9992483Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:45:45.9992719Z fetch-depth: 0 2025-09-07T07:45:45.9992893Z submodules: recursive 2025-09-07T07:45:45.9993077Z show-progress: false 2025-09-07T07:45:45.9993291Z repository: pytorch/pytorch 2025-09-07T07:45:45.9993822Z token: *** 2025-09-07T07:45:45.9993991Z ssh-strict: true 2025-09-07T07:45:45.9994163Z ssh-user: git 2025-09-07T07:45:45.9994335Z persist-credentials: true 2025-09-07T07:45:45.9994533Z clean: true 2025-09-07T07:45:45.9994724Z sparse-checkout-cone-mode: true 2025-09-07T07:45:45.9994945Z fetch-tags: false 2025-09-07T07:45:45.9995106Z lfs: false 2025-09-07T07:45:45.9995275Z set-safe-directory: true 2025-09-07T07:45:45.9995466Z env: 2025-09-07T07:45:45.9995623Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:45.9995807Z ##[endgroup] 2025-09-07T07:45:46.0975960Z Syncing repository: pytorch/pytorch 2025-09-07T07:45:46.0977260Z ##[group]Getting Git version info 2025-09-07T07:45:46.0977629Z Working directory is '/home/alice/_work/pytorch/pytorch' 2025-09-07T07:45:46.0978109Z [command]/usr/bin/git version 2025-09-07T07:45:46.0978347Z git version 2.50.1 2025-09-07T07:45:46.0997529Z ##[endgroup] 2025-09-07T07:45:46.1009014Z Temporarily overriding HOME='/home/alice/_work/_temp/ed92350d-b188-4f38-a788-b23cbc83185b' before making global git config changes 2025-09-07T07:45:46.1009783Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:45:46.1013950Z [command]/usr/bin/git config --global --add safe.directory /home/alice/_work/pytorch/pytorch 2025-09-07T07:45:46.1046563Z Deleting the contents of '/home/alice/_work/pytorch/pytorch' 2025-09-07T07:45:46.1049750Z ##[group]Initializing the repository 2025-09-07T07:45:46.1053068Z [command]/usr/bin/git init /home/alice/_work/pytorch/pytorch 2025-09-07T07:45:46.1100780Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T07:45:46.1101277Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T07:45:46.1101716Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T07:45:46.1102016Z hint: 2025-09-07T07:45:46.1102271Z hint: git config --global init.defaultBranch 2025-09-07T07:45:46.1102534Z hint: 2025-09-07T07:45:46.1102872Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T07:45:46.1103284Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T07:45:46.1103599Z hint: 2025-09-07T07:45:46.1103774Z hint: git branch -m 2025-09-07T07:45:46.1103970Z hint: 2025-09-07T07:45:46.1104229Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T07:45:46.1104686Z Initialized empty Git repository in /home/alice/_work/pytorch/pytorch/.git/ 2025-09-07T07:45:46.1111453Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T07:45:46.1150579Z ##[endgroup] 2025-09-07T07:45:46.1151076Z ##[group]Disabling automatic garbage collection 2025-09-07T07:45:46.1153509Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:45:46.1181819Z ##[endgroup] 2025-09-07T07:45:46.1182193Z ##[group]Setting up auth 2025-09-07T07:45:46.1187460Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:45:46.1216536Z [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' || :" 2025-09-07T07:45:46.1471529Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:45:46.1499830Z [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' || :" 2025-09-07T07:45:46.1739110Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:45:46.1774908Z ##[endgroup] 2025-09-07T07:45:46.1775273Z ##[group]Fetching the repository 2025-09-07T07:45:46.1781994Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:46:52.0461386Z From https://github.com/pytorch/pytorch 2025-09-07T07:46:52.0462024Z * [new branch] 160583 -> origin/160583 2025-09-07T07:46:52.0463018Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T07:46:52.0463578Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T07:46:52.0464329Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T07:46:52.0465012Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T07:46:52.0465766Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T07:46:52.0468397Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T07:46:52.0469800Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T07:46:52.0472641Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T07:46:52.0473347Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T07:46:52.0474929Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T07:46:52.0476294Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T07:46:52.0477856Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T07:46:52.0479533Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T07:46:52.0481425Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T07:46:52.0483581Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T07:46:52.0485261Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T07:46:52.0486821Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T07:46:52.0488545Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T07:46:52.0490030Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T07:46:52.0491950Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T07:46:52.0493494Z * [new branch] addsimde -> origin/addsimde 2025-09-07T07:46:52.0495493Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T07:46:52.0497354Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T07:46:52.0498890Z * [new branch] adi/test -> origin/adi/test 2025-09-07T07:46:52.0500758Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T07:46:52.0502369Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T07:46:52.0504111Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T07:46:52.0505928Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T07:46:52.0507226Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T07:46:52.0508909Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T07:46:52.0511980Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T07:46:52.0513638Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T07:46:52.0515179Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T07:46:52.0517580Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T07:46:52.0518990Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T07:46:52.0520869Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T07:46:52.0522609Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T07:46:52.0524204Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T07:46:52.0525754Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T07:46:52.0527324Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 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origin/xmfan/ca_1051b93192 2025-09-07T07:46:52.9610988Z * [new branch] xmfan/ca_1a722f62c248391fc4a542e8851a5559aa356ae8 -> origin/xmfan/ca_1a722f62c248391fc4a542e8851a5559aa356ae8 2025-09-07T07:46:52.9612416Z * [new branch] xmfan/ca_5a2be192d1 -> origin/xmfan/ca_5a2be192d1 2025-09-07T07:46:52.9614060Z * [new branch] xmfan/ca_9d59b516e9 -> origin/xmfan/ca_9d59b516e9 2025-09-07T07:46:52.9615516Z * [new branch] xmfan/ca_api -> origin/xmfan/ca_api 2025-09-07T07:46:52.9617052Z * [new branch] xmfan/ca_apr8 -> origin/xmfan/ca_apr8 2025-09-07T07:46:52.9618541Z * [new branch] xmfan/ca_base -> origin/xmfan/ca_base 2025-09-07T07:46:52.9620171Z * [new branch] xmfan/ca_cudagraphs -> origin/xmfan/ca_cudagraphs 2025-09-07T07:46:52.9622308Z * [new branch] xmfan/ca_dynamic -> origin/xmfan/ca_dynamic 2025-09-07T07:46:52.9624381Z * [new branch] xmfan/ca_fix_dyn -> origin/xmfan/ca_fix_dyn 2025-09-07T07:46:52.9625835Z * [new branch] xmfan/ca_fix_lowering -> origin/xmfan/ca_fix_lowering 2025-09-07T07:46:52.9627407Z * [new branch] xmfan/ca_fix_polyfills -> origin/xmfan/ca_fix_polyfills 2025-09-07T07:46:52.9628698Z * [new branch] xmfan/ca_jan3 -> origin/xmfan/ca_jan3 2025-09-07T07:46:52.9630611Z * [new branch] xmfan/ca_jun18 -> origin/xmfan/ca_jun18 2025-09-07T07:46:52.9632211Z * [new branch] xmfan/ca_jun24 -> origin/xmfan/ca_jun24 2025-09-07T07:46:52.9633726Z * [new branch] xmfan/ca_mem_base -> origin/xmfan/ca_mem_base 2025-09-07T07:46:52.9635202Z * [new branch] xmfan/ca_mem_fix -> origin/xmfan/ca_mem_fix 2025-09-07T07:46:52.9636840Z * [new branch] xmfan/ca_memory_fix -> origin/xmfan/ca_memory_fix 2025-09-07T07:46:52.9638463Z * [new branch] xmfan/ca_memory_fix_rebased -> origin/xmfan/ca_memory_fix_rebased 2025-09-07T07:46:52.9640148Z * [new branch] xmfan/ca_memory_fix_rebased2 -> origin/xmfan/ca_memory_fix_rebased2 2025-09-07T07:46:52.9641913Z * [new branch] xmfan/ca_move_to_cuda -> origin/xmfan/ca_move_to_cuda 2025-09-07T07:46:52.9643366Z * [new branch] xmfan/ca_nested -> origin/xmfan/ca_nested 2025-09-07T07:46:52.9644996Z * [new branch] xmfan/ca_overhead -> origin/xmfan/ca_overhead 2025-09-07T07:46:52.9646590Z * [new branch] xmfan/ca_overhead_0eba7e5451 -> origin/xmfan/ca_overhead_0eba7e5451 2025-09-07T07:46:52.9648006Z * [new branch] xmfan/ca_scalar -> origin/xmfan/ca_scalar 2025-09-07T07:46:52.9649609Z * [new branch] xmfan/ca_subclass_mem_fix -> origin/xmfan/ca_subclass_mem_fix 2025-09-07T07:46:52.9651358Z * [new branch] xmfan/ca_warm_mem -> origin/xmfan/ca_warm_mem 2025-09-07T07:46:52.9652931Z * [new branch] xmfan/ca_warm_mem_base -> origin/xmfan/ca_warm_mem_base 2025-09-07T07:46:52.9654437Z * [new branch] xmfan/cacu_jun18 -> origin/xmfan/cacu_jun18 2025-09-07T07:46:52.9655953Z * [new branch] xmfan/cacu_jun19 -> origin/xmfan/cacu_jun19 2025-09-07T07:46:52.9657463Z * [new branch] xmfan/cacu_jun4 -> origin/xmfan/cacu_jun4 2025-09-07T07:46:52.9659467Z * [new branch] xmfan/cacu_may27 -> origin/xmfan/cacu_may27 2025-09-07T07:46:52.9661095Z * [new branch] xmfan/disable_duck_shape -> origin/xmfan/disable_duck_shape 2025-09-07T07:46:52.9662866Z * [new branch] xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough 2025-09-07T07:46:52.9664446Z * [new branch] xmfan/issue_123374 -> origin/xmfan/issue_123374 2025-09-07T07:46:52.9666293Z * [new branch] xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:52.9667827Z * [new branch] xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 2025-09-07T07:46:52.9669231Z * [new branch] xmfan/segfault_test -> origin/xmfan/segfault_test 2025-09-07T07:46:52.9670883Z * [new branch] xmfan/single_step -> origin/xmfan/single_step 2025-09-07T07:46:52.9672756Z * [new branch] xmfan/sth_0829 -> origin/xmfan/sth_0829 2025-09-07T07:46:52.9674354Z * [new branch] xmfan/test -> origin/xmfan/test 2025-09-07T07:46:52.9677082Z * [new branch] yguo/debug-0226-constexpr -> origin/yguo/debug-0226-constexpr 2025-09-07T07:46:52.9678606Z * [new branch] yguo/new_latest_changes -> origin/yguo/new_latest_changes 2025-09-07T07:46:52.9680091Z * [new branch] yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes 2025-09-07T07:46:52.9682402Z * [new branch] yihan_quantization -> origin/yihan_quantization 2025-09-07T07:46:52.9684799Z * [new branch] yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark 2025-09-07T07:46:52.9686245Z * [new branch] yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark 2025-09-07T07:46:52.9687694Z * [new branch] yiming/bootcamp -> origin/yiming/bootcamp 2025-09-07T07:46:52.9690096Z * [new branch] zainr/canary-test -> origin/zainr/canary-test 2025-09-07T07:46:52.9692019Z * [new branch] zainr/cleanup-gh-runners -> origin/zainr/cleanup-gh-runners 2025-09-07T07:46:52.9693460Z * [new branch] zainr/git-push-v2 -> origin/zainr/git-push-v2 2025-09-07T07:46:52.9694895Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-09-07T07:46:52.9696376Z * [new branch] zainr/test -> origin/zainr/test 2025-09-07T07:46:52.9697785Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-09-07T07:46:52.9699385Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-09-07T07:46:52.9701197Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-09-07T07:46:52.9703192Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-09-07T07:46:52.9704982Z * [new branch] zb2p -> origin/zb2p 2025-09-07T07:46:52.9706888Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-09-07T07:46:52.9709095Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-09-07T07:46:52.9712279Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-09-07T07:46:52.9714609Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-09-07T07:46:52.9716975Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T07:46:52.9718376Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T07:46:52.9719542Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T07:46:52.9721495Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T07:46:52.9722027Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T07:46:52.9722794Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T07:46:52.9723825Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T07:46:52.9724603Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T07:46:52.9725560Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T07:46:52.9726528Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T07:46:52.9727578Z * [new tag] ciflow/binaries/160720 -> ciflow/binaries/160720 2025-09-07T07:46:52.9728392Z * [new tag] ciflow/binaries/162080 -> ciflow/binaries/162080 2025-09-07T07:46:52.9729359Z * [new tag] ciflow/binaries/162329 -> ciflow/binaries/162329 2025-09-07T07:46:52.9730898Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-09-07T07:46:52.9731732Z * [new tag] ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711 2025-09-07T07:46:52.9732522Z * [new tag] ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432 2025-09-07T07:46:52.9733883Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-09-07T07:46:52.9734460Z * [new tag] ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711 2025-09-07T07:46:52.9735326Z * [new tag] ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432 2025-09-07T07:46:52.9736174Z * [new tag] ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136 2025-09-07T07:46:52.9737288Z * [new tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T07:46:52.9738169Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T07:46:52.9739460Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T07:46:52.9741222Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T07:46:52.9741947Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T07:46:52.9742834Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T07:46:52.9743846Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T07:46:52.9744571Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T07:46:52.9745332Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T07:46:52.9746176Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 2025-09-07T07:46:52.9746964Z * [new tag] ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041 2025-09-07T07:46:52.9747993Z * [new tag] ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142 2025-09-07T07:46:52.9748624Z * [new tag] ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150 2025-09-07T07:46:52.9749599Z * [new tag] ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243 2025-09-07T07:46:52.9750553Z * [new tag] ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320 2025-09-07T07:46:52.9751877Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-09-07T07:46:52.9753150Z * [new tag] ciflow/h100/160480 -> ciflow/h100/160480 2025-09-07T07:46:52.9754125Z * [new tag] ciflow/h100/161749 -> ciflow/h100/161749 2025-09-07T07:46:52.9755392Z * [new tag] ciflow/h100/162022 -> ciflow/h100/162022 2025-09-07T07:46:52.9755867Z * [new tag] ciflow/h100/162278 -> ciflow/h100/162278 2025-09-07T07:46:52.9757528Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-09-07T07:46:52.9758500Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-09-07T07:46:52.9759790Z * [new tag] ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063 2025-09-07T07:46:52.9760925Z * [new tag] ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227 2025-09-07T07:46:52.9762067Z * [new tag] ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323 2025-09-07T07:46:52.9763381Z * [new tag] ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170 2025-09-07T07:46:52.9764412Z * [new tag] ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146 2025-09-07T07:46:52.9765187Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-09-07T07:46:52.9766242Z * [new tag] ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715 2025-09-07T07:46:52.9767347Z * [new tag] ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053 2025-09-07T07:46:52.9768314Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T07:46:52.9769559Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T07:46:52.9770535Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T07:46:52.9771883Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T07:46:52.9772648Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T07:46:52.9773485Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T07:46:52.9774361Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T07:46:52.9775302Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T07:46:52.9776083Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T07:46:52.9777012Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T07:46:52.9777824Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T07:46:52.9778648Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T07:46:52.9779492Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T07:46:52.9780601Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T07:46:52.9781582Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T07:46:52.9782548Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T07:46:52.9783714Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T07:46:52.9784537Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T07:46:52.9785436Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T07:46:52.9786447Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T07:46:52.9787368Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T07:46:52.9788491Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T07:46:52.9789380Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T07:46:52.9790821Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T07:46:52.9791756Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T07:46:52.9792611Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T07:46:52.9793696Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T07:46:52.9794586Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T07:46:52.9795650Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T07:46:52.9796783Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T07:46:52.9797689Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T07:46:52.9798730Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T07:46:52.9799904Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T07:46:52.9801345Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T07:46:52.9802413Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T07:46:52.9803363Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T07:46:52.9804337Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T07:46:52.9805345Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T07:46:52.9806232Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T07:46:52.9807357Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T07:46:52.9809013Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T07:46:52.9809925Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T07:46:52.9811120Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T07:46:52.9811983Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T07:46:52.9812966Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T07:46:52.9813796Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T07:46:52.9814745Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T07:46:52.9815631Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T07:46:52.9816654Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T07:46:52.9817682Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T07:46:52.9818718Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T07:46:52.9819611Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T07:46:52.9821129Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T07:46:52.9822000Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T07:46:52.9823083Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T07:46:52.9824219Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T07:46:52.9825169Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T07:46:52.9826085Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T07:46:52.9827088Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T07:46:52.9828297Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T07:46:52.9830191Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T07:46:52.9831238Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T07:46:52.9832234Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T07:46:52.9833082Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T07:46:52.9834058Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T07:46:52.9835162Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T07:46:52.9836143Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T07:46:52.9837231Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T07:46:52.9838246Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T07:46:52.9839379Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T07:46:52.9840580Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T07:46:52.9842141Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T07:46:52.9843007Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T07:46:52.9843974Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T07:46:52.9845009Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T07:46:52.9846277Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T07:46:52.9847191Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T07:46:52.9848136Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T07:46:52.9849093Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T07:46:52.9850071Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T07:46:52.9851913Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T07:46:52.9852854Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T07:46:52.9853818Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T07:46:52.9854814Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T07:46:52.9855793Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T07:46:52.9856760Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T07:46:52.9857704Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T07:46:52.9858719Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T07:46:52.9859689Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T07:46:52.9861011Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T07:46:52.9862003Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T07:46:52.9863263Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T07:46:52.9864289Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T07:46:52.9865262Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T07:46:52.9866264Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T07:46:52.9867243Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T07:46:52.9868271Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T07:46:52.9869462Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T07:46:52.9870547Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T07:46:52.9871651Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T07:46:52.9872752Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T07:46:52.9873785Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T07:46:52.9875037Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T07:46:52.9876188Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T07:46:52.9877254Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T07:46:52.9878290Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T07:46:52.9879322Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T07:46:52.9880559Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T07:46:52.9881656Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T07:46:52.9882631Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T07:46:52.9883591Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T07:46:52.9884740Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T07:46:52.9885721Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T07:46:52.9886696Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T07:46:52.9887780Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T07:46:52.9888790Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T07:46:52.9889745Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T07:46:52.9891048Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T07:46:52.9892163Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T07:46:52.9893299Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T07:46:52.9894223Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T07:46:52.9895247Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T07:46:52.9896282Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T07:46:52.9897319Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T07:46:52.9898341Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T07:46:52.9899638Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T07:46:52.9901030Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T07:46:52.9902041Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T07:46:52.9903210Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T07:46:52.9904432Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T07:46:52.9905486Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T07:46:52.9906508Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T07:46:52.9907763Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T07:46:52.9909147Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T07:46:52.9909768Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T07:46:52.9911358Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T07:46:52.9912393Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T07:46:52.9913458Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T07:46:52.9914485Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T07:46:52.9915570Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T07:46:52.9916649Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T07:46:52.9917708Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T07:46:52.9918803Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T07:46:52.9919831Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T07:46:52.9921292Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T07:46:52.9922337Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T07:46:52.9923402Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T07:46:52.9924518Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T07:46:52.9925574Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T07:46:52.9926608Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T07:46:52.9927663Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T07:46:52.9928792Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T07:46:52.9929835Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T07:46:52.9931185Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T07:46:52.9932489Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T07:46:52.9933543Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T07:46:52.9934700Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T07:46:52.9935933Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T07:46:52.9937077Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T07:46:52.9938127Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T07:46:52.9939336Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T07:46:52.9940607Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T07:46:52.9941836Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T07:46:52.9942961Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T07:46:52.9944176Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T07:46:52.9945262Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T07:46:52.9946441Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T07:46:52.9947898Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T07:46:52.9949275Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T07:46:52.9950599Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T07:46:52.9952309Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T07:46:52.9952913Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T07:46:52.9954140Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T07:46:52.9955234Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T07:46:52.9956384Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T07:46:52.9957483Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T07:46:52.9958567Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T07:46:52.9959741Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T07:46:52.9961192Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T07:46:52.9962211Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T07:46:52.9963397Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T07:46:52.9964588Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T07:46:52.9965738Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T07:46:52.9966890Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T07:46:52.9968094Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T07:46:52.9969209Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T07:46:52.9970554Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T07:46:52.9971796Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T07:46:52.9973212Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T07:46:52.9974399Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T07:46:52.9975650Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T07:46:52.9977068Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T07:46:52.9977929Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T07:46:52.9978729Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T07:46:52.9979926Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T07:46:52.9981035Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T07:46:52.9982042Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T07:46:52.9982985Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T07:46:52.9983835Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T07:46:52.9984837Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T07:46:52.9985988Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T07:46:52.9987002Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T07:46:52.9988068Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T07:46:52.9989475Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T07:46:52.9990541Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T07:46:52.9992078Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T07:46:52.9993171Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T07:46:52.9993644Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T07:46:52.9994483Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T07:46:52.9995411Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T07:46:52.9996723Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T07:46:52.9997498Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T07:46:52.9998447Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T07:46:52.9999712Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T07:46:53.0001098Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T07:46:53.0002890Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T07:46:53.0003886Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T07:46:53.0005156Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T07:46:53.0006080Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T07:46:53.0007314Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T07:46:53.0008387Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T07:46:53.0009636Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T07:46:53.0010890Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T07:46:53.0011804Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T07:46:53.0012659Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T07:46:53.0013483Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T07:46:53.0014319Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T07:46:53.0015116Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T07:46:53.0016014Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T07:46:53.0017427Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T07:46:53.0017907Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T07:46:53.0018827Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T07:46:53.0019666Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T07:46:53.0021265Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T07:46:53.0021965Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T07:46:53.0023461Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T07:46:53.0024196Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T07:46:53.0025496Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T07:46:53.0026260Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T07:46:53.0027091Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T07:46:53.0027917Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T07:46:53.0029073Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T07:46:53.0030182Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T07:46:53.0031151Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T07:46:53.0032085Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T07:46:53.0032908Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T07:46:53.0033756Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T07:46:53.0034599Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T07:46:53.0035466Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T07:46:53.0036303Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T07:46:53.0037195Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T07:46:53.0038570Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T07:46:53.0039631Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T07:46:53.0041414Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T07:46:53.0042302Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T07:46:53.0043127Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T07:46:53.0044197Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T07:46:53.0045277Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T07:46:53.0046326Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T07:46:53.0047388Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T07:46:53.0048338Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T07:46:53.0049369Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T07:46:53.0050777Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T07:46:53.0051752Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T07:46:53.0053294Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T07:46:53.0053856Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T07:46:53.0054897Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T07:46:53.0055886Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T07:46:53.0056991Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T07:46:53.0058035Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T07:46:53.0059599Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T07:46:53.0060593Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T07:46:53.0061949Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T07:46:53.0062776Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T07:46:53.0063893Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T07:46:53.0064685Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T07:46:53.0065527Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T07:46:53.0066607Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T07:46:53.0067794Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T07:46:53.0068330Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T07:46:53.0069331Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T07:46:53.0070035Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T07:46:53.0071264Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T07:46:53.0072043Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T07:46:53.0073042Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T07:46:53.0073777Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T07:46:53.0074628Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T07:46:53.0075571Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T07:46:53.0076397Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T07:46:53.0077241Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T07:46:53.0078278Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T07:46:53.0079036Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T07:46:53.0080127Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T07:46:53.0081290Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T07:46:53.0082472Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T07:46:53.0083301Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T07:46:53.0084371Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T07:46:53.0085119Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T07:46:53.0086085Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T07:46:53.0086929Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T07:46:53.0087944Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T07:46:53.0088736Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T07:46:53.0089757Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T07:46:53.0091204Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T07:46:53.0091914Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T07:46:53.0092936Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T07:46:53.0093911Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T07:46:53.0094915Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T07:46:53.0095745Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T07:46:53.0096884Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T07:46:53.0097928Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T07:46:53.0098746Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T07:46:53.0099711Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T07:46:53.0100883Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T07:46:53.0101836Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T07:46:53.0103195Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T07:46:53.0103818Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T07:46:53.0104839Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T07:46:53.0105595Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T07:46:53.0106561Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T07:46:53.0107483Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T07:46:53.0108736Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T07:46:53.0109549Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T07:46:53.0110883Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T07:46:53.0111823Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T07:46:53.0112805Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T07:46:53.0113574Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T07:46:53.0114587Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T07:46:53.0115442Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T07:46:53.0116385Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T07:46:53.0117468Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T07:46:53.0118510Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T07:46:53.0119513Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T07:46:53.0120686Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T07:46:53.0121714Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T07:46:53.0122580Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T07:46:53.0123593Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T07:46:53.0124441Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T07:46:53.0125460Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T07:46:53.0126562Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T07:46:53.0127448Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T07:46:53.0128518Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T07:46:53.0129382Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T07:46:53.0130891Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T07:46:53.0131659Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T07:46:53.0132669Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T07:46:53.0133677Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T07:46:53.0134532Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T07:46:53.0135671Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T07:46:53.0136534Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T07:46:53.0137556Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T07:46:53.0138456Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T07:46:53.0139496Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T07:46:53.0140917Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T07:46:53.0141653Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T07:46:53.0142936Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T07:46:53.0143923Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T07:46:53.0144974Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T07:46:53.0145832Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T07:46:53.0146918Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T07:46:53.0147894Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T07:46:53.0148881Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T07:46:53.0149963Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T07:46:53.0151248Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T07:46:53.0152088Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T07:46:53.0153137Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T07:46:53.0154075Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T07:46:53.0155111Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T07:46:53.0156082Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T07:46:53.0157156Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T07:46:53.0158112Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T07:46:53.0159087Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T07:46:53.0160121Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T07:46:53.0161499Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T07:46:53.0162756Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T07:46:53.0163822Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T07:46:53.0164849Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T07:46:53.0165844Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T07:46:53.0166906Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T07:46:53.0167891Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T07:46:53.0168921Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T07:46:53.0169907Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T07:46:53.0171137Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T07:46:53.0172212Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T07:46:53.0173449Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T07:46:53.0174485Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T07:46:53.0176106Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T07:46:53.0177382Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T07:46:53.0178540Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T07:46:53.0179330Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T07:46:53.0180740Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T07:46:53.0182085Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T07:46:53.0182772Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T07:46:53.0183732Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T07:46:53.0184524Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T07:46:53.0185597Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T07:46:53.0186479Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T07:46:53.0187320Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T07:46:53.0188279Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T07:46:53.0189196Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T07:46:53.0190482Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T07:46:53.0191488Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T07:46:53.0192306Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T07:46:53.0193230Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T07:46:53.0194002Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T07:46:53.0194853Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T07:46:53.0195867Z * [new tag] cslpull75 -> cslpull75 2025-09-07T07:46:53.0196823Z * [new tag] cslpull76 -> cslpull76 2025-09-07T07:46:53.0197798Z * [new tag] cslpull77 -> cslpull77 2025-09-07T07:46:53.0198863Z * [new tag] cslpull78 -> cslpull78 2025-09-07T07:46:53.0199800Z * [new tag] cslpull79 -> cslpull79 2025-09-07T07:46:53.0201046Z * [new tag] cslpull80 -> cslpull80 2025-09-07T07:46:53.0202002Z * [new tag] cslpull81 -> cslpull81 2025-09-07T07:46:53.0203061Z * [new tag] cslpull82 -> cslpull82 2025-09-07T07:46:53.0203989Z * [new tag] cslpull83 -> cslpull83 2025-09-07T07:46:53.0205037Z * [new tag] cslpull84 -> cslpull84 2025-09-07T07:46:53.0205883Z * [new tag] cslpull85 -> cslpull85 2025-09-07T07:46:53.0206878Z * [new tag] cslpull86 -> cslpull86 2025-09-07T07:46:53.0207807Z * [new tag] cslpull87 -> cslpull87 2025-09-07T07:46:53.0209051Z * [new tag] cslpull88 -> cslpull88 2025-09-07T07:46:53.0209887Z * [new tag] cslpull89 -> cslpull89 2025-09-07T07:46:53.0211139Z * [new tag] cslpull90 -> cslpull90 2025-09-07T07:46:53.0212388Z * [new tag] cslpull91 -> cslpull91 2025-09-07T07:46:53.0213388Z * [new tag] cslpull92 -> cslpull92 2025-09-07T07:46:53.0214313Z * [new tag] flight_5 -> flight_5 2025-09-07T07:46:53.0215350Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T07:46:53.0216339Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T07:46:53.0217279Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T07:46:53.0218143Z * [new tag] forpull1 -> forpull1 2025-09-07T07:46:53.0219504Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T07:46:53.0220658Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T07:46:53.0222150Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T07:46:53.0222847Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T07:46:53.0223874Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T07:46:53.0224918Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T07:46:53.0226594Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T07:46:53.0227697Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T07:46:53.0228651Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T07:46:53.0229835Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T07:46:53.0230945Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T07:46:53.0232166Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T07:46:53.0233124Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T07:46:53.0234219Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T07:46:53.0235373Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T07:46:53.0236287Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T07:46:53.0237274Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T07:46:53.0238457Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T07:46:53.0239352Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T07:46:53.0241193Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T07:46:53.0242344Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T07:46:53.0243288Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T07:46:53.0244508Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T07:46:53.0245466Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T07:46:53.0246583Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T07:46:53.0247536Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T07:46:53.0248496Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T07:46:53.0249559Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T07:46:53.0250716Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T07:46:53.0252181Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T07:46:53.0252800Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T07:46:53.0253928Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T07:46:53.0255095Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T07:46:53.0255961Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T07:46:53.0257494Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T07:46:53.0258444Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T07:46:53.0259613Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T07:46:53.0260560Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T07:46:53.0261769Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T07:46:53.0262864Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T07:46:53.0264101Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T07:46:53.0264953Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T07:46:53.0266111Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T07:46:53.0267076Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T07:46:53.0268683Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T07:46:53.0269613Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T07:46:53.0270983Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T07:46:53.0272158Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T07:46:53.0273286Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T07:46:53.0274189Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T07:46:53.0275307Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T07:46:53.0276468Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T07:46:53.0277429Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T07:46:53.0278544Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T07:46:53.0279506Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T07:46:53.0281145Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T07:46:53.0283414Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T07:46:53.0284054Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T07:46:53.0285209Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T07:46:53.0286337Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T07:46:53.0287471Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T07:46:53.0288362Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T07:46:53.0289533Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T07:46:53.0290545Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T07:46:53.0291742Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T07:46:53.0292742Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T07:46:53.0293671Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T07:46:53.0294561Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T07:46:53.0295725Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T07:46:53.0296697Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T07:46:53.0297871Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T07:46:53.0298968Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T07:46:53.0300126Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T07:46:53.0301435Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T07:46:53.0302533Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T07:46:53.0303762Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T07:46:53.0304899Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T07:46:53.0305892Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T07:46:53.0306950Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T07:46:53.0308142Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T07:46:53.0309274Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T07:46:53.0310122Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T07:46:53.0311948Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T07:46:53.0312660Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T07:46:53.0316891Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T07:46:53.0317995Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T07:46:53.0319171Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T07:46:53.0320553Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T07:46:53.0321767Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T07:46:53.0323566Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T07:46:53.0326929Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T07:46:53.0327278Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T07:46:53.0327931Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T07:46:53.0328600Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T07:46:53.0329130Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T07:46:53.0330408Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T07:46:53.0331650Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T07:46:53.0332701Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T07:46:53.0333874Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T07:46:53.0335018Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T07:46:53.0336089Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T07:46:53.0337254Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T07:46:53.0338381Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T07:46:53.0339543Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T07:46:53.0340862Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T07:46:53.0342082Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T07:46:53.0343354Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T07:46:53.0344461Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T07:46:53.0346303Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T07:46:53.0346943Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T07:46:53.0348237Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T07:46:53.0349353Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T07:46:53.0350708Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T07:46:53.0352045Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T07:46:53.0352997Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T07:46:53.0354255Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T07:46:53.0355491Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T07:46:53.0356605Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T07:46:53.0357593Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T07:46:53.0358885Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T07:46:53.0360053Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T07:46:53.0361543Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T07:46:53.0362730Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T07:46:53.0363739Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T07:46:53.0364717Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T07:46:53.0365904Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T07:46:53.0367057Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T07:46:53.0368173Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T07:46:53.0369373Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T07:46:53.0370434Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T07:46:53.0380128Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T07:46:53.0380937Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T07:46:53.0381412Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T07:46:53.0381832Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T07:46:53.0382253Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T07:46:53.0383106Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T07:46:53.0383591Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T07:46:53.0384093Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T07:46:53.0384626Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T07:46:53.0385071Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T07:46:53.0385523Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T07:46:53.0386030Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T07:46:53.0386539Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T07:46:53.0387816Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T07:46:53.0388869Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T07:46:53.0390075Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T07:46:53.0391963Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T07:46:53.0393091Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T07:46:53.0394316Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T07:46:53.0395460Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T07:46:53.0396725Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T07:46:53.0397949Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T07:46:53.0399256Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:53.0400631Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T07:46:53.0401872Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T07:46:53.0403535Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T07:46:53.0404553Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T07:46:53.0405776Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T07:46:53.0406865Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T07:46:53.0408119Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T07:46:53.0409277Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T07:46:53.0410802Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T07:46:53.0411853Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T07:46:53.0412912Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T07:46:53.0414046Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T07:46:53.0415106Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T07:46:53.0416278Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T07:46:53.0417353Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T07:46:53.0418591Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T07:46:53.0419789Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T07:46:53.0421359Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T07:46:53.0422554Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T07:46:53.0423934Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T07:46:53.0424912Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T07:46:53.0426125Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T07:46:53.0427238Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T07:46:53.0428353Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T07:46:53.0429480Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T07:46:53.0430665Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T07:46:53.0432884Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T07:46:53.0433871Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T07:46:53.0435037Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T07:46:53.0436105Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T07:46:53.0437405Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T07:46:53.0438516Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T07:46:53.0439799Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T07:46:53.0440986Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T07:46:53.0442229Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T07:46:53.0443732Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T07:46:53.0444578Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T07:46:53.0445649Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T07:46:53.0446801Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T07:46:53.0447966Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T07:46:53.0449075Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T07:46:53.0450549Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T07:46:53.0452142Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T07:46:53.0453303Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T07:46:53.0454451Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T07:46:53.0455533Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T07:46:53.0456668Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T07:46:53.0458193Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T07:46:53.0459169Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T07:46:53.0461183Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T07:46:53.0462290Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T07:46:53.0463583Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T07:46:53.0464681Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T07:46:53.0465822Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T07:46:53.0467021Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T07:46:53.0467971Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T07:46:53.0469077Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T07:46:53.0470169Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T07:46:53.0471712Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T07:46:53.0472762Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T07:46:53.0473872Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T07:46:53.0475334Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T07:46:53.0476176Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T07:46:53.0477218Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T07:46:53.0478331Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T07:46:53.0479514Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T07:46:53.0480992Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T07:46:53.0482565Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T07:46:53.0483592Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T07:46:53.0484634Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T07:46:53.0485756Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T07:46:53.0486761Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T07:46:53.0488029Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T07:46:53.0489084Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T07:46:53.0490453Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T07:46:53.0491554Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T07:46:53.0492881Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T07:46:53.0493885Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T07:46:53.0495044Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T07:46:53.0496120Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T07:46:53.0497397Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T07:46:53.0498618Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T07:46:53.0499632Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T07:46:53.0500942Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T07:46:53.0502069Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T07:46:53.0503328Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T07:46:53.0504290Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T07:46:53.0505470Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T07:46:53.0507412Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T07:46:53.0508214Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T07:46:53.0509296Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T07:46:53.0510747Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T07:46:53.0511938Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T07:46:53.0513070Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T07:46:53.0514031Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T07:46:53.0515262Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T07:46:53.0516186Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T07:46:53.0517256Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T07:46:53.0518390Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T07:46:53.0519486Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T07:46:53.0520978Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T07:46:53.0522140Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T07:46:53.0523185Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T07:46:53.0524324Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T07:46:53.0525429Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T07:46:53.0526365Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T07:46:53.0527428Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T07:46:53.0528603Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T07:46:53.0529573Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T07:46:53.0530906Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T07:46:53.0532120Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T07:46:53.0533178Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T07:46:53.0534351Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T07:46:53.0535527Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T07:46:53.0536954Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T07:46:53.0537860Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T07:46:53.0538960Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T07:46:53.0540174Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T07:46:53.0541447Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T07:46:53.0542780Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T07:46:53.0543872Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T07:46:53.0545002Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T07:46:53.0546102Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T07:46:53.0547289Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T07:46:53.0548508Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T07:46:53.0549611Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T07:46:53.0551446Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T07:46:53.0552672Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T07:46:53.0553320Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T07:46:53.0554757Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T07:46:53.0555943Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T07:46:53.0556732Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T07:46:53.0557760Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T07:46:53.0558651Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T07:46:53.0559860Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T07:46:53.0561013Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T07:46:53.0562167Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T07:46:53.0562935Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T07:46:53.0563833Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T07:46:53.0564941Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T07:46:53.0565974Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T07:46:53.0567120Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T07:46:53.0568057Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T07:46:53.0569027Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T07:46:53.0570111Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T07:46:53.0571579Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T07:46:53.0572418Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T07:46:53.0573537Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T07:46:53.0574383Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T07:46:53.0575909Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T07:46:53.0576637Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T07:46:53.0577864Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T07:46:53.0578860Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T07:46:53.0580473Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T07:46:53.0581155Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T07:46:53.0582192Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T07:46:53.0583126Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T07:46:53.0583967Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T07:46:53.0584821Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T07:46:53.0585984Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T07:46:53.0587094Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T07:46:53.0588227Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T07:46:53.0589372Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T07:46:53.0590525Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T07:46:53.0592071Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T07:46:53.0592484Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T07:46:53.0593449Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T07:46:53.0594569Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T07:46:53.0595653Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T07:46:53.0596967Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T07:46:53.0597747Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T07:46:53.0598915Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T07:46:53.0600181Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T07:46:53.0601581Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T07:46:53.0602397Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T07:46:53.0603286Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T07:46:53.0604205Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T07:46:53.0605492Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T07:46:53.0606455Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T07:46:53.0607695Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T07:46:53.0608804Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T07:46:53.0609649Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T07:46:53.0611267Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T07:46:53.0612098Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T07:46:53.0613217Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T07:46:53.0614321Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T07:46:53.0615437Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T07:46:53.0616270Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T07:46:53.0617118Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T07:46:53.0618803Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T07:46:53.0620175Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T07:46:53.0622001Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T07:46:53.0623080Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T07:46:53.0624352Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T07:46:53.0625479Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T07:46:53.0626256Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T07:46:53.0627431Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T07:46:53.0628572Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T07:46:53.0629432Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T07:46:53.0631106Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T07:46:53.0632359Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T07:46:53.0633245Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T07:46:53.0634460Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T07:46:53.0635597Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T07:46:53.0636367Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T07:46:53.0637560Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T07:46:53.0638438Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T07:46:53.0639376Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T07:46:53.0640980Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T07:46:53.0642412Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T07:46:53.0643551Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T07:46:53.0644799Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T07:46:53.0646013Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T07:46:53.0646792Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T07:46:53.0647643Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T07:46:53.0648876Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T07:46:53.0649853Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T07:46:53.0651631Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T07:46:53.0652794Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T07:46:53.0653577Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T07:46:53.0654866Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T07:46:53.0656190Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T07:46:53.0657533Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T07:46:53.0658307Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T07:46:53.0659483Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T07:46:53.0660624Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T07:46:53.0661955Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T07:46:53.0663330Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T07:46:53.0664521Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T07:46:53.0665239Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T07:46:53.0666454Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T07:46:53.0667929Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T07:46:53.0668440Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T07:46:53.0669670Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T07:46:53.0671606Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T07:46:53.0672332Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T07:46:53.0673642Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T07:46:53.0674817Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T07:46:53.0676039Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T07:46:53.0677097Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T07:46:53.0677943Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T07:46:53.0679222Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T07:46:53.0680892Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T07:46:53.0681798Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T07:46:53.0682968Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T07:46:53.0684140Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T07:46:53.0685162Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T07:46:53.0686541Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T07:46:53.0687685Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T07:46:53.0688835Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T07:46:53.0689708Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T07:46:53.0691347Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T07:46:53.0692514Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T07:46:53.0693325Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T07:46:53.0694562Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T07:46:53.0695411Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T07:46:53.0697184Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T07:46:53.0698223Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T07:46:53.0699558Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T07:46:53.0701070Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T07:46:53.0702302Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T07:46:53.0703739Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T07:46:53.0704580Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T07:46:53.0705839Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T07:46:53.0707119Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T07:46:53.0708157Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T07:46:53.0709421Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T07:46:53.0711664Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T07:46:53.0712087Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T07:46:53.0713040Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T07:46:53.0714273Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T07:46:53.0715522Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T07:46:53.0716743Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T07:46:53.0717942Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T07:46:53.0718867Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T07:46:53.0720198Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T07:46:53.0722178Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T07:46:53.0723171Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T07:46:53.0724348Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T07:46:53.0725469Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T07:46:53.0726658Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T07:46:53.0727539Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T07:46:53.0728427Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T07:46:53.0729847Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T07:46:53.0732015Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T07:46:53.0732395Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T07:46:53.0733366Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T07:46:53.0734360Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T07:46:53.0735672Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T07:46:53.0736622Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T07:46:53.0737740Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T07:46:53.0738754Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T07:46:53.0740120Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T07:46:53.0741593Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T07:46:53.0743051Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T07:46:53.0743958Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T07:46:53.0745294Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T07:46:53.0746286Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T07:46:53.0747532Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T07:46:53.0748830Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T07:46:53.0749648Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T07:46:53.0751270Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T07:46:53.0752423Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T07:46:53.0753322Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T07:46:53.0754349Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T07:46:53.0755590Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T07:46:53.0756795Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T07:46:53.0758822Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T07:46:53.0759787Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T07:46:53.0761450Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T07:46:53.0762570Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T07:46:53.0763796Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T07:46:53.0764890Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T07:46:53.0766146Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T07:46:53.0767536Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T07:46:53.0768471Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T07:46:53.0769809Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T07:46:53.0771188Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T07:46:53.0772180Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T07:46:53.0773518Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T07:46:53.0774697Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T07:46:53.0775862Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T07:46:53.0777034Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T07:46:53.0778269Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T07:46:53.0779113Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T07:46:53.0780503Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T07:46:53.0781801Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T07:46:53.0783066Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T07:46:53.0784168Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T07:46:53.0785524Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T07:46:53.0786510Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T07:46:53.0787759Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T07:46:53.0789078Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T07:46:53.0789864Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T07:46:53.0791441Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T07:46:53.0792156Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T07:46:53.0793533Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T07:46:53.0794827Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T07:46:53.0796025Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T07:46:53.0797157Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T07:46:53.0798488Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T07:46:53.0799809Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T07:46:53.0801365Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T07:46:53.0802544Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T07:46:53.0803723Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T07:46:53.0805179Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T07:46:53.0806358Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T07:46:53.0807258Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T07:46:53.0808607Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T07:46:53.0809798Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T07:46:53.0811290Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T07:46:53.0812461Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T07:46:53.0813662Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T07:46:53.0814956Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T07:46:53.0816053Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T07:46:53.0817533Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T07:46:53.0818186Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T07:46:53.0819505Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T07:46:53.0821068Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T07:46:53.0822265Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T07:46:53.0823642Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T07:46:53.0824554Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T07:46:53.0825489Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T07:46:53.0826816Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T07:46:53.0827977Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T07:46:53.0829258Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T07:46:53.0830816Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T07:46:53.0832118Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T07:46:53.0833464Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T07:46:53.0834573Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T07:46:53.0835644Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T07:46:53.0836952Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T07:46:53.0838179Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T07:46:53.0839500Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T07:46:53.1675565Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:46:53.1705306Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:53.1710167Z ##[endgroup] 2025-09-07T07:46:53.1710727Z ##[group]Determining the checkout info 2025-09-07T07:46:53.1711243Z ##[endgroup] 2025-09-07T07:46:53.1714967Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:46:53.1765924Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:46:53.1799266Z ##[group]Checking out the ref 2025-09-07T07:46:53.1802588Z [command]/usr/bin/git checkout --progress 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You can look around, make experimental 2025-09-07T07:46:54.5233933Z changes and commit them, and you can discard any commits you make in this 2025-09-07T07:46:54.5234428Z state without impacting any branches by switching back to a branch. 2025-09-07T07:46:54.5234713Z 2025-09-07T07:46:54.5234892Z If you want to create a new branch to retain commits you create, you may 2025-09-07T07:46:54.5235324Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T07:46:54.5235576Z 2025-09-07T07:46:54.5235675Z git switch -c 2025-09-07T07:46:54.5235850Z 2025-09-07T07:46:54.5235944Z Or undo this operation with: 2025-09-07T07:46:54.5236104Z 2025-09-07T07:46:54.5236184Z git switch - 2025-09-07T07:46:54.5236316Z 2025-09-07T07:46:54.5236526Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T07:46:54.5236826Z 2025-09-07T07:46:54.5236984Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:46:54.5352458Z ##[endgroup] 2025-09-07T07:46:54.5352834Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:46:54.5358400Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:46:54.5402353Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:46:54.5432893Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:46:54.5464155Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:46:54.5495054Z ##[endgroup] 2025-09-07T07:46:54.5495433Z ##[group]Fetching submodules 2025-09-07T07:46:54.5497900Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:46:54.5777657Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:46:54.6047423Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T07:46:54.6058007Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T07:46:54.6068943Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T07:46:54.6079670Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T07:46:54.6091200Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T07:46:54.6102635Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T07:46:54.6113857Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T07:46:54.6124921Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T07:46:54.6135678Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T07:46:54.6146777Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T07:46:54.6157574Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T07:46:54.6169145Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T07:46:54.6180479Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T07:46:54.6192047Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T07:46:54.6203064Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T07:46:54.6215187Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T07:46:54.6226120Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T07:46:54.6236898Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T07:46:54.6248022Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:46:54.6258986Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T07:46:54.6270592Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T07:46:54.6281710Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T07:46:54.6293215Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T07:46:54.6305086Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T07:46:54.6316864Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T07:46:54.6328492Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T07:46:54.6340497Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T07:46:54.6352343Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T07:46:54.6364591Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T07:46:54.6376502Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T07:46:54.6388455Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T07:46:54.6399997Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T07:46:54.6411819Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T07:46:54.6423345Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T07:46:54.6435001Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T07:46:54.6446546Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T07:46:54.6458737Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T07:46:54.6495352Z Cloning into '/home/alice/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T07:46:55.3075839Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T07:46:55.6185549Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T07:46:55.9113248Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T07:46:56.3383729Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T07:46:56.8367900Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T07:46:57.9546333Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T07:47:07.1604642Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T07:47:11.6201897Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T07:47:12.8363687Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T07:47:16.6223902Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T07:47:17.2333208Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T07:47:17.9718869Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T07:47:19.1013355Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T07:47:21.0085924Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T07:47:23.5326939Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T07:47:24.5763180Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T07:47:26.2496747Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T07:47:27.9571656Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T07:47:28.8075502Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T07:47:30.0624351Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T07:47:31.3297141Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T07:47:32.1976126Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T07:47:32.8983657Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T07:47:34.0983032Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T07:47:34.6826533Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T07:47:35.5816531Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T07:47:41.3750751Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T07:47:45.7054711Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T07:47:50.6138447Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T07:47:50.9554876Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T07:47:58.3004985Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T07:47:59.9344494Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T07:48:01.7769051Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T07:48:02.7070891Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T07:48:03.1499741Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T07:48:04.0019501Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T07:48:04.5411941Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:48:04.5547141Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:48:04.5654794Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:48:04.5916086Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:48:04.6783901Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:48:04.7331659Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:48:05.5001571Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:48:05.6558013Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:48:05.6591159Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:48:05.6623835Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T07:48:08.9483032Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:48:08.9729014Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:48:09.3395097Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:48:09.3890073Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:48:09.5023772Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:48:09.5467521Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:48:10.1789646Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:48:10.3532679Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:48:10.3559650Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T07:48:10.3567532Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:48:10.3574839Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:48:10.3582778Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T07:48:10.3591520Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T07:48:10.3599970Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:48:10.3608711Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T07:48:10.3642464Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T07:48:11.6112554Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T07:48:12.6353311Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T07:48:13.3231618Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T07:48:15.0195302Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T07:48:15.9237207Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T07:48:16.3669031Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T07:48:24.6605053Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:48:25.4941670Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:48:26.0449050Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:48:26.7380828Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:48:26.7839324Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:26.7965456Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:48:26.9022964Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:48:26.9751618Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:48:26.9780019Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:48:26.9790516Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:48:26.9821590Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T07:48:29.9494152Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T07:48:32.6918012Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:48:34.0106017Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:48:34.1549046Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:48:34.1874108Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:48:34.2267460Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:48:34.2526756Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:48:34.2966341Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:34.3104232Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:48:34.3130712Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T07:48:34.3161171Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T07:48:47.6465548Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:48:47.7803633Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:48:47.9202250Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:48:48.0698499Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:48:48.1587604Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:48:48.2250526Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:48:48.2283670Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T07:48:50.7672461Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T07:48:52.3578308Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T07:48:54.2827734Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:48:54.2914865Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:48:54.3208796Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:48:54.3401779Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:48:54.3719042Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:48:54.4579847Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:48:54.5498054Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:48:54.5825513Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:48:54.5912489Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:48:54.5945130Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T07:48:56.6257720Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T07:48:57.4293024Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T07:48:59.0216624Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T07:48:59.7001493Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T07:49:00.5709888Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T07:49:01.9236568Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T07:49:10.1696715Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T07:49:13.0964000Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:49:13.2402619Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:49:13.3341182Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:49:13.5234946Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:49:13.8589209Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:49:13.8617430Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T07:49:15.3036677Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:49:15.3558576Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:49:15.4082010Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:49:15.5166306Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:49:15.5447461Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:49:15.5858713Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:49:15.6534705Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:49:15.7136526Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:49:15.7573941Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:49:15.8780173Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:49:16.8782985Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:49:16.9014256Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-09-07T07:49:16.9050732Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-09-07T07:49:18.8160987Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:49:19.3139054Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:49:19.3303240Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:49:19.3525202Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:49:19.3692125Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:49:19.3856091Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:49:19.4068497Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:49:19.6276646Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:49:19.6304106Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:49:19.6464996Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:49:19.6497478Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T07:49:20.4940033Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T07:49:22.0689663Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T07:49:22.8412530Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T07:49:33.2342741Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T07:49:35.7019570Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T07:49:36.6119242Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T07:49:37.6596130Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T07:49:43.8560092Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:49:43.8965775Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:49:43.9139214Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:49:44.0174985Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:49:44.0328188Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:49:44.0484707Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:49:44.0654889Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:49:44.0683261Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:49:44.0695551Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:49:44.0725796Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'... 2025-09-07T07:49:46.8746588Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'... 2025-09-07T07:49:48.6003732Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:49:48.7135361Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:49:49.4864747Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:49:49.5299592Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T07:49:49.9124052Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T07:49:49.9186850Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:49:49.9247118Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/protobuf/third_party/googletest' 2025-09-07T07:49:49.9281367Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/protobuf/third_party/benchmark'... 2025-09-07T07:49:50.7792849Z Cloning into '/home/alice/_work/pytorch/pytorch/third_party/protobuf/third_party/googletest'... 2025-09-07T07:49:52.7675853Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T07:49:52.8442192Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T07:49:52.8572686Z Submodule 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file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:49:58.4906570Z Entering 'third_party/XNNPACK' 2025-09-07T07:49:58.4947132Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:49:58.4983147Z Entering 'third_party/aiter' 2025-09-07T07:49:58.5024521Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:49:58.5046768Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:49:58.5089591Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:49:58.5119220Z Entering 'third_party/benchmark' 2025-09-07T07:49:58.5161423Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:49:58.5191383Z Entering 'third_party/composable_kernel' 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file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:49:58.7374270Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:49:58.7414956Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:49:58.7434719Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:49:58.7475468Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:49:58.7498308Z Entering 'third_party/kleidiai' 2025-09-07T07:49:58.7539802Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:49:58.7561525Z Entering 'third_party/mimalloc' 2025-09-07T07:49:58.7602884Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:49:58.7624347Z Entering 'third_party/nlohmann' 2025-09-07T07:49:58.7664947Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:49:58.7687322Z Entering 'third_party/onnx' 2025-09-07T07:49:58.7728682Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:49:58.7763745Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:49:58.7806016Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:49:58.7832279Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:49:58.7873259Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:49:58.7894272Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 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2025-09-07T07:49:59.9117982Z 7e1e1fe3858c63c251c637ae41a20de425dde96f android/libs/fbjni (v0.1.0-12-g7e1e1fe) 2025-09-07T07:49:59.9205194Z 4dfe081cf6bcd15db339cf2680b9281b8451eeb3 third_party/FP16 (4dfe081) 2025-09-07T07:49:59.9293252Z b408327ac2a15ec3e43352421954f5b1967701d1 third_party/FXdiv (b408327) 2025-09-07T07:49:59.9393008Z c07e3a0400713d546e0dea2d5466dd22ea389c73 third_party/NNPACK (c07e3a0) 2025-09-07T07:49:59.9446940Z 2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07 third_party/NVTX (v3.1.0-263-g2942f16) 2025-09-07T07:49:59.9530084Z 1d8f600fd424278486eade7ed3e877c99f0846b1 third_party/VulkanMemoryAllocator (v2.1.0-982-g1d8f600) 2025-09-07T07:49:59.9999386Z 51a0103656eff6fc9bfd39a4597923c4b542c883 third_party/XNNPACK (remotes/origin/ds/ndk-1243-g51a0103656) 2025-09-07T07:50:00.0039997Z 01aae101b9e5e94d6c16a9514c9fb8df99c93150 third_party/aiter (v0.1.1-92-g01aae101) 2025-09-07T07:50:00.0069280Z 299e5928955cc62af9968370293b916f5130916f third_party/benchmark (v1.9.3) 2025-09-07T07:50:00.0149588Z 7fe50dc3da2069d6645d9deb8c017a876472a977 third_party/composable_kernel (rocm-6.4.3-459-g7fe50dc3d) 2025-09-07T07:50:00.0278705Z 89c932f313c6437c38f2982869beacc89c2f2246 third_party/cpp-httplib (v0.26.0) 2025-09-07T07:50:00.0404563Z 5e3d2445e6a84d9599bee2bf78edbb4d80865e1d third_party/cpuinfo (5e3d244) 2025-09-07T07:50:00.0445924Z f937055efc6d414d11f4c6577e3977fe74f35fb6 third_party/cudnn_frontend (v0.5-52-gf937055) 2025-09-07T07:50:00.0543838Z e51efbfe18fe4f4cbb66ab814c55bf4aa0185491 third_party/cutlass (v4.1.0) 2025-09-07T07:50:00.0603388Z 4b39c551efe15e6bbade20565b0ceb2d8ce3352d third_party/fbgemm (v1.3.0-rc1-342-g4b39c551) 2025-09-07T07:50:00.0692329Z 979702c87a8713a8e0a5e9fee122b90d2ef13be5 third_party/flash-attention (v2.7.4) 2025-09-07T07:50:00.0721718Z a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757 third_party/flatbuffers (v24.12.23) 2025-09-07T07:50:00.1086833Z 40626af88bd7df9a5fb80be7b25ac85b122d6c21 third_party/fmt (11.2.0) 2025-09-07T07:50:00.1208433Z 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third_party/sleef (3.8) 2025-09-07T07:50:00.3143758Z af0118d13e52f5a08841464a768e01a0bf3e3075 third_party/tensorpipe (heads/main) 2025-09-07T07:50:00.3157898Z ##[group]Cleaning the repository 2025-09-07T07:50:00.3162313Z [command]/usr/bin/git clean -ffdx 2025-09-07T07:50:00.3493956Z [command]/usr/bin/git reset --hard HEAD 2025-09-07T07:50:00.8662134Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:50:00.8692806Z ##[endgroup] 2025-09-07T07:50:00.8694819Z ##[group]Disabling automatic garbage collection 2025-09-07T07:50:00.8699231Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:50:00.8733699Z ##[endgroup] 2025-09-07T07:50:00.8734223Z ##[group]Setting up auth 2025-09-07T07:50:00.8739037Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:50:00.8771157Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 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'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:01.6141142Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6175772Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:01.6201925Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6235048Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:01.6262811Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6301129Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:01.6328097Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6362897Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:01.6388979Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6424024Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:01.6450715Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6486373Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:01.6512895Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6550678Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:01.6577032Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6611480Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:01.6637482Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6675951Z Entering 'third_party/kleidiai' 2025-09-07T07:50:01.6706427Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6741900Z Entering 'third_party/mimalloc' 2025-09-07T07:50:01.6769062Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6805666Z Entering 'third_party/nlohmann' 2025-09-07T07:50:01.6833853Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6871773Z Entering 'third_party/onnx' 2025-09-07T07:50:01.6899791Z http.https://github.com/.extraheader 2025-09-07T07:50:01.6952889Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:01.6981830Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7022216Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:01.7050554Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7086654Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:01.7113748Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7148323Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:01.7174735Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7208984Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:01.7235349Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7270015Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:01.7296187Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7331612Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:01.7357630Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7391488Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:01.7417460Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7452185Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:01.7478160Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7511125Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:01.7538985Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7575820Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:01.7601885Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7639645Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:01.7666027Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7719541Z Entering 'third_party/pocketfft' 2025-09-07T07:50:01.7747964Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7782621Z Entering 'third_party/protobuf' 2025-09-07T07:50:01.7810015Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7850413Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:01.7878016Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7913843Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:01.7940949Z http.https://github.com/.extraheader 2025-09-07T07:50:01.7980053Z Entering 'third_party/psimd' 2025-09-07T07:50:01.8008733Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8043930Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:01.8071280Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8106018Z Entering 'third_party/pybind11' 2025-09-07T07:50:01.8133250Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8168646Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:01.8196826Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8232031Z Entering 'third_party/sleef' 2025-09-07T07:50:01.8259617Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8294955Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:01.8323031Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8358410Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:01.8385959Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8421096Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:01.8447157Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8481150Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:01.8507921Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8541786Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:01.8567725Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8600513Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:01.8628084Z http.https://github.com/.extraheader 2025-09-07T07:50:01.8691005Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:01.8728692Z ##[endgroup] 2025-09-07T07:50:01.8729037Z ##[group]Fetching the repository 2025-09-07T07:50:01.8735831Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:50:02.4797881Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:50:02.4827472Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:02.4833108Z ##[endgroup] 2025-09-07T07:50:02.4833521Z ##[group]Determining the checkout info 2025-09-07T07:50:02.4834305Z ##[endgroup] 2025-09-07T07:50:02.4837794Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:50:02.5027070Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:50:02.5059405Z ##[group]Checking out the ref 2025-09-07T07:50:02.5063879Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:02.5399268Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:50:02.5411757Z ##[endgroup] 2025-09-07T07:50:02.5412159Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:50:02.5415786Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:02.5458426Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:50:02.5488642Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:50:02.5519993Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:50:02.5549041Z ##[endgroup] 2025-09-07T07:50:02.5549492Z ##[group]Fetching submodules 2025-09-07T07:50:02.5552498Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:50:02.5852438Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T07:50:02.5878622Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T07:50:02.5903443Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T07:50:02.5928949Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T07:50:02.5953549Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T07:50:02.5978586Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:02.6003856Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T07:50:02.6043340Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T07:50:02.6067763Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:02.6101528Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T07:50:02.6126542Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T07:50:02.6158587Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T07:50:02.6183542Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T07:50:02.6209004Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T07:50:02.6234623Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T07:50:02.6268727Z Synchronizing submodule url for 'third_party/fbgemm' 2025-09-07T07:50:02.6294289Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:02.6320071Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:02.6350138Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:02.6374179Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:02.6404950Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:02.6427527Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:02.6449922Z Synchronizing submodule url for 'third_party/fbgemm/external/json' 2025-09-07T07:50:02.6477728Z Synchronizing submodule url for 'third_party/flash-attention' 2025-09-07T07:50:02.6502009Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:02.6532374Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:02.6565795Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T07:50:02.6594263Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T07:50:02.6619690Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:02.6645155Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T07:50:02.6671126Z Synchronizing submodule url for 'third_party/googletest' 2025-09-07T07:50:02.6696071Z Synchronizing submodule url for 'third_party/ideep' 2025-09-07T07:50:02.6717842Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:02.6752721Z Synchronizing submodule url for 'third_party/ittapi' 2025-09-07T07:50:02.6777835Z Synchronizing submodule url for 'third_party/kineto' 2025-09-07T07:50:02.6802445Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:02.6826848Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:02.6853259Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:02.6877413Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:02.6901448Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:02.6923353Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:02.6951282Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:02.6975781Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:02.6999441Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:02.7024366Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:02.7050821Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:02.7073635Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:02.7099883Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T07:50:02.7125432Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T07:50:02.7150065Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T07:50:02.7176461Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T07:50:02.7214425Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:02.7244831Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T07:50:02.7269445Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:02.7293479Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:02.7316414Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:02.7339299Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:02.7364089Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:02.7387076Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:02.7409433Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:02.7431082Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:02.7457131Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:02.7483688Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:02.7527635Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T07:50:02.7552272Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T07:50:02.7578516Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:02.7602677Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:02.7629537Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T07:50:02.7655244Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T07:50:02.7679387Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T07:50:02.7704624Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T07:50:02.7728572Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T07:50:02.7753777Z Synchronizing submodule url for 'third_party/tensorpipe' 2025-09-07T07:50:02.7776453Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:02.7800079Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:02.7822512Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:02.7845695Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:02.7866992Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:02.7909824Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:50:02.8313551Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:50:02.8441123Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:50:02.8542382Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:50:02.8765394Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:50:02.9580167Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:50:02.9928402Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:50:03.6674616Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:50:03.8695559Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:50:04.1504684Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:50:04.1712481Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:50:04.4909920Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:50:04.5463336Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:50:04.6667596Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:50:04.7122558Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:50:04.9453999Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:50:05.0743431Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:50:05.1319055Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:50:05.2865282Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:50:05.4069356Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:50:06.2457707Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:50:06.2833744Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:50:06.2974780Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:50:06.3976397Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:50:06.4736780Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:50:06.7985968Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:50:06.8176609Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:50:07.0298146Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:50:07.0586359Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:50:07.0972159Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:50:07.1191646Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:50:07.1541088Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:50:07.1682589Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:50:07.9449800Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:50:07.9666850Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:50:08.0516170Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:50:08.1918161Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:50:08.3068362Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:50:08.3231765Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:50:08.3539228Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:50:08.3679076Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:50:08.3782815Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:50:08.3951234Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:50:08.4291477Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:50:08.5353214Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:50:08.5515126Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:50:08.5800137Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:50:08.6146110Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:50:08.6588937Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:50:08.7093777Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:50:08.8218679Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:50:09.1013375Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:50:09.1339322Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:50:09.1986552Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:50:09.2161247Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:50:09.2498320Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:50:09.2628287Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:50:09.2884718Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:50:09.3036398Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:50:09.3180169Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:50:09.3327044Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:50:09.6359149Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4' 2025-09-07T07:50:09.6715593Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929' 2025-09-07T07:50:09.8712857Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50' 2025-09-07T07:50:09.8856888Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa' 2025-09-07T07:50:10.1279712Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a' 2025-09-07T07:50:10.1423467Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8' 2025-09-07T07:50:10.1827681Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081' 2025-09-07T07:50:10.1939358Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900' 2025-09-07T07:50:10.2090892Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8' 2025-09-07T07:50:10.2308667Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8' 2025-09-07T07:50:10.2736516Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67' 2025-09-07T07:50:10.3226698Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68' 2025-09-07T07:50:10.3453621Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075' 2025-09-07T07:50:10.3798477Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e' 2025-09-07T07:50:10.3952233Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281' 2025-09-07T07:50:10.4470531Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b' 2025-09-07T07:50:10.4717120Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef' 2025-09-07T07:50:10.4819223Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5' 2025-09-07T07:50:10.4869284Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0 2025-09-07T07:50:10.5136605Z Entering 'android/libs/fbjni' 2025-09-07T07:50:10.5182644Z Entering 'third_party/FP16' 2025-09-07T07:50:10.5226975Z Entering 'third_party/FXdiv' 2025-09-07T07:50:10.5270863Z Entering 'third_party/NNPACK' 2025-09-07T07:50:10.5314508Z Entering 'third_party/NVTX' 2025-09-07T07:50:10.5359920Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:10.5402666Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:10.5462123Z Entering 'third_party/aiter' 2025-09-07T07:50:10.5506248Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:10.5558120Z Entering 'third_party/benchmark' 2025-09-07T07:50:10.5602536Z Entering 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2025-09-07T07:50:10.7853197Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:10.7898465Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:10.7943014Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:10.8003576Z Entering 'third_party/pocketfft' 2025-09-07T07:50:10.8047936Z Entering 'third_party/protobuf' 2025-09-07T07:50:10.8094212Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:10.8135190Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:10.8180944Z Entering 'third_party/psimd' 2025-09-07T07:50:10.8224822Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:10.8269154Z Entering 'third_party/pybind11' 2025-09-07T07:50:10.8314231Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:10.8357744Z Entering 'third_party/sleef' 2025-09-07T07:50:10.8402181Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:10.8445096Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:10.8487350Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:10.8527430Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:10.8567228Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:10.8607849Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:10.8669799Z ##[endgroup] 2025-09-07T07:50:10.8670179Z ##[group]Persisting credentials for submodules 2025-09-07T07:50:10.8676738Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'url\.https\:\/\/github\.com\/\.insteadOf' && git config --local --unset-all 'url.https://github.com/.insteadOf' || :" 2025-09-07T07:50:10.8940172Z Entering 'android/libs/fbjni' 2025-09-07T07:50:10.8967158Z url.https://github.com/.insteadof 2025-09-07T07:50:10.8967458Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9004104Z Entering 'third_party/FP16' 2025-09-07T07:50:10.9032014Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9032354Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9067181Z Entering 'third_party/FXdiv' 2025-09-07T07:50:10.9094521Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9094806Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9129107Z Entering 'third_party/NNPACK' 2025-09-07T07:50:10.9156505Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9156798Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9191321Z Entering 'third_party/NVTX' 2025-09-07T07:50:10.9218554Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9218837Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9254088Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:10.9281176Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9281467Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9315927Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:10.9343783Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9344169Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9392307Z Entering 'third_party/aiter' 2025-09-07T07:50:10.9419953Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9420409Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9455271Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:10.9482016Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9482318Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9527437Z Entering 'third_party/benchmark' 2025-09-07T07:50:10.9556981Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9557264Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9592418Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:10.9619876Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9620342Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9661797Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:10.9689339Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9724953Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9725252Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:10.9752703Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9752987Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9787574Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:10.9815553Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9815852Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9850934Z Entering 'third_party/cutlass' 2025-09-07T07:50:10.9878430Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9878703Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9921871Z Entering 'third_party/fbgemm' 2025-09-07T07:50:10.9949560Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9949844Z url.https://github.com/.insteadof 2025-09-07T07:50:10.9987184Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:11.0013417Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0013712Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0048647Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:11.0076137Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0076550Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0118091Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:11.0144229Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0144543Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0179086Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:11.0205334Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0205633Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0247899Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:11.0274169Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0274464Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0308289Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:11.0336029Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0336306Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0373218Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:11.0399976Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0400397Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0438993Z Entering 'third_party/flash-attention' 2025-09-07T07:50:11.0468401Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0468679Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0503967Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:11.0531493Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0531770Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0572828Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:11.0599050Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0599604Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0644280Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:11.0673812Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0674125Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0711473Z Entering 'third_party/fmt' 2025-09-07T07:50:11.0738310Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0740950Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0773170Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:11.0803068Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0803376Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0838553Z Entering 'third_party/gloo' 2025-09-07T07:50:11.0865685Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0865977Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0900942Z Entering 'third_party/googletest' 2025-09-07T07:50:11.0928723Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0929052Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0964073Z Entering 'third_party/ideep' 2025-09-07T07:50:11.0993978Z url.https://github.com/.insteadof 2025-09-07T07:50:11.0994253Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1027324Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:11.1053561Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1053862Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1097721Z Entering 'third_party/ittapi' 2025-09-07T07:50:11.1125565Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1125841Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1160798Z Entering 'third_party/kineto' 2025-09-07T07:50:11.1188219Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1188510Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1222591Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:11.1249537Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1249827Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1284526Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:11.1314227Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1314520Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1350760Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:11.1377670Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1377982Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1413428Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:11.1439933Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1440422Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1474923Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:11.1508715Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1509071Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1534979Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:11.1563198Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1563497Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1602520Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:11.1629410Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1629704Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1664243Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:11.1690990Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1726444Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1726824Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:11.1753572Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1753866Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1789602Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:11.1816383Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1816654Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1854617Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:11.1883993Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1884295Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1918672Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:11.1947092Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1947403Z url.https://github.com/.insteadof 2025-09-07T07:50:11.1985469Z Entering 'third_party/kleidiai' 2025-09-07T07:50:11.2013540Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2013824Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2049159Z Entering 'third_party/mimalloc' 2025-09-07T07:50:11.2076580Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2076858Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2111944Z Entering 'third_party/nlohmann' 2025-09-07T07:50:11.2139656Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2139938Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2177977Z Entering 'third_party/onnx' 2025-09-07T07:50:11.2205293Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2205600Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2254415Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:11.2283073Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2283365Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2322729Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:11.2351282Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2351570Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2387129Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:11.2413359Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2413650Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2451838Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:11.2478304Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2478592Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2513930Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:11.2540775Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2541074Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2576094Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:11.2604658Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2604929Z url.https://github.com/.insteadof 2025-09-07T07:50:11.2989575Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:11.3016632Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3016926Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3052384Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:11.3081103Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3081392Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3116120Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:11.3144705Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3144998Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3178497Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:11.3206874Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3207141Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3243515Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:11.3270647Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3270930Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3309134Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:11.3335942Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3336223Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3391191Z Entering 'third_party/pocketfft' 2025-09-07T07:50:11.3419465Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3419754Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3455216Z Entering 'third_party/protobuf' 2025-09-07T07:50:11.3483344Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3483621Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3520868Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:11.3547631Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3547927Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3583448Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:11.3610346Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3610653Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3648850Z Entering 'third_party/psimd' 2025-09-07T07:50:11.3676570Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3676860Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3710693Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:11.3738465Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3738708Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3774003Z Entering 'third_party/pybind11' 2025-09-07T07:50:11.3800814Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3801075Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3835639Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:11.3863597Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3863886Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3898463Z Entering 'third_party/sleef' 2025-09-07T07:50:11.3926230Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3926536Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3960691Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:11.3989395Z url.https://github.com/.insteadof 2025-09-07T07:50:11.3989666Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4024079Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:11.4051268Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4051556Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4086582Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:11.4115133Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4115446Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4150078Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:11.4176937Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4177244Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4212511Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:11.4240854Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4241150Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4274589Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:11.4302095Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4302365Z url.https://github.com/.insteadof 2025-09-07T07:50:11.4359889Z [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" 2025-09-07T07:50:11.4625535Z Entering 'android/libs/fbjni' 2025-09-07T07:50:11.4666531Z file:/home/alice/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:50:11.4687833Z Entering 'third_party/FP16' 2025-09-07T07:50:11.4729096Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:50:11.4751988Z Entering 'third_party/FXdiv' 2025-09-07T07:50:11.4793361Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:50:11.4814417Z Entering 'third_party/NNPACK' 2025-09-07T07:50:11.4856170Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:50:11.4878074Z Entering 'third_party/NVTX' 2025-09-07T07:50:11.4920413Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:50:11.4942895Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:11.4983352Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:50:11.5005799Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:11.5046890Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:50:11.5082091Z Entering 'third_party/aiter' 2025-09-07T07:50:11.5123615Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:50:11.5145205Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:11.5185158Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:50:11.5216721Z Entering 'third_party/benchmark' 2025-09-07T07:50:11.5259353Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:11.5281283Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:11.5322747Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:50:11.5352523Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:11.5393569Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:50:11.5415425Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:11.5457237Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:50:11.5479424Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:11.5520651Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:50:11.5541591Z Entering 'third_party/cutlass' 2025-09-07T07:50:11.5582897Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T07:50:11.5612756Z Entering 'third_party/fbgemm' 2025-09-07T07:50:11.5655103Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:50:11.5678062Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:11.5718767Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:50:11.5740546Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:11.5782211Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:50:11.5808697Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:11.5850410Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:50:11.5871561Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:11.5911934Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:50:11.5941077Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:11.5981589Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:50:11.6002008Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:11.6042563Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:50:11.6062614Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:11.6103913Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:50:11.6129308Z Entering 'third_party/flash-attention' 2025-09-07T07:50:11.6171735Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:50:11.6192458Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:11.6234002Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:50:11.6260420Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:11.6300391Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:50:11.6330453Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:11.6372428Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:50:11.6396003Z Entering 'third_party/fmt' 2025-09-07T07:50:11.6436756Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:11.6457968Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:11.6498755Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:50:11.6520120Z Entering 'third_party/gloo' 2025-09-07T07:50:11.6560800Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:50:11.6582159Z Entering 'third_party/googletest' 2025-09-07T07:50:11.6623300Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.6644686Z Entering 'third_party/ideep' 2025-09-07T07:50:11.6685658Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:50:11.6704943Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:11.6745953Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:50:11.6774693Z Entering 'third_party/ittapi' 2025-09-07T07:50:11.6816245Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:50:11.6837540Z Entering 'third_party/kineto' 2025-09-07T07:50:11.6879898Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:50:11.6900525Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:11.6943067Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:50:11.6962689Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:11.7004978Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:50:11.7029335Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:11.7077093Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:50:11.7098049Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:11.7138906Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:11.7159709Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:11.7201973Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:50:11.7221260Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:11.7263993Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:50:11.7287486Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:11.7329652Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:50:11.7350427Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:11.7393511Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.7413904Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:11.7455643Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:50:11.7478021Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:11.7519641Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:50:11.7543679Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:11.7585103Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:50:11.7605901Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:11.7646206Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.7672111Z Entering 'third_party/kleidiai' 2025-09-07T07:50:11.7715728Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:50:11.7738167Z Entering 'third_party/mimalloc' 2025-09-07T07:50:11.7779485Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:50:11.7802062Z Entering 'third_party/nlohmann' 2025-09-07T07:50:11.7842539Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:50:11.7865244Z Entering 'third_party/onnx' 2025-09-07T07:50:11.7906119Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:50:11.7942109Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:11.7983957Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:11.8009312Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:11.8051553Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:50:11.8072936Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:11.8113915Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:11.8134256Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:11.8174251Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.8194933Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:11.8234358Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T07:50:11.8254418Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:11.8294108Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T07:50:11.8316816Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:11.8358531Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T07:50:11.8378537Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:11.8418410Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T07:50:11.8438586Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:11.8478740Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T07:50:11.8497262Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:11.8538237Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T07:50:11.8560426Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:11.8600789Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config remote.origin.url 2025-09-07T07:50:11.8623595Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:11.8663622Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config remote.origin.url 2025-09-07T07:50:11.8703641Z Entering 'third_party/pocketfft' 2025-09-07T07:50:11.8744088Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/pocketfft/config remote.origin.url 2025-09-07T07:50:11.8765211Z Entering 'third_party/protobuf' 2025-09-07T07:50:11.8805706Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/protobuf/config remote.origin.url 2025-09-07T07:50:11.8828684Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:11.8869525Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:11.8889736Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:11.8929577Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.8953527Z Entering 'third_party/psimd' 2025-09-07T07:50:11.8993975Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/psimd/config remote.origin.url 2025-09-07T07:50:11.9015091Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:11.9057443Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/pthreadpool/config remote.origin.url 2025-09-07T07:50:11.9079489Z Entering 'third_party/pybind11' 2025-09-07T07:50:11.9121343Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:11.9143531Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:11.9185070Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/python-peachpy/config remote.origin.url 2025-09-07T07:50:11.9207124Z Entering 'third_party/sleef' 2025-09-07T07:50:11.9249402Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/sleef/config remote.origin.url 2025-09-07T07:50:11.9270918Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:11.9314101Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/config remote.origin.url 2025-09-07T07:50:11.9334819Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:11.9376674Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:11.9397064Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:11.9437152Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libnop/config remote.origin.url 2025-09-07T07:50:11.9457054Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:11.9497017Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libuv/config remote.origin.url 2025-09-07T07:50:11.9517508Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:11.9563783Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:11.9584892Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:11.9628820Z file:/home/alice/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config remote.origin.url 2025-09-07T07:50:11.9914931Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:' 2025-09-07T07:50:12.0184257Z Entering 'android/libs/fbjni' 2025-09-07T07:50:12.0230483Z Entering 'third_party/FP16' 2025-09-07T07:50:12.0275025Z Entering 'third_party/FXdiv' 2025-09-07T07:50:12.0319333Z Entering 'third_party/NNPACK' 2025-09-07T07:50:12.0364424Z Entering 'third_party/NVTX' 2025-09-07T07:50:12.0409335Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:12.0454522Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:12.0513834Z Entering 'third_party/aiter' 2025-09-07T07:50:12.0559419Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:12.0612342Z Entering 'third_party/benchmark' 2025-09-07T07:50:12.0658888Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:12.0711670Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:12.0756323Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:12.0800847Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:12.0845647Z Entering 'third_party/cutlass' 2025-09-07T07:50:12.0898317Z Entering 'third_party/fbgemm' 2025-09-07T07:50:12.0944404Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:12.0987339Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:12.1036982Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:12.1078965Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:12.1129298Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:12.1171063Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:12.1212682Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:12.1258018Z Entering 'third_party/flash-attention' 2025-09-07T07:50:12.1304313Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:12.1351433Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:12.1404023Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:12.1452387Z Entering 'third_party/fmt' 2025-09-07T07:50:12.1497450Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:12.1542240Z Entering 'third_party/gloo' 2025-09-07T07:50:12.1587446Z Entering 'third_party/googletest' 2025-09-07T07:50:12.1631906Z Entering 'third_party/ideep' 2025-09-07T07:50:12.1675263Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:12.1725111Z Entering 'third_party/ittapi' 2025-09-07T07:50:12.1770486Z Entering 'third_party/kineto' 2025-09-07T07:50:12.1814274Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:12.1855302Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:12.1900197Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:12.1943120Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:12.1984288Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:12.2024748Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:12.2069265Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:12.2110749Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:12.2152031Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:12.2193563Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:12.2237839Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:12.2279075Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:12.2322193Z Entering 'third_party/kleidiai' 2025-09-07T07:50:12.2366908Z Entering 'third_party/mimalloc' 2025-09-07T07:50:12.2411725Z Entering 'third_party/nlohmann' 2025-09-07T07:50:12.2456850Z Entering 'third_party/onnx' 2025-09-07T07:50:12.2516077Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:12.2563477Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:12.2608693Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:12.2650525Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:12.2691004Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:12.2731957Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:12.2773967Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:12.2814909Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:12.2855914Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:12.2896354Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:12.2939958Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:12.2984109Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:12.3044712Z Entering 'third_party/pocketfft' 2025-09-07T07:50:12.3089414Z Entering 'third_party/protobuf' 2025-09-07T07:50:12.3135580Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:12.3177893Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:12.3222535Z Entering 'third_party/psimd' 2025-09-07T07:50:12.3267665Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:12.3311667Z Entering 'third_party/pybind11' 2025-09-07T07:50:12.3356664Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:12.3400879Z Entering 'third_party/sleef' 2025-09-07T07:50:12.3444755Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:12.3488018Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:12.3529900Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:12.3571455Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:12.3619312Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:12.3660130Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:12.3729637Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T07:50:12.3989908Z Entering 'android/libs/fbjni' 2025-09-07T07:50:12.4030988Z Entering 'third_party/FP16' 2025-09-07T07:50:12.4090804Z Entering 'third_party/FXdiv' 2025-09-07T07:50:12.4147412Z Entering 'third_party/NNPACK' 2025-09-07T07:50:12.4205635Z Entering 'third_party/NVTX' 2025-09-07T07:50:12.4264641Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:12.4321290Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:12.4397824Z Entering 'third_party/aiter' 2025-09-07T07:50:12.4455580Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:12.4524531Z Entering 'third_party/benchmark' 2025-09-07T07:50:12.4581748Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:12.4649317Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:12.4706182Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:12.4756745Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:12.4801439Z Entering 'third_party/cutlass' 2025-09-07T07:50:12.4854435Z Entering 'third_party/fbgemm' 2025-09-07T07:50:12.4899962Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:12.4943320Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:12.4992072Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:12.5036305Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:12.5093451Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:12.5134547Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:12.5175043Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:12.5222038Z Entering 'third_party/flash-attention' 2025-09-07T07:50:12.5265660Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:12.5312934Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:12.5363381Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:12.5409662Z Entering 'third_party/fmt' 2025-09-07T07:50:12.5453346Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:12.5497905Z Entering 'third_party/gloo' 2025-09-07T07:50:12.5541281Z Entering 'third_party/googletest' 2025-09-07T07:50:12.5585633Z Entering 'third_party/ideep' 2025-09-07T07:50:12.5627299Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:12.5677284Z Entering 'third_party/ittapi' 2025-09-07T07:50:12.5720987Z Entering 'third_party/kineto' 2025-09-07T07:50:12.5763427Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:12.5804525Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:12.5848663Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:12.5891036Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:12.5933277Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:12.5974342Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:12.6018609Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:12.6060698Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:12.6103845Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:12.6147113Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:12.6192595Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:12.6234347Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:12.6279653Z Entering 'third_party/kleidiai' 2025-09-07T07:50:12.6324032Z Entering 'third_party/mimalloc' 2025-09-07T07:50:12.6367673Z Entering 'third_party/nlohmann' 2025-09-07T07:50:12.6412473Z Entering 'third_party/onnx' 2025-09-07T07:50:12.6470797Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:12.6519381Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:12.6564413Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:12.6607433Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:12.6649009Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:12.6690489Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:12.6733538Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:12.6775858Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:12.6818043Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:12.6856719Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:12.6901563Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:12.6946932Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:12.7008193Z Entering 'third_party/pocketfft' 2025-09-07T07:50:12.7051359Z Entering 'third_party/protobuf' 2025-09-07T07:50:12.7098086Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:12.7142124Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:12.7186002Z Entering 'third_party/psimd' 2025-09-07T07:50:12.7229315Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:12.7273112Z Entering 'third_party/pybind11' 2025-09-07T07:50:12.7317007Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:12.7361584Z Entering 'third_party/sleef' 2025-09-07T07:50:12.7405924Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:12.7451817Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:12.7492607Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:12.7533041Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:12.7575231Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:12.7616273Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:12.7676940Z ##[endgroup] 2025-09-07T07:50:12.7723409Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T07:50:12.7750196Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:12.7919624Z Prepare all required actions 2025-09-07T07:50:12.7920096Z Getting action download info 2025-09-07T07:50:12.9441556Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T07:50:12.9441791Z env: 2025-09-07T07:50:12.9441954Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:12.9442139Z ##[endgroup] 2025-09-07T07:50:12.9487337Z ##[group]Run set -euo pipefail 2025-09-07T07:50:12.9487605Z set -euo pipefail 2025-09-07T07:50:12.9487820Z function get_ec2_metadata() { 2025-09-07T07:50:12.9488094Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T07:50:12.9488541Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T07:50:12.9488946Z  category=$1 2025-09-07T07:50:12.9489208Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T07:50:12.9489521Z  runner_name_str=i-0b7d0f7dc0527ca9b-1001 2025-09-07T07:50:12.9489800Z  if [[ -f /.inarc ]]; then 2025-09-07T07:50:12.9490447Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T07:50:12.9490723Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T07:50:12.9491055Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T07:50:12.9491357Z  else 2025-09-07T07:50:12.9491964Z  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}" 2025-09-07T07:50:12.9492593Z  fi 2025-09-07T07:50:12.9492746Z } 2025-09-07T07:50:12.9492943Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T07:50:12.9493248Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T07:50:12.9493585Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T07:50:12.9493907Z echo "system info $(uname -a)" 2025-09-07T07:50:12.9508323Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:12.9508613Z env: 2025-09-07T07:50:12.9508778Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:12.9508971Z ##[endgroup] 2025-09-07T07:50:12.9550775Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:12.9556501Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:12.9561971Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:12.9574549Z system info Linux 32ccf0b8d8bd 6.8.0-1017-aws #18~22.04.1-Ubuntu SMP Thu Oct 3 19:57:42 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T07:50:12.9594821Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:50:12.9595641Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:50:12.9609513Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:12.9609820Z env: 2025-09-07T07:50:12.9609983Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:12.9610172Z ##[endgroup] 2025-09-07T07:50:12.9680543Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T07:50:12.9680775Z with: 2025-09-07T07:50:12.9680931Z shell: bash 2025-09-07T07:50:12.9681094Z timeout_minutes: 5 2025-09-07T07:50:12.9681275Z max_attempts: 3 2025-09-07T07:50:12.9681454Z retry_wait_seconds: 30 2025-09-07T07:50:12.9683300Z command: AWS_ACCOUNT_ID=$(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 2025-09-07T07:50:12.9684906Z polling_interval_seconds: 1 2025-09-07T07:50:12.9685115Z warning_on_retry: true 2025-09-07T07:50:12.9685304Z continue_on_error: false 2025-09-07T07:50:12.9685495Z env: 2025-09-07T07:50:12.9685651Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:12.9685840Z AWS_RETRY_MODE: standard 2025-09-07T07:50:12.9686024Z AWS_MAX_ATTEMPTS: 5 2025-09-07T07:50:12.9686208Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T07:50:12.9686408Z ##[endgroup] 2025-09-07T07:50:14.4693804Z 2025-09-07T07:50:14.4694368Z WARNING! Your credentials are stored unencrypted in '/home/alice/.docker/config.json'. 2025-09-07T07:50:14.4694938Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:14.4695353Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:14.4695585Z 2025-09-07T07:50:14.4695685Z Login Succeeded 2025-09-07T07:50:15.0406781Z Command completed after 1 attempt(s). 2025-09-07T07:50:15.0486376Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:15.0486803Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:15.0487146Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:15.0502414Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:15.0502778Z env: 2025-09-07T07:50:15.0502952Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.0503142Z ##[endgroup] 2025-09-07T07:50:15.0595613Z ##[group]Run set +e 2025-09-07T07:50:15.0595833Z set +e 2025-09-07T07:50:15.0596002Z set -x 2025-09-07T07:50:15.0596156Z  2025-09-07T07:50:15.0596342Z PT_DOMAIN=download.pytorch.org 2025-09-07T07:50:15.0596769Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T07:50:15.0597318Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T07:50:15.0597727Z # one is returned at random 2025-09-07T07:50:15.0598024Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T07:50:15.0598496Z  2025-09-07T07:50:15.0598675Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:50:15.0598988Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T07:50:15.0599362Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T07:50:15.0599648Z  2025-09-07T07:50:15.0599832Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:50:15.0600126Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T07:50:15.0600558Z  exit 1 2025-09-07T07:50:15.0600722Z  fi 2025-09-07T07:50:15.0600885Z fi 2025-09-07T07:50:15.0601035Z  2025-09-07T07:50:15.0601217Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T07:50:15.0601477Z  # Clean up any old records first 2025-09-07T07:50:15.0601755Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T07:50:15.0601990Z fi 2025-09-07T07:50:15.0602138Z  2025-09-07T07:50:15.0602357Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T07:50:15.0602638Z cat /etc/hosts 2025-09-07T07:50:15.0616622Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:15.0616917Z env: 2025-09-07T07:50:15.0617075Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.0617261Z ##[endgroup] 2025-09-07T07:50:15.0647063Z + PT_DOMAIN=download.pytorch.org 2025-09-07T07:50:15.0652254Z ++ dig -4 +short download.pytorch.org 2025-09-07T07:50:15.0654730Z ++ tail -n1 2025-09-07T07:50:15.0846366Z + RESOLVED_IP=3.170.131.12 2025-09-07T07:50:15.0846633Z + '[' -z 3.170.131.12 ']' 2025-09-07T07:50:15.0846886Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T07:50:15.0864666Z + echo '3.170.131.12 download.pytorch.org' 2025-09-07T07:50:15.0865438Z + sudo tee -a /etc/hosts 2025-09-07T07:50:15.0926293Z 3.170.131.12 download.pytorch.org 2025-09-07T07:50:15.0934853Z + cat /etc/hosts 2025-09-07T07:50:15.0943259Z 127.0.0.1 localhost 2025-09-07T07:50:15.0947695Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T07:50:15.0948025Z fe00:: ip6-localnet 2025-09-07T07:50:15.0948238Z ff00:: ip6-mcastprefix 2025-09-07T07:50:15.0948457Z ff02::1 ip6-allnodes 2025-09-07T07:50:15.0948655Z ff02::2 ip6-allrouters 2025-09-07T07:50:15.0948862Z 172.17.0.2 32ccf0b8d8bd 2025-09-07T07:50:15.0949080Z 3.170.131.12 download.pytorch.org 2025-09-07T07:50:15.0966960Z ##[group]Run set +x 2025-09-07T07:50:15.0967168Z set +x 2025-09-07T07:50:15.0967334Z  2025-09-07T07:50:15.0967493Z max_attempts=30 2025-09-07T07:50:15.0967694Z delay=10 2025-09-07T07:50:15.0967871Z attempt=1 2025-09-07T07:50:15.0968040Z  2025-09-07T07:50:15.0968222Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T07:50:15.0968604Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T07:50:15.0969287Z  if docker info > /dev/null 2>&1; then 2025-09-07T07:50:15.0969595Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T07:50:15.0969888Z  exit 0 2025-09-07T07:50:15.0970053Z  else 2025-09-07T07:50:15.0970402Z  echo "Docker is not running yet." 2025-09-07T07:50:15.0970661Z  echo "Retrying in $delay seconds..." 2025-09-07T07:50:15.0970899Z  sleep $delay 2025-09-07T07:50:15.0971077Z  fi 2025-09-07T07:50:15.0971235Z done 2025-09-07T07:50:15.0971482Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T07:50:15.0971790Z exit 1 2025-09-07T07:50:15.0984833Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:15.0985125Z env: 2025-09-07T07:50:15.0985289Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.0985477Z ##[endgroup] 2025-09-07T07:50:15.1027411Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T07:50:15.1491600Z Docker is running. Proceeding with the next steps 2025-09-07T07:50:15.1608840Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T07:50:15.1609196Z with: 2025-09-07T07:50:15.1609855Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1610771Z use-custom-docker-registry: true 2025-09-07T07:50:15.1611012Z docker-build-dir: .ci/docker 2025-09-07T07:50:15.1611231Z docker-build-script: ./build.sh 2025-09-07T07:50:15.1611447Z working-directory: . 2025-09-07T07:50:15.1611702Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.1611993Z force-push: false 2025-09-07T07:50:15.1612164Z env: 2025-09-07T07:50:15.1612321Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.1612509Z ##[endgroup] 2025-09-07T07:50:15.1628119Z ##[group]Run set -ex 2025-09-07T07:50:15.1628340Z set -ex 2025-09-07T07:50:15.1628494Z  2025-09-07T07:50:15.1628810Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T07:50:15.1629281Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T07:50:15.1629679Z # job could then download the pre-built image as usual 2025-09-07T07:50:15.1630161Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T07:50:15.1630890Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1631125Z else 2025-09-07T07:50:15.1631320Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1631628Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1631913Z  2025-09-07T07:50:15.1632316Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T07:50:15.1632764Z  exit 0 2025-09-07T07:50:15.1632935Z fi 2025-09-07T07:50:15.1633092Z  2025-09-07T07:50:15.1633336Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T07:50:15.1633758Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T07:50:15.1634143Z  # use it as it is, but first let's extract the tag 2025-09-07T07:50:15.1634485Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T07:50:15.1634846Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1635189Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1635478Z else 2025-09-07T07:50:15.1635858Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T07:50:15.1636126Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T07:50:15.1636405Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T07:50:15.1636639Z  fi 2025-09-07T07:50:15.1636974Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T07:50:15.1637402Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1637857Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1638347Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1638646Z fi 2025-09-07T07:50:15.1651678Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:15.1651956Z env: 2025-09-07T07:50:15.1652110Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.1652324Z REPO_NAME: pytorch 2025-09-07T07:50:15.1653195Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1653921Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:50:15.1654126Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T07:50:15.1654404Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.1667564Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T07:50:15.1667835Z CUSTOM_TAG_PREFIX: 2025-09-07T07:50:15.1668037Z ##[endgroup] 2025-09-07T07:50:15.1698135Z + [[ -d .ci/docker ]] 2025-09-07T07:50:15.1698345Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T07:50:15.1698557Z + [[ true == \t\r\u\e ]] 2025-09-07T07:50:15.1698745Z + echo skip=false 2025-09-07T07:50:15.1699581Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 == *\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* ]] 2025-09-07T07:50:15.1706006Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1706825Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T07:50:15.1719873Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1720940Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1722276Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1742225Z ##[group]Run set +e 2025-09-07T07:50:15.1742469Z set +e 2025-09-07T07:50:15.1742650Z set -x 2025-09-07T07:50:15.1742901Z  2025-09-07T07:50:15.1743051Z login() { 2025-09-07T07:50:15.1743417Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:50:15.1743889Z } 2025-09-07T07:50:15.1744042Z  2025-09-07T07:50:15.1744194Z retry () { 2025-09-07T07:50:15.1744398Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:50:15.1744626Z } 2025-09-07T07:50:15.1744775Z  2025-09-07T07:50:15.1744938Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:50:15.1745153Z  2025-09-07T07:50:15.1745318Z START_TIME=$(date +%s) 2025-09-07T07:50:15.1745532Z # Wait up to 120 minutes 2025-09-07T07:50:15.1745794Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T07:50:15.1746138Z  # Check if image already exists, if it does then skip building it 2025-09-07T07:50:15.1746492Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T07:50:15.1746925Z  exit 0 2025-09-07T07:50:15.1747092Z  fi 2025-09-07T07:50:15.1747248Z  2025-09-07T07:50:15.1747541Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T07:50:15.1748015Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T07:50:15.1748474Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T07:50:15.1748840Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T07:50:15.1749124Z  # It's a Docker build job, let's build the image 2025-09-07T07:50:15.1749383Z  break 2025-09-07T07:50:15.1749552Z  else 2025-09-07T07:50:15.1749800Z  # It's a regular build job, wait for the image to become available 2025-09-07T07:50:15.1750090Z  sleep 300 2025-09-07T07:50:15.1750435Z  fi 2025-09-07T07:50:15.1750602Z done 2025-09-07T07:50:15.1750763Z  2025-09-07T07:50:15.1751170Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T07:50:15.1751577Z # be empty. The default action would be to continue rebuild the image 2025-09-07T07:50:15.1751943Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T07:50:15.1752266Z  # if we're on the base branch then use the parent commit 2025-09-07T07:50:15.1752563Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T07:50:15.1752785Z else 2025-09-07T07:50:15.1753016Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T07:50:15.1753351Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T07:50:15.1753607Z fi 2025-09-07T07:50:15.1753755Z  2025-09-07T07:50:15.1753923Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T07:50:15.1754179Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1754413Z  2025-09-07T07:50:15.1754740Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T07:50:15.1755122Z  exit 0 2025-09-07T07:50:15.1755281Z fi 2025-09-07T07:50:15.1755429Z  2025-09-07T07:50:15.1755645Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T07:50:15.1756118Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T07:50:15.1756522Z  exit 1 2025-09-07T07:50:15.1756684Z fi 2025-09-07T07:50:15.1756833Z  2025-09-07T07:50:15.1757087Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T07:50:15.1757547Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T07:50:15.1757976Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T07:50:15.1758457Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T07:50:15.1758989Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T07:50:15.1759307Z fi 2025-09-07T07:50:15.1759451Z  2025-09-07T07:50:15.1759642Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:15.1772690Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:15.1772971Z env: 2025-09-07T07:50:15.1773127Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:15.1773339Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:50:15.1773586Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:15.1774327Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1775448Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:15.1776023Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.1776303Z DOCKER_PUSH: 2025-09-07T07:50:15.1776483Z ##[endgroup] 2025-09-07T07:50:15.1804153Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.1804615Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.1806882Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:50:15.1808865Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:15.9774450Z 2025-09-07T07:50:15.9775047Z WARNING! Your credentials are stored unencrypted in '/home/alice/.docker/config.json'. 2025-09-07T07:50:15.9775935Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:15.9776593Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:15.9776950Z 2025-09-07T07:50:15.9777092Z Login Succeeded 2025-09-07T07:50:15.9805666Z ++ date +%s 2025-09-07T07:50:15.9815391Z + START_TIME=1757231415 2025-09-07T07:50:15.9819636Z ++ date +%s 2025-09-07T07:50:15.9829863Z + [[ 1757224215 -lt 1757231415 ]] 2025-09-07T07:50:15.9830900Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.3625215Z { 2025-09-07T07:50:16.3625399Z "schemaVersion": 2, 2025-09-07T07:50:16.3625726Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T07:50:16.3626085Z "config": { 2025-09-07T07:50:16.3626354Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T07:50:16.3626664Z "size": 31375, 2025-09-07T07:50:16.3627034Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T07:50:16.3627397Z }, 2025-09-07T07:50:16.3627548Z "layers": [ 2025-09-07T07:50:16.3627711Z { 2025-09-07T07:50:16.3627986Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3628360Z "size": 30448359, 2025-09-07T07:50:16.3628725Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T07:50:16.3629134Z }, 2025-09-07T07:50:16.3629289Z { 2025-09-07T07:50:16.3629566Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3629922Z "size": 1554, 2025-09-07T07:50:16.3630439Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T07:50:16.3630839Z }, 2025-09-07T07:50:16.3631000Z { 2025-09-07T07:50:16.3631288Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3631648Z "size": 313297922, 2025-09-07T07:50:16.3632007Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T07:50:16.3632419Z }, 2025-09-07T07:50:16.3632578Z { 2025-09-07T07:50:16.3632854Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3633198Z "size": 792, 2025-09-07T07:50:16.3633544Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T07:50:16.3633937Z }, 2025-09-07T07:50:16.3634094Z { 2025-09-07T07:50:16.3634355Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3634710Z "size": 106, 2025-09-07T07:50:16.3635043Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T07:50:16.3635430Z }, 2025-09-07T07:50:16.3635582Z { 2025-09-07T07:50:16.3635849Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3636195Z "size": 704, 2025-09-07T07:50:16.3636534Z "digest": "sha256:ffd43b71f3ccf3ba563606231cb1d191eb9dd0052f422d54835e6af350525170" 2025-09-07T07:50:16.3636929Z }, 2025-09-07T07:50:16.3637349Z { 2025-09-07T07:50:16.3637619Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3637970Z "size": 1215, 2025-09-07T07:50:16.3638308Z "digest": "sha256:830692b57f6e2758398ec80c3b67a20441d12696b54ed14f2ecebf926198f7d6" 2025-09-07T07:50:16.3638699Z }, 2025-09-07T07:50:16.3638857Z { 2025-09-07T07:50:16.3639120Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3639416Z "size": 482, 2025-09-07T07:50:16.3639685Z "digest": "sha256:5bad36d184686719399be50830a98939d7dbda2313fb407df5915217483fc6a3" 2025-09-07T07:50:16.3640000Z }, 2025-09-07T07:50:16.3640139Z { 2025-09-07T07:50:16.3640502Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3640785Z "size": 110343614, 2025-09-07T07:50:16.3641086Z "digest": "sha256:0e34fdd9ac5c39eb0a9d2c2d258b26f42bb79d7dc0a22014bf201daa2e033eb4" 2025-09-07T07:50:16.3641421Z }, 2025-09-07T07:50:16.3641549Z { 2025-09-07T07:50:16.3641795Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3642079Z "size": 4786, 2025-09-07T07:50:16.3642520Z "digest": "sha256:3c868a62868ef54f82ac11be8dabe1b4365d000bacfe4c104e08022fc96dd767" 2025-09-07T07:50:16.3642843Z }, 2025-09-07T07:50:16.3642978Z { 2025-09-07T07:50:16.3643197Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3643484Z "size": 1710, 2025-09-07T07:50:16.3643760Z "digest": "sha256:62170a22dd571d55ffccac64c0be17f4006d2498cfbf7c6289325f0899cba005" 2025-09-07T07:50:16.3644082Z }, 2025-09-07T07:50:16.3644219Z { 2025-09-07T07:50:16.3644443Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3644719Z "size": 724, 2025-09-07T07:50:16.3645015Z "digest": "sha256:553c1d23b6c4dbd8ab136d0c3659460391ffa14cb9b43be9d7b2f47f90895697" 2025-09-07T07:50:16.3645338Z }, 2025-09-07T07:50:16.3645474Z { 2025-09-07T07:50:16.3645694Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3645987Z "size": 543, 2025-09-07T07:50:16.3646274Z "digest": "sha256:9408d557a804a7dce00897e03ce9f4f447281eb38ce4bc331098a1f1a5ff0d30" 2025-09-07T07:50:16.3646593Z }, 2025-09-07T07:50:16.3646720Z { 2025-09-07T07:50:16.3646941Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3647224Z "size": 3241148049, 2025-09-07T07:50:16.3647568Z "digest": "sha256:df607cfc7c07db6d442e0274e2be8cdc507df8716717363aa92f2fea069bdd9a" 2025-09-07T07:50:16.3647899Z }, 2025-09-07T07:50:16.3648050Z { 2025-09-07T07:50:16.3648277Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3648563Z "size": 32, 2025-09-07T07:50:16.3648846Z "digest": 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"sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T07:50:16.3711003Z }, 2025-09-07T07:50:16.3711150Z { 2025-09-07T07:50:16.3711369Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3711657Z "size": 32, 2025-09-07T07:50:16.3711931Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:50:16.3712253Z }, 2025-09-07T07:50:16.3712378Z { 2025-09-07T07:50:16.3712594Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3712877Z "size": 109, 2025-09-07T07:50:16.3713162Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T07:50:16.3713486Z }, 2025-09-07T07:50:16.3713618Z { 2025-09-07T07:50:16.3713838Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3714128Z "size": 1897, 2025-09-07T07:50:16.3714408Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T07:50:16.3714747Z }, 2025-09-07T07:50:16.3714882Z { 2025-09-07T07:50:16.3715104Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3715385Z "size": 243440375, 2025-09-07T07:50:16.3715681Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T07:50:16.3716006Z }, 2025-09-07T07:50:16.3716139Z { 2025-09-07T07:50:16.3716358Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3716654Z "size": 106, 2025-09-07T07:50:16.3716933Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T07:50:16.3717248Z }, 2025-09-07T07:50:16.3717376Z { 2025-09-07T07:50:16.3717595Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3717874Z "size": 166, 2025-09-07T07:50:16.3718293Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T07:50:16.3718603Z }, 2025-09-07T07:50:16.3718735Z { 2025-09-07T07:50:16.3718959Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3719237Z "size": 7943, 2025-09-07T07:50:16.3719508Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T07:50:16.3719826Z }, 2025-09-07T07:50:16.3719956Z { 2025-09-07T07:50:16.3720175Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3720579Z "size": 8072, 2025-09-07T07:50:16.3720873Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T07:50:16.3721193Z }, 2025-09-07T07:50:16.3721324Z { 2025-09-07T07:50:16.3721535Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3721817Z "size": 304, 2025-09-07T07:50:16.3722092Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T07:50:16.3722415Z }, 2025-09-07T07:50:16.3722543Z { 2025-09-07T07:50:16.3722900Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3723193Z "size": 13362696, 2025-09-07T07:50:16.3723475Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T07:50:16.3723782Z }, 2025-09-07T07:50:16.3723916Z { 2025-09-07T07:50:16.3724138Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3724419Z "size": 108, 2025-09-07T07:50:16.3724706Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T07:50:16.3725028Z }, 2025-09-07T07:50:16.3725161Z { 2025-09-07T07:50:16.3725380Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3725657Z "size": 54145663, 2025-09-07T07:50:16.3725947Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T07:50:16.3726275Z }, 2025-09-07T07:50:16.3726408Z { 2025-09-07T07:50:16.3726629Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:16.3726913Z "size": 32, 2025-09-07T07:50:16.3727195Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:50:16.3727519Z } 2025-09-07T07:50:16.3727645Z ] 2025-09-07T07:50:16.3727780Z } 2025-09-07T07:50:16.3727926Z + exit 0 2025-09-07T07:50:16.3749168Z ##[group]Run set -eux 2025-09-07T07:50:16.3749373Z set -eux 2025-09-07T07:50:16.3749674Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T07:50:16.3750655Z 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 2025-09-07T07:50:16.3765509Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.3765795Z env: 2025-09-07T07:50:16.3765958Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.3766151Z ##[endgroup] 2025-09-07T07:50:16.3798736Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T07:50:16.3801896Z + jq --raw-output .SecretString 2025-09-07T07:50:16.3802440Z + jq -r .docker_hub_readonly_token 2025-09-07T07:50:16.3804100Z + docker login --username pytorchbot --password-stdin 2025-09-07T07:50:16.9400754Z 2025-09-07T07:50:16.9402572Z An error occurred (AccessDeniedException) when calling the GetSecretValue operation: User: arn:aws:sts::308535385114:assumed-role/gh-ci-github-action-runners-runner-role/i-0b7d0f7dc0527ca9b is not authorized to perform: secretsmanager:GetSecretValue on resource: docker_hub_readonly_token because no identity-based policy allows the secretsmanager:GetSecretValue action 2025-09-07T07:50:17.0258754Z Error: Cannot perform an interactive login from a non TTY device 2025-09-07T07:50:17.0282979Z + true 2025-09-07T07:50:17.0353906Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:50:17.0354225Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:50:17.0354531Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T07:50:17.0369066Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:17.0369367Z env: 2025-09-07T07:50:17.0369535Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:17.0370370Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.0371081Z ##[endgroup] 2025-09-07T07:50:17.0403343Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.0439980Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T07:50:17.0440499Z with: 2025-09-07T07:50:17.0441152Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.0441924Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.0442201Z env: 2025-09-07T07:50:17.0442362Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:17.0442554Z ##[endgroup] 2025-09-07T07:50:17.0454729Z ##[group]Run set -x 2025-09-07T07:50:17.0454935Z set -x 2025-09-07T07:50:17.0455106Z set +e 2025-09-07T07:50:17.0455265Z  2025-09-07T07:50:17.0455412Z login() { 2025-09-07T07:50:17.0455764Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:50:17.0456135Z } 2025-09-07T07:50:17.0456296Z  2025-09-07T07:50:17.0456471Z retry () { 2025-09-07T07:50:17.0456673Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:50:17.0456895Z } 2025-09-07T07:50:17.0457053Z  2025-09-07T07:50:17.0457231Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:50:17.0457457Z  2025-09-07T07:50:17.0457802Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T07:50:17.0458281Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T07:50:17.0458545Z  2025-09-07T07:50:17.0458694Z set -e 2025-09-07T07:50:17.0458934Z # ignore output since only exit code is used for conditional 2025-09-07T07:50:17.0459280Z # only pull docker image if it's not available locally 2025-09-07T07:50:17.0459663Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T07:50:17.0460023Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T07:50:17.0460502Z fi 2025-09-07T07:50:17.0473443Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:17.0473744Z env: 2025-09-07T07:50:17.0473906Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:17.0474585Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.0475349Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.0475624Z ##[endgroup] 2025-09-07T07:50:17.0503852Z + set +e 2025-09-07T07:50:17.0504099Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.0504437Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.0508156Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:50:17.0509032Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.8347005Z 2025-09-07T07:50:17.8347318Z WARNING! Your credentials are stored unencrypted in '/home/alice/.docker/config.json'. 2025-09-07T07:50:17.8347825Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:17.8348503Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:17.8348721Z 2025-09-07T07:50:17.8348810Z Login Succeeded 2025-09-07T07:50:17.8380799Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.8381758Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T07:50:18.2196403Z + IMAGE_SIZE=36183.606596946716 2025-09-07T07:50:18.2196772Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T07:50:18.2197106Z + set -e 2025-09-07T07:50:18.2198591Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.2199533Z Compressed size of image in MB: 36183.606596946716 2025-09-07T07:50:18.2318809Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.2320397Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.5872989Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T07:50:18.5873807Z e6fdc8487bfe: Pulling fs layer 2025-09-07T07:50:18.5874065Z 171dcef20c49: Pulling fs layer 2025-09-07T07:50:18.5874323Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T07:50:18.5874559Z 744f9ba90a65: Pulling fs layer 2025-09-07T07:50:18.5874816Z d3c08322a332: Pulling fs layer 2025-09-07T07:50:18.5875050Z ffd43b71f3cc: Pulling fs layer 2025-09-07T07:50:18.5875291Z 830692b57f6e: Pulling fs layer 2025-09-07T07:50:18.5875526Z 5bad36d18468: Pulling fs layer 2025-09-07T07:50:18.5875775Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T07:50:18.5875999Z 3c868a62868e: Pulling fs layer 2025-09-07T07:50:18.5876258Z 744f9ba90a65: Waiting 2025-09-07T07:50:18.5876469Z 62170a22dd57: Pulling fs layer 2025-09-07T07:50:18.5876691Z 830692b57f6e: Waiting 2025-09-07T07:50:18.5876895Z 553c1d23b6c4: Pulling fs layer 2025-09-07T07:50:18.5877121Z ffd43b71f3cc: Waiting 2025-09-07T07:50:18.5877323Z 5bad36d18468: Waiting 2025-09-07T07:50:18.5877516Z d3c08322a332: Waiting 2025-09-07T07:50:18.5877705Z 0e34fdd9ac5c: Waiting 2025-09-07T07:50:18.5877898Z 62170a22dd57: Waiting 2025-09-07T07:50:18.5878098Z 9408d557a804: Pulling fs layer 2025-09-07T07:50:18.5878322Z 3c868a62868e: Waiting 2025-09-07T07:50:18.5878537Z df607cfc7c07: Pulling fs layer 2025-09-07T07:50:18.5878757Z 9408d557a804: Waiting 2025-09-07T07:50:18.5878960Z 553c1d23b6c4: Waiting 2025-09-07T07:50:18.5879168Z 4f4fb700ef54: Pulling fs layer 2025-09-07T07:50:18.5879403Z 40a8e39faeda: Pulling fs layer 2025-09-07T07:50:18.5879643Z d895771c9fac: Pulling fs layer 2025-09-07T07:50:18.5879875Z c4ee04f39d49: Pulling fs layer 2025-09-07T07:50:18.5880106Z 3690c9826e48: Pulling fs layer 2025-09-07T07:50:18.5880669Z df607cfc7c07: Waiting 2025-09-07T07:50:18.5880882Z 57cbc5013733: Pulling fs layer 2025-09-07T07:50:18.5881111Z 40a8e39faeda: Waiting 2025-09-07T07:50:18.5881362Z c4ee04f39d49: Waiting 2025-09-07T07:50:18.5881560Z d895771c9fac: Waiting 2025-09-07T07:50:18.5881770Z f5f4b06b58bb: Pulling fs layer 2025-09-07T07:50:18.5881995Z 3690c9826e48: Waiting 2025-09-07T07:50:18.5882197Z f59713ce4bf4: Pulling fs layer 2025-09-07T07:50:18.5882421Z 57cbc5013733: Waiting 2025-09-07T07:50:18.5882615Z fe0486521517: Pulling fs layer 2025-09-07T07:50:18.5882836Z f5f4b06b58bb: Waiting 2025-09-07T07:50:18.5883043Z 8c21cc3715a2: Pulling fs layer 2025-09-07T07:50:18.5883268Z f59713ce4bf4: Waiting 2025-09-07T07:50:18.5883464Z fe0486521517: Waiting 2025-09-07T07:50:18.5883677Z d37c58456a6a: Pulling fs layer 2025-09-07T07:50:18.5883917Z d042f63abc13: Pulling fs layer 2025-09-07T07:50:18.5884483Z 621284a9c05a: Pulling fs layer 2025-09-07T07:50:18.5884722Z 85f605d2dd3a: Pulling fs layer 2025-09-07T07:50:18.5884956Z 381b5539e598: Pulling fs layer 2025-09-07T07:50:18.5885178Z 8c21cc3715a2: Waiting 2025-09-07T07:50:18.5885371Z d37c58456a6a: Waiting 2025-09-07T07:50:18.5885578Z a487c0c80029: Pulling fs layer 2025-09-07T07:50:18.5885813Z 48bcb81e2566: Pulling fs layer 2025-09-07T07:50:18.5886044Z e261928c0043: Pulling fs layer 2025-09-07T07:50:18.5886268Z 0fea55428091: Pulling fs layer 2025-09-07T07:50:18.5886490Z a487c0c80029: Waiting 2025-09-07T07:50:18.5886683Z 85f605d2dd3a: Waiting 2025-09-07T07:50:18.5886879Z d042f63abc13: Waiting 2025-09-07T07:50:18.5887078Z b4291bccbb84: Pulling fs layer 2025-09-07T07:50:18.5887312Z 621284a9c05a: Waiting 2025-09-07T07:50:18.5887709Z 381b5539e598: Waiting 2025-09-07T07:50:18.5887906Z 48bcb81e2566: Waiting 2025-09-07T07:50:18.5888103Z ddc91b09189a: Pulling fs layer 2025-09-07T07:50:18.5888326Z e261928c0043: Waiting 2025-09-07T07:50:18.5888528Z 7540c7428627: Pulling fs layer 2025-09-07T07:50:18.5888753Z ddc91b09189a: Waiting 2025-09-07T07:50:18.5888941Z b4291bccbb84: Waiting 2025-09-07T07:50:18.5889132Z 7540c7428627: Waiting 2025-09-07T07:50:18.5889333Z 003c4e2598fb: Pulling fs layer 2025-09-07T07:50:18.5889532Z 5687149362ae: Pulling fs layer 2025-09-07T07:50:18.5889720Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T07:50:18.5889914Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T07:50:18.5890129Z 3c9055753b4c: Pulling fs layer 2025-09-07T07:50:18.5890468Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T07:50:18.5890659Z 6623ea814971: Pulling fs layer 2025-09-07T07:50:18.5890849Z cdd2cf54eb2a: Waiting 2025-09-07T07:50:18.5891031Z d3ad4df1ba3a: Waiting 2025-09-07T07:50:18.5891226Z 11696c3aa380: Pulling fs layer 2025-09-07T07:50:18.5891414Z 003c4e2598fb: Waiting 2025-09-07T07:50:18.5891585Z 3c9055753b4c: Waiting 2025-09-07T07:50:18.5891751Z 5687149362ae: Waiting 2025-09-07T07:50:18.5891918Z 31cf8d0bd21c: Waiting 2025-09-07T07:50:18.5892093Z ef4d544e35ca: Pulling fs layer 2025-09-07T07:50:18.5892291Z 6623ea814971: Waiting 2025-09-07T07:50:18.5892456Z 11696c3aa380: Waiting 2025-09-07T07:50:18.5892632Z 5c5108865e5e: Pulling fs layer 2025-09-07T07:50:18.5892827Z 9e97578e9edf: Pulling fs layer 2025-09-07T07:50:18.5893013Z ef4d544e35ca: Waiting 2025-09-07T07:50:18.5893188Z da5a91b54cb5: Pulling fs layer 2025-09-07T07:50:18.5893374Z 1e93be219e89: Pulling fs layer 2025-09-07T07:50:18.5893562Z 136825afebb5: Pulling fs layer 2025-09-07T07:50:18.5893745Z 5c5108865e5e: Waiting 2025-09-07T07:50:18.5893904Z 9e97578e9edf: Waiting 2025-09-07T07:50:18.5894067Z 22b39805302d: Pulling fs layer 2025-09-07T07:50:18.5894252Z 1e93be219e89: Waiting 2025-09-07T07:50:18.5894417Z da5a91b54cb5: Waiting 2025-09-07T07:50:18.5894580Z 136825afebb5: Waiting 2025-09-07T07:50:18.5894750Z d12add675e35: Pulling fs layer 2025-09-07T07:50:18.5894953Z bc127046d33a: Pulling fs layer 2025-09-07T07:50:18.5895139Z d12add675e35: Waiting 2025-09-07T07:50:18.5895303Z 22b39805302d: Waiting 2025-09-07T07:50:18.5895461Z bc127046d33a: Waiting 2025-09-07T07:50:18.5895630Z 951e8ce83841: Pulling fs layer 2025-09-07T07:50:18.5895820Z 32340b97ae50: Pulling fs layer 2025-09-07T07:50:18.5896000Z 951e8ce83841: Waiting 2025-09-07T07:50:18.5896151Z 32340b97ae50: Waiting 2025-09-07T07:50:18.5896324Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T07:50:18.5896521Z d8c4b845cfc7: Pulling fs layer 2025-09-07T07:50:18.5896714Z b35c180f4d8d: Pulling fs layer 2025-09-07T07:50:18.5896911Z 5f967b3c303a: Pulling fs layer 2025-09-07T07:50:18.5897098Z 5bbb04cd6b57: Waiting 2025-09-07T07:50:18.5897269Z 04770904f012: Pulling fs layer 2025-09-07T07:50:18.5897458Z 73373941fb32: Pulling fs layer 2025-09-07T07:50:18.5897643Z 9572e6cd907b: Pulling fs layer 2025-09-07T07:50:18.5897825Z b35c180f4d8d: Waiting 2025-09-07T07:50:18.5898004Z 64a544aba233: Pulling fs layer 2025-09-07T07:50:18.5898195Z 7e35418a2499: Pulling fs layer 2025-09-07T07:50:18.5898379Z 5f967b3c303a: Waiting 2025-09-07T07:50:18.5898557Z 2ed8e82748d4: Pulling fs layer 2025-09-07T07:50:18.5898928Z c988fbcccd70: Pulling fs layer 2025-09-07T07:50:18.5899115Z 64a544aba233: Waiting 2025-09-07T07:50:18.5899281Z 9572e6cd907b: Waiting 2025-09-07T07:50:18.5899457Z 2ed8e82748d4: Waiting 2025-09-07T07:50:18.5899622Z 7e35418a2499: Waiting 2025-09-07T07:50:18.5899778Z c988fbcccd70: Waiting 2025-09-07T07:50:18.7316215Z 171dcef20c49: Verifying Checksum 2025-09-07T07:50:18.7316489Z 171dcef20c49: Download complete 2025-09-07T07:50:18.8765199Z 744f9ba90a65: Verifying Checksum 2025-09-07T07:50:18.8765557Z 744f9ba90a65: Download complete 2025-09-07T07:50:19.0134154Z d3c08322a332: Verifying Checksum 2025-09-07T07:50:19.0134656Z d3c08322a332: Download complete 2025-09-07T07:50:19.0196234Z e6fdc8487bfe: Download complete 2025-09-07T07:50:19.1622064Z ffd43b71f3cc: Download complete 2025-09-07T07:50:19.1792301Z 830692b57f6e: Verifying Checksum 2025-09-07T07:50:19.1792771Z 830692b57f6e: Download complete 2025-09-07T07:50:19.3235712Z 5bad36d18468: Download complete 2025-09-07T07:50:19.4852473Z 3c868a62868e: Verifying Checksum 2025-09-07T07:50:19.4852960Z 3c868a62868e: Download complete 2025-09-07T07:50:19.6300023Z 62170a22dd57: Verifying Checksum 2025-09-07T07:50:19.6301062Z 62170a22dd57: Download complete 2025-09-07T07:50:19.7855323Z 553c1d23b6c4: Download complete 2025-09-07T07:50:19.9972293Z e6fdc8487bfe: Pull complete 2025-09-07T07:50:20.1039953Z 9408d557a804: Verifying Checksum 2025-09-07T07:50:20.1040688Z 9408d557a804: Download complete 2025-09-07T07:50:20.4139815Z 171dcef20c49: Pull complete 2025-09-07T07:50:20.4627628Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T07:50:20.4627961Z 0e34fdd9ac5c: Download complete 2025-09-07T07:50:20.5221989Z 4f4fb700ef54: Download complete 2025-09-07T07:50:20.6779710Z 40a8e39faeda: Verifying Checksum 2025-09-07T07:50:20.6780053Z 40a8e39faeda: Download complete 2025-09-07T07:50:21.3510462Z d895771c9fac: Verifying Checksum 2025-09-07T07:50:21.3510804Z d895771c9fac: Download complete 2025-09-07T07:50:21.4928938Z c4ee04f39d49: Verifying Checksum 2025-09-07T07:50:21.4929209Z c4ee04f39d49: Download complete 2025-09-07T07:50:21.7289929Z 3690c9826e48: Verifying Checksum 2025-09-07T07:50:21.7290373Z 3690c9826e48: Download complete 2025-09-07T07:50:21.8482945Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T07:50:21.8483309Z 4c92b3f72f1d: Download complete 2025-09-07T07:50:21.8852089Z 57cbc5013733: Verifying Checksum 2025-09-07T07:50:21.8852421Z 57cbc5013733: Download complete 2025-09-07T07:50:21.9835274Z f5f4b06b58bb: Verifying Checksum 2025-09-07T07:50:22.0495336Z f5f4b06b58bb: Download complete 2025-09-07T07:50:22.0495654Z f59713ce4bf4: Verifying Checksum 2025-09-07T07:50:22.1283449Z fe0486521517: Download complete 2025-09-07T07:50:22.2722209Z d37c58456a6a: Verifying Checksum 2025-09-07T07:50:22.2722503Z d37c58456a6a: Download complete 2025-09-07T07:50:27.5587085Z d042f63abc13: Verifying Checksum 2025-09-07T07:50:27.5587426Z d042f63abc13: Download complete 2025-09-07T07:50:27.7282074Z 621284a9c05a: Download complete 2025-09-07T07:50:27.8826564Z 85f605d2dd3a: Download complete 2025-09-07T07:50:31.7877601Z 4c92b3f72f1d: Pull complete 2025-09-07T07:50:32.5788878Z 381b5539e598: Verifying Checksum 2025-09-07T07:50:32.5789254Z 381b5539e598: Download complete 2025-09-07T07:50:32.7257457Z a487c0c80029: Verifying Checksum 2025-09-07T07:50:32.7257761Z a487c0c80029: Download complete 2025-09-07T07:50:32.8863791Z 48bcb81e2566: Verifying Checksum 2025-09-07T07:50:32.8864111Z 48bcb81e2566: Download complete 2025-09-07T07:50:33.1287309Z e261928c0043: Verifying Checksum 2025-09-07T07:50:33.1287652Z e261928c0043: Download complete 2025-09-07T07:50:33.3745874Z 0fea55428091: Download complete 2025-09-07T07:50:33.8959114Z b4291bccbb84: Verifying Checksum 2025-09-07T07:50:33.8959443Z b4291bccbb84: Download complete 2025-09-07T07:50:34.0627430Z ddc91b09189a: Verifying Checksum 2025-09-07T07:50:34.0628001Z ddc91b09189a: Download complete 2025-09-07T07:50:34.2299128Z 7540c7428627: Verifying Checksum 2025-09-07T07:50:34.2299405Z 7540c7428627: Download complete 2025-09-07T07:50:34.5313642Z 003c4e2598fb: Verifying Checksum 2025-09-07T07:50:34.5314605Z 003c4e2598fb: Download complete 2025-09-07T07:50:34.6900638Z 5687149362ae: Verifying Checksum 2025-09-07T07:50:34.6901014Z 5687149362ae: Download complete 2025-09-07T07:50:34.8467257Z cdd2cf54eb2a: Download complete 2025-09-07T07:50:36.5657489Z 744f9ba90a65: Pull complete 2025-09-07T07:50:39.6309098Z d3c08322a332: Pull complete 2025-09-07T07:50:45.3088489Z ffd43b71f3cc: Pull complete 2025-09-07T07:50:49.2993971Z 830692b57f6e: Pull complete 2025-09-07T07:50:54.6210164Z 5bad36d18468: Pull complete 2025-09-07T07:50:57.5834992Z df607cfc7c07: Verifying Checksum 2025-09-07T07:50:57.5836218Z df607cfc7c07: Download complete 2025-09-07T07:50:57.8688279Z 3c9055753b4c: Verifying Checksum 2025-09-07T07:50:57.8688809Z 3c9055753b4c: Download complete 2025-09-07T07:51:00.6365482Z 0e34fdd9ac5c: Pull complete 2025-09-07T07:51:02.5845712Z 3c868a62868e: Pull complete 2025-09-07T07:51:03.9167859Z 31cf8d0bd21c: Verifying Checksum 2025-09-07T07:51:03.9168222Z 31cf8d0bd21c: Download complete 2025-09-07T07:51:04.7905464Z 62170a22dd57: Pull complete 2025-09-07T07:51:07.0151872Z 553c1d23b6c4: Pull complete 2025-09-07T07:51:10.5225530Z 9408d557a804: Pull complete 2025-09-07T07:51:40.9330754Z 8c21cc3715a2: Verifying Checksum 2025-09-07T07:51:40.9331149Z 8c21cc3715a2: Download complete 2025-09-07T07:51:41.3575050Z 11696c3aa380: Verifying Checksum 2025-09-07T07:51:41.3575549Z 11696c3aa380: Download complete 2025-09-07T07:51:41.5058570Z ef4d544e35ca: Verifying Checksum 2025-09-07T07:51:41.5058866Z ef4d544e35ca: Download complete 2025-09-07T07:51:41.6789284Z 5c5108865e5e: Verifying Checksum 2025-09-07T07:51:41.6789600Z 5c5108865e5e: Download complete 2025-09-07T07:51:41.8250705Z 9e97578e9edf: Download complete 2025-09-07T07:51:41.9693459Z da5a91b54cb5: Verifying Checksum 2025-09-07T07:51:41.9693775Z da5a91b54cb5: Download complete 2025-09-07T07:51:42.3733147Z 1e93be219e89: Verifying Checksum 2025-09-07T07:51:42.3733648Z 1e93be219e89: Download complete 2025-09-07T07:51:42.5371947Z 136825afebb5: Download complete 2025-09-07T07:51:42.6923703Z 22b39805302d: Verifying Checksum 2025-09-07T07:51:42.6924080Z 22b39805302d: Download complete 2025-09-07T07:51:42.8548401Z d12add675e35: Verifying Checksum 2025-09-07T07:51:42.8548696Z d12add675e35: Download complete 2025-09-07T07:51:43.0211188Z bc127046d33a: Verifying Checksum 2025-09-07T07:51:43.0211516Z bc127046d33a: Download complete 2025-09-07T07:51:43.4978803Z 951e8ce83841: Verifying Checksum 2025-09-07T07:51:43.4979349Z 951e8ce83841: Download complete 2025-09-07T07:51:43.6727476Z 32340b97ae50: Verifying Checksum 2025-09-07T07:51:43.6727838Z 32340b97ae50: Download complete 2025-09-07T07:51:43.8222942Z 5bbb04cd6b57: Download complete 2025-09-07T07:51:43.9871785Z d8c4b845cfc7: Verifying Checksum 2025-09-07T07:51:43.9872151Z d8c4b845cfc7: Download complete 2025-09-07T07:51:46.8502830Z b35c180f4d8d: Verifying Checksum 2025-09-07T07:51:46.8503176Z b35c180f4d8d: Download complete 2025-09-07T07:51:47.0177366Z 5f967b3c303a: Download complete 2025-09-07T07:51:47.1491432Z 04770904f012: Verifying Checksum 2025-09-07T07:51:47.1491789Z 04770904f012: Download complete 2025-09-07T07:51:47.3102046Z 73373941fb32: Download complete 2025-09-07T07:51:47.4592507Z 9572e6cd907b: Verifying Checksum 2025-09-07T07:51:47.4592851Z 9572e6cd907b: Download complete 2025-09-07T07:51:47.6004243Z 64a544aba233: Verifying Checksum 2025-09-07T07:51:47.6004578Z 64a544aba233: Download complete 2025-09-07T07:51:47.8812306Z 7e35418a2499: Verifying Checksum 2025-09-07T07:51:47.8812692Z 7e35418a2499: Download complete 2025-09-07T07:51:48.0148520Z 2ed8e82748d4: Download complete 2025-09-07T07:51:48.6998035Z c988fbcccd70: Verifying Checksum 2025-09-07T07:51:48.6998376Z c988fbcccd70: Download complete 2025-09-07T07:52:08.9468797Z df607cfc7c07: Pull complete 2025-09-07T07:52:14.5507432Z 6623ea814971: Verifying Checksum 2025-09-07T07:52:14.5507842Z 6623ea814971: Download complete 2025-09-07T07:52:15.2773963Z 4f4fb700ef54: Pull complete 2025-09-07T07:52:19.2945342Z 40a8e39faeda: Pull complete 2025-09-07T07:52:26.8178944Z d895771c9fac: Pull complete 2025-09-07T07:52:33.2077809Z c4ee04f39d49: Pull complete 2025-09-07T07:52:37.3343893Z 3690c9826e48: Pull complete 2025-09-07T07:52:42.3522208Z 57cbc5013733: Pull complete 2025-09-07T07:52:46.9321670Z f5f4b06b58bb: Pull complete 2025-09-07T07:52:52.4669524Z f59713ce4bf4: Pull complete 2025-09-07T07:52:56.9635735Z fe0486521517: Pull complete 2025-09-07T07:54:15.5684047Z d3ad4df1ba3a: Verifying Checksum 2025-09-07T07:54:15.5684437Z d3ad4df1ba3a: Download complete 2025-09-07T07:58:29.4332706Z 8c21cc3715a2: Pull complete 2025-09-07T07:58:39.8419140Z d37c58456a6a: Pull complete 2025-09-07T07:58:50.7565079Z d042f63abc13: Pull complete 2025-09-07T07:58:59.0231663Z 621284a9c05a: Pull complete 2025-09-07T07:59:07.4042362Z 85f605d2dd3a: Pull complete 2025-09-07T07:59:27.6835009Z 381b5539e598: Pull complete 2025-09-07T07:59:34.8804666Z a487c0c80029: Pull complete 2025-09-07T07:59:46.2028587Z 48bcb81e2566: Pull complete 2025-09-07T08:00:01.5901312Z e261928c0043: Pull complete 2025-09-07T08:00:06.8690087Z 0fea55428091: Pull complete 2025-09-07T08:00:12.9365488Z b4291bccbb84: Pull complete 2025-09-07T08:00:18.0859622Z ddc91b09189a: Pull complete 2025-09-07T08:00:21.8554523Z 7540c7428627: Pull complete 2025-09-07T08:00:29.7139282Z 003c4e2598fb: Pull complete 2025-09-07T08:00:34.2823428Z 5687149362ae: Pull complete 2025-09-07T08:00:38.4136925Z cdd2cf54eb2a: Pull complete 2025-09-07T08:07:22.9898852Z d3ad4df1ba3a: Pull complete 2025-09-07T08:07:29.8515236Z 3c9055753b4c: Pull complete 2025-09-07T08:07:34.4460012Z 31cf8d0bd21c: Pull complete 2025-09-07T08:13:31.2470891Z 6623ea814971: Pull complete 2025-09-07T08:13:38.4705385Z 11696c3aa380: Pull complete 2025-09-07T08:13:42.6275066Z ef4d544e35ca: Pull complete 2025-09-07T08:13:49.3150125Z 5c5108865e5e: Pull complete 2025-09-07T08:13:52.6763388Z 9e97578e9edf: Pull complete 2025-09-07T08:13:53.5223732Z da5a91b54cb5: Pull complete 2025-09-07T08:13:57.7106198Z 1e93be219e89: Pull complete 2025-09-07T08:14:05.5495235Z 136825afebb5: Pull complete 2025-09-07T08:14:08.6334874Z 22b39805302d: Pull complete 2025-09-07T08:14:12.5282461Z d12add675e35: Pull complete 2025-09-07T08:14:14.3937929Z bc127046d33a: Pull complete 2025-09-07T08:14:17.9797554Z 951e8ce83841: Pull complete 2025-09-07T08:14:19.9373475Z 32340b97ae50: Pull complete 2025-09-07T08:14:21.7191836Z 5bbb04cd6b57: Pull complete 2025-09-07T08:14:22.8078017Z d8c4b845cfc7: Pull complete 2025-09-07T08:14:32.3798325Z b35c180f4d8d: Pull complete 2025-09-07T08:14:35.9126769Z 5f967b3c303a: Pull complete 2025-09-07T08:14:40.4143904Z 04770904f012: Pull complete 2025-09-07T08:14:44.4668521Z 73373941fb32: Pull complete 2025-09-07T08:14:48.4046139Z 9572e6cd907b: Pull complete 2025-09-07T08:14:55.2460429Z 64a544aba233: Pull complete 2025-09-07T08:15:05.3636763Z 7e35418a2499: Pull complete 2025-09-07T08:15:12.1908907Z 2ed8e82748d4: Pull complete 2025-09-07T08:15:21.6977070Z c988fbcccd70: Pull complete 2025-09-07T08:15:28.9494354Z Digest: sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T08:15:29.6795628Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:15:29.6823266Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:15:29.8081285Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:15:29.8082172Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:15:29.8096984Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:29.8097285Z env: 2025-09-07T08:15:29.8097462Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:29.8097654Z ##[endgroup] 2025-09-07T08:15:29.8615029Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:15:29.8615928Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:15:29.8630638Z shell: /usr/bin/bash -e {0} 2025-09-07T08:15:29.8630856Z env: 2025-09-07T08:15:29.8631022Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:29.8631227Z ##[endgroup] 2025-09-07T08:15:30.2941983Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:15:30.2943164Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:15:30.2960456Z shell: /usr/bin/bash -e {0} 2025-09-07T08:15:30.2960703Z env: 2025-09-07T08:15:30.2960901Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:30.2961198Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:30.2961523Z ##[endgroup] 2025-09-07T08:15:30.3416977Z Prepare all required actions 2025-09-07T08:15:30.6072739Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T08:15:30.6073146Z with: 2025-09-07T08:15:30.6073958Z github-token: *** 2025-09-07T08:15:30.6074169Z env: 2025-09-07T08:15:30.6074363Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:30.6074658Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:30.6075053Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:15:30.6075384Z ##[endgroup] 2025-09-07T08:15:30.6099370Z ##[group]Run set -eux 2025-09-07T08:15:30.6099613Z set -eux 2025-09-07T08:15:30.6099941Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T08:15:30.6115348Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:30.6115667Z env: 2025-09-07T08:15:30.6115833Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:30.6116091Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:30.6116474Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:15:30.6117347Z GITHUB_TOKEN: *** 2025-09-07T08:15:30.6117562Z ##[endgroup] 2025-09-07T08:15:30.6602293Z + python3 .github/scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1001 2025-09-07T08:15:31.2684245Z Setting output job-id=49775781859 2025-09-07T08:15:31.2685147Z Setting output job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:15:31.3162963Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:15:31.3163706Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:15:31.3164556Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T08:15:31.3165292Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T08:15:31.3178879Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:31.3179176Z env: 2025-09-07T08:15:31.3179337Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:31.3179583Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:31.3179909Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:15:31.3180189Z JOB_ID: 49775781859 2025-09-07T08:15:31.3180719Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:15:31.3181100Z WORKFLOW_NAME: inductor-perf-nightly-h100 2025-09-07T08:15:31.3181345Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T08:15:31.3181546Z MONITOR_LOG_INTERVAL: 15 2025-09-07T08:15:31.3181744Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T08:15:31.3181958Z ##[endgroup] 2025-09-07T08:15:31.5949845Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:15:32.7916954Z Collecting psutil==5.9.8 2025-09-07T08:15:33.0342162Z 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) 2025-09-07T08:15:33.5952277Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 681.8 kB/s eta 0:00:00 2025-09-07T08:15:35.1147553Z Collecting dataclasses_json==0.6.7 2025-09-07T08:15:35.5856289Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T08:15:37.1905188Z Collecting nvidia-ml-py==11.525.84 2025-09-07T08:15:37.2387857Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T08:15:38.8246785Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T08:15:38.8373727Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T08:15:40.7335377Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T08:15:40.7689064Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T08:15:41.6354011Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 47.0 kB/s eta 0:00:00 2025-09-07T08:15:42.4575853Z Collecting packaging>=17.0 2025-09-07T08:15:42.6833346Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T08:15:43.3686112Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 82.3 kB/s eta 0:00:00 2025-09-07T08:15:44.0718543Z Collecting mypy-extensions>=0.3.0 2025-09-07T08:15:44.0833421Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T08:15:45.3682702Z Collecting typing-extensions>=3.7.4 2025-09-07T08:15:45.7597326Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T08:15:46.4318133Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 51.3 kB/s eta 0:00:00 2025-09-07T08:15:46.4959610Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T08:15:54.0101054Z 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 2025-09-07T08:15:54.0751545Z Prepare all required actions 2025-09-07T08:15:54.0751900Z Getting action download info 2025-09-07T08:15:54.3390657Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T08:15:56.3441327Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T08:16:01.9554305Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T08:16:01.9554799Z with: 2025-09-07T08:16:01.9555144Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:16:01.9555583Z s3-bucket: gha-artifacts 2025-09-07T08:16:01.9555920Z env: 2025-09-07T08:16:01.9556196Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:01.9556636Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:01.9557226Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:01.9557720Z ##[endgroup] 2025-09-07T08:16:02.3349136Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:16:02.3349598Z with: 2025-09-07T08:16:02.3349923Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:16:02.3350626Z s3-bucket: gha-artifacts 2025-09-07T08:16:02.3350979Z region: us-east-1 2025-09-07T08:16:02.3351267Z env: 2025-09-07T08:16:02.3351544Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:02.3352003Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:02.3352603Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:02.3353106Z ##[endgroup] 2025-09-07T08:16:02.7387853Z (node:8202) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:16:02.7388513Z 2025-09-07T08:16:02.7388756Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:16:02.7389412Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:16:02.7390102Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:16:02.8686775Z Found 1 objects with prefix pytorch/pytorch/17525296438/linux-jammy-cuda12.8-py3.10-gcc9-sm90/ 2025-09-07T08:16:03.0512009Z Starting download (1/1): /home/alice/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:16:16.8201109Z Finished download (1/1): /home/alice/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:16:16.8208954Z Artifact download has finished successfully 2025-09-07T08:16:16.8525547Z ##[group]Run unzip -o artifacts.zip 2025-09-07T08:16:16.8525817Z unzip -o artifacts.zip 2025-09-07T08:16:17.1923635Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:17.1924006Z env: 2025-09-07T08:16:17.1924210Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:17.1924521Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:17.1924944Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:17.1925298Z ##[endgroup] 2025-09-07T08:16:17.1987182Z Archive: artifacts.zip 2025-09-07T08:16:17.1988532Z creating: dist/ 2025-09-07T08:16:22.8784571Z inflating: dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:16:22.8784988Z creating: dist/vision/ 2025-09-07T08:16:22.8896890Z inflating: dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 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build/bin/FileStoreTest 2025-09-07T08:16:36.2413331Z inflating: build/bin/ProcessGroupMPITest 2025-09-07T08:16:36.2415943Z inflating: build/bin/example_allreduce 2025-09-07T08:16:36.3429017Z inflating: build/bin/Dict_test 2025-09-07T08:16:36.5181380Z inflating: build/bin/Dimname_test 2025-09-07T08:16:36.5234999Z inflating: build/bin/NamedTensor_test 2025-09-07T08:16:36.5296072Z inflating: build/bin/MaybeOwned_test 2025-09-07T08:16:36.5352030Z inflating: build/bin/atest 2025-09-07T08:16:36.5411865Z inflating: build/bin/basic 2025-09-07T08:16:36.5467624Z inflating: build/bin/apply_utils_test 2025-09-07T08:16:36.5519332Z inflating: build/bin/broadcast_test 2025-09-07T08:16:36.5568361Z inflating: build/bin/cpu_allocator_test 2025-09-07T08:16:36.5623815Z inflating: build/bin/cpu_generator_test 2025-09-07T08:16:36.5674125Z inflating: build/bin/cpu_profiling_allocator_test 2025-09-07T08:16:36.5760656Z inflating: build/bin/cpu_rng_test 2025-09-07T08:16:36.5809558Z inflating: build/bin/dlconvertor_test 2025-09-07T08:16:36.5864491Z inflating: build/bin/extension_backend_test 2025-09-07T08:16:36.5916707Z inflating: build/bin/half_test 2025-09-07T08:16:36.6942299Z inflating: build/bin/lazy_tensor_test 2025-09-07T08:16:36.6993597Z inflating: build/bin/memory_format_test 2025-09-07T08:16:36.7044883Z inflating: build/bin/math_kernel_test 2025-09-07T08:16:36.7135428Z inflating: build/bin/ivalue_test 2025-09-07T08:16:36.7186200Z inflating: build/bin/memory_overlapping_test 2025-09-07T08:16:36.7236755Z inflating: build/bin/mobile_memory_cleanup 2025-09-07T08:16:36.7290043Z inflating: build/bin/native_test 2025-09-07T08:16:36.7338174Z inflating: build/bin/operator_name_test 2025-09-07T08:16:36.7386971Z inflating: build/bin/operators_test 2025-09-07T08:16:36.7436139Z inflating: build/bin/packedtensoraccessor_test 2025-09-07T08:16:36.7499377Z inflating: build/bin/pow_test 2025-09-07T08:16:36.7553643Z inflating: build/bin/quantized_test 2025-09-07T08:16:36.7601281Z inflating: build/bin/reduce_ops_test 2025-09-07T08:16:36.7650547Z inflating: build/bin/reportMemoryUsage_test 2025-09-07T08:16:36.7704264Z inflating: build/bin/scalar_tensor_test 2025-09-07T08:16:36.7760078Z inflating: build/bin/scalar_test 2025-09-07T08:16:36.7809064Z inflating: build/bin/StorageUtils_test 2025-09-07T08:16:36.7859632Z inflating: build/bin/stride_properties_test 2025-09-07T08:16:36.7934641Z inflating: build/bin/tensor_iterator_test 2025-09-07T08:16:36.7986240Z inflating: build/bin/test_parallel 2025-09-07T08:16:36.8034006Z inflating: build/bin/thread_init_test 2025-09-07T08:16:36.8086225Z inflating: build/bin/type_ptr_test 2025-09-07T08:16:36.8142377Z inflating: build/bin/type_test 2025-09-07T08:16:36.8192114Z inflating: build/bin/undefined_tensor_test 2025-09-07T08:16:36.8238669Z inflating: build/bin/verify_api_visibility 2025-09-07T08:16:36.8304574Z inflating: build/bin/legacy_vmap_test 2025-09-07T08:16:36.8353197Z inflating: build/bin/weakref_test 2025-09-07T08:16:36.8402281Z inflating: build/bin/xla_tensor_test 2025-09-07T08:16:36.8451760Z inflating: build/bin/wrapdim_test 2025-09-07T08:16:36.8507890Z inflating: build/bin/IListRef_test 2025-09-07T08:16:36.8620039Z inflating: build/bin/kernel_function_legacy_test 2025-09-07T08:16:36.8718890Z inflating: build/bin/List_test 2025-09-07T08:16:36.8781711Z inflating: build/bin/KernelFunction_test 2025-09-07T08:16:36.8871035Z inflating: build/bin/kernel_function_test 2025-09-07T08:16:36.8990702Z inflating: build/bin/kernel_lambda_legacy_test 2025-09-07T08:16:36.9086512Z inflating: build/bin/kernel_lambda_test 2025-09-07T08:16:36.9144191Z inflating: build/bin/kernel_stackbased_test 2025-09-07T08:16:36.9233472Z inflating: build/bin/make_boxed_from_unboxed_functor_test 2025-09-07T08:16:36.9282328Z inflating: build/bin/CppSignature_test 2025-09-07T08:16:36.9334711Z inflating: build/bin/backend_fallback_test 2025-09-07T08:16:36.9381108Z inflating: build/bin/op_allowlist_test 2025-09-07T08:16:37.1145461Z inflating: build/bin/op_registration_test 2025-09-07T08:16:37.2688255Z inflating: build/bin/inline_container_test 2025-09-07T08:16:37.2737757Z inflating: build/bin/cuda_allocator_test 2025-09-07T08:16:37.2787754Z inflating: build/bin/cuda_apply_test 2025-09-07T08:16:37.2843856Z inflating: build/bin/cuda_atomic_ops_test 2025-09-07T08:16:37.2897787Z inflating: build/bin/cuda_caching_host_allocator_test 2025-09-07T08:16:37.2963547Z inflating: build/bin/cuda_complex_math_test 2025-09-07T08:16:37.3019861Z inflating: build/bin/cuda_complex_test 2025-09-07T08:16:37.4235323Z inflating: build/bin/cuda_cub_test 2025-09-07T08:16:37.5875422Z inflating: build/bin/cuda_device_test 2025-09-07T08:16:37.7197149Z inflating: build/bin/cuda_distributions_test 2025-09-07T08:16:37.9068319Z inflating: build/bin/cuda_dlconvertor_test 2025-09-07T08:16:37.9116620Z inflating: build/bin/cuda_exchange_device_test 2025-09-07T08:16:37.9164829Z inflating: build/bin/cuda_half_test 2025-09-07T08:16:37.9218522Z inflating: build/bin/cuda_generator_test 2025-09-07T08:16:37.9267255Z inflating: build/bin/cuda_integer_divider_test 2025-09-07T08:16:37.9314555Z inflating: build/bin/cuda_optional_test 2025-09-07T08:16:37.9364037Z inflating: build/bin/cuda_packedtensoraccessor_test 2025-09-07T08:16:37.9414659Z inflating: build/bin/cuda_reportMemoryUsage_test 2025-09-07T08:16:37.9462452Z inflating: build/bin/cuda_allocatorTraceTracker_test 2025-09-07T08:16:37.9519527Z inflating: build/bin/cuda_stream_test 2025-09-07T08:16:38.0771284Z inflating: build/bin/cuda_cudnn_test 2025-09-07T08:16:38.2597575Z inflating: build/bin/cuda_vectorized_test 2025-09-07T08:16:38.2941850Z inflating: build/bin/test_nativert 2025-09-07T08:16:38.2994627Z inflating: build/bin/test_dist_autograd 2025-09-07T08:16:38.3059729Z inflating: build/bin/test_cpp_rpc 2025-09-07T08:16:38.5554501Z inflating: build/bin/test_api 2025-09-07T08:16:38.7253920Z inflating: build/bin/parallel_benchmark 2025-09-07T08:16:38.7316092Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T08:16:38.7376535Z inflating: build/bin/ProcessGroupNCCLTest 2025-09-07T08:16:38.7431286Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T08:16:38.9226770Z inflating: build/bin/ProcessGroupNCCLErrorsTest 2025-09-07T08:16:39.2803924Z inflating: build/bin/test_jit 2025-09-07T08:16:39.5528502Z inflating: build/bin/test_lazy 2025-09-07T08:16:39.7004723Z inflating: build/bin/torch_shm_manager 2025-09-07T08:16:39.7005265Z creating: .additional_ci_files/ 2025-09-07T08:16:39.7086196Z inflating: .additional_ci_files/test-times.json 2025-09-07T08:16:39.9092252Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T08:16:40.0693002Z ##[group]Run rm artifacts.zip 2025-09-07T08:16:40.0693282Z rm artifacts.zip 2025-09-07T08:16:40.0707855Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:40.0708157Z env: 2025-09-07T08:16:40.0708318Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:40.0708570Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:40.0708919Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:40.0709203Z ##[endgroup] 2025-09-07T08:16:40.5196897Z ##[group]Run df -H 2025-09-07T08:16:40.5197161Z df -H 2025-09-07T08:16:40.5211576Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:40.5211871Z env: 2025-09-07T08:16:40.5212042Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:40.5212288Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:40.5212612Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:40.5212888Z ##[endgroup] 2025-09-07T08:16:40.8058318Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T08:16:40.8058686Z overlay 7.3T 696G 6.6T 10% / 2025-09-07T08:16:40.8058992Z tmpfs 68M 0 68M 0% /dev 2025-09-07T08:16:40.8059295Z shm 68M 0 68M 0% /dev/shm 2025-09-07T08:16:40.8059613Z /dev/root 7.3T 696G 6.6T 10% /home/alice/_work 2025-09-07T08:16:40.8060004Z tmpfs 215G 111k 215G 1% /run/docker.sock 2025-09-07T08:16:40.8060737Z tmpfs 1.1T 13k 1.1T 1% /proc/driver/nvidia 2025-09-07T08:16:40.8061528Z tmpfs 430G 2.9M 430G 1% /run/.ro3168962224/nvidia-persistenced/socket 2025-09-07T08:16:40.8062128Z tmpfs 1.1T 0 1.1T 0% /proc/acpi 2025-09-07T08:16:40.8062430Z tmpfs 1.1T 0 1.1T 0% /proc/scsi 2025-09-07T08:16:40.8062725Z tmpfs 1.1T 0 1.1T 0% /sys/firmware 2025-09-07T08:16:40.8089302Z Prepare all required actions 2025-09-07T08:16:40.8090102Z Getting action download info 2025-09-07T08:16:41.0913121Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T08:16:41.0913425Z with: 2025-09-07T08:16:41.0913608Z env: 2025-09-07T08:16:41.0913786Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:41.0914069Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:41.0914455Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:41.0914783Z ##[endgroup] 2025-09-07T08:16:41.4409479Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:16:41.4409791Z with: 2025-09-07T08:16:41.4409986Z name: td_results 2025-09-07T08:16:41.4410475Z s3-bucket: gha-artifacts 2025-09-07T08:16:41.4410732Z region: us-east-1 2025-09-07T08:16:41.4410948Z env: 2025-09-07T08:16:41.4411138Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:41.4411442Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:41.4411891Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:41.4412233Z ##[endgroup] 2025-09-07T08:16:41.8586124Z (node:8226) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:16:41.8586566Z 2025-09-07T08:16:41.8586751Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:16:41.8587245Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:16:41.8587752Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:16:41.9782493Z Found 0 objects with prefix pytorch/pytorch/17525296438/td_results/ 2025-09-07T08:16:41.9789099Z Artifact download has finished successfully 2025-09-07T08:16:42.0599182Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T08:16:42.0599527Z mkdir -p .additional_ci_files 2025-09-07T08:16:42.0599908Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T08:16:42.0614729Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:42.0615029Z env: 2025-09-07T08:16:42.0615192Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:42.0615459Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:42.0615806Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:42.0616088Z ##[endgroup] 2025-09-07T08:16:42.1044426Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T08:16:42.3941040Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T08:16:42.3941425Z .github/scripts/parse_ref.py 2025-09-07T08:16:42.3956625Z shell: /usr/bin/bash -e {0} 2025-09-07T08:16:42.3956848Z env: 2025-09-07T08:16:42.3957028Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:42.3957289Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:42.3957620Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:42.3957904Z ##[endgroup] 2025-09-07T08:16:42.4523655Z Setting output branch=main 2025-09-07T08:16:42.4621602Z Prepare all required actions 2025-09-07T08:16:42.4621936Z Getting action download info 2025-09-07T08:16:43.0858488Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T08:16:43.0858810Z with: 2025-09-07T08:16:43.0859205Z github-token: *** 2025-09-07T08:16:43.0864318Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T08:16:43.0869573Z job-name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:16:43.0869919Z env: 2025-09-07T08:16:43.0870080Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.0870482Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.0870810Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:43.0871079Z ##[endgroup] 2025-09-07T08:16:43.2538416Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T08:16:43.2538672Z with: 2025-09-07T08:16:43.2538836Z shell: bash 2025-09-07T08:16:43.2539023Z timeout_minutes: 10 2025-09-07T08:16:43.2539225Z max_attempts: 5 2025-09-07T08:16:43.2539425Z retry_wait_seconds: 30 2025-09-07T08:16:43.2540044Z 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 2025-09-07T08:16:43.2540910Z polling_interval_seconds: 1 2025-09-07T08:16:43.2541141Z warning_on_retry: true 2025-09-07T08:16:43.2541353Z continue_on_error: false 2025-09-07T08:16:43.2541556Z env: 2025-09-07T08:16:43.2541726Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.2541987Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.2542366Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:43.2542827Z GITHUB_TOKEN: *** 2025-09-07T08:16:43.2543107Z ##[endgroup] 2025-09-07T08:16:43.3269874Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:16:43.5949597Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:16:44.4719904Z Collecting requests==2.27.1 2025-09-07T08:16:44.5334919Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T08:16:45.3231939Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 67.2 kB/s eta 0:00:00 2025-09-07T08:16:46.2131795Z Collecting pyyaml==6.0.2 2025-09-07T08:16:46.2261817Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T08:16:46.7817091Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 1.3 MB/s eta 0:00:00 2025-09-07T08:16:47.0011416Z Collecting charset-normalizer~=2.0.0 2025-09-07T08:16:47.0137380Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T08:16:47.4837592Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T08:16:47.4842966Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T08:16:47.4847410Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T08:16:47.5517207Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T08:16:49.4792701Z WARNING: The script normalizer is installed in '/home/alice/.local/bin' which is not on PATH. 2025-09-07T08:16:49.4793520Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T08:16:52.1151234Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T08:16:52.3338227Z Command completed after 1 attempt(s). 2025-09-07T08:16:52.5297076Z ##[group]Run set -x 2025-09-07T08:16:52.5297297Z set -x 2025-09-07T08:16:52.5297469Z  2025-09-07T08:16:52.5297773Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:16:52.5298141Z # in runner workspace 2025-09-07T08:16:52.5298435Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T08:16:52.5313427Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:52.5313719Z env: 2025-09-07T08:16:52.5313883Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:52.5314126Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:52.5314451Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:52.5314718Z ##[endgroup] 2025-09-07T08:16:52.5662041Z + python3 /home/alice/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T08:16:52.8908964Z Setting output branch=main 2025-09-07T08:16:52.9397837Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:16:52.9398227Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:16:52.9398500Z echo "Job name: ${JOB_NAME}" 2025-09-07T08:16:52.9398754Z  2025-09-07T08:16:52.9399063Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:16:52.9399451Z # in runner workspace 2025-09-07T08:16:52.9399789Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T08:16:52.9400182Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T08:16:52.9400625Z  --job-name "${JOB_NAME}" \ 2025-09-07T08:16:52.9406451Z  --test-matrix "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" \ 2025-09-07T08:16:52.9411846Z  --selected-test-configs "" \ 2025-09-07T08:16:52.9412096Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T08:16:52.9412323Z  --tag "${TAG}" \ 2025-09-07T08:16:52.9412537Z  --event-name "${EVENT_NAME}" \ 2025-09-07T08:16:52.9412773Z  --schedule "${SCHEDULE}" \ 2025-09-07T08:16:52.9413014Z  --branch "${HEAD_BRANCH}" 2025-09-07T08:16:52.9427207Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:52.9427498Z env: 2025-09-07T08:16:52.9427665Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:52.9427932Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:52.9428253Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:52.9428726Z GITHUB_TOKEN: *** 2025-09-07T08:16:52.9429044Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:16:52.9429390Z PR_NUMBER: 2025-09-07T08:16:52.9429549Z TAG: 2025-09-07T08:16:52.9429694Z EVENT_NAME: schedule 2025-09-07T08:16:52.9429886Z SCHEDULE: 0 7 * * 0 2025-09-07T08:16:52.9430057Z HEAD_BRANCH: main 2025-09-07T08:16:52.9430367Z ##[endgroup] 2025-09-07T08:16:52.9841698Z Workflow: inductor-perf-nightly-h100 2025-09-07T08:16:52.9842123Z Job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:16:53.6620975Z Setting output keep-going=True 2025-09-07T08:16:53.6621361Z Setting output ci-verbose-test-logs=False 2025-09-07T08:16:53.6621695Z Setting output ci-test-showlocals=False 2025-09-07T08:16:53.6622007Z Setting output ci-no-test-timeout=False 2025-09-07T08:16:53.6622334Z Setting output ci-no-td=False 2025-09-07T08:16:53.6622624Z Setting output ci-td-distributed=False 2025-09-07T08:16:53.6637562Z Setting output is-unstable=False 2025-09-07T08:16:53.6637894Z Setting output reenabled-issues= 2025-09-07T08:16:53.6643724Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T08:16:53.6649286Z Setting output is-test-matrix-empty=False 2025-09-07T08:16:53.9291285Z ##[group]Run echo "Filtered matrix:" 2025-09-07T08:16:53.9291577Z echo "Filtered matrix:" 2025-09-07T08:16:53.9296541Z echo "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" 2025-09-07T08:16:53.9301602Z  2025-09-07T08:16:53.9301807Z echo 2025-09-07T08:16:53.9302017Z echo "Is the current job unstable? False" 2025-09-07T08:16:53.9302260Z  2025-09-07T08:16:53.9302403Z echo 2025-09-07T08:16:53.9302587Z echo "Is keep-going label set? True" 2025-09-07T08:16:53.9302840Z  2025-09-07T08:16:53.9303085Z echo 2025-09-07T08:16:53.9303254Z echo "Reenabled issues? " 2025-09-07T08:16:53.9316712Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:53.9317224Z env: 2025-09-07T08:16:53.9317394Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:53.9317635Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:53.9317967Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:53.9318272Z ##[endgroup] 2025-09-07T08:16:54.2575740Z Filtered matrix: 2025-09-07T08:16:54.2586650Z {include: [{config: inductor_huggingface_perf_cuda_h100, shard: 1, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 2, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 3, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 4, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 5, num_shards: 5, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 1, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 2, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 3, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 4, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 5, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 6, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 7, num_shards: 7, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 1, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 2, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 3, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 4, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 5, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 6, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 7, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 8, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 9, num_shards: 9, runner: linux.aws.h100}]} 2025-09-07T08:16:54.2593397Z 2025-09-07T08:16:54.2593495Z Is the current job unstable? False 2025-09-07T08:16:54.2593672Z 2025-09-07T08:16:54.2593771Z Is keep-going label set? True 2025-09-07T08:16:54.2593932Z 2025-09-07T08:16:54.2594011Z Reenabled issues? 2025-09-07T08:16:54.2724200Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:16:54.2724641Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:16:54.2737563Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:54.2737855Z env: 2025-09-07T08:16:54.2738016Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:54.2738260Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:54.2738592Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:54.2738860Z JOB_TIMEOUT: 1440 2025-09-07T08:16:54.2739033Z ##[endgroup] 2025-09-07T08:16:54.7003513Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:54.7003968Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:54.7004322Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:54.7018610Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:54.7018909Z env: 2025-09-07T08:16:54.7019072Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:54.7019323Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:54.7019654Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:54.7019929Z ##[endgroup] 2025-09-07T08:16:54.7759686Z ##[group]Run set -x 2025-09-07T08:16:54.7760040Z set -x 2025-09-07T08:16:54.7760657Z  2025-09-07T08:16:54.7760867Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T08:16:54.7761197Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T08:16:54.7761535Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T08:16:54.7761829Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T08:16:54.7762070Z else 2025-09-07T08:16:54.7762276Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:16:54.7762533Z fi 2025-09-07T08:16:54.7762700Z  2025-09-07T08:16:54.7762905Z # Leaving 1GB for the runner and other things 2025-09-07T08:16:54.7763374Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T08:16:54.7764077Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T08:16:54.7764661Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T08:16:54.7765092Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T08:16:54.7765426Z  2025-09-07T08:16:54.7765631Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:16:54.7765905Z  SHM_OPTS= 2025-09-07T08:16:54.7766095Z  JENKINS_USER= 2025-09-07T08:16:54.7766373Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T08:16:54.7766766Z  # if for some reason cleanup action doesn't stop container 2025-09-07T08:16:54.7767082Z  # when job is cancelled 2025-09-07T08:16:54.7767335Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T08:16:54.7767564Z else 2025-09-07T08:16:54.7767763Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T08:16:54.7768018Z  JENKINS_USER="--user jenkins" 2025-09-07T08:16:54.7768245Z  DOCKER_SHELL_CMD= 2025-09-07T08:16:54.7768431Z fi 2025-09-07T08:16:54.7768583Z  2025-09-07T08:16:54.7768831Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T08:16:54.7769208Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T08:16:54.7769632Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T08:16:54.7770010Z # shellcheck disable=SC2086,SC2090 2025-09-07T08:16:54.7770377Z container_name=$(docker run \ 2025-09-07T08:16:54.7770603Z  ${GPU_FLAG:-} \ 2025-09-07T08:16:54.7770841Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T08:16:54.7771096Z  -e BUILD_ENVIRONMENT \ 2025-09-07T08:16:54.7771314Z  -e PR_NUMBER \ 2025-09-07T08:16:54.7771513Z  -e GITHUB_ACTIONS \ 2025-09-07T08:16:54.7771719Z  -e GITHUB_REPOSITORY \ 2025-09-07T08:16:54.7771931Z  -e GITHUB_WORKFLOW \ 2025-09-07T08:16:54.7772138Z  -e GITHUB_JOB \ 2025-09-07T08:16:54.7772331Z  -e GITHUB_RUN_ID \ 2025-09-07T08:16:54.7772532Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T08:16:54.7772737Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T08:16:54.7772945Z  -e JOB_ID \ 2025-09-07T08:16:54.7773126Z  -e JOB_NAME \ 2025-09-07T08:16:54.7773315Z  -e BASE_SHA \ 2025-09-07T08:16:54.7773490Z  -e BRANCH \ 2025-09-07T08:16:54.7773667Z  -e SHA1 \ 2025-09-07T08:16:54.7773851Z  -e AWS_DEFAULT_REGION \ 2025-09-07T08:16:54.7774060Z  -e IN_WHEEL_TEST \ 2025-09-07T08:16:54.7774252Z  -e SHARD_NUMBER \ 2025-09-07T08:16:54.7774462Z  -e TEST_CONFIG \ 2025-09-07T08:16:54.7774660Z  -e NUM_TEST_SHARDS \ 2025-09-07T08:16:54.7774876Z  -e REENABLED_ISSUES \ 2025-09-07T08:16:54.7775100Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T08:16:54.7775552Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T08:16:54.7775786Z  -e TEST_SHOWLOCALS \ 2025-09-07T08:16:54.7776162Z  -e NO_TEST_TIMEOUT \ 2025-09-07T08:16:54.7776353Z  -e NO_TD \ 2025-09-07T08:16:54.7776535Z  -e TD_DISTRIBUTED \ 2025-09-07T08:16:54.7776757Z  -e PR_LABELS \ 2025-09-07T08:16:54.7776990Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T08:16:54.7777259Z  -e SCCACHE_BUCKET \ 2025-09-07T08:16:54.7777474Z  -e SCCACHE_REGION \ 2025-09-07T08:16:54.7777685Z  -e XLA_CUDA \ 2025-09-07T08:16:54.7777891Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T08:16:54.7778154Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T08:16:54.7778425Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T08:16:54.7778694Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T08:16:54.7778946Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T08:16:54.7779187Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T08:16:54.7779446Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T08:16:54.7779683Z  -e DASHBOARD_TAG \ 2025-09-07T08:16:54.7779893Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T08:16:54.7780146Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T08:16:54.7780616Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T08:16:54.7780915Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T08:16:54.7781203Z  --security-opt seccomp=unconfined \ 2025-09-07T08:16:54.7781448Z  --cap-add=SYS_PTRACE \ 2025-09-07T08:16:54.7781665Z  --ipc=host \ 2025-09-07T08:16:54.7781850Z  ${SHM_OPTS} \ 2025-09-07T08:16:54.7782031Z  --tty \ 2025-09-07T08:16:54.7782195Z  --detach \ 2025-09-07T08:16:54.7782387Z  --name="${container_name}" \ 2025-09-07T08:16:54.7782625Z  ${JENKINS_USER} \ 2025-09-07T08:16:54.7782952Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T08:16:54.7783259Z  -w /var/lib/jenkins/workspace \ 2025-09-07T08:16:54.7783489Z  "${DOCKER_IMAGE}" \ 2025-09-07T08:16:54.7783693Z  ${DOCKER_SHELL_CMD} 2025-09-07T08:16:54.7783883Z ) 2025-09-07T08:16:54.7784102Z # Propagate download.pytorch.org IP to container 2025-09-07T08:16:54.7784574Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T08:16:54.7785081Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T08:16:54.7785386Z  2025-09-07T08:16:54.7785586Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:16:54.7785997Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T08:16:54.7786359Z fi 2025-09-07T08:16:54.7786511Z  2025-09-07T08:16:54.7786864Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T08:16:54.7799974Z shell: /usr/bin/bash -e {0} 2025-09-07T08:16:54.7800196Z env: 2025-09-07T08:16:54.7800513Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:54.7800766Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:54.7801115Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T08:16:54.7801463Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:16:54.7801736Z PR_NUMBER: 2025-09-07T08:16:54.7801929Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T08:16:54.7802185Z GITHUB_WORKFLOW: inductor-perf-nightly-h100 2025-09-07T08:16:54.7802426Z GITHUB_JOB: test 2025-09-07T08:16:54.7802597Z GITHUB_RUN_ID: 17525296438 2025-09-07T08:16:54.7802791Z GITHUB_RUN_NUMBER: 662 2025-09-07T08:16:54.7802977Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T08:16:54.7803153Z JOB_ID: 49775781859 2025-09-07T08:16:54.7803659Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:16:54.7804011Z BRANCH: main 2025-09-07T08:16:54.7804333Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:16:54.7804601Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:16:54.7804867Z TEST_CONFIG: inductor_torchbench_perf_cuda_h100 2025-09-07T08:16:54.7805103Z SHARD_NUMBER: 1 2025-09-07T08:16:54.7805282Z NUM_TEST_SHARDS: 9 2025-09-07T08:16:54.7805459Z REENABLED_ISSUES: 2025-09-07T08:16:54.7805633Z CONTINUE_THROUGH_ERROR: True 2025-09-07T08:16:54.7805838Z VERBOSE_TEST_LOGS: False 2025-09-07T08:16:54.7806026Z TEST_SHOWLOCALS: False 2025-09-07T08:16:54.7806210Z NO_TEST_TIMEOUT: False 2025-09-07T08:16:54.7806377Z NO_TD: False 2025-09-07T08:16:54.7806538Z TD_DISTRIBUTED: False 2025-09-07T08:16:54.7806764Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T08:16:54.7807022Z SCCACHE_REGION: us-east-1 2025-09-07T08:16:54.7807215Z SHM_SIZE: 2g 2025-09-07T08:16:54.7807874Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:16:54.7808552Z XLA_CUDA: 2025-09-07T08:16:54.7808806Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:16:54.7809134Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T08:16:54.7809365Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T08:16:54.7810411Z DASHBOARD_TAG: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:16:54.7811489Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T08:16:54.7811800Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T08:16:54.7812101Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T08:16:54.7812491Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T08:16:54.7812863Z ##[endgroup] 2025-09-07T08:16:55.0442316Z + [[ inductor_torchbench_perf_cuda_h100 == \m\u\l\t\i\g\p\u ]] 2025-09-07T08:16:55.0442704Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *onnx* ]] 2025-09-07T08:16:55.0442999Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:16:55.0445679Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T08:16:55.0455971Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1998.949 ' 2025-09-07T08:16:55.0456248Z + TOTAL_MEMORY_WITH_SWAP=2001 2025-09-07T08:16:55.0456537Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T08:16:55.0456850Z + SHM_OPTS=--shm-size=2g 2025-09-07T08:16:55.0457060Z + JENKINS_USER='--user jenkins' 2025-09-07T08:16:55.0457273Z + DOCKER_SHELL_CMD= 2025-09-07T08:16:55.0465496Z +++ nproc --ignore=2 2025-09-07T08:16:55.0480142Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5227 -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=22 -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=1998g --memory-swap=2001g --env-file=/tmp/github_env_17525296438 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=2g --tty --detach --name= --user jenkins -v /home/alice/_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-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:35:46.6215265Z + container_name=c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T08:35:46.6218242Z + grep download.pytorch.org /etc/hosts 2025-09-07T08:35:46.6219841Z + docker exec -i c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T08:35:46.6672949Z + echo DOCKER_CONTAINER_ID=c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T08:35:46.6675427Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T08:35:46.6677419Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:35:46.6679826Z + docker exec -t c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T08:35:47.0603802Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T08:35:47.3783052Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.19.1) 2025-09-07T08:35:47.3786313Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (4.15.0) 2025-09-07T08:35:47.3790603Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.13.3) 2025-09-07T08:35:47.3794281Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2.8.8) 2025-09-07T08:35:47.3797143Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.1.6) 2025-09-07T08:35:47.3801457Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2025.3.0) 2025-09-07T08:35:47.3813449Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.3.0) 2025-09-07T08:35:47.4132933Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.22.4) 2025-09-07T08:35:47.4150364Z 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==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.3.0) 2025-09-07T08:35:47.4183030Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from jinja2->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.0.2) 2025-09-07T08:35:48.2242595Z Installing collected packages: torch 2025-09-07T08:35:58.0770837Z ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. 2025-09-07T08:35:58.0771775Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T08:35:58.0772206Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T08:35:58.0772695Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T08:35:58.0773281Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T08:35:58.0774014Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T08:35:58.0774751Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T08:35:58.0775816Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T08:35:58.1492127Z + export TERM=vt100 2025-09-07T08:35:58.1492735Z + TERM=vt100 2025-09-07T08:35:58.1495336Z ++ dirname .ci/pytorch/test.sh 2025-09-07T08:35:58.1505250Z + source .ci/pytorch/common.sh 2025-09-07T08:35:58.1508129Z +++ dirname .ci/pytorch/common.sh 2025-09-07T08:35:58.1515550Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T08:35:58.1516412Z +++ declare -f -t trap_add 2025-09-07T08:35:58.1520125Z ++ set -ex -o pipefail 2025-09-07T08:35:58.1520553Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:35:58.1520878Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T08:35:58.1525079Z ++ dirname .ci/pytorch/test.sh 2025-09-07T08:35:58.1535237Z + source .ci/pytorch/common-build.sh 2025-09-07T08:35:58.1536806Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *win-* ]] 2025-09-07T08:35:58.1545337Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T08:35:58.1553663Z +++ cd .ci/pytorch 2025-09-07T08:35:58.1554489Z +++ pwd -P 2025-09-07T08:35:58.1556396Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T08:35:58.1556846Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-pch* ]] 2025-09-07T08:35:58.1557167Z ++ which sccache 2025-09-07T08:35:58.1572015Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T08:35:58.1572339Z ++ sccache --stop-server 2025-09-07T08:35:58.1601058Z ++ true 2025-09-07T08:35:58.1601273Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T08:35:58.1612508Z ++ trap_add sccache_epilogue EXIT 2025-09-07T08:35:58.1612802Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T08:35:58.1613030Z ++ shift 2025-09-07T08:35:58.1613209Z ++ for trap_add_name in "$@" 2025-09-07T08:35:58.1620193Z ++++ trap -p EXIT 2025-09-07T08:35:58.1622681Z +++ eval 'extract_trap_cmd ' 2025-09-07T08:35:58.1622990Z ++++ extract_trap_cmd 2025-09-07T08:35:58.1623202Z ++++ printf '%s\n' '' 2025-09-07T08:35:58.1623413Z +++ printf '%s\n' sccache_epilogue 2025-09-07T08:35:58.1625601Z ++ trap -- ' 2025-09-07T08:35:58.1625887Z sccache_epilogue' EXIT 2025-09-07T08:35:58.1626196Z ++ [[ -n 1 ]] 2025-09-07T08:35:58.1626610Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T08:35:58.1627280Z Skipping sccache server initialization, setting environment variables 2025-09-07T08:35:58.1627646Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:35:58.1627875Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:35:58.1628159Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:35:58.1628515Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:35:58.1628847Z ++ export RUST_LOG=sccache::server=error 2025-09-07T08:35:58.1629120Z ++ RUST_LOG=sccache::server=error 2025-09-07T08:35:58.1629357Z ++ sccache --zero-stats 2025-09-07T08:35:58.5327143Z Statistics zeroed. 2025-09-07T08:35:58.5335104Z ++ which ccache 2025-09-07T08:35:58.5349944Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *rocm* ]] 2025-09-07T08:35:58.5350645Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *s390x* ]] 2025-09-07T08:35:58.5351095Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T08:35:58.5353666Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T08:35:58.5365957Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T08:35:58.5366353Z + trap_add cleanup_workspace EXIT 2025-09-07T08:35:58.5366698Z + trap_add_cmd=cleanup_workspace 2025-09-07T08:35:58.5366980Z + shift 2025-09-07T08:35:58.5367212Z + for trap_add_name in "$@" 2025-09-07T08:35:58.5373861Z +++ trap -p EXIT 2025-09-07T08:35:58.5376351Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T08:35:58.5376625Z sccache_epilogue'\'' EXIT' 2025-09-07T08:35:58.5376864Z +++ extract_trap_cmd trap -- ' 2025-09-07T08:35:58.5377083Z sccache_epilogue' EXIT 2025-09-07T08:35:58.5377298Z +++ printf '%s\n' ' 2025-09-07T08:35:58.5377488Z sccache_epilogue' 2025-09-07T08:35:58.5377692Z ++ printf '%s\n' cleanup_workspace 2025-09-07T08:35:58.5379244Z + trap -- ' 2025-09-07T08:35:58.5379521Z sccache_epilogue 2025-09-07T08:35:58.5379769Z cleanup_workspace' EXIT 2025-09-07T08:35:58.5380499Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T08:36:08.6406016Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T08:36:08.6430105Z + echo 'Environment variables:' 2025-09-07T08:36:08.6430734Z Environment variables: 2025-09-07T08:36:08.6430949Z + env 2025-09-07T08:36:08.6440381Z GITHUB_WORKSPACE=/home/alice/_work/pytorch/pytorch 2025-09-07T08:36:08.6440711Z CONTINUE_THROUGH_ERROR=True 2025-09-07T08:36:08.6441072Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:36:08.6447294Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T08:36:08.6447589Z HOSTNAME=c52ec34ab417 2025-09-07T08:36:08.6448028Z GITHUB_PATH=/home/alice/_work/_temp/_runner_file_commands/add_path_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6448506Z GITHUB_ACTION=__run_2 2025-09-07T08:36:08.6448735Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T08:36:08.6448986Z GITHUB_RUN_NUMBER=662 2025-09-07T08:36:08.6449232Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T08:36:08.6449554Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T08:36:08.6449893Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T08:36:08.6450184Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:36:08.6450765Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T08:36:08.6451038Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T08:36:08.6451313Z GITHUB_REF_TYPE=branch 2025-09-07T08:36:08.6451568Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.6451855Z XLA_CUDA= 2025-09-07T08:36:08.6452044Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T08:36:08.6452399Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T08:36:08.6452764Z *** 2025-09-07T08:36:08.6452951Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T08:36:08.6453202Z GITHUB_ACTIONS=true 2025-09-07T08:36:08.6453420Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:36:08.6453709Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:36:08.6454043Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.6454367Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.6454927Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T08:36:08.6455452Z UCC_HOME=/usr 2025-09-07T08:36:08.6455646Z VERBOSE_TEST_LOGS=False 2025-09-07T08:36:08.6455868Z GITHUB_REF=refs/heads/main 2025-09-07T08:36:08.6456083Z SHARD_NUMBER=1 2025-09-07T08:36:08.6456285Z GITHUB_REF_PROTECTED=true 2025-09-07T08:36:08.6456506Z HOME=/var/lib/jenkins 2025-09-07T08:36:08.6456717Z SCCACHE_SERVER_PORT=5227 2025-09-07T08:36:08.6456963Z GITHUB_API_URL=https://api.github.com 2025-09-07T08:36:08.6457256Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T08:36:08.6457564Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T08:36:08.6457858Z USE_SYSTEM_NCCL=1 2025-09-07T08:36:08.6458053Z NUM_TEST_SHARDS=9 2025-09-07T08:36:08.6458273Z UCX_HOME=/usr 2025-09-07T08:36:08.6458636Z GITHUB_STATE=/home/alice/_work/_temp/_runner_file_commands/save_state_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6459174Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:36:08.6459680Z GITHUB_ENV=/home/alice/_work/_temp/_runner_file_commands/set_env_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6460141Z GITHUB_EVENT_PATH=/home/alice/_work/_temp/_github_workflow/event.json 2025-09-07T08:36:08.6460594Z GITHUB_EVENT_NAME=schedule 2025-09-07T08:36:08.6461493Z DASHBOARD_TAG=training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:36:08.6462398Z GITHUB_RUN_ID=17525296438 2025-09-07T08:36:08.6462582Z INSTALLED_OPENBLAS= 2025-09-07T08:36:08.6463059Z GITHUB_STEP_SUMMARY=/home/alice/_work/_temp/_runner_file_commands/step_summary_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6463501Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T08:36:08.6463704Z PR_NUMBER= 2025-09-07T08:36:08.6463858Z DESIRED_CUDA=12.8.1 2025-09-07T08:36:08.6464383Z GITHUB_RUN_ATTEMPT=1 2025-09-07T08:36:08.6464590Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T08:36:08.6465008Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T08:36:08.6465254Z TERM=vt100 2025-09-07T08:36:08.6465412Z INSTALLED_VISION=yes 2025-09-07T08:36:08.6465587Z BRANCH=main 2025-09-07T08:36:08.6465748Z SCCACHE_REGION=us-east-1 2025-09-07T08:36:08.6465943Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T08:36:08.6466157Z CUDA_PATH=/usr/local/cuda 2025-09-07T08:36:08.6466475Z GITHUB_ACTION_PATH=/home/alice/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T08:36:08.6466844Z GITHUB_SERVER_URL=https://github.com 2025-09-07T08:36:08.6467104Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T08:36:08.6467354Z REENABLED_ISSUES= 2025-09-07T08:36:08.6467519Z DOCS= 2025-09-07T08:36:08.6467667Z SHLVL=1 2025-09-07T08:36:08.6467809Z MAX_JOBS=22 2025-09-07T08:36:08.6467970Z GITHUB_ACTOR_ID=97764156 2025-09-07T08:36:08.6468224Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.6468497Z GITHUB_REF_NAME=main 2025-09-07T08:36:08.6468769Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:36:08.6469083Z GITHUB_JOB=test 2025-09-07T08:36:08.6469266Z NO_TEST_TIMEOUT=False 2025-09-07T08:36:08.6469453Z TD_DISTRIBUTED=False 2025-09-07T08:36:08.6469639Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T08:36:08.6469860Z GITHUB_RETENTION_DAYS=90 2025-09-07T08:36:08.6470051Z OPENSSL_DIR=/opt/openssl 2025-09-07T08:36:08.6470369Z GITHUB_ACTION_REPOSITORY= 2025-09-07T08:36:08.6470915Z 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 2025-09-07T08:36:08.6471476Z GITHUB_BASE_REF= 2025-09-07T08:36:08.6471644Z INSTALLED_ACL= 2025-09-07T08:36:08.6471969Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T08:36:08.6472330Z CI=true 2025-09-07T08:36:08.6472502Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T08:36:08.6472752Z RUST_LOG=sccache::server=error 2025-09-07T08:36:08.6472950Z JOB_ID=49775781859 2025-09-07T08:36:08.6473118Z GITHUB_HEAD_REF= 2025-09-07T08:36:08.6473289Z GITHUB_ACTION_REF= 2025-09-07T08:36:08.6473501Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T08:36:08.6473761Z TEST_SHOWLOCALS=False 2025-09-07T08:36:08.6473966Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T08:36:08.6474217Z DEBIAN_FRONTEND=noninteractive 2025-09-07T08:36:08.6474602Z GITHUB_OUTPUT=/home/alice/_work/_temp/_runner_file_commands/set_output_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6474993Z NO_TD=False 2025-09-07T08:36:08.6475174Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T08:36:08.6475399Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T08:36:08.6475623Z _=/usr/bin/env 2025-09-07T08:36:08.6475856Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T08:36:08.6719380Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T08:36:08.6720085Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T08:36:08.6720866Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T08:36:08.6721481Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T08:36:08.6721953Z + BUILD_DIR=build 2025-09-07T08:36:08.6722226Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T08:36:08.6722540Z + BUILD_BIN_DIR=build/bin 2025-09-07T08:36:08.6722811Z + SHARD_NUMBER=1 2025-09-07T08:36:08.6723059Z + NUM_TEST_SHARDS=9 2025-09-07T08:36:08.6723333Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.6723660Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.6723962Z + export VALGRIND=ON 2025-09-07T08:36:08.6724240Z + VALGRIND=ON 2025-09-07T08:36:08.6724578Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *clang9* ]] 2025-09-07T08:36:08.6725032Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T08:36:08.6812111Z + detect_cuda_arch 2025-09-07T08:36:08.6812475Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:08.6812979Z + command -v nvidia-smi 2025-09-07T08:36:08.6813183Z /usr/bin/nvidia-smi 2025-09-07T08:36:08.6813453Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T08:36:08.6813734Z ++ tail -n 1 2025-09-07T08:36:08.6965529Z + TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T08:36:08.6965809Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T08:36:08.6966165Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *s390x* ]] 2025-09-07T08:36:08.6966516Z + [[ 0 == \1 ]] 2025-09-07T08:36:08.6966733Z + [[ True == \1 ]] 2025-09-07T08:36:08.6967023Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *bazel* ]] 2025-09-07T08:36:08.6971189Z ++ realpath build/custom_test_artifacts 2025-09-07T08:36:08.6982842Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T08:36:08.6983362Z + [[ -n '' ]] 2025-09-07T08:36:08.6983589Z + echo 'Environment variables' 2025-09-07T08:36:08.6983854Z Environment variables 2025-09-07T08:36:08.6984077Z + env 2025-09-07T08:36:08.6991591Z GITHUB_WORKSPACE=/home/alice/_work/pytorch/pytorch 2025-09-07T08:36:08.6991943Z CONTINUE_THROUGH_ERROR=True 2025-09-07T08:36:08.6992299Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:36:08.6992821Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T08:36:08.6993096Z HOSTNAME=c52ec34ab417 2025-09-07T08:36:08.6993555Z GITHUB_PATH=/home/alice/_work/_temp/_runner_file_commands/add_path_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.6994062Z GITHUB_ACTION=__run_2 2025-09-07T08:36:08.6994305Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T08:36:08.6994572Z GITHUB_RUN_NUMBER=662 2025-09-07T08:36:08.6994841Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T08:36:08.6995164Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T08:36:08.6995461Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T08:36:08.6995750Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:36:08.6996119Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T08:36:08.6996414Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T08:36:08.6996709Z GITHUB_REF_TYPE=branch 2025-09-07T08:36:08.6996942Z TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T08:36:08.6997232Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.6997538Z XLA_CUDA= 2025-09-07T08:36:08.6997747Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T08:36:08.6998121Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T08:36:08.6998632Z *** 2025-09-07T08:36:08.6998838Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T08:36:08.6999103Z GITHUB_ACTIONS=true 2025-09-07T08:36:08.6999336Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:36:08.6999646Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:36:08.7000007Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.7000495Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.7001103Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T08:36:08.7001656Z UCC_HOME=/usr 2025-09-07T08:36:08.7001876Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.7002130Z VERBOSE_TEST_LOGS=False 2025-09-07T08:36:08.7002374Z GITHUB_REF=refs/heads/main 2025-09-07T08:36:08.7002607Z SHARD_NUMBER=1 2025-09-07T08:36:08.7002823Z GITHUB_REF_PROTECTED=true 2025-09-07T08:36:08.7003078Z HOME=/var/lib/jenkins 2025-09-07T08:36:08.7003307Z SCCACHE_SERVER_PORT=5227 2025-09-07T08:36:08.7003571Z GITHUB_API_URL=https://api.github.com 2025-09-07T08:36:08.7003878Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T08:36:08.7004193Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T08:36:08.7004506Z USE_SYSTEM_NCCL=1 2025-09-07T08:36:08.7004715Z NUM_TEST_SHARDS=9 2025-09-07T08:36:08.7004920Z UCX_HOME=/usr 2025-09-07T08:36:08.7005405Z GITHUB_STATE=/home/alice/_work/_temp/_runner_file_commands/save_state_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.7006090Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T08:36:08.7006984Z GITHUB_ENV=/home/alice/_work/_temp/_runner_file_commands/set_env_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.7007583Z GITHUB_EVENT_PATH=/home/alice/_work/_temp/_github_workflow/event.json 2025-09-07T08:36:08.7008137Z GITHUB_EVENT_NAME=schedule 2025-09-07T08:36:08.7009086Z DASHBOARD_TAG=training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:36:08.7009980Z GITHUB_RUN_ID=17525296438 2025-09-07T08:36:08.7010182Z INSTALLED_OPENBLAS= 2025-09-07T08:36:08.7010695Z GITHUB_STEP_SUMMARY=/home/alice/_work/_temp/_runner_file_commands/step_summary_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.7011124Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T08:36:08.7011322Z PR_NUMBER= 2025-09-07T08:36:08.7011478Z DESIRED_CUDA=12.8.1 2025-09-07T08:36:08.7011643Z GITHUB_RUN_ATTEMPT=1 2025-09-07T08:36:08.7011815Z VALGRIND=ON 2025-09-07T08:36:08.7011978Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T08:36:08.7012224Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T08:36:08.7012470Z TERM=vt100 2025-09-07T08:36:08.7012632Z INSTALLED_VISION=yes 2025-09-07T08:36:08.7012802Z BRANCH=main 2025-09-07T08:36:08.7012960Z SCCACHE_REGION=us-east-1 2025-09-07T08:36:08.7013162Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T08:36:08.7013373Z CUDA_PATH=/usr/local/cuda 2025-09-07T08:36:08.7013688Z GITHUB_ACTION_PATH=/home/alice/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T08:36:08.7014047Z GITHUB_SERVER_URL=https://github.com 2025-09-07T08:36:08.7014296Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T08:36:08.7014536Z REENABLED_ISSUES= 2025-09-07T08:36:08.7014692Z DOCS= 2025-09-07T08:36:08.7014832Z SHLVL=1 2025-09-07T08:36:08.7014971Z MAX_JOBS=22 2025-09-07T08:36:08.7015127Z GITHUB_ACTOR_ID=97764156 2025-09-07T08:36:08.7015370Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.7015642Z GITHUB_REF_NAME=main 2025-09-07T08:36:08.7015913Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:36:08.7016215Z GITHUB_JOB=test 2025-09-07T08:36:08.7016402Z NO_TEST_TIMEOUT=False 2025-09-07T08:36:08.7016581Z TD_DISTRIBUTED=False 2025-09-07T08:36:08.7016765Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T08:36:08.7016982Z GITHUB_RETENTION_DAYS=90 2025-09-07T08:36:08.7017168Z OPENSSL_DIR=/opt/openssl 2025-09-07T08:36:08.7017358Z GITHUB_ACTION_REPOSITORY= 2025-09-07T08:36:08.7017896Z 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 2025-09-07T08:36:08.7018464Z GITHUB_BASE_REF= 2025-09-07T08:36:08.7018627Z INSTALLED_ACL= 2025-09-07T08:36:08.7018960Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T08:36:08.7019315Z CI=true 2025-09-07T08:36:08.7019475Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T08:36:08.7019706Z RUST_LOG=sccache::server=error 2025-09-07T08:36:08.7019904Z JOB_ID=49775781859 2025-09-07T08:36:08.7020061Z GITHUB_HEAD_REF= 2025-09-07T08:36:08.7020349Z GITHUB_ACTION_REF= 2025-09-07T08:36:08.7020575Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T08:36:08.7020828Z TEST_SHOWLOCALS=False 2025-09-07T08:36:08.7021032Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T08:36:08.7021283Z DEBIAN_FRONTEND=noninteractive 2025-09-07T08:36:08.7021667Z GITHUB_OUTPUT=/home/alice/_work/_temp/_runner_file_commands/set_output_820ce813-0e44-41e4-8731-2cb3b80e4f4a 2025-09-07T08:36:08.7022064Z NO_TD=False 2025-09-07T08:36:08.7022247Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T08:36:08.7022476Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T08:36:08.7022700Z _=/usr/bin/env 2025-09-07T08:36:08.7022951Z + echo 'Testing pytorch' 2025-09-07T08:36:08.7023136Z Testing pytorch 2025-09-07T08:36:08.7023311Z + export LANG=C.UTF-8 2025-09-07T08:36:08.7023485Z + LANG=C.UTF-8 2025-09-07T08:36:08.7023642Z + PR_NUMBER= 2025-09-07T08:36:08.7024023Z + [[ inductor_torchbench_perf_cuda_h100 == \d\e\f\a\u\l\t ]] 2025-09-07T08:36:08.7024364Z + [[ inductor_torchbench_perf_cuda_h100 == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T08:36:08.7024865Z + [[ inductor_torchbench_perf_cuda_h100 == \s\l\o\w ]] 2025-09-07T08:36:08.7025190Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *slow-gradcheck* ]] 2025-09-07T08:36:08.7025519Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:08.7025817Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T08:36:08.7026069Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T08:36:08.7026327Z + [[ inductor_torchbench_perf_cuda_h100 == *crossref* ]] 2025-09-07T08:36:08.7026615Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:08.7026900Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T08:36:08.7027198Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T08:36:08.7027461Z + pip_install ninja==1.10.2 2025-09-07T08:36:08.7027720Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:08.7028053Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T08:36:09.7156684Z Collecting ninja==1.10.2 2025-09-07T08:36:09.7535241Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T08:36:10.1846770Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T08:36:12.1761871Z Installing collected packages: ninja 2025-09-07T08:36:12.1762738Z Attempting uninstall: ninja 2025-09-07T08:36:12.1770656Z Found existing installation: ninja 1.11.1.3 2025-09-07T08:36:12.1792696Z Uninstalling ninja-1.11.1.3: 2025-09-07T08:36:12.7418696Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T08:36:14.2020444Z Successfully installed ninja-1.10.2 2025-09-07T08:36:14.2754176Z + 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 2025-09-07T08:36:14.2755888Z + 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 2025-09-07T08:36:14.2756930Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T08:36:14.2757375Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *asan* ]] 2025-09-07T08:36:14.2757812Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-debug* ]] 2025-09-07T08:36:14.2758246Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T08:36:14.2758858Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass' 2025-09-07T08:36:14.2759625Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass 2025-09-07T08:36:14.2760146Z + cd test 2025-09-07T08:36:14.2760646Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T08:36:14.7619693Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:14.7621173Z import pynvml # type: ignore[import] 2025-09-07T08:36:15.7660197Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T08:36:15.7661066Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T08:36:15.7661499Z + [[ inductor_torchbench_perf_cuda_h100 == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T08:36:15.7664002Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T08:36:15.7664643Z + [[ inductor_torchbench_perf_cuda_h100 == *pr_time_benchmarks* ]] 2025-09-07T08:36:15.7665007Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamo_eager* ]] 2025-09-07T08:36:15.7665353Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_eager* ]] 2025-09-07T08:36:15.7666451Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_inductor* ]] 2025-09-07T08:36:15.7666818Z + [[ inductor_torchbench_perf_cuda_h100 == *max_autotune_inductor* ]] 2025-09-07T08:36:15.7667418Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor* ]] 2025-09-07T08:36:15.7667714Z + [[ inductor_torchbench_perf_cuda_h100 != *perf* ]] 2025-09-07T08:36:15.7668012Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamic* ]] 2025-09-07T08:36:15.7668296Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T08:36:15.7668580Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T08:36:15.7682639Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T08:36:15.7683029Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-bazel-* ]] 2025-09-07T08:36:15.7686622Z + cd test 2025-09-07T08:36:15.7687129Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T08:36:16.2529131Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:16.2530186Z import pynvml # type: ignore[import] 2025-09-07T08:36:17.7652626Z PyTorch built with: 2025-09-07T08:36:17.7652901Z - GCC 9.5 2025-09-07T08:36:17.7653105Z - C++ Version: 201703 2025-09-07T08:36:17.7653621Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T08:36:17.7654277Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T08:36:17.7654681Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T08:36:17.7654985Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T08:36:17.7655278Z - NNPACK is enabled 2025-09-07T08:36:17.7655518Z - CPU capability usage: AVX2 2025-09-07T08:36:17.7655765Z - CUDA Runtime 12.8 2025-09-07T08:36:17.7656069Z - NVCC architecture flags: -gencode;arch=compute_90,code=sm_90 2025-09-07T08:36:17.7656436Z - CuDNN 90.8 2025-09-07T08:36:17.7660846Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=93fb23d6fae7c4e82c4239a1033e522088742634, CUDA_VERSION=12.8, CUDNN_VERSION=9.8.0, CXX_COMPILER=/opt/cache/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=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=2.9.0, 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, 2025-09-07T08:36:17.7664700Z 2025-09-07T08:36:19.7506210Z + cd test 2025-09-07T08:36:19.7506584Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T08:36:20.2530868Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:20.2531916Z import pynvml # type: ignore[import] 2025-09-07T08:36:20.9765484Z ATen/Parallel: 2025-09-07T08:36:20.9765769Z at::get_num_threads() : 24 2025-09-07T08:36:20.9766046Z at::get_num_interop_threads() : 96 2025-09-07T08:36:20.9766346Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T08:36:20.9767058Z omp_get_max_threads() : 24 2025-09-07T08:36:20.9767581Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T08:36:20.9768327Z mkl_get_max_threads() : 24 2025-09-07T08:36:20.9768687Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T08:36:20.9769102Z std::thread::hardware_concurrency() : 192 2025-09-07T08:36:20.9769404Z Environment variables: 2025-09-07T08:36:20.9769662Z OMP_NUM_THREADS : [not set] 2025-09-07T08:36:20.9769911Z MKL_NUM_THREADS : [not set] 2025-09-07T08:36:20.9770160Z ATen parallel backend: OpenMP 2025-09-07T08:36:20.9770735Z 2025-09-07T08:36:21.3266449Z + [[ inductor_torchbench_perf_cuda_h100 == *numpy_2* ]] 2025-09-07T08:36:21.3266905Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T08:36:21.3267234Z + [[ inductor_torchbench_perf_cuda_h100 == *backward* ]] 2025-09-07T08:36:21.3267544Z + [[ inductor_torchbench_perf_cuda_h100 == *xla* ]] 2025-09-07T08:36:21.3267847Z + [[ inductor_torchbench_perf_cuda_h100 == *vllm* ]] 2025-09-07T08:36:21.3268154Z + [[ inductor_torchbench_perf_cuda_h100 == *executorch* ]] 2025-09-07T08:36:21.3268498Z + [[ inductor_torchbench_perf_cuda_h100 == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T08:36:21.3268862Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T08:36:21.3269193Z + [[ inductor_torchbench_perf_cuda_h100 == distributed ]] 2025-09-07T08:36:21.3269534Z + [[ inductor_torchbench_perf_cuda_h100 == *operator_benchmark* ]] 2025-09-07T08:36:21.3269923Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_distributed* ]] 2025-09-07T08:36:21.3270618Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-halide* ]] 2025-09-07T08:36:21.3271007Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-triton-cpu* ]] 2025-09-07T08:36:21.3271446Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-micro-benchmark* ]] 2025-09-07T08:36:21.3271882Z + [[ inductor_torchbench_perf_cuda_h100 == *huggingface* ]] 2025-09-07T08:36:21.3272239Z + [[ inductor_torchbench_perf_cuda_h100 == *timm* ]] 2025-09-07T08:36:21.3272573Z + [[ inductor_torchbench_perf_cuda_h100 == cachebench ]] 2025-09-07T08:36:21.3272945Z + [[ inductor_torchbench_perf_cuda_h100 == verify_cachebench ]] 2025-09-07T08:36:21.3273322Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench* ]] 2025-09-07T08:36:21.3273638Z + install_torchaudio 2025-09-07T08:36:21.3273850Z + local commit 2025-09-07T08:36:21.3274055Z ++ get_pinned_commit audio 2025-09-07T08:36:21.3274303Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T08:36:21.3289178Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T08:36:21.3289730Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T08:36:21.3290614Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T08:36:21.3291088Z + local wheel_dir=dist/audio 2025-09-07T08:36:21.3291288Z + local found_whl=0 2025-09-07T08:36:21.3291484Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:21.3291808Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:21.3292129Z + found_whl=1 2025-09-07T08:36:21.3292286Z + break 2025-09-07T08:36:21.3292424Z + '[' 1 == 0 ']' 2025-09-07T08:36:21.3292613Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:21.3292965Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.3293418Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:21.3293728Z + local args 2025-09-07T08:36:21.3294004Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:21.3294338Z + for path in "${args[@]}" 2025-09-07T08:36:21.3294658Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:21.3295109Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.3295918Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.6644407Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.6703222Z Installing collected packages: torchaudio 2025-09-07T08:36:23.9102363Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T08:36:24.0642358Z + install_torchvision 2025-09-07T08:36:24.0642652Z + local orig_preload 2025-09-07T08:36:24.0642921Z + local commit 2025-09-07T08:36:24.0648361Z ++ get_pinned_commit vision 2025-09-07T08:36:24.0648688Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T08:36:24.2181922Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T08:36:24.2182388Z + orig_preload= 2025-09-07T08:36:24.2182614Z + '[' -n '' ']' 2025-09-07T08:36:24.2182991Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:24.2183326Z + export FORCE_CUDA=1 2025-09-07T08:36:24.2183544Z + FORCE_CUDA=1 2025-09-07T08:36:24.2183757Z + export WITH_CUDA=1 2025-09-07T08:36:24.2183976Z + WITH_CUDA=1 2025-09-07T08:36:24.2184512Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T08:36:24.2185339Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T08:36:24.2185849Z + local wheel_dir=dist/vision 2025-09-07T08:36:24.2186094Z + local found_whl=0 2025-09-07T08:36:24.2186328Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:24.2186743Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:24.2187145Z + found_whl=1 2025-09-07T08:36:24.2187335Z + break 2025-09-07T08:36:24.2187509Z + '[' 1 == 0 ']' 2025-09-07T08:36:24.2187717Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:24.2188174Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.2188775Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:24.2189175Z + local args 2025-09-07T08:36:24.2189532Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:24.2189962Z + for path in "${args[@]}" 2025-09-07T08:36:24.2190769Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:24.2191404Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.2192097Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.5710103Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.5796651Z Installing collected packages: torchvision 2025-09-07T08:36:26.1274160Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T08:36:26.1679362Z + '[' -n '' ']' 2025-09-07T08:36:26.1679581Z + id=0 2025-09-07T08:36:26.1679794Z + pip_install opencv-python==4.8.0.74 2025-09-07T08:36:26.1680184Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:26.1680976Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T08:36:27.7981320Z Collecting opencv-python==4.8.0.74 2025-09-07T08:36:27.8398383Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T08:36:29.1688695Z Requirement already satisfied: numpy>=1.21.2 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from opencv-python==4.8.0.74) (1.22.4) 2025-09-07T08:36:29.1826178Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T08:36:33.8173806Z Installing collected packages: opencv-python 2025-09-07T08:36:33.8174184Z Attempting uninstall: opencv-python 2025-09-07T08:36:33.8185034Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T08:36:33.8269000Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T08:36:33.9947479Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T08:36:36.6137628Z Successfully installed opencv-python-4.8.0.74 2025-09-07T08:36:36.9695151Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T08:36:36.9695761Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T08:36:36.9696295Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench_gcp_smoketest* ]] 2025-09-07T08:36:36.9696711Z + [[ inductor_torchbench_perf_cuda_h100 != *cpu* ]] 2025-09-07T08:36:36.9697027Z + install_torchrec_and_fbgemm 2025-09-07T08:36:36.9697290Z + local torchrec_commit 2025-09-07T08:36:36.9702814Z ++ get_pinned_commit torchrec 2025-09-07T08:36:36.9703187Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T08:36:36.9719511Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T08:36:36.9719837Z + local fbgemm_commit 2025-09-07T08:36:36.9724063Z ++ get_pinned_commit fbgemm 2025-09-07T08:36:36.9724345Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T08:36:36.9738410Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T08:36:36.9738773Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:36.9739079Z + pip_uninstall torchrec-nightly 2025-09-07T08:36:36.9739341Z + pip3 uninstall -y torchrec-nightly 2025-09-07T08:36:37.3217162Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T08:36:37.3586125Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T08:36:37.3586667Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T08:36:37.6999337Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T08:36:37.7287577Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T08:36:37.7288087Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:37.7288679Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T08:36:38.0623451Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T08:36:38.0624885Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T08:36:38.0627193Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T08:36:38.0637982Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T08:36:38.0640940Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T08:36:38.0647040Z Requirement already satisfied: tomli>=2.0.1 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (2.2.1) 2025-09-07T08:36:38.0687414Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T08:36:38.0695613Z Requirement already satisfied: wheel>=0.32.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (0.45.1) 2025-09-07T08:36:38.0702152Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T08:36:38.0705239Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T08:36:38.0779045Z Requirement already satisfied: mypy-extensions>=0.3.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from typing-inspect->pyre-extensions) (1.1.0) 2025-09-07T08:36:38.9579209Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:38.9579915Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T08:36:38.9676644Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T08:36:38.9677348Z + local wheel_dir=dist/torchrec 2025-09-07T08:36:38.9677891Z + local found_whl=0 2025-09-07T08:36:38.9678130Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:38.9678460Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T08:36:38.9678791Z + found_whl=1 2025-09-07T08:36:38.9678999Z + break 2025-09-07T08:36:38.9679180Z + '[' 1 == 0 ']' 2025-09-07T08:36:38.9679407Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:38.9679767Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:38.9680350Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T08:36:38.9680675Z + local args 2025-09-07T08:36:38.9680951Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T08:36:38.9681309Z + for path in "${args[@]}" 2025-09-07T08:36:38.9681645Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T08:36:38.9682111Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:38.9682621Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:39.2975334Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:39.3035480Z Installing collected packages: torchrec 2025-09-07T08:36:39.5795485Z Successfully installed torchrec-0.3.2 2025-09-07T08:36:39.6103275Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T08:36:39.6104312Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T08:36:39.6104931Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T08:36:39.6105195Z + local found_whl=0 2025-09-07T08:36:39.6105452Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:39.6105855Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:39.6106246Z + found_whl=1 2025-09-07T08:36:39.6106465Z + break 2025-09-07T08:36:39.6106674Z + '[' 1 == 0 ']' 2025-09-07T08:36:39.6106927Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:39.6107412Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:39.6107967Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:39.6108350Z + local args 2025-09-07T08:36:39.6108679Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:39.6109084Z + for path in "${args[@]}" 2025-09-07T08:36:39.6109485Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:39.6110064Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:39.6110897Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:39.9557533Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:40.0491567Z Installing collected packages: fbgemm-gpu 2025-09-07T08:36:41.8384810Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T08:36:41.8677075Z + PYTHONPATH=/torchbench 2025-09-07T08:36:41.8677351Z + test_dynamo_benchmark torchbench 0 2025-09-07T08:36:41.8686224Z ++ pwd 2025-09-07T08:36:41.8689990Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:41.8690488Z + local suite=torchbench 2025-09-07T08:36:41.8690694Z + shift 2025-09-07T08:36:41.8690880Z + local shard_id=0 2025-09-07T08:36:41.8691075Z + shift 2025-09-07T08:36:41.8691567Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T08:36:41.8691923Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T08:36:41.8692248Z + [[ inductor_torchbench_perf_cuda_h100 == *b200* ]] 2025-09-07T08:36:41.8700424Z + test_single_dynamo_benchmark dashboard torchbench 0 2025-09-07T08:36:41.8700759Z ++ pwd 2025-09-07T08:36:41.8701477Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:41.8701882Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:41.8717756Z + local name=dashboard 2025-09-07T08:36:41.8717996Z + shift 2025-09-07T08:36:41.8718193Z + local suite=torchbench 2025-09-07T08:36:41.8718427Z + shift 2025-09-07T08:36:41.8718613Z + local shard_id=0 2025-09-07T08:36:41.8718837Z + shift 2025-09-07T08:36:41.8719021Z + partition_flags=() 2025-09-07T08:36:41.8719269Z + local partition_flags 2025-09-07T08:36:41.8719510Z + [[ -n 9 ]] 2025-09-07T08:36:41.8719713Z + [[ -n 0 ]] 2025-09-07T08:36:41.8720079Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T08:36:41.8720780Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T08:36:41.8721164Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T08:36:41.8721643Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 9 --partition-id 0 2025-09-07T08:36:41.8722352Z ++ pwd 2025-09-07T08:36:41.8724492Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:41.8724931Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:41.8738120Z + local suite=torchbench 2025-09-07T08:36:41.8738314Z + shift 2025-09-07T08:36:41.8738482Z + local backend=inductor 2025-09-07T08:36:41.8746028Z + modes=() 2025-09-07T08:36:41.8746202Z + local modes 2025-09-07T08:36:41.8747183Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T08:36:41.8748303Z + modes+=(training) 2025-09-07T08:36:41.8749337Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T08:36:41.8750573Z + modes+=(inference) 2025-09-07T08:36:41.8750788Z + targets=('accuracy' 'performance') 2025-09-07T08:36:41.8751031Z + local targets 2025-09-07T08:36:41.8751215Z + local device=cuda 2025-09-07T08:36:41.8751441Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T08:36:41.8751760Z + [[ inductor_torchbench_perf_cuda_h100 == *cuda_a10g* ]] 2025-09-07T08:36:41.8752076Z + [[ inductor_torchbench_perf_cuda_h100 == *h100* ]] 2025-09-07T08:36:41.8752338Z + device=cuda_h100 2025-09-07T08:36:41.8752532Z + for mode in "${modes[@]}" 2025-09-07T08:36:41.8752756Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:36:41.8753004Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T08:36:41.8753223Z + dtype=amp 2025-09-07T08:36:41.8753405Z + for target in "${targets[@]}" 2025-09-07T08:36:41.8753632Z + target_flag=('--accuracy') 2025-09-07T08:36:41.8753849Z + local target_flag 2025-09-07T08:36:41.8754042Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T08:36:41.8754297Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T08:36:41.8754565Z + target_flag+=(--no-translation-validation) 2025-09-07T08:36:41.8755676Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T08:36:41.8757609Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T08:36:41.8759495Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:36:42.4046041Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:42.4047272Z import pynvml # type: ignore[import] 2025-09-07T08:36:46.8240976Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:46.8242258Z import pynvml # type: ignore[import] 2025-09-07T08:36:49.3178863Z 2025-09-07T08:36:49.5169655Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:36:49.516000 300 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:36:50.4485095Z 2025-09-07T08:36:50.4486339Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:36:50.4486693Z cuda train torchrec_dlrm 2025-09-07T08:37:00.7127452Z [rank0]:W0907 08:37:00.711000 300 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:37:08.4305344Z [rank0]:E0907 08:37:08.429000 300 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00093, (ref-fp64): 0.00004 and shape=torch.Size([256]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T08:37:08.4306791Z [rank0]:E0907 08:37:08.430000 300 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name model.over_arch.model.0._mlp.2._linear.bias 2025-09-07T08:37:08.4538681Z fail_accuracy 2025-09-07T08:37:10.7842935Z [rank0]:[W907 08:37:10.877837895 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T08:37:12.0354580Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:37:12.0355739Z import pynvml # type: ignore[import] 2025-09-07T08:37:14.5164153Z 2025-09-07T08:37:16.9359239Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:37:16.9359631Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:37:16.9359934Z cuda train BERT_pytorch 2025-09-07T08:37:49.4697002Z pass 2025-09-07T08:37:53.1252074Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:37:53.1253318Z import pynvml # type: ignore[import] 2025-09-07T08:37:55.6879011Z 2025-09-07T08:37:59.3699965Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:37:59.3700575Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:37:59.3700900Z cuda train Background_Matting 2025-09-07T08:37:59.4053347Z pass_due_to_skip 2025-09-07T08:38:01.0293729Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:38:01.0294842Z import pynvml # type: ignore[import] 2025-09-07T08:38:03.5603606Z 2025-09-07T08:38:06.5148374Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:38:06.5149340Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:38:06.5149645Z cuda train LearningToPaint 2025-09-07T08:38:18.6041898Z pass 2025-09-07T08:38:21.9036819Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:38:21.9037922Z import pynvml # type: ignore[import] 2025-09-07T08:38:24.3772471Z 2025-09-07T08:38:25.8133332Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/vgg16-397923af.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/vgg16-397923af.pth 2025-09-07T08:38:25.8365133Z 2025-09-07T08:38:25.8365276Z 2025-09-07T08:38:25.9368655Z 0% 0.00/528M [00:00 will be ignored 2025-09-07T08:39:22.9114018Z pass 2025-09-07T08:39:26.8822011Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:39:26.8825167Z import pynvml # type: ignore[import] 2025-09-07T08:39:29.4645467Z 2025-09-07T08:39:29.9825796Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/alexnet-owt-7be5be79.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/alexnet-owt-7be5be79.pth 2025-09-07T08:39:30.0025344Z 2025-09-07T08:39:30.0025516Z 2025-09-07T08:39:30.1026958Z 0% 0.00/233M [00:00 will be ignored 2025-09-07T08:40:04.9536017Z pass 2025-09-07T08:40:07.8232390Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:40:07.8233484Z import pynvml # type: ignore[import] 2025-09-07T08:40:10.3076865Z 2025-09-07T08:40:12.5414992Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:40:12.5415327Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:40:12.5415636Z cuda train basic_gnn_gcn 2025-09-07T08:40:17.9277267Z W0907 08:40:17.926000 8690 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T08:40:19.6328974Z pass 2025-09-07T08:40:22.6779464Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:40:22.6781466Z import pynvml # type: ignore[import] 2025-09-07T08:40:25.2433877Z 2025-09-07T08:40:27.7358304Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:40:27.7358641Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:40:27.7358921Z cuda train basic_gnn_gin 2025-09-07T08:40:32.2006780Z W0907 08:40:32.199000 9119 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:40:35.0012059Z pass 2025-09-07T08:40:38.1552762Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:40:38.1553854Z import pynvml # type: ignore[import] 2025-09-07T08:40:40.7620710Z 2025-09-07T08:40:42.8989678Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:40:42.8990059Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:40:42.8990785Z cuda train basic_gnn_sage 2025-09-07T08:40:47.9521779Z W0907 08:40:47.951000 9449 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:40:50.2316628Z pass 2025-09-07T08:40:52.6980761Z accuracy pass_rate=80.00% 2025-09-07T08:40:52.6985512Z calls_captured gmean=0.00x mean=239.300x 2025-09-07T08:40:52.6987899Z unique_graphs gmean=0.00x mean=3.600x 2025-09-07T08:40:52.6991302Z graph_breaks gmean=0.00x mean=7.900x 2025-09-07T08:40:52.6994939Z unique_graph_breaks gmean=0.00x mean=4.700x 2025-09-07T08:40:52.6998135Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:40:52.7001495Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:40:52.7004897Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T08:40:52.7005624Z compilation_latency mean=15.310 seconds 2025-09-07T08:40:53.5466631Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs-true* ]] 2025-09-07T08:40:53.5468836Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:40:54.0412171Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:40:54.0413148Z import pynvml # type: ignore[import] 2025-09-07T08:40:57.7457065Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:40:57.7458087Z import pynvml # type: ignore[import] 2025-09-07T08:41:00.1961757Z 2025-09-07T08:41:00.3849813Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:41:00.384000 9896 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:41:01.2701814Z 2025-09-07T08:41:01.2702077Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:41:01.2702545Z cuda train torchrec_dlrm 2025-09-07T08:41:09.6306212Z [rank0]:W0907 08:41:09.629000 9896 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:41:15.3068053Z [rank0]:E0907 08:41:15.305000 9896 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00093, (ref-fp64): 0.00004 and shape=torch.Size([256]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T08:41:15.3069450Z [rank0]:E0907 08:41:15.306000 9896 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name model.over_arch.model.0._mlp.2._linear.bias 2025-09-07T08:41:15.3310573Z fail_accuracy 2025-09-07T08:41:17.3332607Z [rank0]:[W907 08:41:17.426763834 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T08:41:18.6422032Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:41:18.6423246Z import pynvml # type: ignore[import] 2025-09-07T08:41:21.0799061Z 2025-09-07T08:41:23.2185804Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:41:23.2186179Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:41:23.2186472Z cuda train BERT_pytorch 2025-09-07T08:41:50.1976546Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:41:50.1977960Z pred = mod(*cloned_inputs) 2025-09-07T08:41:50.1978522Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T08:41:50.1979086Z x = self.bert(x, segment_label) 2025-09-07T08:41:50.1979595Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T08:41:50.1980120Z x = self.embedding(x, segment_info) 2025-09-07T08:41:50.1981080Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T08:41:50.1981793Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T08:41:50.1982119Z 2025-09-07T08:41:50.1982126Z 2025-09-07T08:41:50.5850011Z pass 2025-09-07T08:41:54.1665498Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:41:54.1666776Z import pynvml # type: ignore[import] 2025-09-07T08:41:56.6291641Z 2025-09-07T08:41:59.7739467Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:41:59.7739829Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:41:59.7740142Z cuda train Background_Matting 2025-09-07T08:42:00.0252881Z pass_due_to_skip 2025-09-07T08:42:01.6484103Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:42:01.6485276Z import pynvml # type: ignore[import] 2025-09-07T08:42:04.2039462Z 2025-09-07T08:42:07.1831773Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:42:07.1832105Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:42:07.1832399Z cuda train LearningToPaint 2025-09-07T08:42:17.6922238Z pass 2025-09-07T08:42:20.9994566Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:42:20.9995654Z import pynvml # type: ignore[import] 2025-09-07T08:42:23.4698791Z 2025-09-07T08:42:26.2831570Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:42:26.2831887Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:42:26.2832133Z cuda train Super_SloMo 2025-09-07T08:43:03.3374962Z W0907 08:43:03.336000 10777 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:43:13.9862862Z pass 2025-09-07T08:43:17.9058923Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:43:17.9061777Z import pynvml # type: ignore[import] 2025-09-07T08:43:20.3490971Z 2025-09-07T08:43:22.0039206Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:43:22.0039545Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:43:22.0039825Z cuda train alexnet 2025-09-07T08:43:33.7899355Z pass 2025-09-07T08:43:36.7496729Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:43:36.7498085Z import pynvml # type: ignore[import] 2025-09-07T08:43:39.1894743Z 2025-09-07T08:43:41.4340052Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:43:41.4340533Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:43:41.4340791Z cuda train basic_gnn_edgecnn 2025-09-07T08:43:43.9785504Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T08:43:43.9786637Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T08:43:43.9786862Z 2025-09-07T08:43:43.9786867Z 2025-09-07T08:43:45.9552756Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 190, in propagate 2025-09-07T08:43:45.9553588Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:43:45.9554000Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 141, in _collect 2025-09-07T08:43:45.9554340Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:43:45.9554664Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 88, in _lift 2025-09-07T08:43:45.9555013Z return src.index_select(self.node_dim, index) 2025-09-07T08:43:45.9555224Z 2025-09-07T08:43:45.9555228Z 2025-09-07T08:43:45.9849055Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 190, in propagate 2025-09-07T08:43:45.9850682Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:43:45.9851337Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 141, in _collect 2025-09-07T08:43:45.9851866Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:43:45.9852362Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 88, in _lift 2025-09-07T08:43:45.9852906Z return src.index_select(self.node_dim, index) 2025-09-07T08:43:45.9853250Z 2025-09-07T08:43:45.9853258Z 2025-09-07T08:43:46.3239793Z W0907 08:43:46.323000 11292 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T08:43:48.1641112Z pass 2025-09-07T08:43:51.1961412Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:43:51.1962502Z import pynvml # type: ignore[import] 2025-09-07T08:43:53.8238513Z 2025-09-07T08:43:56.0942848Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:43:56.0943249Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:43:56.0943539Z cuda train basic_gnn_gcn 2025-09-07T08:43:58.0758570Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T08:43:58.0759809Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T08:43:58.0760872Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:43:58.0761491Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:43:58.0761731Z 2025-09-07T08:43:58.0761735Z 2025-09-07T08:43:58.3900142Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp04m3_8o_.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:43:58.3901750Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:43:58.3902882Z File "/tmp/jenkins_pyg/tmp04m3_8o_.py", line 188, in propagate 2025-09-07T08:43:58.3903598Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:43:58.3904901Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:43:58.3905839Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:43:58.3906708Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:43:58.3907540Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:43:58.3908370Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:43:58.3909194Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:43:58.3910024Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:43:58.3910961Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:43:58.3911734Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:43:58.3912559Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:43:58.3912893Z 2025-09-07T08:43:58.3912899Z 2025-09-07T08:43:58.6981540Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:43:58.6982529Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:43:58.6983087Z File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 188, in propagate 2025-09-07T08:43:58.6983618Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:43:58.6984414Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:43:58.6985128Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:43:58.6985755Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:43:58.6986386Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:43:58.6987032Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:43:58.6987664Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:43:58.6988285Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:43:58.6988852Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:43:58.6989432Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:43:58.6990026Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:43:58.6990439Z 2025-09-07T08:43:58.6990444Z 2025-09-07T08:43:59.0520726Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:43:59.0521679Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:43:59.0522109Z File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 188, in propagate 2025-09-07T08:43:59.0522694Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:43:59.0523509Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:43:59.0524188Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:43:59.0976368Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:43:59.0977438Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:43:59.0978076Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:43:59.0978706Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:43:59.0979321Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:43:59.0979901Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:43:59.0980659Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:43:59.0981253Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:43:59.0981503Z 2025-09-07T08:43:59.0981508Z 2025-09-07T08:44:00.3392486Z W0907 08:44:00.338000 11494 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T08:44:01.7718554Z pass 2025-09-07T08:44:04.6911266Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:04.6913483Z import pynvml # type: ignore[import] 2025-09-07T08:44:07.2784393Z 2025-09-07T08:44:09.4716453Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:44:09.4716781Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:44:09.4717067Z cuda train basic_gnn_gin 2025-09-07T08:44:11.8831261Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:44:11.8832400Z pred = mod(*cloned_inputs) 2025-09-07T08:44:11.8833001Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:44:11.8833588Z x = self.convs[i](x, edge_index) 2025-09-07T08:44:11.8833940Z File "/tmp/jenkins_pyg/tmpoqimkyzo.py", line 225, in forward 2025-09-07T08:44:11.8834330Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:44:11.8834715Z File "/tmp/jenkins_pyg/tmpoqimkyzo.py", line 182, in propagate 2025-09-07T08:44:11.8835220Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:44:11.8836024Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:44:11.8836677Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:44:11.8837258Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:44:11.8837812Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:44:11.8838361Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:44:11.8838916Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:44:11.8839461Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:44:11.8839974Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:44:11.8840631Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:44:11.8841181Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:44:11.8841412Z 2025-09-07T08:44:11.8841416Z 2025-09-07T08:44:12.5566130Z W0907 08:44:12.555000 11660 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:44:14.7319785Z pass 2025-09-07T08:44:17.5527419Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:17.5528489Z import pynvml # type: ignore[import] 2025-09-07T08:44:20.0013409Z 2025-09-07T08:44:22.1492657Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:44:22.1492954Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:44:22.1493204Z cuda train basic_gnn_sage 2025-09-07T08:44:24.3953890Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:44:24.3954963Z pred = mod(*cloned_inputs) 2025-09-07T08:44:24.3955516Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:44:24.3956123Z x = self.convs[i](x, edge_index) 2025-09-07T08:44:24.3956459Z File "/tmp/jenkins_pyg/tmpl58hrs45.py", line 228, in forward 2025-09-07T08:44:24.3956842Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:44:24.3957217Z File "/tmp/jenkins_pyg/tmpl58hrs45.py", line 182, in propagate 2025-09-07T08:44:24.3957705Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:44:24.3958442Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:44:24.3959112Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:44:24.3959733Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:44:24.3960866Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:44:24.3961502Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T08:44:24.3962104Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T08:44:24.3962701Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:44:24.3963256Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:44:24.3963826Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T08:44:24.3964415Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T08:44:24.3964665Z 2025-09-07T08:44:24.3964668Z 2025-09-07T08:44:24.9168479Z W0907 08:44:24.915000 11806 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:44:26.6214855Z pass 2025-09-07T08:44:28.9001000Z accuracy pass_rate=80.00% 2025-09-07T08:44:28.9012840Z calls_captured gmean=0.00x mean=239.300x 2025-09-07T08:44:28.9016352Z unique_graphs gmean=0.00x mean=3.600x 2025-09-07T08:44:28.9019585Z graph_breaks gmean=0.00x mean=7.900x 2025-09-07T08:44:28.9023224Z unique_graph_breaks gmean=0.00x mean=4.700x 2025-09-07T08:44:28.9026279Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:44:28.9029368Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:44:28.9032984Z cudagraph_skips gmean=0.00x mean=1.000x 2025-09-07T08:44:28.9034082Z compilation_latency mean=12.615 seconds 2025-09-07T08:44:29.7471929Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *dynamic-true* ]] 2025-09-07T08:44:29.7474269Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:44:30.2482477Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:30.2483546Z import pynvml # type: ignore[import] 2025-09-07T08:44:33.9536644Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:33.9537716Z import pynvml # type: ignore[import] 2025-09-07T08:44:36.4089772Z 2025-09-07T08:44:36.5962790Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:44:36.595000 12001 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:44:37.5049661Z 2025-09-07T08:44:37.5050100Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:44:37.5050711Z cuda train torchrec_dlrm 2025-09-07T08:44:46.9927278Z [rank0]:W0907 08:44:46.991000 12001 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:44:48.3922892Z [rank0]:E0907 08:44:48.391000 12001 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00093, (ref-fp64): 0.00004 and shape=torch.Size([256]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T08:44:48.3925091Z [rank0]:E0907 08:44:48.391000 12001 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name model.over_arch.model.0._mlp.2._linear.bias 2025-09-07T08:44:48.4167710Z fail_accuracy 2025-09-07T08:44:50.1545521Z [rank0]:[W907 08:44:50.248138357 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T08:44:51.2956844Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:51.2958131Z import pynvml # type: ignore[import] 2025-09-07T08:44:53.7177339Z 2025-09-07T08:44:55.8573236Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:44:55.8573639Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:44:55.8573980Z cuda train BERT_pytorch 2025-09-07T08:45:03.4245027Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:45:03.4246159Z pred = mod(*cloned_inputs) 2025-09-07T08:45:03.4246715Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T08:45:03.4247280Z x = self.bert(x, segment_label) 2025-09-07T08:45:03.4247793Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T08:45:03.4248305Z x = self.embedding(x, segment_info) 2025-09-07T08:45:03.4249531Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T08:45:03.4250702Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T08:45:03.4251049Z 2025-09-07T08:45:03.4251054Z 2025-09-07T08:45:04.7912349Z pass 2025-09-07T08:45:07.4893929Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:45:07.4894992Z import pynvml # type: ignore[import] 2025-09-07T08:45:09.9323227Z 2025-09-07T08:45:13.0006921Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:45:13.0007234Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:45:13.0007517Z cuda train Background_Matting 2025-09-07T08:45:13.0470018Z pass_due_to_skip 2025-09-07T08:45:14.6682548Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:45:17.1120936Z import pynvml # type: ignore[import] 2025-09-07T08:45:17.1121185Z 2025-09-07T08:45:20.0152990Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:45:20.0153297Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:45:20.0153558Z cuda train LearningToPaint 2025-09-07T08:45:26.4643020Z pass 2025-09-07T08:45:29.6031623Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:45:29.6032735Z import pynvml # type: ignore[import] 2025-09-07T08:45:32.0714248Z 2025-09-07T08:45:34.7049922Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:45:34.7050644Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:45:34.7050982Z cuda train Super_SloMo 2025-09-07T08:45:43.6964481Z W0907 08:45:43.695000 13076 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:45:45.9965234Z pass 2025-09-07T08:45:49.1748033Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:45:49.1749136Z import pynvml # type: ignore[import] 2025-09-07T08:45:51.7624067Z 2025-09-07T08:45:53.4156572Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:45:53.4156915Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:45:53.4157252Z cuda train alexnet 2025-09-07T08:45:58.2643924Z pass 2025-09-07T08:46:01.5432321Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:01.5433417Z import pynvml # type: ignore[import] 2025-09-07T08:46:04.2128514Z 2025-09-07T08:46:06.4065669Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:46:06.4066039Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:46:06.4066358Z cuda train basic_gnn_edgecnn 2025-09-07T08:46:08.5141203Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T08:46:08.5142973Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T08:46:08.5143237Z 2025-09-07T08:46:08.5143242Z 2025-09-07T08:46:09.5737427Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 190, in propagate 2025-09-07T08:46:09.5738261Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:46:09.5738689Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 141, in _collect 2025-09-07T08:46:09.5739061Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:46:09.5739408Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 88, in _lift 2025-09-07T08:46:09.5739799Z return src.index_select(self.node_dim, index) 2025-09-07T08:46:09.5740033Z 2025-09-07T08:46:09.5740037Z 2025-09-07T08:46:09.5978323Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 190, in propagate 2025-09-07T08:46:09.5979123Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:46:09.5979552Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 141, in _collect 2025-09-07T08:46:09.5979928Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:46:09.5980458Z File "/tmp/jenkins_pyg/tmphx8zr6vy.py", line 88, in _lift 2025-09-07T08:46:09.5980825Z return src.index_select(self.node_dim, index) 2025-09-07T08:46:09.5981046Z 2025-09-07T08:46:09.5981050Z 2025-09-07T08:46:09.6278409Z W0907 08:46:09.627000 13644 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T08:46:10.2802730Z pass 2025-09-07T08:46:13.6808723Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:13.6809823Z import pynvml # type: ignore[import] 2025-09-07T08:46:16.2311477Z 2025-09-07T08:46:18.4243191Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:46:18.4243588Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:46:18.4243880Z cuda train basic_gnn_gcn 2025-09-07T08:46:20.0337926Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T08:46:20.0339198Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T08:46:20.0339879Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:46:20.0340820Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:46:20.0341075Z 2025-09-07T08:46:20.0341079Z 2025-09-07T08:46:20.1301599Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp04m3_8o_.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:46:20.1302520Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:46:20.1303131Z File "/tmp/jenkins_pyg/tmp04m3_8o_.py", line 188, in propagate 2025-09-07T08:46:20.1303957Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:46:20.1305160Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:46:20.1306257Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:46:20.1307261Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:46:20.1308248Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:46:20.1309883Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:46:20.1311543Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:46:20.1312534Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:46:20.1313625Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:46:20.1314201Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:46:20.1314777Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:46:20.1315022Z 2025-09-07T08:46:20.1315025Z 2025-09-07T08:46:20.2772333Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:46:20.2773334Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:46:20.2773786Z File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 188, in propagate 2025-09-07T08:46:20.2774302Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:46:20.2775070Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:46:20.2775755Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:46:20.2776389Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:46:20.2777019Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:46:20.2777630Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:46:20.2778232Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:46:20.2778851Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:46:20.2779420Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:46:20.2780004Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:46:20.2780966Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:46:20.2781217Z 2025-09-07T08:46:20.2781222Z 2025-09-07T08:46:20.4215712Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:46:20.4216645Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:46:20.4217081Z File "/tmp/jenkins_pyg/tmpw8y24jr1.py", line 188, in propagate 2025-09-07T08:46:20.4217583Z out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size) 2025-09-07T08:46:20.4218339Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:46:20.4219025Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:46:20.4219641Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:46:20.4220680Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:46:20.4221311Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:46:20.4221930Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:46:20.4222535Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:46:20.4223226Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:46:20.5226125Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:46:20.5234862Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:46:20.5235409Z 2025-09-07T08:46:20.5235413Z 2025-09-07T08:46:20.5983852Z W0907 08:46:20.597000 13781 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T08:46:20.9815500Z pass 2025-09-07T08:46:24.6040521Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:24.6041609Z import pynvml # type: ignore[import] 2025-09-07T08:46:27.2616635Z 2025-09-07T08:46:29.4563348Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:46:29.4563706Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:46:29.4564025Z cuda train basic_gnn_gin 2025-09-07T08:46:30.8828000Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:46:30.8829204Z pred = mod(*cloned_inputs) 2025-09-07T08:46:30.8829781Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:46:30.8830772Z x = self.convs[i](x, edge_index) 2025-09-07T08:46:30.8831141Z File "/tmp/jenkins_pyg/tmpoqimkyzo.py", line 225, in forward 2025-09-07T08:46:30.8831540Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:46:30.8831957Z File "/tmp/jenkins_pyg/tmpoqimkyzo.py", line 182, in propagate 2025-09-07T08:46:30.8832488Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:46:30.8833267Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:46:30.8833955Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:46:30.8834580Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:46:30.8835201Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:46:30.8835889Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:46:30.8836511Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:46:30.8837103Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:46:30.8837655Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:46:30.8838208Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:46:30.8838786Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:46:30.8839041Z 2025-09-07T08:46:30.8839045Z 2025-09-07T08:46:31.2202075Z W0907 08:46:31.219000 13918 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:46:31.7817908Z pass 2025-09-07T08:46:36.0884707Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:36.0885829Z import pynvml # type: ignore[import] 2025-09-07T08:46:38.6987552Z 2025-09-07T08:46:40.8590905Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:46:40.8591324Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:46:40.9788890Z cuda train basic_gnn_sage 2025-09-07T08:46:42.2206589Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:46:42.2208700Z pred = mod(*cloned_inputs) 2025-09-07T08:46:42.2209480Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:46:42.2210156Z x = self.convs[i](x, edge_index) 2025-09-07T08:46:42.2210885Z File "/tmp/jenkins_pyg/tmpl58hrs45.py", line 228, in forward 2025-09-07T08:46:42.2211331Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:46:42.2211774Z File "/tmp/jenkins_pyg/tmpl58hrs45.py", line 182, in propagate 2025-09-07T08:46:42.2212372Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:46:42.2213280Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:46:42.2214090Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:46:42.2214818Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:46:42.2215556Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:46:42.2216276Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T08:46:42.2216988Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T08:46:42.2217690Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:46:42.2218349Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:46:42.2219002Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T08:46:42.2219692Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T08:46:42.2219906Z 2025-09-07T08:46:42.2219910Z 2025-09-07T08:46:42.5343414Z W0907 08:46:42.533000 14055 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:46:43.1494758Z pass 2025-09-07T08:46:46.7271252Z accuracy pass_rate=80.00% 2025-09-07T08:46:46.7282781Z calls_captured gmean=0.00x mean=239.500x 2025-09-07T08:46:46.7285810Z unique_graphs gmean=0.00x mean=3.600x 2025-09-07T08:46:46.7289271Z graph_breaks gmean=0.00x mean=7.900x 2025-09-07T08:46:46.7292957Z unique_graph_breaks gmean=0.00x mean=4.700x 2025-09-07T08:46:46.7296302Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:46:46.7299522Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:46:46.7303202Z cudagraph_skips gmean=0.00x mean=1.000x 2025-09-07T08:46:46.7304431Z compilation_latency mean=4.609 seconds 2025-09-07T08:46:47.6167092Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cppwrapper-true* ]] 2025-09-07T08:46:47.6168330Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T08:46:47.6169548Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:46:48.1167408Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:48.1168871Z import pynvml # type: ignore[import] 2025-09-07T08:46:51.8267059Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:46:51.8268899Z import pynvml # type: ignore[import] 2025-09-07T08:46:54.2679884Z 2025-09-07T08:46:54.4557092Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:46:54.455000 14241 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:46:56.1042188Z 2025-09-07T08:46:56.1042605Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:46:56.1042979Z cuda train torchrec_dlrm 2025-09-07T08:47:16.8642149Z [rank0]:W0907 08:47:16.863000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8654035Z [rank0]:W0907 08:47:16.865000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8666435Z [rank0]:W0907 08:47:16.866000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8677834Z [rank0]:W0907 08:47:16.867000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8689004Z [rank0]:W0907 08:47:16.868000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8700523Z [rank0]:W0907 08:47:16.869000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8712846Z [rank0]:W0907 08:47:16.870000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8723936Z [rank0]:W0907 08:47:16.872000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8735101Z [rank0]:W0907 08:47:16.873000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8746277Z [rank0]:W0907 08:47:16.874000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8758125Z [rank0]:W0907 08:47:16.875000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8769210Z [rank0]:W0907 08:47:16.876000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8780307Z [rank0]:W0907 08:47:16.877000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8792384Z [rank0]:W0907 08:47:16.878000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8803445Z [rank0]:W0907 08:47:16.880000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8814608Z [rank0]:W0907 08:47:16.881000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8825740Z [rank0]:W0907 08:47:16.882000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8837025Z [rank0]:W0907 08:47:16.883000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8848465Z [rank0]:W0907 08:47:16.884000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8859237Z [rank0]:W0907 08:47:16.885000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8870352Z [rank0]:W0907 08:47:16.886000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8881423Z [rank0]:W0907 08:47:16.887000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8896655Z [rank0]:W0907 08:47:16.889000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8907772Z [rank0]:W0907 08:47:16.890000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8918611Z [rank0]:W0907 08:47:16.891000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:16.8929424Z [rank0]:W0907 08:47:16.892000 14241 site-packages/torch/_inductor/ir.py:7717] [2/0_1] aten._embedding_bag_backward.default is missing a c-shim implementation, using proxy executor as fallback 2025-09-07T08:47:21.8268731Z [rank0]:W0907 08:47:21.826000 14241 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:47:32.3168018Z [rank0]:E0907 08:47:32.315000 14241 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00093, (ref-fp64): 0.00004 and shape=torch.Size([256]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T08:47:32.3172818Z [rank0]:E0907 08:47:32.316000 14241 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name model.over_arch.model.0._mlp.2._linear.bias 2025-09-07T08:47:32.3392456Z fail_accuracy 2025-09-07T08:47:34.3661379Z [rank0]:[W907 08:47:34.459650316 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T08:47:35.6000556Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:47:35.6001638Z import pynvml # type: ignore[import] 2025-09-07T08:47:38.0236474Z 2025-09-07T08:47:40.1448315Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:47:40.1448684Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:47:40.1449525Z cuda train BERT_pytorch 2025-09-07T08:48:44.4796416Z pass 2025-09-07T08:48:48.7908262Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:48:48.7909319Z import pynvml # type: ignore[import] 2025-09-07T08:48:51.2750564Z 2025-09-07T08:48:54.8448208Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:48:54.8448578Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:48:54.8448896Z cuda train Background_Matting 2025-09-07T08:48:54.9114262Z pass_due_to_skip 2025-09-07T08:48:56.5624253Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:48:56.5625364Z import pynvml # type: ignore[import] 2025-09-07T08:48:58.9962364Z 2025-09-07T08:49:01.9234055Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:49:01.9234399Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:49:01.9234691Z cuda train LearningToPaint 2025-09-07T08:49:28.3218415Z pass 2025-09-07T08:49:31.6984815Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:49:31.6986520Z import pynvml # type: ignore[import] 2025-09-07T08:49:34.2661169Z 2025-09-07T08:49:36.8566687Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:49:36.8567076Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:49:36.8567370Z cuda train Super_SloMo 2025-09-07T08:50:40.4354507Z W0907 08:50:40.434000 17069 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:50:59.7560538Z pass 2025-09-07T08:51:04.3952038Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:51:04.3953045Z import pynvml # type: ignore[import] 2025-09-07T08:51:07.0228097Z 2025-09-07T08:51:08.6886383Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:51:08.6886785Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:51:08.6887089Z cuda train alexnet 2025-09-07T08:51:26.6124868Z pass 2025-09-07T08:51:29.4602498Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:51:29.4603740Z import pynvml # type: ignore[import] 2025-09-07T08:51:32.1356506Z 2025-09-07T08:51:34.4748195Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:51:34.4748559Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:51:34.4748866Z cuda train basic_gnn_edgecnn 2025-09-07T08:51:50.7494495Z W0907 08:51:50.748000 18468 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T08:51:55.1308818Z pass 2025-09-07T08:51:58.0283925Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:51:58.0285769Z import pynvml # type: ignore[import] 2025-09-07T08:52:00.4987291Z 2025-09-07T08:52:02.7251717Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:52:02.7252101Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:52:02.7252412Z cuda train basic_gnn_gcn 2025-09-07T08:52:19.5188469Z W0907 08:52:19.517000 19128 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T08:52:22.9706308Z pass 2025-09-07T08:52:25.7727986Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:52:25.7729397Z import pynvml # type: ignore[import] 2025-09-07T08:52:28.1955542Z 2025-09-07T08:52:30.5452161Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:52:30.5452584Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:52:30.5452889Z cuda train basic_gnn_gin 2025-09-07T08:52:39.2199742Z W0907 08:52:39.218000 19820 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:52:42.5908424Z pass 2025-09-07T08:52:45.7692841Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:52:45.7693899Z import pynvml # type: ignore[import] 2025-09-07T08:52:48.2391156Z 2025-09-07T08:52:50.4428855Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:52:50.4429252Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:52:50.4429554Z cuda train basic_gnn_sage 2025-09-07T08:52:59.6057197Z W0907 08:52:59.604000 20228 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:53:03.4676768Z pass 2025-09-07T08:53:06.1409315Z accuracy pass_rate=80.00% 2025-09-07T08:53:06.1415316Z calls_captured gmean=0.00x mean=239.300x 2025-09-07T08:53:06.1418379Z unique_graphs gmean=0.00x mean=3.600x 2025-09-07T08:53:06.1421527Z graph_breaks gmean=0.00x mean=7.900x 2025-09-07T08:53:06.1432675Z unique_graph_breaks gmean=0.00x mean=4.700x 2025-09-07T08:53:06.1435972Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:53:06.1439212Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:53:06.1442720Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T08:53:06.1443785Z compilation_latency mean=28.568 seconds 2025-09-07T08:53:06.9654523Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing_cudagraphs-true* ]] 2025-09-07T08:53:06.9655714Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:53:06.9656812Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freeze_autotune_cudagraphs-true* ]] 2025-09-07T08:53:06.9657910Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:53:06.9658942Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *aotinductor-true* ]] 2025-09-07T08:53:06.9659957Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:53:06.9663900Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *maxautotune-true* ]] 2025-09-07T08:53:06.9665207Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T08:53:06.9666260Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:53:07.4614281Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:53:07.4615257Z import pynvml # type: ignore[import] 2025-09-07T08:53:11.3147037Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:53:11.3148111Z import pynvml # type: ignore[import] 2025-09-07T08:53:14.0861605Z 2025-09-07T08:53:14.2756044Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:53:14.274000 20713 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:53:15.1495931Z 2025-09-07T08:53:15.1496203Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:53:15.1496726Z cuda train torchrec_dlrm 2025-09-07T08:53:22.5423091Z Autotune Choices Stats: 2025-09-07T08:53:22.5424879Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_63", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007935999892652035, "best_triton_pos": 0} 2025-09-07T08:53:22.5428393Z AUTOTUNE mm(4x512, 512x1728) 2025-09-07T08:53:22.5428869Z strides: [512, 1], [1, 512] 2025-09-07T08:53:22.5429287Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:22.5431079Z triton_mm_63 0.0079 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:22.5432691Z triton_mm_67 0.0082 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:22.5433683Z mm 0.0085 ms 92.9% 2025-09-07T08:53:22.5434753Z triton_mm_75 0.0086 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:22.5435721Z triton_mm_71 0.0089 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:22.5436677Z triton_mm_62 0.0091 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:22.5437626Z triton_mm_66 0.0091 ms 87.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:22.5438583Z triton_mm_60 0.0093 ms 84.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:22.5439986Z triton_mm_61 0.0094 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:22.5441326Z triton_mm_70 0.0098 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:22.5442172Z SingleProcess AUTOTUNE benchmarking takes 0.2117 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T08:53:23.3827856Z Autotune Choices Stats: 2025-09-07T08:53:23.3828999Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_4", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.0055680000223219395, "best_triton_pos": 0} 2025-09-07T08:53:23.3950729Z AUTOTUNE mm(4x13, 13x512) 2025-09-07T08:53:23.3951010Z strides: [13, 1], [1, 13] 2025-09-07T08:53:23.3951298Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:23.3951969Z triton_mm_4 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:23.3952972Z triton_mm_1 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:23.3953979Z triton_mm_5 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:23.3954992Z triton_mm_2 0.0057 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:23.3955943Z triton_mm_0 0.0057 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:23.3956905Z triton_mm_9 0.0059 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:23.3957876Z triton_mm_11 0.0059 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:23.3958860Z triton_mm_10 0.0059 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:53:23.3959819Z triton_mm_3 0.0060 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:23.3961101Z triton_mm_7 0.0060 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:23.3961946Z SingleProcess AUTOTUNE benchmarking takes 0.1614 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T08:53:23.8930776Z Autotune Choices Stats: 2025-09-07T08:53:23.8932135Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009472000412642956, "best_triton_pos": 1, "best_triton_time": 0.009824000298976898, "best_triton_kernel": "triton_mm_148", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T08:53:23.9582601Z AUTOTUNE mm(4x1728, 1728x512) 2025-09-07T08:53:23.9582948Z strides: [1728, 1], [1, 1728] 2025-09-07T08:53:23.9583215Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:23.9583489Z mm 0.0095 ms 100.0% 2025-09-07T08:53:23.9584561Z triton_mm_148 0.0098 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:23.9585804Z triton_mm_152 0.0109 ms 86.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:23.9586787Z triton_mm_156 0.0121 ms 78.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:23.9587767Z triton_mm_160 0.0132 ms 71.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:23.9588727Z triton_mm_147 0.0142 ms 66.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:23.9589685Z triton_mm_151 0.0154 ms 61.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:23.9590828Z triton_mm_146 0.0155 ms 61.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:23.9591786Z triton_mm_155 0.0173 ms 54.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:23.9592762Z triton_mm_145 0.0177 ms 53.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:23.9593628Z SingleProcess AUTOTUNE benchmarking takes 0.2904 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:24.1953745Z Autotune Choices Stats: 2025-09-07T08:53:24.1954898Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_165", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007104000076651573, "best_triton_pos": 0} 2025-09-07T08:53:24.2389903Z AUTOTUNE mm(4x512, 512x512) 2025-09-07T08:53:24.2390157Z strides: [512, 1], [1, 512] 2025-09-07T08:53:24.2390889Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:24.2391553Z triton_mm_165 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:24.2392191Z mm 0.0073 ms 96.9% 2025-09-07T08:53:24.2392767Z triton_mm_169 0.0075 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:24.2393736Z triton_mm_173 0.0080 ms 89.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:24.2394832Z triton_mm_177 0.0080 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:24.2395780Z triton_mm_164 0.0083 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:24.2396737Z triton_mm_163 0.0085 ms 83.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:24.2397719Z triton_mm_162 0.0086 ms 82.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:24.2399116Z triton_mm_168 0.0086 ms 82.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:24.2400391Z triton_mm_172 0.0093 ms 76.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:24.2401239Z SingleProcess AUTOTUNE benchmarking takes 0.2601 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:24.4765040Z Autotune Choices Stats: 2025-09-07T08:53:24.4766239Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_16", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006816000211983919, "best_triton_pos": 0} 2025-09-07T08:53:24.5846543Z AUTOTUNE mm(4x512, 512x256) 2025-09-07T08:53:24.5847015Z strides: [512, 1], [1, 512] 2025-09-07T08:53:24.5847461Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:24.5848535Z triton_mm_16 0.0068 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:24.5850113Z triton_mm_20 0.0071 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:24.5851734Z mm 0.0075 ms 90.6% 2025-09-07T08:53:24.5852719Z triton_mm_24 0.0080 ms 85.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:24.5854346Z triton_mm_15 0.0082 ms 83.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:24.5855532Z triton_mm_28 0.0083 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:24.5856419Z triton_mm_14 0.0083 ms 82.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:24.5857303Z triton_mm_13 0.0086 ms 79.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:24.5858182Z triton_mm_19 0.0086 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:24.5859053Z triton_mm_26 0.0088 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:24.5859832Z SingleProcess AUTOTUNE benchmarking takes 0.3254 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:25.0135621Z Autotune Choices Stats: 2025-09-07T08:53:25.0136669Z {"num_choices": 12, "num_triton_choices": 11, "best_kernel": "triton_mm_205", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1", "best_time": 0.006207999773323536, "best_triton_pos": 0} 2025-09-07T08:53:25.3894371Z AUTOTUNE addmm(4x1, 4x256, 256x1) 2025-09-07T08:53:25.3894685Z strides: [1, 1], [256, 1], [1, 0] 2025-09-07T08:53:25.3895007Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:53:25.3895736Z triton_mm_205 0.0062 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:53:25.3897198Z triton_mm_201 0.0065 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T08:53:25.3898193Z triton_mm_198 0.0066 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:53:25.3899387Z triton_mm_203 0.0066 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T08:53:25.3900762Z triton_mm_197 0.0068 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:53:25.3901734Z triton_mm_204 0.0068 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T08:53:25.3902785Z triton_mm_196 0.0070 ms 88.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T08:53:25.3903758Z triton_mm_202 0.0074 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T08:53:25.3904803Z triton_mm_200 0.0091 ms 68.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T08:53:25.3905365Z addmm 0.0104 ms 59.9% 2025-09-07T08:53:25.3905789Z SingleProcess AUTOTUNE benchmarking takes 0.5200 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T08:53:26.1559192Z Autotune Choices Stats: 2025-09-07T08:53:26.1560530Z {"num_choices": 14, "num_triton_choices": 13, "best_kernel": "triton_mm_37", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.0063680000603199005, "best_triton_pos": 0} 2025-09-07T08:53:26.1712859Z AUTOTUNE mm(8x256, 256x64) 2025-09-07T08:53:26.1713158Z strides: [256, 1], [1, 256] 2025-09-07T08:53:26.1713416Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:26.1714105Z triton_mm_37 0.0064 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:26.1715257Z triton_mm_41 0.0064 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:26.1716222Z triton_mm_40 0.0067 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:26.1717185Z triton_mm_33 0.0068 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:26.1718139Z triton_mm_36 0.0068 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:26.1719099Z triton_mm_32 0.0069 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:26.1720045Z triton_mm_31 0.0070 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:26.1721138Z triton_mm_30 0.0072 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:26.1721743Z mm 0.0072 ms 88.1% 2025-09-07T08:53:26.1722648Z triton_mm_39 0.0073 ms 87.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:26.1723675Z SingleProcess AUTOTUNE benchmarking takes 0.1831 seconds and 0.0002 seconds precompiling for 14 choices 2025-09-07T08:53:31.0818895Z Autotune Choices Stats: 2025-09-07T08:53:31.0821163Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_325", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8", "best_time": 0.00598399993032217, "best_triton_pos": 0} 2025-09-07T08:53:31.1078954Z AUTOTUNE mm(512x4, 4x1728) 2025-09-07T08:53:31.1079184Z strides: [1, 512], [1728, 1] 2025-09-07T08:53:31.1079421Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:31.1080085Z triton_mm_325 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:31.1081153Z triton_mm_321 0.0060 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:31.1082073Z triton_mm_323 0.0060 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:31.1082963Z triton_mm_318 0.0061 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:31.1083856Z triton_mm_319 0.0061 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:53:31.1084750Z triton_mm_320 0.0061 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.1085646Z triton_mm_322 0.0061 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:31.1086555Z triton_mm_317 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.1087497Z triton_mm_324 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:31.1088423Z triton_mm_314 0.0062 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:31.1089202Z SingleProcess AUTOTUNE benchmarking takes 0.1789 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T08:53:31.4674949Z Autotune Choices Stats: 2025-09-07T08:53:31.4676153Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_334", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.00595200015231967, "best_triton_pos": 0} 2025-09-07T08:53:31.5370055Z AUTOTUNE mm(1728x4, 4x512) 2025-09-07T08:53:31.5371021Z strides: [1, 1728], [512, 1] 2025-09-07T08:53:31.5371431Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:31.5372459Z triton_mm_334 0.0060 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:31.5373963Z triton_mm_336 0.0060 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.5375950Z triton_mm_340 0.0060 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:31.5377601Z triton_mm_337 0.0061 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:31.5378677Z triton_mm_335 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:53:31.5379733Z triton_mm_338 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:31.5380940Z triton_mm_339 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:31.5382006Z triton_mm_341 0.0061 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:31.5383145Z triton_mm_333 0.0061 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.5384194Z triton_mm_332 0.0062 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:31.5385122Z SingleProcess AUTOTUNE benchmarking takes 0.2222 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:53:31.7790402Z Autotune Choices Stats: 2025-09-07T08:53:31.7791398Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_285", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.005727999843657017, "best_triton_pos": 0} 2025-09-07T08:53:31.7986904Z AUTOTUNE mm(512x4, 4x512) 2025-09-07T08:53:31.7987277Z strides: [1, 512], [512, 1] 2025-09-07T08:53:31.7987525Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:31.7988185Z triton_mm_285 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:31.7989163Z triton_mm_281 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:31.7990116Z triton_mm_284 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.7991221Z triton_mm_286 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:53:31.7992177Z triton_mm_287 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:31.7993155Z triton_mm_280 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:31.7994145Z triton_mm_282 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:31.7995112Z triton_mm_283 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:31.7996350Z triton_mm_288 0.0059 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:31.7997461Z triton_mm_289 0.0060 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:31.7998203Z SingleProcess AUTOTUNE benchmarking takes 0.1715 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:53:32.1472351Z Autotune Choices Stats: 2025-09-07T08:53:32.1473330Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_249", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.005696000065654516, "best_triton_pos": 0} 2025-09-07T08:53:32.2363257Z AUTOTUNE mm(256x8, 8x512) 2025-09-07T08:53:32.2363550Z strides: [8, 1], [512, 1] 2025-09-07T08:53:32.2363846Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:32.2364617Z triton_mm_249 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:32.2365771Z triton_mm_250 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:32.2366891Z triton_mm_254 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:32.2367851Z triton_mm_247 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:32.2368812Z triton_mm_248 0.0058 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:32.2369775Z triton_mm_251 0.0058 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:32.2371031Z triton_mm_253 0.0058 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:53:32.2372000Z triton_mm_252 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:32.2372970Z triton_mm_257 0.0060 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:32.2373982Z triton_mm_255 0.0061 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:32.2374840Z SingleProcess AUTOTUNE benchmarking takes 0.2419 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:53:32.5739609Z Autotune Choices Stats: 2025-09-07T08:53:32.5740856Z {"num_choices": 16, "num_triton_choices": 15, "best_kernel": "triton_mm_544", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.005696000065654516, "best_triton_pos": 0} 2025-09-07T08:53:32.5849485Z AUTOTUNE mm(64x4, 4x256) 2025-09-07T08:53:32.5849726Z strides: [1, 64], [256, 1] 2025-09-07T08:53:32.5849980Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:32.5851294Z triton_mm_544 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:32.5852322Z triton_mm_556 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:32.5853523Z triton_mm_545 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:32.5854474Z triton_mm_546 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:32.5855420Z triton_mm_547 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:32.5856393Z triton_mm_548 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:32.5857365Z triton_mm_550 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:53:32.5858270Z triton_mm_555 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:32.5859160Z triton_mm_549 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:32.5860052Z triton_mm_551 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:32.5860977Z SingleProcess AUTOTUNE benchmarking takes 0.1524 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T08:53:32.9354812Z Autotune Choices Stats: 2025-09-07T08:53:32.9355801Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_382", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007584000006318092, "best_triton_pos": 0} 2025-09-07T08:53:33.1368953Z AUTOTUNE mm(4x512, 512x1728) 2025-09-07T08:53:33.1369247Z strides: [512, 1], [1728, 1] 2025-09-07T08:53:33.1369524Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:33.1370554Z triton_mm_382 0.0076 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:33.1371613Z triton_mm_386 0.0078 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:33.1372250Z mm 0.0079 ms 96.3% 2025-09-07T08:53:33.1372826Z triton_mm_390 0.0084 ms 89.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:33.1373798Z triton_mm_394 0.0084 ms 89.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:33.1374789Z triton_mm_380 0.0086 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:33.1375737Z triton_mm_381 0.0087 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:33.1377116Z triton_mm_385 0.0089 ms 84.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:33.1378018Z triton_mm_389 0.0093 ms 81.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:33.1379117Z triton_mm_392 0.0093 ms 81.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:33.1379896Z SingleProcess AUTOTUNE benchmarking takes 0.3695 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:34.3334106Z Autotune Choices Stats: 2025-09-07T08:53:34.3335196Z {"num_choices": 12, "num_triton_choices": 11, "best_kernel": "triton_mm_593", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2", "best_time": 0.005727999843657017, "best_triton_pos": 0} 2025-09-07T08:53:34.3899420Z AUTOTUNE mm(512x4, 4x13) 2025-09-07T08:53:34.3899652Z strides: [1, 512], [13, 1] 2025-09-07T08:53:34.3899879Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:34.3900785Z triton_mm_593 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:34.3901687Z triton_mm_594 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:34.3902554Z triton_mm_592 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:34.3903464Z triton_mm_595 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:34.3904299Z triton_mm_596 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:34.3905142Z triton_mm_598 0.0058 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:34.3905994Z triton_mm_597 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:34.3906834Z triton_mm_601 0.0059 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:53:34.3907829Z triton_mm_599 0.0060 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:34.3908810Z triton_mm_600 0.0060 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:34.3909665Z SingleProcess AUTOTUNE benchmarking takes 0.1643 seconds and 0.0002 seconds precompiling for 12 choices 2025-09-07T08:53:34.7384158Z Autotune Choices Stats: 2025-09-07T08:53:34.7385102Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_267", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006943999789655209, "best_triton_pos": 0} 2025-09-07T08:53:34.8646656Z AUTOTUNE mm(4x512, 512x512) 2025-09-07T08:53:34.8647220Z strides: [512, 1], [512, 1] 2025-09-07T08:53:34.8647624Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:34.8648764Z triton_mm_267 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:34.8649844Z triton_mm_271 0.0073 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:34.8650746Z mm 0.0073 ms 94.8% 2025-09-07T08:53:34.8651240Z triton_mm_266 0.0081 ms 86.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:34.8652094Z triton_mm_275 0.0081 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:34.8652944Z triton_mm_265 0.0081 ms 85.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:34.8653782Z triton_mm_279 0.0083 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:34.8654615Z triton_mm_270 0.0085 ms 81.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:34.8655449Z triton_mm_264 0.0088 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:34.8656278Z triton_mm_277 0.0088 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:34.8657007Z SingleProcess AUTOTUNE benchmarking takes 0.2927 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:35.5751081Z Autotune Choices Stats: 2025-09-07T08:53:35.5752159Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_234", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.006688000168651342, "best_triton_pos": 0} 2025-09-07T08:53:35.8381952Z AUTOTUNE mm(4x256, 256x512) 2025-09-07T08:53:35.8382185Z strides: [256, 1], [512, 1] 2025-09-07T08:53:35.8382397Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:35.8383051Z triton_mm_234 0.0067 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:35.8383895Z triton_mm_238 0.0067 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:35.8384756Z triton_mm_233 0.0068 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:35.8385600Z triton_mm_232 0.0069 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:35.8386123Z mm 0.0070 ms 95.9% 2025-09-07T08:53:35.8386608Z triton_mm_246 0.0070 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:35.8387480Z triton_mm_237 0.0071 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:35.8388468Z triton_mm_241 0.0071 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:35.8389927Z triton_mm_231 0.0072 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:35.8391360Z triton_mm_244 0.0072 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:35.8392209Z SingleProcess AUTOTUNE benchmarking takes 0.7529 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:35.9853647Z Autotune Choices Stats: 2025-09-07T08:53:35.9854572Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_206", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.005632000043988228, "best_triton_pos": 0} 2025-09-07T08:53:36.0419109Z AUTOTUNE mm(4x1, 1x256) 2025-09-07T08:53:36.0419365Z strides: [1, 1], [256, 1] 2025-09-07T08:53:36.0419643Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:36.0420686Z triton_mm_206 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:36.0421738Z triton_mm_210 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:36.0422794Z triton_mm_211 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.0423775Z triton_mm_212 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.0424771Z triton_mm_213 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:36.0425756Z triton_mm_217 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:36.0426732Z triton_mm_208 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:36.0427765Z triton_mm_209 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:36.0428810Z triton_mm_214 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:36.0429785Z triton_mm_215 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:36.0430760Z SingleProcess AUTOTUNE benchmarking takes 0.1732 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T08:53:36.4279856Z Autotune Choices Stats: 2025-09-07T08:53:36.4281789Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_541", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.005760000087320805, "best_triton_pos": 0} 2025-09-07T08:53:36.4652072Z AUTOTUNE mm(4x64, 64x256) 2025-09-07T08:53:36.4652322Z strides: [64, 1], [256, 1] 2025-09-07T08:53:36.4652596Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:36.4653653Z triton_mm_541 0.0058 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:36.4654669Z triton_mm_531 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:36.4655839Z triton_mm_534 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.4656787Z triton_mm_535 0.0058 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:36.4657819Z triton_mm_528 0.0059 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:53:36.4658731Z triton_mm_540 0.0059 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.4659616Z triton_mm_530 0.0059 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:36.4660664Z triton_mm_529 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:36.4661554Z triton_mm_543 0.0060 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:36.4662450Z triton_mm_536 0.0060 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.4663309Z SingleProcess AUTOTUNE benchmarking takes 0.1966 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:36.6024377Z Autotune Choices Stats: 2025-09-07T08:53:36.6025951Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_221", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.005535999778658152, "best_triton_pos": 0} 2025-09-07T08:53:36.6293843Z AUTOTUNE mm(1x4, 4x256) 2025-09-07T08:53:36.6294085Z strides: [1, 1], [256, 1] 2025-09-07T08:53:36.6294362Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:36.6295021Z triton_mm_221 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:36.6296001Z triton_mm_222 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:53:36.6296972Z triton_mm_223 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.6297983Z triton_mm_225 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:53:36.6298890Z triton_mm_218 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:53:36.6299725Z triton_mm_220 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:36.6300870Z triton_mm_224 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:36.6301973Z triton_mm_226 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:36.6303059Z triton_mm_227 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:36.6303910Z triton_mm_228 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:53:36.6304652Z SingleProcess AUTOTUNE benchmarking takes 0.1438 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T08:53:37.5011023Z Autotune Choices Stats: 2025-09-07T08:53:37.5012444Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009088000282645226, "best_triton_pos": 1, "best_triton_time": 0.010304000228643417, "best_triton_kernel": "triton_mm_349", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T08:53:37.5154943Z AUTOTUNE mm(4x1728, 1728x512) 2025-09-07T08:53:37.5155217Z strides: [1728, 1], [512, 1] 2025-09-07T08:53:37.5155489Z dtypes: torch.float16, torch.float16 2025-09-07T08:53:37.5155762Z mm 0.0091 ms 100.0% 2025-09-07T08:53:37.5156400Z triton_mm_349 0.0103 ms 88.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:37.5157461Z triton_mm_353 0.0113 ms 80.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:37.5158530Z triton_mm_357 0.0116 ms 78.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:37.5159580Z triton_mm_361 0.0131 ms 69.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:53:37.5160762Z triton_mm_348 0.0141 ms 64.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:53:37.5161791Z triton_mm_347 0.0142 ms 63.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:53:37.5162819Z triton_mm_352 0.0151 ms 60.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:37.5163858Z triton_mm_359 0.0168 ms 54.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:53:37.5164887Z triton_mm_356 0.0174 ms 52.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:53:37.5165810Z SingleProcess AUTOTUNE benchmarking takes 0.2049 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:53:39.3805204Z [rank0]:W0907 08:53:39.379000 20713 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:53:45.2317054Z [rank0]:E0907 08:53:45.230000 20713 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00047, (ref-fp64): 0.00004 and shape=torch.Size([256]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T08:53:45.2387180Z [rank0]:E0907 08:53:45.231000 20713 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name model.over_arch.model.0._mlp.2._linear.bias 2025-09-07T08:53:45.2566926Z fail_accuracy 2025-09-07T08:53:47.4615301Z [rank0]:[W907 08:53:47.554916787 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T08:53:48.7617815Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:53:48.7618855Z import pynvml # type: ignore[import] 2025-09-07T08:53:51.1978095Z 2025-09-07T08:53:53.3309181Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:53:53.3309734Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:53:53.3318406Z cuda train BERT_pytorch 2025-09-07T08:54:13.2264008Z Autotune Choices Stats: 2025-09-07T08:54:13.2265368Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.012256000190973282, "best_triton_pos": 1, "best_triton_time": 0.013024000450968742, "best_triton_kernel": "triton_mm_131", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T08:54:13.2978823Z AUTOTUNE addmm(512x3072, 512x768, 768x3072) 2025-09-07T08:54:13.2979138Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T08:54:13.2979462Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:54:13.2979802Z bias_addmm 0.0123 ms 100.0% 2025-09-07T08:54:13.2980791Z triton_mm_131 0.0130 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:13.2981802Z triton_mm_120 0.0132 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:13.2982902Z triton_mm_124 0.0137 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:13.2983892Z triton_mm_130 0.0140 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:13.2984852Z triton_mm_123 0.0151 ms 81.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:13.2985806Z triton_mm_127 0.0151 ms 81.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:13.2986778Z triton_mm_125 0.0157 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:13.2987787Z triton_mm_126 0.0170 ms 72.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:13.2988503Z addmm 0.0172 ms 71.2% 2025-09-07T08:54:13.2988997Z SingleProcess AUTOTUNE benchmarking takes 0.3391 seconds and 0.0007 seconds precompiling for 21 choices 2025-09-07T08:54:14.0175351Z Autotune Choices Stats: 2025-09-07T08:54:14.0177177Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.012896000407636166, "best_triton_pos": 1, "best_triton_time": 0.014688000082969666, "best_triton_kernel": "triton_mm_1801", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:54:14.0207306Z AUTOTUNE mm(512x3072, 3072x768) 2025-09-07T08:54:14.0207906Z strides: [3072, 1], [1, 3072] 2025-09-07T08:54:14.0208174Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:14.0208502Z mm 0.0129 ms 100.0% 2025-09-07T08:54:14.0209188Z triton_mm_1801 0.0147 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:14.0210183Z triton_mm_1805 0.0170 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:14.0211346Z triton_mm_1797 0.0202 ms 63.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:14.0212333Z triton_mm_1811 0.0226 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:14.0213302Z triton_mm_1800 0.0264 ms 48.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:14.0214266Z triton_mm_1804 0.0270 ms 47.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:14.0215234Z triton_mm_1794 0.0278 ms 46.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:14.0216197Z triton_mm_1796 0.0286 ms 45.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:14.0217168Z triton_mm_1810 0.0295 ms 43.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:14.0218022Z SingleProcess AUTOTUNE benchmarking takes 0.2640 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:15.2110503Z Autotune Choices Stats: 2025-09-07T08:54:15.2111489Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_8", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.008767999708652496, "best_triton_pos": 0} 2025-09-07T08:54:15.2139902Z AUTOTUNE mm(512x768, 768x768) 2025-09-07T08:54:15.2140182Z strides: [768, 1], [1, 768] 2025-09-07T08:54:15.2140600Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:15.2142149Z triton_mm_8 0.0088 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:15.2142937Z mm 0.0088 ms 99.6% 2025-09-07T08:54:15.2143538Z triton_mm_12 0.0098 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:15.2144534Z triton_mm_4 0.0109 ms 80.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:15.2145475Z triton_mm_7 0.0109 ms 80.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:15.2146411Z triton_mm_11 0.0113 ms 77.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.2147889Z triton_mm_18 0.0114 ms 77.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:15.2149273Z triton_mm_1 0.0120 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:15.2150404Z triton_mm_3 0.0122 ms 71.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:15.2151356Z triton_mm_14 0.0124 ms 70.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:15.2152196Z SingleProcess AUTOTUNE benchmarking takes 0.2344 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:15.4426702Z Autotune Choices Stats: 2025-09-07T08:54:15.4427646Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_64", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.007455999962985516, "best_triton_pos": 0} 2025-09-07T08:54:15.4454153Z AUTOTUNE bmm(48x128x64, 48x64x128) 2025-09-07T08:54:15.4454598Z strides: [8192, 64, 1], [8192, 128, 1] 2025-09-07T08:54:15.4455064Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:15.4456175Z triton_bmm_64 0.0075 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:15.4457815Z triton_bmm_66 0.0075 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.4459496Z triton_bmm_69 0.0075 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:15.4460847Z triton_bmm_65 0.0076 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:15.4461767Z triton_bmm_68 0.0076 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.4462737Z triton_bmm_75 0.0078 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:15.4463631Z triton_bmm_61 0.0079 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:15.4464525Z triton_bmm_67 0.0079 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:15.4465421Z triton_bmm_70 0.0079 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.4466322Z triton_bmm_71 0.0080 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:15.4467117Z SingleProcess AUTOTUNE benchmarking takes 0.2299 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:15.6603746Z Autotune Choices Stats: 2025-09-07T08:54:15.6605810Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_87", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.007327999919652939, "best_triton_pos": 0} 2025-09-07T08:54:15.6837750Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T08:54:15.6838041Z strides: [16384, 128, 1], [8192, 64, 1] 2025-09-07T08:54:15.6838443Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:15.6839141Z triton_bmm_87 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.6841435Z triton_bmm_85 0.0076 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:15.6843004Z triton_bmm_88 0.0076 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:15.6844535Z triton_bmm_83 0.0076 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:15.6846074Z triton_bmm_86 0.0077 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:15.6847614Z triton_bmm_77 0.0078 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:15.6849271Z triton_bmm_84 0.0078 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:15.6850347Z bmm 0.0080 ms 92.0% 2025-09-07T08:54:15.6850916Z triton_bmm_93 0.0081 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:15.6851895Z triton_bmm_78 0.0081 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:15.6852738Z SingleProcess AUTOTUNE benchmarking takes 0.2379 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T08:54:16.7839341Z Autotune Choices Stats: 2025-09-07T08:54:16.7840734Z {"num_choices": 16, "num_triton_choices": 11, "best_kernel": "triton_mm_1815", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1", "best_time": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T08:54:16.8132310Z AUTOTUNE mm(4x768, 768x2) 2025-09-07T08:54:16.8132583Z strides: [768, 1], [1, 768] 2025-09-07T08:54:16.8132804Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:16.8133422Z triton_mm_1815 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:54:16.8134322Z triton_mm_1821 0.0069 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T08:54:16.8135177Z triton_mm_1822 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:54:16.8135995Z triton_mm_1814 0.0079 ms 87.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=1 2025-09-07T08:54:16.8136820Z triton_mm_1818 0.0083 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=1 2025-09-07T08:54:16.9612847Z triton_mm_1813 0.0090 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=1 2025-09-07T08:54:16.9614540Z triton_mm_1820 0.0090 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=1 2025-09-07T08:54:16.9615823Z mm 0.0095 ms 72.1% 2025-09-07T08:54:16.9616257Z decompose_k_mm_6_split_1 0.0100 ms 68.5% k_split=6 2025-09-07T08:54:16.9616802Z decompose_k_mm_4_split_3 0.0103 ms 67.0% k_split=4 2025-09-07T08:54:16.9617653Z SingleProcess AUTOTUNE benchmarking takes 1.0861 seconds and 0.0002 seconds precompiling for 16 choices 2025-09-07T08:54:17.2155688Z Autotune Choices Stats: 2025-09-07T08:54:17.2156646Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1840", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.04623999819159508, "best_triton_pos": 0} 2025-09-07T08:54:17.3245977Z AUTOTUNE mm(512x768, 768x20005) 2025-09-07T08:54:17.3246408Z strides: [768, 1], [1, 768] 2025-09-07T08:54:17.3246809Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:17.3247886Z triton_mm_1840 0.0462 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:17.3249515Z triton_mm_1834 0.0501 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:17.3251129Z triton_mm_1841 0.0511 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:17.3252056Z triton_mm_1839 0.0562 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:17.3252958Z triton_mm_1835 0.0564 ms 82.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:17.3253860Z triton_mm_1832 0.0580 ms 79.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:17.3254766Z triton_mm_1833 0.0592 ms 78.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:17.3255671Z triton_mm_1837 0.0604 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:17.3256566Z triton_mm_1830 0.0623 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:17.3257461Z triton_mm_1836 0.0623 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:17.3258249Z SingleProcess AUTOTUNE benchmarking takes 0.5108 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:35.4045918Z Autotune Choices Stats: 2025-09-07T08:54:35.4047948Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.05225599929690361, "best_triton_pos": 1, "best_triton_time": 0.0804160013794899, "best_triton_kernel": "triton_mm_1878", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T08:54:35.4477309Z AUTOTUNE mm(20005x512, 512x768) 2025-09-07T08:54:35.4477583Z strides: [1, 20032], [768, 1] 2025-09-07T08:54:35.4477859Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:35.4478544Z mm 0.0523 ms 100.0% 2025-09-07T08:54:35.4479210Z triton_mm_1878 0.0804 ms 65.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.4480833Z triton_mm_1872 0.0813 ms 64.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.4481909Z triton_mm_1877 0.0822 ms 63.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.4482975Z triton_mm_1870 0.0836 ms 62.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.4484030Z triton_mm_1871 0.0859 ms 60.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:35.4485084Z triton_mm_1879 0.0972 ms 53.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:35.4486133Z triton_mm_1867 0.1067 ms 49.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:35.4487182Z triton_mm_1874 0.1082 ms 48.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.4488237Z triton_mm_1875 0.1198 ms 43.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:35.4489168Z SingleProcess AUTOTUNE benchmarking takes 0.4955 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T08:54:35.8618277Z Autotune Choices Stats: 2025-09-07T08:54:35.8619553Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010784000158309937, "best_triton_pos": 1, "best_triton_time": 0.012000000104308128, "best_triton_kernel": "triton_mm_1934", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T08:54:35.8922597Z AUTOTUNE mm(768x512, 512x3072) 2025-09-07T08:54:35.8922843Z strides: [1, 768], [3072, 1] 2025-09-07T08:54:35.8923096Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:35.8923357Z mm 0.0108 ms 100.0% 2025-09-07T08:54:35.8923955Z triton_mm_1934 0.0120 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.8925028Z triton_mm_1933 0.0123 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:35.8926241Z triton_mm_1940 0.0128 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.8927246Z triton_mm_1937 0.0128 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:35.8928240Z triton_mm_1932 0.0130 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.8929230Z triton_mm_1936 0.0134 ms 80.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.8930709Z triton_mm_1939 0.0136 ms 79.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:35.8931918Z triton_mm_1930 0.0145 ms 74.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:35.8932918Z triton_mm_1941 0.0156 ms 69.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:35.8933794Z SingleProcess AUTOTUNE benchmarking takes 0.2327 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:36.2898786Z Autotune Choices Stats: 2025-09-07T08:54:36.2901261Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010847999714314938, "best_triton_pos": 1, "best_triton_time": 0.012223999947309494, "best_triton_kernel": "triton_mm_1972", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T08:54:36.3663299Z AUTOTUNE mm(3072x512, 512x768) 2025-09-07T08:54:36.3663767Z strides: [1, 3072], [768, 1] 2025-09-07T08:54:36.3664216Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:36.3664667Z mm 0.0108 ms 100.0% 2025-09-07T08:54:36.3665724Z triton_mm_1972 0.0122 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.3666643Z triton_mm_1971 0.0123 ms 88.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:36.3667543Z triton_mm_1975 0.0126 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:36.3668457Z triton_mm_1978 0.0128 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.3669370Z triton_mm_1970 0.0129 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.3670449Z triton_mm_1974 0.0131 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.3671367Z triton_mm_1977 0.0134 ms 80.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.3672281Z triton_mm_1968 0.0141 ms 77.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:36.3673179Z triton_mm_1979 0.0149 ms 72.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:36.3673973Z SingleProcess AUTOTUNE benchmarking takes 0.2795 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:36.9937772Z Autotune Choices Stats: 2025-09-07T08:54:36.9939691Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01104000024497509, "best_triton_pos": 1, "best_triton_time": 0.012095999903976917, "best_triton_kernel": "triton_mm_1922", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T08:54:36.9970697Z AUTOTUNE mm(512x768, 768x3072) 2025-09-07T08:54:36.9971135Z strides: [768, 1], [3072, 1] 2025-09-07T08:54:36.9971538Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:36.9972464Z mm 0.0110 ms 100.0% 2025-09-07T08:54:36.9973416Z triton_mm_1922 0.0121 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:36.9975384Z triton_mm_1915 0.0127 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.9976590Z triton_mm_1911 0.0129 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:36.9977574Z triton_mm_1921 0.0130 ms 85.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.9978554Z triton_mm_1914 0.0135 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:36.9979535Z triton_mm_1918 0.0139 ms 79.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:36.9980671Z triton_mm_1916 0.0146 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:36.9981676Z triton_mm_1913 0.0153 ms 72.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.9982742Z triton_mm_1917 0.0156 ms 70.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:36.9983601Z SingleProcess AUTOTUNE benchmarking takes 0.2059 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:37.9631884Z Autotune Choices Stats: 2025-09-07T08:54:37.9633129Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.008415999822318554, "best_triton_pos": 1, "best_triton_time": 0.008704000152647495, "best_triton_kernel": "triton_mm_2011", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T08:54:38.0492176Z AUTOTUNE mm(768x512, 512x768) 2025-09-07T08:54:38.0492487Z strides: [1, 768], [768, 1] 2025-09-07T08:54:38.0492756Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:38.0493027Z mm 0.0084 ms 100.0% 2025-09-07T08:54:38.0493658Z triton_mm_2011 0.0087 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:38.0494704Z triton_mm_2010 0.0095 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:38.0495771Z triton_mm_2006 0.0095 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:38.0496668Z triton_mm_2009 0.0098 ms 86.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:38.0497568Z triton_mm_2013 0.0098 ms 85.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:38.0498464Z triton_mm_2017 0.0100 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:38.0499760Z triton_mm_2007 0.0101 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:38.0501212Z triton_mm_2016 0.0101 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:38.0502126Z triton_mm_2008 0.0109 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:38.0503034Z SingleProcess AUTOTUNE benchmarking takes 0.2768 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:39.3673578Z Autotune Choices Stats: 2025-09-07T08:54:39.3674934Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.04396799951791763, "best_triton_pos": 1, "best_triton_time": 0.0674239993095398, "best_triton_kernel": "triton_mm_1850", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:54:39.5000040Z AUTOTUNE mm(512x20008, 20008x768) 2025-09-07T08:54:39.5000500Z strides: [20032, 1], [768, 1] 2025-09-07T08:54:39.5000762Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:39.5001010Z mm 0.0440 ms 100.0% 2025-09-07T08:54:39.5001566Z triton_mm_1850 0.0674 ms 65.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:39.5002497Z triton_mm_1854 0.0811 ms 54.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:39.5003427Z triton_mm_1846 0.0952 ms 46.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:39.5004341Z triton_mm_1860 0.1205 ms 36.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:39.5005274Z triton_mm_1849 0.1322 ms 33.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:39.5006178Z triton_mm_1853 0.1362 ms 32.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:39.5007078Z triton_mm_1845 0.1509 ms 29.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:39.5007985Z triton_mm_1859 0.1541 ms 28.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:39.5008900Z triton_mm_1852 0.1561 ms 28.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:39.5009696Z SingleProcess AUTOTUNE benchmarking takes 0.6529 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:39.9811864Z Autotune Choices Stats: 2025-09-07T08:54:39.9813501Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_1900", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.005535999778658152, "best_triton_pos": 0} 2025-09-07T08:54:40.1328377Z AUTOTUNE mm(2x4, 4x768) 2025-09-07T08:54:40.1328802Z strides: [1, 2], [768, 1] 2025-09-07T08:54:40.1329211Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:40.1331265Z triton_mm_1900 0.0055 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:40.1333283Z triton_mm_1897 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:40.1334902Z triton_mm_1898 0.0056 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:40.1336585Z triton_mm_1902 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:54:40.1337629Z triton_mm_1903 0.0056 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:40.1338470Z triton_mm_1895 0.0056 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:54:40.1339306Z triton_mm_1893 0.0057 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:54:40.1340146Z triton_mm_1899 0.0057 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:40.1341181Z triton_mm_1892 0.0057 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:54:40.1342042Z triton_mm_1894 0.0057 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:40.1342861Z SingleProcess AUTOTUNE benchmarking takes 0.2671 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T08:54:40.9621569Z Autotune Choices Stats: 2025-09-07T08:54:40.9622743Z {"num_choices": 13, "num_triton_choices": 12, "best_kernel": "triton_mm_1882", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.005632000043988228, "best_triton_pos": 0} 2025-09-07T08:54:41.0649457Z AUTOTUNE mm(4x2, 2x768) 2025-09-07T08:54:41.0649882Z strides: [2, 1], [768, 1] 2025-09-07T08:54:41.0650569Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:41.0651604Z triton_mm_1882 0.0056 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:41.0653120Z triton_mm_1881 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:54:41.0654604Z triton_mm_1883 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:54:41.0656077Z triton_mm_1887 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:41.0657370Z triton_mm_1889 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:41.0658269Z triton_mm_1891 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:41.0659556Z triton_mm_1880 0.0057 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:54:41.0660779Z triton_mm_1884 0.0057 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:41.0661670Z triton_mm_1885 0.0057 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:41.0662658Z triton_mm_1886 0.0057 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:41.0663451Z SingleProcess AUTOTUNE benchmarking takes 0.2175 seconds and 0.0002 seconds precompiling for 13 choices 2025-09-07T08:54:41.3106606Z Autotune Choices Stats: 2025-09-07T08:54:41.3107962Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.013024000450968742, "best_triton_pos": 1, "best_triton_time": 0.014047999866306782, "best_triton_kernel": "triton_mm_1950", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:54:41.4168684Z AUTOTUNE mm(512x3072, 3072x768) 2025-09-07T08:54:41.4169141Z strides: [3072, 1], [768, 1] 2025-09-07T08:54:41.4169550Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:41.4169989Z mm 0.0130 ms 100.0% 2025-09-07T08:54:41.4171231Z triton_mm_1950 0.0140 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:41.4172763Z triton_mm_1954 0.0168 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:41.4174290Z triton_mm_1946 0.0206 ms 63.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:41.4175759Z triton_mm_1960 0.0237 ms 54.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:41.4177264Z triton_mm_1953 0.0256 ms 50.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:41.4178228Z triton_mm_1949 0.0258 ms 50.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:41.4179195Z triton_mm_1959 0.0283 ms 46.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:41.4180158Z triton_mm_1945 0.0288 ms 45.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:41.4181256Z triton_mm_1943 0.0296 ms 44.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:41.4182104Z SingleProcess AUTOTUNE benchmarking takes 0.3506 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:54:41.8515579Z Autotune Choices Stats: 2025-09-07T08:54:41.8517345Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.008671999908983707, "best_triton_pos": 1, "best_triton_time": 0.008832000195980072, "best_triton_kernel": "triton_mm_1988", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:54:41.9158403Z AUTOTUNE mm(512x768, 768x768) 2025-09-07T08:54:41.9159511Z strides: [768, 1], [768, 1] 2025-09-07T08:54:41.9160005Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:41.9161080Z mm 0.0087 ms 100.0% 2025-09-07T08:54:41.9162296Z triton_mm_1988 0.0088 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:41.9164303Z triton_mm_1992 0.0098 ms 88.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:41.9166266Z triton_mm_1987 0.0109 ms 79.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:41.9167846Z triton_mm_1991 0.0110 ms 79.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:41.9168997Z triton_mm_1984 0.0111 ms 77.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:41.9170159Z triton_mm_1998 0.0113 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:41.9171489Z triton_mm_1990 0.0118 ms 73.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:41.9172656Z triton_mm_1994 0.0120 ms 72.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:41.9173821Z triton_mm_1983 0.0120 ms 72.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:41.9174842Z SingleProcess AUTOTUNE benchmarking takes 0.4977 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T08:54:42.0895921Z Autotune Choices Stats: 2025-09-07T08:54:42.0897185Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_2027", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.007712000049650669, "best_triton_pos": 0} 2025-09-07T08:54:42.1580099Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T08:54:42.1581037Z strides: [16384, 1, 128], [8192, 64, 1] 2025-09-07T08:54:42.1581472Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:42.1582532Z triton_bmm_2027 0.0077 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.1584191Z triton_bmm_2028 0.0078 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.1585673Z triton_bmm_2029 0.0079 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.1587545Z triton_bmm_2025 0.0080 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:42.1588861Z triton_bmm_2030 0.0080 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:42.1590529Z triton_bmm_2031 0.0081 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.1592038Z triton_bmm_2026 0.0081 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:42.1593368Z triton_bmm_2032 0.0081 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.1594684Z triton_bmm_2034 0.0082 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.1595991Z triton_bmm_2035 0.0083 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:42.1597146Z SingleProcess AUTOTUNE benchmarking takes 0.2407 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T08:54:42.3384827Z Autotune Choices Stats: 2025-09-07T08:54:42.3385921Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_bmm_2040", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.007327999919652939, "best_triton_pos": 0} 2025-09-07T08:54:42.3926218Z AUTOTUNE bmm(48x128x64, 48x64x128) 2025-09-07T08:54:42.3926568Z strides: [8192, 64, 1], [8192, 1, 64] 2025-09-07T08:54:42.3926910Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:42.3927721Z triton_bmm_2040 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:42.3928815Z triton_bmm_2043 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:42.3929868Z triton_bmm_2044 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:42.3931104Z triton_bmm_2047 0.0074 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.3932107Z triton_bmm_2048 0.0075 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:42.3933124Z triton_bmm_2037 0.0075 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:42.3934128Z triton_bmm_2045 0.0075 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.3935129Z triton_bmm_2042 0.0076 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:42.3936118Z triton_bmm_2050 0.0076 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.3937273Z triton_bmm_2046 0.0077 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.3938190Z SingleProcess AUTOTUNE benchmarking takes 0.2338 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T08:54:42.5564828Z Autotune Choices Stats: 2025-09-07T08:54:42.5566219Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_bmm_2069", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8", "best_time": 0.007872000336647034, "best_triton_pos": 0} 2025-09-07T08:54:42.5813456Z AUTOTUNE bmm(48x64x128, 48x128x128) 2025-09-07T08:54:42.5813754Z strides: [8192, 1, 64], [16384, 128, 1] 2025-09-07T08:54:42.5814035Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:42.5814713Z triton_bmm_2069 0.0079 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.5815709Z triton_bmm_2062 0.0079 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:42.5816802Z triton_bmm_2068 0.0079 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.5817873Z triton_bmm_2064 0.0080 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.5818867Z triton_bmm_2063 0.0081 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:42.5819859Z triton_bmm_2058 0.0081 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:42.5821149Z triton_bmm_2066 0.0081 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.5822144Z triton_bmm_2067 0.0081 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:42.5823213Z triton_bmm_2065 0.0082 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.5824187Z triton_bmm_2071 0.0082 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:54:42.5825039Z SingleProcess AUTOTUNE benchmarking takes 0.1881 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:54:42.7551304Z Autotune Choices Stats: 2025-09-07T08:54:42.7552269Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_bmm_2073", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4", "best_time": 0.007679999805986881, "best_triton_pos": 0} 2025-09-07T08:54:42.7838194Z AUTOTUNE bmm(48x128x128, 48x128x64) 2025-09-07T08:54:42.7838648Z strides: [16384, 128, 1], [8192, 1, 128] 2025-09-07T08:54:42.7839070Z dtypes: torch.float16, torch.float16 2025-09-07T08:54:42.7840079Z triton_bmm_2073 0.0077 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:54:42.7842057Z triton_bmm_2083 0.0079 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.7843494Z triton_bmm_2079 0.0081 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:54:42.7845305Z triton_bmm_2081 0.0082 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.7846802Z triton_bmm_2082 0.0082 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.7848205Z triton_bmm_2084 0.0082 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:54:42.7849112Z triton_bmm_2080 0.0083 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:54:42.7850015Z triton_bmm_2086 0.0083 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:54:42.7851054Z triton_bmm_2088 0.0083 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:54:42.7851631Z bmm 0.0084 ms 92.0% 2025-09-07T08:54:42.7852036Z SingleProcess AUTOTUNE benchmarking takes 0.2020 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T08:54:47.8611078Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:54:47.8612172Z pred = mod(*cloned_inputs) 2025-09-07T08:54:47.8612724Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward 2025-09-07T08:54:47.8613292Z x = self.bert(x, segment_label) 2025-09-07T08:54:47.8613812Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward 2025-09-07T08:54:47.8614363Z x = self.embedding(x, segment_info) 2025-09-07T08:54:47.8614929Z File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward 2025-09-07T08:54:47.8615636Z x = self.token(sequence) + self.position(sequence) + self.segment(segment_label) 2025-09-07T08:54:47.8615966Z 2025-09-07T08:54:47.8615971Z 2025-09-07T08:54:49.0339673Z pass 2025-09-07T08:54:53.2506677Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:54:53.2507824Z import pynvml # type: ignore[import] 2025-09-07T08:54:55.7396203Z 2025-09-07T08:54:58.8484984Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:54:58.8485373Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:54:58.8485719Z cuda train Background_Matting 2025-09-07T08:54:58.8713140Z pass_due_to_skip 2025-09-07T08:55:00.4792848Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:55:00.4794341Z import pynvml # type: ignore[import] 2025-09-07T08:55:02.9265800Z 2025-09-07T08:55:05.9093383Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:55:05.9093765Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:55:05.9094084Z cuda train LearningToPaint 2025-09-07T08:55:13.5967421Z Autotune Choices Stats: 2025-09-07T08:55:13.5969145Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_150", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.007071999832987785, "best_triton_pos": 0} 2025-09-07T08:55:13.5987548Z AUTOTUNE mm(4x512, 512x65) 2025-09-07T08:55:13.5987780Z strides: [512, 1], [1, 512] 2025-09-07T08:55:13.5988227Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:13.5988805Z triton_mm_150 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:55:13.5989698Z triton_mm_154 0.0073 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:13.5990716Z triton_mm_149 0.0082 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:55:13.5991557Z triton_mm_148 0.0083 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:13.5992398Z triton_mm_158 0.0084 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:55:13.5993237Z triton_mm_162 0.0084 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:55:13.5994108Z triton_mm_147 0.0085 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:55:13.5994961Z triton_mm_153 0.0086 ms 82.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:13.5995847Z triton_mm_157 0.0087 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:13.5996735Z triton_mm_160 0.0092 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:55:13.5997515Z SingleProcess AUTOTUNE benchmarking takes 0.2045 seconds and 0.0208 seconds precompiling for 18 choices 2025-09-07T08:55:14.4263653Z Autotune Choices Stats: 2025-09-07T08:55:14.4265575Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_4", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.01152000017464161, "best_triton_pos": 0} 2025-09-07T08:55:14.4283850Z AUTOTUNE convolution(4x9x128x128, 64x9x3x3) 2025-09-07T08:55:14.4284148Z strides: [147456, 1, 1152, 9], [81, 1, 27, 9] 2025-09-07T08:55:14.4284416Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.4285168Z triton_convolution2d_4 0.0115 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.4286479Z triton_convolution2d_0 0.0136 ms 84.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.4287790Z triton_convolution2d_3 0.0138 ms 83.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.4289040Z triton_convolution2d_5 0.0172 ms 66.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.4289802Z convolution 0.0187 ms 61.6% 2025-09-07T08:55:14.4291421Z triton_convolution2d_2 0.0192 ms 60.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:14.4292936Z triton_convolution2d_1 0.0335 ms 34.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.4293917Z SingleProcess AUTOTUNE benchmarking takes 0.1518 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T08:55:14.5282211Z Autotune Choices Stats: 2025-09-07T08:55:14.5283578Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011359999887645245, "best_triton_pos": 1, "best_triton_time": 0.01664000004529953, "best_triton_kernel": "triton_convolution2d_11", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:55:14.5302959Z AUTOTUNE convolution(4x64x64x64, 64x64x3x3) 2025-09-07T08:55:14.5303245Z strides: [262144, 1, 4096, 64], [576, 1, 192, 64] 2025-09-07T08:55:14.5303518Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.5303759Z convolution 0.0114 ms 100.0% 2025-09-07T08:55:14.5304402Z triton_convolution2d_11 0.0166 ms 68.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.5305459Z triton_convolution2d_10 0.0171 ms 66.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.5306595Z triton_convolution2d_9 0.0179 ms 63.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.5307721Z triton_convolution2d_6 0.0214 ms 53.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.5308846Z triton_convolution2d_12 0.0235 ms 48.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.5309971Z triton_convolution2d_7 0.0307 ms 37.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.5311413Z triton_convolution2d_8 0.0565 ms 20.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:14.5312325Z SingleProcess AUTOTUNE benchmarking takes 0.1014 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:14.6285408Z Autotune Choices Stats: 2025-09-07T08:55:14.6287356Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010495999827980995, "best_triton_pos": 1, "best_triton_time": 0.01600000075995922, "best_triton_kernel": "triton_convolution2d_18", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:55:14.6305810Z AUTOTUNE convolution(4x64x32x32, 64x64x3x3) 2025-09-07T08:55:14.6306106Z strides: [65536, 1, 2048, 64], [576, 1, 192, 64] 2025-09-07T08:55:14.6306403Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.6306645Z convolution 0.0105 ms 100.0% 2025-09-07T08:55:14.6307519Z triton_convolution2d_18 0.0160 ms 65.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.6308778Z triton_convolution2d_17 0.0161 ms 65.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.6309903Z triton_convolution2d_16 0.0167 ms 62.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.6311302Z triton_convolution2d_13 0.0201 ms 52.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.6312436Z triton_convolution2d_19 0.0209 ms 50.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.6313561Z triton_convolution2d_14 0.0292 ms 36.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.6314687Z triton_convolution2d_15 0.0520 ms 20.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:14.6315591Z SingleProcess AUTOTUNE benchmarking takes 0.0996 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:14.7255406Z Autotune Choices Stats: 2025-09-07T08:55:14.7257140Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_25", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8", "best_time": 0.006943999789655209, "best_triton_pos": 0} 2025-09-07T08:55:14.7275044Z AUTOTUNE convolution(4x64x64x64, 64x64x1x1) 2025-09-07T08:55:14.7275329Z strides: [262144, 1, 4096, 64], [64, 1, 64, 64] 2025-09-07T08:55:14.7275599Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.7276441Z triton_convolution2d_25 0.0069 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:14.7277784Z triton_convolution2d_24 0.0071 ms 97.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:14.7279103Z triton_convolution2d_23 0.0074 ms 93.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:14.7280618Z triton_convolution2d_20 0.0075 ms 93.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:14.7281924Z triton_convolution2d_26 0.0082 ms 84.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:14.7283227Z triton_convolution2d_21 0.0091 ms 76.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:14.7284041Z convolution 0.0110 ms 63.3% 2025-09-07T08:55:14.7285031Z triton_convolution2d_22 0.0124 ms 56.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T08:55:14.7286184Z SingleProcess AUTOTUNE benchmarking takes 0.0963 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:14.8280968Z Autotune Choices Stats: 2025-09-07T08:55:14.8282314Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009727999567985535, "best_triton_pos": 1, "best_triton_time": 0.016448000445961952, "best_triton_kernel": "triton_convolution2d_45", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:14.8301866Z AUTOTUNE convolution(4x64x32x32, 128x64x3x3) 2025-09-07T08:55:14.8302152Z strides: [65536, 1, 2048, 64], [576, 1, 192, 64] 2025-09-07T08:55:14.8302429Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.8302766Z convolution 0.0097 ms 100.0% 2025-09-07T08:55:14.8303447Z triton_convolution2d_45 0.0164 ms 59.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.8304598Z triton_convolution2d_46 0.0171 ms 56.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.8305745Z triton_convolution2d_44 0.0193 ms 50.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.8306900Z triton_convolution2d_41 0.0228 ms 42.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.8308030Z triton_convolution2d_47 0.0235 ms 41.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.8309178Z triton_convolution2d_42 0.0302 ms 32.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.8310635Z triton_convolution2d_43 0.0564 ms 17.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:14.8311549Z SingleProcess AUTOTUNE benchmarking takes 0.1004 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:14.9420784Z Autotune Choices Stats: 2025-09-07T08:55:14.9423124Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01158399973064661, "best_triton_pos": 1, "best_triton_time": 0.02864000014960766, "best_triton_kernel": "triton_convolution2d_52", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:14.9440492Z AUTOTUNE convolution(4x128x16x16, 128x128x3x3) 2025-09-07T08:55:14.9440800Z strides: [32768, 1, 2048, 128], [1152, 1, 384, 128] 2025-09-07T08:55:14.9441082Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:14.9441334Z convolution 0.0116 ms 100.0% 2025-09-07T08:55:14.9442018Z triton_convolution2d_52 0.0286 ms 40.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.9443404Z triton_convolution2d_53 0.0331 ms 35.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.9444706Z triton_convolution2d_54 0.0366 ms 31.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.9445863Z triton_convolution2d_51 0.0382 ms 30.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:14.9447006Z triton_convolution2d_48 0.0458 ms 25.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.9448142Z triton_convolution2d_49 0.0536 ms 21.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:14.9449283Z triton_convolution2d_50 0.0951 ms 12.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:14.9450387Z SingleProcess AUTOTUNE benchmarking takes 0.1133 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.0377327Z Autotune Choices Stats: 2025-09-07T08:55:15.0379094Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_59", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.006560000125318766, "best_triton_pos": 0} 2025-09-07T08:55:15.0397538Z AUTOTUNE convolution(4x64x32x32, 128x64x1x1) 2025-09-07T08:55:15.0397856Z strides: [65536, 1, 2048, 64], [64, 1, 64, 64] 2025-09-07T08:55:15.0398163Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.0398928Z triton_convolution2d_59 0.0066 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.0400157Z triton_convolution2d_60 0.0069 ms 94.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.0401036Z convolution 0.0076 ms 86.9% 2025-09-07T08:55:15.0401757Z triton_convolution2d_55 0.0076 ms 86.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.0402981Z triton_convolution2d_58 0.0077 ms 85.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.0404211Z triton_convolution2d_61 0.0078 ms 83.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.0405424Z triton_convolution2d_56 0.0086 ms 76.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.0406650Z triton_convolution2d_57 0.0121 ms 54.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T08:55:15.0407813Z SingleProcess AUTOTUNE benchmarking takes 0.0951 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.1593412Z Autotune Choices Stats: 2025-09-07T08:55:15.1594948Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011071999557316303, "best_triton_pos": 1, "best_triton_time": 0.030047999694943428, "best_triton_kernel": "triton_convolution2d_80", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:15.1614075Z AUTOTUNE convolution(4x128x16x16, 256x128x3x3) 2025-09-07T08:55:15.1614363Z strides: [32768, 1, 2048, 128], [1152, 1, 384, 128] 2025-09-07T08:55:15.1614643Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.1614898Z convolution 0.0111 ms 100.0% 2025-09-07T08:55:15.1615600Z triton_convolution2d_80 0.0300 ms 36.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.1617305Z triton_convolution2d_79 0.0387 ms 28.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.1619266Z triton_convolution2d_82 0.0403 ms 27.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.1621749Z triton_convolution2d_81 0.0412 ms 26.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.1623824Z triton_convolution2d_77 0.0545 ms 20.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.1625752Z triton_convolution2d_76 0.0550 ms 20.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.1627485Z triton_convolution2d_78 0.0721 ms 15.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:15.1628461Z SingleProcess AUTOTUNE benchmarking takes 0.1194 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.2999812Z Autotune Choices Stats: 2025-09-07T08:55:15.3001518Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013344000093638897, "best_triton_pos": 1, "best_triton_time": 0.05305600166320801, "best_triton_kernel": "triton_convolution2d_87", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:15.3020851Z AUTOTUNE convolution(4x256x8x8, 256x256x3x3) 2025-09-07T08:55:15.3021127Z strides: [16384, 1, 2048, 256], [2304, 1, 768, 256] 2025-09-07T08:55:15.3021405Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.3021644Z convolution 0.0133 ms 100.0% 2025-09-07T08:55:15.3022280Z triton_convolution2d_87 0.0531 ms 25.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.3023420Z triton_convolution2d_89 0.0691 ms 19.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.3024676Z triton_convolution2d_86 0.0701 ms 19.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.3025875Z triton_convolution2d_88 0.0754 ms 17.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.3027101Z triton_convolution2d_85 0.0970 ms 13.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:15.3028326Z triton_convolution2d_84 0.0998 ms 13.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.3029544Z triton_convolution2d_83 0.1029 ms 13.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.3030659Z SingleProcess AUTOTUNE benchmarking takes 0.1400 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.3959807Z Autotune Choices Stats: 2025-09-07T08:55:15.3961130Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_94", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4", "best_time": 0.007712000049650669, "best_triton_pos": 0} 2025-09-07T08:55:15.3981045Z AUTOTUNE convolution(4x128x16x16, 256x128x1x1) 2025-09-07T08:55:15.3981361Z strides: [32768, 1, 2048, 128], [128, 1, 128, 128] 2025-09-07T08:55:15.3981641Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.3982355Z triton_convolution2d_94 0.0077 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.3983127Z convolution 0.0083 ms 93.4% 2025-09-07T08:55:15.3983802Z triton_convolution2d_93 0.0091 ms 84.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.3984936Z triton_convolution2d_95 0.0092 ms 83.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.3986087Z triton_convolution2d_96 0.0094 ms 82.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.3987311Z triton_convolution2d_90 0.0105 ms 73.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.3988527Z triton_convolution2d_91 0.0109 ms 70.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.3989759Z triton_convolution2d_92 0.0134 ms 57.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T08:55:15.3990885Z SingleProcess AUTOTUNE benchmarking takes 0.0953 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.5991263Z Autotune Choices Stats: 2025-09-07T08:55:15.5992977Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013407999649643898, "best_triton_pos": 1, "best_triton_time": 0.05648000165820122, "best_triton_kernel": "triton_convolution2d_115", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:15.6012879Z AUTOTUNE convolution(4x256x8x8, 512x256x3x3) 2025-09-07T08:55:15.6013228Z strides: [16384, 1, 2048, 256], [2304, 1, 768, 256] 2025-09-07T08:55:15.6013554Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.6013839Z convolution 0.0134 ms 100.0% 2025-09-07T08:55:15.6014635Z triton_convolution2d_115 0.0565 ms 23.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.6015985Z triton_convolution2d_114 0.0693 ms 19.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.6017339Z triton_convolution2d_117 0.0724 ms 18.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.6018669Z triton_convolution2d_116 0.0760 ms 17.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.6020004Z triton_convolution2d_113 0.0912 ms 14.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:55:15.6021593Z triton_convolution2d_112 0.0988 ms 13.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.6023020Z triton_convolution2d_111 0.1083 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.6024075Z SingleProcess AUTOTUNE benchmarking takes 0.2008 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.7932183Z Autotune Choices Stats: 2025-09-07T08:55:15.7934399Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.016896000131964684, "best_triton_pos": 1, "best_triton_time": 0.10902400314807892, "best_triton_kernel": "triton_convolution2d_122", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:55:15.7953078Z AUTOTUNE convolution(4x512x4x4, 512x512x3x3) 2025-09-07T08:55:15.7953473Z strides: [8192, 1, 2048, 512], [4608, 1, 1536, 512] 2025-09-07T08:55:15.7953840Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.7954154Z convolution 0.0169 ms 100.0% 2025-09-07T08:55:15.7955030Z triton_convolution2d_122 0.1090 ms 15.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.7956510Z triton_convolution2d_124 0.1123 ms 15.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.7957994Z triton_convolution2d_121 0.1226 ms 13.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.7959693Z triton_convolution2d_123 0.1443 ms 11.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:55:15.7961532Z triton_convolution2d_120 0.1618 ms 10.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=4 2025-09-07T08:55:15.7962998Z triton_convolution2d_119 0.1744 ms 9.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.7964465Z triton_convolution2d_118 0.2445 ms 6.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:55:15.7965632Z SingleProcess AUTOTUNE benchmarking takes 0.1933 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:15.8893348Z Autotune Choices Stats: 2025-09-07T08:55:15.8895192Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.008415999822318554, "best_triton_pos": 1, "best_triton_time": 0.010304000228643417, "best_triton_kernel": "triton_convolution2d_129", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T08:55:15.8914744Z AUTOTUNE convolution(4x256x8x8, 512x256x1x1) 2025-09-07T08:55:15.8915113Z strides: [16384, 1, 2048, 256], [256, 1, 256, 256] 2025-09-07T08:55:15.8915467Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:15.8915787Z convolution 0.0084 ms 100.0% 2025-09-07T08:55:15.8917032Z triton_convolution2d_129 0.0103 ms 81.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.8919154Z triton_convolution2d_128 0.0119 ms 70.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.8921447Z triton_convolution2d_130 0.0121 ms 69.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.8923478Z triton_convolution2d_131 0.0122 ms 68.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T08:55:15.8925460Z triton_convolution2d_127 0.0126 ms 66.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T08:55:15.8927575Z triton_convolution2d_126 0.0143 ms 58.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.8929055Z triton_convolution2d_125 0.0156 ms 54.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T08:55:15.8930332Z SingleProcess AUTOTUNE benchmarking takes 0.0955 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:55:20.1019890Z Autotune Choices Stats: 2025-09-07T08:55:20.1022986Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_180", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2", "best_time": 0.005696000065654516, "best_triton_pos": 0} 2025-09-07T08:55:20.1041646Z AUTOTUNE mm(65x4, 4x512) 2025-09-07T08:55:20.1042140Z strides: [1, 65], [512, 1] 2025-09-07T08:55:20.1042387Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:20.1043044Z triton_mm_180 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T08:55:20.1044051Z triton_mm_182 0.0057 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:55:20.1045034Z triton_mm_181 0.0057 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:55:20.1045997Z triton_mm_184 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:20.1046958Z triton_mm_185 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:55:20.1047925Z triton_mm_192 0.0059 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:55:20.1048882Z triton_mm_183 0.0059 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:55:20.1049832Z triton_mm_186 0.0059 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:55:20.1050953Z triton_mm_187 0.0059 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:20.1051921Z triton_mm_191 0.0059 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:20.1052764Z SingleProcess AUTOTUNE benchmarking takes 0.1583 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:55:20.7195992Z Autotune Choices Stats: 2025-09-07T08:55:20.7197036Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_165", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.006304000038653612, "best_triton_pos": 0} 2025-09-07T08:55:20.7218653Z AUTOTUNE mm(4x65, 65x512) 2025-09-07T08:55:20.7218943Z strides: [65, 1], [512, 1] 2025-09-07T08:55:20.7219201Z dtypes: torch.float16, torch.float16 2025-09-07T08:55:20.7219907Z triton_mm_165 0.0063 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:20.7221319Z triton_mm_176 0.0064 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:20.7222324Z triton_mm_177 0.0064 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:55:20.7223423Z triton_mm_164 0.0064 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:55:20.7224873Z triton_mm_166 0.0064 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:55:20.7225907Z triton_mm_170 0.0064 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:20.7227141Z triton_mm_171 0.0064 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:55:20.7228251Z triton_mm_167 0.0064 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:55:20.7229225Z triton_mm_174 0.0066 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:55:20.7230200Z triton_mm_179 0.0066 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:55:20.7231240Z SingleProcess AUTOTUNE benchmarking takes 0.1645 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:55:23.0999334Z pass 2025-09-07T08:55:26.6038952Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:55:26.6040051Z import pynvml # type: ignore[import] 2025-09-07T08:55:29.0713035Z 2025-09-07T08:55:31.8043594Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:55:31.8043978Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:55:31.8044306Z cuda train Super_SloMo 2025-09-07T08:56:32.9297681Z Autotune Choices Stats: 2025-09-07T08:56:32.9299512Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_324", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.0578560009598732, "best_triton_pos": 0} 2025-09-07T08:56:33.1341880Z AUTOTUNE convolution(4x3x352x352, 64x3x3x3) 2025-09-07T08:56:33.1342513Z strides: [371712, 123904, 352, 1], [27, 9, 3, 1] 2025-09-07T08:56:33.1343178Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:33.1344445Z triton_convolution2d_324 0.0579 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:33.1346521Z triton_convolution2d_320 0.0661 ms 87.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:33.1348620Z triton_convolution2d_322 0.0663 ms 87.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:33.1350580Z triton_convolution2d_319 0.0714 ms 81.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:33.1351846Z triton_convolution2d_323 0.0826 ms 70.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:33.1353082Z triton_convolution2d_321 0.1063 ms 54.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:33.1353843Z convolution 0.1329 ms 43.5% 2025-09-07T08:56:33.1354901Z SingleProcess AUTOTUNE benchmarking takes 0.3291 seconds and 0.0004 seconds precompiling for 7 choices 2025-09-07T08:56:33.8941838Z Autotune Choices Stats: 2025-09-07T08:56:33.8944290Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.22089600563049316, "best_triton_pos": 1, "best_triton_time": 0.26121601462364197, "best_triton_kernel": "triton_convolution2d_328", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:34.0406094Z AUTOTUNE convolution(4x64x352x352, 64x64x3x3) 2025-09-07T08:56:34.0406705Z strides: [7929856, 123904, 352, 1], [576, 9, 3, 1] 2025-09-07T08:56:34.0415343Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:34.0415662Z convolution 0.2209 ms 100.0% 2025-09-07T08:56:34.0416410Z triton_convolution2d_328 0.2612 ms 84.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.0417621Z triton_convolution2d_331 0.2658 ms 83.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.0418793Z triton_convolution2d_326 0.2958 ms 74.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.0419947Z triton_convolution2d_329 0.3049 ms 72.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.0421319Z triton_convolution2d_330 0.3290 ms 67.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.0422464Z triton_convolution2d_325 0.3807 ms 58.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.0423675Z triton_convolution2d_327 0.9620 ms 23.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:34.0424597Z SingleProcess AUTOTUNE benchmarking takes 0.4206 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:34.3104972Z Autotune Choices Stats: 2025-09-07T08:56:34.3106120Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_1", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.16364799439907074, "best_triton_pos": 0} 2025-09-07T08:56:34.3296097Z AUTOTUNE convolution(4x6x352x352, 32x6x7x7) 2025-09-07T08:56:34.3296434Z strides: [743424, 123904, 352, 1], [294, 49, 7, 1] 2025-09-07T08:56:34.3296771Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:34.3297541Z triton_convolution2d_1 0.1636 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.3298831Z triton_convolution2d_5 0.1732 ms 94.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.3299734Z convolution 0.1800 ms 90.9% 2025-09-07T08:56:34.3302235Z triton_convolution2d_3 0.2226 ms 73.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.3303753Z triton_convolution2d_0 0.2412 ms 67.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.3304973Z triton_convolution2d_4 0.3130 ms 52.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.3306190Z triton_convolution2d_2 0.3266 ms 50.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:34.3307166Z SingleProcess AUTOTUNE benchmarking takes 0.2334 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T08:56:34.9048299Z Autotune Choices Stats: 2025-09-07T08:56:34.9050164Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.3136320114135742, "best_triton_pos": 1, "best_triton_time": 0.5186560153961182, "best_triton_kernel": "triton_convolution2d_7", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:34.9542014Z AUTOTUNE convolution(4x32x352x352, 32x32x7x7) 2025-09-07T08:56:34.9542363Z strides: [3964928, 123904, 352, 1], [1568, 49, 7, 1] 2025-09-07T08:56:34.9542762Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:34.9543055Z convolution 0.3136 ms 100.0% 2025-09-07T08:56:34.9543829Z triton_convolution2d_7 0.5187 ms 60.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.9545068Z triton_convolution2d_12 0.7403 ms 42.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.9546331Z triton_convolution2d_6 0.7778 ms 40.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.9547547Z triton_convolution2d_9 0.8220 ms 38.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.9548768Z triton_convolution2d_10 1.0053 ms 31.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:34.9550132Z triton_convolution2d_11 1.0260 ms 30.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:34.9551523Z triton_convolution2d_8 1.3484 ms 23.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:34.9552496Z SingleProcess AUTOTUNE benchmarking takes 0.3369 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:35.2288753Z Autotune Choices Stats: 2025-09-07T08:56:35.2292085Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.1910720020532608, "best_triton_pos": 1, "best_triton_time": 0.194815993309021, "best_triton_kernel": "triton_convolution2d_140", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:35.3644988Z AUTOTUNE convolution(4x64x352x352, 32x64x3x3) 2025-09-07T08:56:35.3645574Z strides: [7929856, 123904, 352, 1], [576, 9, 3, 1] 2025-09-07T08:56:35.3646090Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:35.3646553Z convolution 0.1911 ms 100.0% 2025-09-07T08:56:35.3647775Z triton_convolution2d_140 0.1948 ms 98.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:35.3649866Z triton_convolution2d_139 0.2565 ms 74.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:35.3652336Z triton_convolution2d_145 0.2580 ms 74.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:35.3653457Z triton_convolution2d_142 0.2719 ms 70.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:35.3654529Z triton_convolution2d_143 0.3173 ms 60.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:35.3655590Z triton_convolution2d_144 0.3382 ms 56.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:35.3656675Z triton_convolution2d_141 0.5099 ms 37.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:35.3657539Z SingleProcess AUTOTUNE benchmarking takes 0.3962 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:35.8942439Z Autotune Choices Stats: 2025-09-07T08:56:35.8943990Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.32864001393318176, "best_triton_pos": 1, "best_triton_time": 0.48399999737739563, "best_triton_kernel": "triton_convolution2d_160", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:36.0176181Z AUTOTUNE convolution(4x20x352x352, 32x20x7x7) 2025-09-07T08:56:36.0176532Z strides: [2478080, 123904, 352, 1], [980, 49, 7, 1] 2025-09-07T08:56:36.0176851Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:36.0177138Z convolution 0.3286 ms 100.0% 2025-09-07T08:56:36.0177933Z triton_convolution2d_160 0.4840 ms 67.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.0179203Z triton_convolution2d_165 0.5368 ms 61.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.0180804Z triton_convolution2d_162 0.5968 ms 55.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.0181961Z triton_convolution2d_159 0.6543 ms 50.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.0183673Z triton_convolution2d_163 0.7287 ms 45.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.0185030Z triton_convolution2d_164 0.7625 ms 43.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.0186178Z triton_convolution2d_161 1.1971 ms 27.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:36.0187093Z SingleProcess AUTOTUNE benchmarking takes 0.4068 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:36.2874733Z Autotune Choices Stats: 2025-09-07T08:56:36.2876176Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09907200187444687, "best_triton_pos": 1, "best_triton_time": 0.14582400023937225, "best_triton_kernel": "triton_convolution2d_338", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:36.3727992Z AUTOTUNE convolution(4x64x176x176, 128x64x3x3) 2025-09-07T08:56:36.3728606Z strides: [1982464, 30976, 176, 1], [576, 9, 3, 1] 2025-09-07T08:56:36.3729103Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:36.3729554Z convolution 0.0991 ms 100.0% 2025-09-07T08:56:36.3731763Z triton_convolution2d_338 0.1458 ms 67.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.3733820Z triton_convolution2d_335 0.1498 ms 66.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.3735854Z triton_convolution2d_333 0.1519 ms 65.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.3737812Z triton_convolution2d_337 0.1660 ms 59.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.3739800Z triton_convolution2d_336 0.1668 ms 59.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.3741167Z triton_convolution2d_332 0.1754 ms 56.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.3742248Z triton_convolution2d_334 0.5180 ms 19.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:36.3743162Z SingleProcess AUTOTUNE benchmarking takes 0.2899 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:36.8952244Z Autotune Choices Stats: 2025-09-07T08:56:36.8953663Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.13436800241470337, "best_triton_pos": 1, "best_triton_time": 0.3115519881248474, "best_triton_kernel": "triton_convolution2d_345", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:36.9935196Z AUTOTUNE convolution(4x128x176x176, 128x128x3x3) 2025-09-07T08:56:36.9935758Z strides: [3964928, 30976, 176, 1], [1152, 9, 3, 1] 2025-09-07T08:56:36.9936515Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:36.9936953Z convolution 0.1344 ms 100.0% 2025-09-07T08:56:36.9938150Z triton_convolution2d_345 0.3116 ms 43.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.9940130Z triton_convolution2d_340 0.3160 ms 42.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.9941672Z triton_convolution2d_342 0.3497 ms 38.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.9942926Z triton_convolution2d_343 0.3710 ms 36.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.9944077Z triton_convolution2d_339 0.3772 ms 35.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:36.9945217Z triton_convolution2d_344 0.3854 ms 34.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:36.9946356Z triton_convolution2d_341 1.0940 ms 12.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:36.9947271Z SingleProcess AUTOTUNE benchmarking takes 0.3636 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:37.1935044Z Autotune Choices Stats: 2025-09-07T08:56:37.1936180Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_19", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.0942080020904541, "best_triton_pos": 0} 2025-09-07T08:56:37.3275091Z AUTOTUNE convolution(4x32x176x176, 64x32x5x5) 2025-09-07T08:56:37.3275410Z strides: [991232, 30976, 176, 1], [800, 25, 5, 1] 2025-09-07T08:56:37.3275712Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:37.3276516Z triton_convolution2d_19 0.0942 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.3277301Z convolution 0.1024 ms 92.0% 2025-09-07T08:56:37.3278039Z triton_convolution2d_14 0.1038 ms 90.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.3279270Z triton_convolution2d_16 0.1079 ms 87.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.3280827Z triton_convolution2d_17 0.1271 ms 74.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.3281991Z triton_convolution2d_13 0.1275 ms 73.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.3283368Z triton_convolution2d_18 0.1308 ms 72.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.3284670Z triton_convolution2d_15 0.3471 ms 27.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:37.3285585Z SingleProcess AUTOTUNE benchmarking takes 0.3080 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:37.8657399Z Autotune Choices Stats: 2025-09-07T08:56:37.8658827Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.10447999835014343, "best_triton_pos": 1, "best_triton_time": 0.2210880070924759, "best_triton_kernel": "triton_convolution2d_26", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:37.8990754Z AUTOTUNE convolution(4x64x176x176, 64x64x5x5) 2025-09-07T08:56:37.8991157Z strides: [1982464, 30976, 176, 1], [1600, 25, 5, 1] 2025-09-07T08:56:37.8991461Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:37.8991726Z convolution 0.1045 ms 100.0% 2025-09-07T08:56:37.8992471Z triton_convolution2d_26 0.2211 ms 47.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.8993716Z triton_convolution2d_21 0.2375 ms 44.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.8994956Z triton_convolution2d_23 0.2605 ms 40.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.8996188Z triton_convolution2d_24 0.3329 ms 31.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.8997408Z triton_convolution2d_20 0.3503 ms 29.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:37.8998629Z triton_convolution2d_25 0.3818 ms 27.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:37.8999869Z triton_convolution2d_22 0.7176 ms 14.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:37.9000961Z SingleProcess AUTOTUNE benchmarking takes 0.2900 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:38.1294903Z Autotune Choices Stats: 2025-09-07T08:56:38.1297152Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.10444799810647964, "best_triton_pos": 1, "best_triton_time": 0.15884800255298615, "best_triton_kernel": "triton_convolution2d_131", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:38.1487086Z AUTOTUNE convolution(4x128x176x176, 64x128x3x3) 2025-09-07T08:56:38.1487671Z strides: [3964928, 30976, 176, 1], [1152, 9, 3, 1] 2025-09-07T08:56:38.1488204Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:38.1488657Z convolution 0.1044 ms 100.0% 2025-09-07T08:56:38.1490652Z triton_convolution2d_131 0.1588 ms 65.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.1492033Z triton_convolution2d_128 0.1594 ms 65.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.1493177Z triton_convolution2d_126 0.1621 ms 64.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.1494311Z triton_convolution2d_129 0.1924 ms 54.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.1495445Z triton_convolution2d_130 0.1940 ms 53.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.1496580Z triton_convolution2d_125 0.2100 ms 49.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.1497718Z triton_convolution2d_127 0.5571 ms 18.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:38.1498618Z SingleProcess AUTOTUNE benchmarking takes 0.2358 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:38.7165076Z Autotune Choices Stats: 2025-09-07T08:56:38.7167358Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.09942399710416794, "best_triton_pos": 1, "best_triton_time": 0.14819200336933136, "best_triton_kernel": "triton_convolution2d_352", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:38.9313488Z AUTOTUNE convolution(4x128x88x88, 256x128x3x3) 2025-09-07T08:56:38.9313826Z strides: [991232, 7744, 88, 1], [1152, 9, 3, 1] 2025-09-07T08:56:38.9314137Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:38.9314411Z convolution 0.0994 ms 100.0% 2025-09-07T08:56:38.9315169Z triton_convolution2d_352 0.1482 ms 67.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.9316440Z triton_convolution2d_347 0.1608 ms 61.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.9317700Z triton_convolution2d_349 0.1733 ms 57.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.9318936Z triton_convolution2d_350 0.1929 ms 51.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.9320182Z triton_convolution2d_346 0.2260 ms 44.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:38.9322081Z triton_convolution2d_351 0.2358 ms 42.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:38.9323252Z triton_convolution2d_348 0.5505 ms 18.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:38.9324405Z SingleProcess AUTOTUNE benchmarking takes 0.4401 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:39.4494454Z Autotune Choices Stats: 2025-09-07T08:56:39.4496712Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.0952640026807785, "best_triton_pos": 1, "best_triton_time": 0.3134720027446747, "best_triton_kernel": "triton_convolution2d_359", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:39.6596747Z AUTOTUNE convolution(4x256x88x88, 256x256x3x3) 2025-09-07T08:56:39.6597134Z strides: [1982464, 7744, 88, 1], [2304, 9, 3, 1] 2025-09-07T08:56:39.6597503Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:39.6597837Z convolution 0.0953 ms 100.0% 2025-09-07T08:56:39.6598737Z triton_convolution2d_359 0.3135 ms 30.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.6600526Z triton_convolution2d_354 0.3152 ms 30.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.6602015Z triton_convolution2d_356 0.3585 ms 26.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.6603500Z triton_convolution2d_357 0.3726 ms 25.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.6604967Z triton_convolution2d_353 0.4398 ms 21.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.6606436Z triton_convolution2d_358 0.4732 ms 20.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.6607899Z triton_convolution2d_355 1.0997 ms 8.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:39.6609067Z SingleProcess AUTOTUNE benchmarking takes 0.4719 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:39.8224814Z Autotune Choices Stats: 2025-09-07T08:56:39.8226674Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_33", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.03996799886226654, "best_triton_pos": 0} 2025-09-07T08:56:39.9012023Z AUTOTUNE convolution(4x64x88x88, 128x64x3x3) 2025-09-07T08:56:39.9012419Z strides: [495616, 7744, 88, 1], [576, 9, 3, 1] 2025-09-07T08:56:39.9012776Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:39.9013698Z triton_convolution2d_33 0.0400 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.9015049Z convolution 0.0412 ms 97.0% 2025-09-07T08:56:39.9015968Z triton_convolution2d_30 0.0413 ms 96.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.9017658Z triton_convolution2d_28 0.0446 ms 89.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.9019133Z triton_convolution2d_31 0.0495 ms 80.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.9022082Z triton_convolution2d_32 0.0500 ms 80.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:39.9023650Z triton_convolution2d_27 0.0675 ms 59.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:39.9025125Z triton_convolution2d_29 0.1309 ms 30.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:39.9026291Z SingleProcess AUTOTUNE benchmarking takes 0.1990 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:40.3557204Z Autotune Choices Stats: 2025-09-07T08:56:40.3558915Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.051872000098228455, "best_triton_pos": 1, "best_triton_time": 0.07942400127649307, "best_triton_kernel": "triton_convolution2d_40", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:40.3766146Z AUTOTUNE convolution(4x128x88x88, 128x128x3x3) 2025-09-07T08:56:40.3766526Z strides: [991232, 7744, 88, 1], [1152, 9, 3, 1] 2025-09-07T08:56:40.3766864Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:40.3767169Z convolution 0.0519 ms 100.0% 2025-09-07T08:56:40.3768041Z triton_convolution2d_40 0.0794 ms 65.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.3769520Z triton_convolution2d_35 0.0855 ms 60.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.3771158Z triton_convolution2d_37 0.0908 ms 57.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.3772500Z triton_convolution2d_38 0.1014 ms 51.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.3773834Z triton_convolution2d_39 0.1017 ms 51.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.3775160Z triton_convolution2d_34 0.1515 ms 34.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.3776831Z triton_convolution2d_36 0.2814 ms 18.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:40.3777907Z SingleProcess AUTOTUNE benchmarking takes 0.1904 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:40.6151604Z Autotune Choices Stats: 2025-09-07T08:56:40.6153104Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.07369600236415863, "best_triton_pos": 1, "best_triton_time": 0.16105599701404572, "best_triton_kernel": "triton_convolution2d_112", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:40.6344795Z AUTOTUNE convolution(4x256x88x88, 128x256x3x3) 2025-09-07T08:56:40.6345148Z strides: [1982464, 7744, 88, 1], [2304, 9, 3, 1] 2025-09-07T08:56:40.6345467Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:40.6345751Z convolution 0.0737 ms 100.0% 2025-09-07T08:56:40.6346543Z triton_convolution2d_112 0.1611 ms 45.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.6347843Z triton_convolution2d_117 0.1712 ms 43.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.6349114Z triton_convolution2d_114 0.1796 ms 41.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.6350834Z triton_convolution2d_115 0.1978 ms 37.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.6352249Z triton_convolution2d_116 0.1996 ms 36.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:40.6353593Z triton_convolution2d_111 0.2883 ms 25.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:40.6354938Z triton_convolution2d_113 0.5495 ms 13.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:40.6356001Z SingleProcess AUTOTUNE benchmarking takes 0.2440 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:41.1280607Z Autotune Choices Stats: 2025-09-07T08:56:41.1282985Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.06457599997520447, "best_triton_pos": 1, "best_triton_time": 0.15744000673294067, "best_triton_kernel": "triton_convolution2d_368", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:41.1308478Z AUTOTUNE convolution(4x256x44x44, 512x256x3x3) 2025-09-07T08:56:41.1309050Z strides: [507904, 1984, 44, 1], [2304, 9, 3, 1] 2025-09-07T08:56:41.1309557Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:41.1310012Z convolution 0.0646 ms 100.0% 2025-09-07T08:56:41.1311810Z triton_convolution2d_368 0.1574 ms 41.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.1313386Z triton_convolution2d_373 0.1691 ms 38.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.1314814Z triton_convolution2d_370 0.1818 ms 35.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.1316046Z triton_convolution2d_371 0.2264 ms 28.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.1317268Z triton_convolution2d_372 0.2469 ms 26.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.1318496Z triton_convolution2d_367 0.2551 ms 25.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.1319719Z triton_convolution2d_369 0.3780 ms 17.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:41.1320854Z SingleProcess AUTOTUNE benchmarking takes 0.2408 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:41.6474590Z Autotune Choices Stats: 2025-09-07T08:56:41.6475998Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.08806400001049042, "best_triton_pos": 1, "best_triton_time": 0.308351993560791, "best_triton_kernel": "triton_convolution2d_375", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:41.6839899Z AUTOTUNE convolution(4x512x44x44, 512x512x3x3) 2025-09-07T08:56:41.6840410Z strides: [991232, 1936, 44, 1], [4608, 9, 3, 1] 2025-09-07T08:56:41.6840730Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:41.6840993Z convolution 0.0881 ms 100.0% 2025-09-07T08:56:41.6841735Z triton_convolution2d_375 0.3084 ms 28.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.6842905Z triton_convolution2d_380 0.3336 ms 26.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.6844079Z triton_convolution2d_377 0.3713 ms 23.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.6845238Z triton_convolution2d_378 0.4533 ms 19.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.6846374Z triton_convolution2d_379 0.4887 ms 18.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:41.6847505Z triton_convolution2d_374 0.5452 ms 16.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:41.6848637Z triton_convolution2d_376 0.8288 ms 10.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:41.6849843Z SingleProcess AUTOTUNE benchmarking takes 0.3004 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:42.1626719Z Autotune Choices Stats: 2025-09-07T08:56:42.1628482Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.0568000003695488, "best_triton_pos": 1, "best_triton_time": 0.16115200519561768, "best_triton_kernel": "triton_convolution2d_437", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:42.1728693Z AUTOTUNE convolution(4x256x44x44, 512x256x3x3) 2025-09-07T08:56:42.1729038Z strides: [495616, 1936, 44, 1], [2304, 9, 3, 1] 2025-09-07T08:56:42.1729364Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:42.1729662Z convolution 0.0568 ms 100.0% 2025-09-07T08:56:42.1730671Z triton_convolution2d_437 0.1612 ms 35.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.1732010Z triton_convolution2d_442 0.1679 ms 33.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.1733172Z triton_convolution2d_439 0.1787 ms 31.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.1734305Z triton_convolution2d_440 0.2262 ms 25.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.1735457Z triton_convolution2d_441 0.2470 ms 23.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.1736601Z triton_convolution2d_436 0.2582 ms 22.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.1737761Z triton_convolution2d_438 0.4094 ms 13.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:42.1738674Z SingleProcess AUTOTUNE benchmarking takes 0.2431 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:42.3391802Z Autotune Choices Stats: 2025-09-07T08:56:42.3392901Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_318", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.08271999657154083, "best_triton_pos": 0} 2025-09-07T08:56:42.4119529Z AUTOTUNE convolution(4x32x352x352, 5x32x3x3) 2025-09-07T08:56:42.4119836Z strides: [3964928, 123904, 352, 1], [288, 9, 3, 1] 2025-09-07T08:56:42.4120134Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:42.4121316Z triton_convolution2d_318 0.0827 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.4122812Z triton_convolution2d_316 0.0922 ms 89.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.4124370Z triton_convolution2d_317 0.0925 ms 89.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.4125142Z convolution 0.1184 ms 69.9% 2025-09-07T08:56:42.4126042Z triton_convolution2d_314 0.1210 ms 68.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.4127296Z triton_convolution2d_315 0.1319 ms 62.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:42.4128509Z triton_convolution2d_313 0.1448 ms 57.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.4129468Z SingleProcess AUTOTUNE benchmarking takes 0.2115 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T08:56:42.8072804Z Autotune Choices Stats: 2025-09-07T08:56:42.8074215Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03145600110292435, "best_triton_pos": 1, "best_triton_time": 0.04310400038957596, "best_triton_kernel": "triton_convolution2d_47", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:42.8969985Z AUTOTUNE convolution(4x128x44x44, 256x128x3x3) 2025-09-07T08:56:42.8970743Z strides: [247808, 1936, 44, 1], [1152, 9, 3, 1] 2025-09-07T08:56:42.8971065Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:42.8971345Z convolution 0.0315 ms 100.0% 2025-09-07T08:56:42.8972103Z triton_convolution2d_47 0.0431 ms 73.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.8973373Z triton_convolution2d_44 0.0491 ms 64.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.8974598Z triton_convolution2d_42 0.0610 ms 51.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.8975798Z triton_convolution2d_45 0.0624 ms 50.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.8976989Z triton_convolution2d_46 0.0643 ms 49.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:42.8978179Z triton_convolution2d_41 0.0902 ms 34.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:42.8979419Z triton_convolution2d_43 0.1077 ms 29.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:42.8980550Z SingleProcess AUTOTUNE benchmarking takes 0.2179 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:43.3993359Z Autotune Choices Stats: 2025-09-07T08:56:43.6083074Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04054399952292442, "best_triton_pos": 1, "best_triton_time": 0.08780799806118011, "best_triton_kernel": "triton_convolution2d_54", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:43.8964778Z AUTOTUNE convolution(4x256x44x44, 256x256x3x3) 2025-09-07T08:56:43.8965086Z strides: [495616, 1936, 44, 1], [2304, 9, 3, 1] 2025-09-07T08:56:43.8965385Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:43.8965644Z convolution 0.0405 ms 100.0% 2025-09-07T08:56:43.8966334Z triton_convolution2d_54 0.0878 ms 46.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:43.8967498Z triton_convolution2d_51 0.0931 ms 43.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:43.8968654Z triton_convolution2d_49 0.1210 ms 33.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:43.8969784Z triton_convolution2d_52 0.1252 ms 32.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:43.8971330Z triton_convolution2d_53 0.1267 ms 32.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:43.8972468Z triton_convolution2d_48 0.1832 ms 22.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:43.8973607Z triton_convolution2d_50 0.2084 ms 19.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:43.8974518Z SingleProcess AUTOTUNE benchmarking takes 0.7392 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:44.1548121Z Autotune Choices Stats: 2025-09-07T08:56:44.1550790Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.05846399813890457, "best_triton_pos": 1, "best_triton_time": 0.17286400496959686, "best_triton_kernel": "triton_convolution2d_103", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:44.3779450Z AUTOTUNE convolution(4x512x44x44, 256x512x3x3) 2025-09-07T08:56:44.3779985Z strides: [991232, 1936, 44, 1], [4608, 9, 3, 1] 2025-09-07T08:56:44.3780959Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:44.3781411Z convolution 0.0585 ms 100.0% 2025-09-07T08:56:44.3782645Z triton_convolution2d_103 0.1729 ms 33.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:44.3783912Z triton_convolution2d_100 0.1871 ms 31.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:44.3785145Z triton_convolution2d_98 0.2333 ms 25.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.3786366Z triton_convolution2d_102 0.2443 ms 23.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:44.3787830Z triton_convolution2d_101 0.2516 ms 23.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.3789219Z triton_convolution2d_97 0.3533 ms 16.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.3790594Z triton_convolution2d_99 0.3711 ms 15.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:44.3791621Z SingleProcess AUTOTUNE benchmarking takes 0.4674 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:44.7228075Z Autotune Choices Stats: 2025-09-07T08:56:44.7229934Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_158", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.08240000158548355, "best_triton_pos": 0} 2025-09-07T08:56:44.7586264Z AUTOTUNE convolution(4x32x352x352, 4x32x3x3) 2025-09-07T08:56:44.7586819Z strides: [3964928, 123904, 352, 1], [288, 9, 3, 1] 2025-09-07T08:56:44.7587324Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:44.7588586Z triton_convolution2d_158 0.0824 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:44.7590868Z triton_convolution2d_157 0.0891 ms 92.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.7592948Z triton_convolution2d_156 0.0921 ms 89.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:44.7593707Z convolution 0.1175 ms 70.1% 2025-09-07T08:56:44.7594431Z triton_convolution2d_154 0.1215 ms 67.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.7595668Z triton_convolution2d_155 0.1316 ms 62.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:44.7596899Z triton_convolution2d_153 0.1434 ms 57.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:44.7597876Z SingleProcess AUTOTUNE benchmarking takes 0.1737 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T08:56:45.2313537Z Autotune Choices Stats: 2025-09-07T08:56:45.2314920Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.036479998379945755, "best_triton_pos": 1, "best_triton_time": 0.08665599673986435, "best_triton_kernel": "triton_convolution2d_61", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:45.4129795Z AUTOTUNE convolution(4x256x22x22, 512x256x3x3) 2025-09-07T08:56:45.4130134Z strides: [123904, 484, 22, 1], [2304, 9, 3, 1] 2025-09-07T08:56:45.4130699Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:45.4130967Z convolution 0.0365 ms 100.0% 2025-09-07T08:56:45.4132094Z triton_convolution2d_61 0.0867 ms 42.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.4133455Z triton_convolution2d_59 0.0889 ms 41.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.4134615Z triton_convolution2d_58 0.0904 ms 40.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.4135749Z triton_convolution2d_60 0.1159 ms 31.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.4136877Z triton_convolution2d_56 0.1172 ms 31.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.4137999Z triton_convolution2d_55 0.1726 ms 21.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.4139115Z triton_convolution2d_57 0.1906 ms 19.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:45.4140012Z SingleProcess AUTOTUNE benchmarking takes 0.3495 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:45.9032745Z Autotune Choices Stats: 2025-09-07T08:56:45.9034283Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.05942400172352791, "best_triton_pos": 1, "best_triton_time": 0.16521599888801575, "best_triton_kernel": "triton_convolution2d_68", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:45.9408400Z AUTOTUNE convolution(4x512x22x22, 512x512x3x3) 2025-09-07T08:56:45.9408800Z strides: [247808, 484, 22, 1], [4608, 9, 3, 1] 2025-09-07T08:56:45.9409139Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:45.9409467Z convolution 0.0594 ms 100.0% 2025-09-07T08:56:45.9410767Z triton_convolution2d_68 0.1652 ms 36.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.9412311Z triton_convolution2d_65 0.1747 ms 34.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.9413653Z triton_convolution2d_66 0.1773 ms 33.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.9414970Z triton_convolution2d_67 0.2206 ms 26.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:45.9416301Z triton_convolution2d_63 0.2253 ms 26.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.9417628Z triton_convolution2d_62 0.3545 ms 16.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:45.9419317Z triton_convolution2d_64 0.3717 ms 16.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:45.9420716Z SingleProcess AUTOTUNE benchmarking takes 0.2684 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:46.4189423Z Autotune Choices Stats: 2025-09-07T08:56:46.4192388Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.08377599716186523, "best_triton_pos": 1, "best_triton_time": 0.3302080035209656, "best_triton_kernel": "triton_convolution2d_96", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:56:46.4478693Z AUTOTUNE convolution(4x1024x22x22, 512x1024x3x3) 2025-09-07T08:56:46.4479023Z strides: [495616, 484, 22, 1], [9216, 9, 3, 1] 2025-09-07T08:56:46.4479324Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:46.4479601Z convolution 0.0838 ms 100.0% 2025-09-07T08:56:46.4480537Z triton_convolution2d_96 0.3302 ms 25.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.4481778Z triton_convolution2d_93 0.3427 ms 24.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.4483007Z triton_convolution2d_94 0.3622 ms 23.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.4484153Z triton_convolution2d_95 0.4412 ms 19.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.4485286Z triton_convolution2d_91 0.4443 ms 18.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.4486422Z triton_convolution2d_90 0.6984 ms 12.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.4487554Z triton_convolution2d_92 0.7259 ms 11.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:46.4488454Z SingleProcess AUTOTUNE benchmarking takes 0.2911 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:56:46.7231844Z Autotune Choices Stats: 2025-09-07T08:56:46.7233937Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03852799907326698, "best_triton_pos": 1, "best_triton_time": 0.1050880029797554, "best_triton_kernel": "triton_convolution2d_73", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:56:46.8699859Z AUTOTUNE convolution(4x512x11x11, 512x512x3x3) 2025-09-07T08:56:46.8700686Z strides: [61952, 121, 11, 1], [4608, 9, 3, 1] 2025-09-07T08:56:46.8701165Z dtypes: torch.float16, torch.float16 2025-09-07T08:56:46.8701605Z convolution 0.0385 ms 100.0% 2025-09-07T08:56:46.8702964Z triton_convolution2d_73 0.1051 ms 36.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.8704688Z triton_convolution2d_75 0.1735 ms 22.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.8706156Z triton_convolution2d_72 0.1888 ms 20.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.8707393Z triton_convolution2d_74 0.2133 ms 18.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:56:46.8708613Z triton_convolution2d_70 0.2347 ms 16.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.8709848Z triton_convolution2d_71 0.2528 ms 15.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=512, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:56:46.8711254Z triton_convolution2d_69 0.5154 ms 7.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:56:46.8712239Z SingleProcess AUTOTUNE benchmarking takes 0.3728 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:57:14.3421308Z W0907 08:57:14.341000 34790 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:57:26.2610648Z pass 2025-09-07T08:57:30.8155746Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:57:30.8160908Z import pynvml # type: ignore[import] 2025-09-07T08:57:33.4466887Z 2025-09-07T08:57:35.1367145Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:57:35.1367456Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:57:35.1367700Z cuda train alexnet 2025-09-07T08:57:43.4296529Z Autotune Choices Stats: 2025-09-07T08:57:43.4297561Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_42", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.042688000947237015, "best_triton_pos": 0} 2025-09-07T08:57:43.4335640Z AUTOTUNE mm(4x9216, 9216x4096) 2025-09-07T08:57:43.4335977Z strides: [9216, 1], [1, 9216] 2025-09-07T08:57:43.4336205Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:43.4336959Z triton_mm_42 0.0427 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:43.4338447Z triton_mm_38 0.0428 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:43.4339394Z mm 0.0436 ms 97.9% 2025-09-07T08:57:43.4340675Z triton_mm_46 0.0485 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:43.4341636Z triton_mm_50 0.0580 ms 73.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:43.4343272Z triton_mm_37 0.0716 ms 59.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:43.4344185Z triton_mm_41 0.0753 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:43.4345693Z triton_mm_35 0.0755 ms 56.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:57:43.4346940Z triton_mm_36 0.0759 ms 56.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:43.4347815Z triton_mm_45 0.0804 ms 53.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:43.4348721Z SingleProcess AUTOTUNE benchmarking takes 0.3721 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T08:57:44.0287197Z Autotune Choices Stats: 2025-09-07T08:57:44.0288160Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_55", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.023520000278949738, "best_triton_pos": 0} 2025-09-07T08:57:44.0316821Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T08:57:44.0317067Z strides: [4096, 1], [1, 4096] 2025-09-07T08:57:44.0317315Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:44.0317954Z triton_mm_55 0.0235 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:44.0318937Z triton_mm_59 0.0236 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:44.0319557Z mm 0.0253 ms 92.8% 2025-09-07T08:57:44.0320126Z triton_mm_63 0.0262 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:44.0321521Z triton_mm_67 0.0306 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:44.0322486Z triton_mm_52 0.0380 ms 61.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:57:44.0323440Z triton_mm_58 0.0388 ms 60.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:44.0324394Z triton_mm_54 0.0395 ms 59.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:44.0325341Z triton_mm_62 0.0411 ms 57.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:44.0326284Z triton_mm_53 0.0412 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:44.0327122Z SingleProcess AUTOTUNE benchmarking takes 0.2845 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:57:44.6453142Z Autotune Choices Stats: 2025-09-07T08:57:44.6455340Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.03388800099492073, "best_triton_pos": 1, "best_triton_time": 0.09180799871683121, "best_triton_kernel": "triton_convolution2d_4", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T08:57:44.6488896Z AUTOTUNE convolution(4x3x224x224, 64x3x11x11) 2025-09-07T08:57:44.6489629Z strides: [150528, 1, 672, 3], [363, 1, 33, 3] 2025-09-07T08:57:44.6489939Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:44.6490635Z convolution 0.0339 ms 100.0% 2025-09-07T08:57:44.6491423Z triton_convolution2d_4 0.0918 ms 36.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.6492675Z triton_convolution2d_0 0.0957 ms 35.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.6493926Z triton_convolution2d_3 0.1097 ms 30.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.6495163Z triton_convolution2d_2 0.1502 ms 22.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:57:44.6496388Z triton_convolution2d_5 0.1716 ms 19.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.6497599Z triton_convolution2d_1 0.3766 ms 9.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=11, KERNEL_W=11, PADDING_H=2, PADDING_W=2, STRIDE_H=4, STRIDE_W=4, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.6498567Z SingleProcess AUTOTUNE benchmarking takes 0.1956 seconds and 0.0005 seconds precompiling for 7 choices 2025-09-07T08:57:44.7579341Z Autotune Choices Stats: 2025-09-07T08:57:44.7581134Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015135999768972397, "best_triton_pos": 1, "best_triton_time": 0.0382080003619194, "best_triton_kernel": "triton_convolution2d_10", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:57:44.7611603Z AUTOTUNE convolution(4x64x27x27, 192x64x5x5) 2025-09-07T08:57:44.7612008Z strides: [46656, 1, 1728, 64], [1600, 1, 320, 64] 2025-09-07T08:57:44.7612342Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:44.7612636Z convolution 0.0151 ms 100.0% 2025-09-07T08:57:44.7613400Z triton_convolution2d_10 0.0382 ms 39.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.7614655Z triton_convolution2d_11 0.0476 ms 31.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.7615902Z triton_convolution2d_9 0.0478 ms 31.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.7617144Z triton_convolution2d_12 0.0504 ms 30.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.7618371Z triton_convolution2d_7 0.0632 ms 23.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.7620004Z triton_convolution2d_6 0.0638 ms 23.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.7621630Z triton_convolution2d_8 0.1262 ms 12.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=5, KERNEL_W=5, PADDING_H=2, PADDING_W=2, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:57:44.7622545Z SingleProcess AUTOTUNE benchmarking takes 0.1110 seconds and 0.0005 seconds precompiling for 8 choices 2025-09-07T08:57:44.8935370Z Autotune Choices Stats: 2025-09-07T08:57:44.8936755Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012896000407636166, "best_triton_pos": 1, "best_triton_time": 0.04262400045990944, "best_triton_kernel": "triton_convolution2d_17", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:57:44.8965447Z AUTOTUNE convolution(4x192x13x13, 384x192x3x3) 2025-09-07T08:57:44.8965784Z strides: [32448, 1, 2496, 192], [1728, 1, 576, 192] 2025-09-07T08:57:44.8966105Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:44.8966385Z convolution 0.0129 ms 100.0% 2025-09-07T08:57:44.8967122Z triton_convolution2d_17 0.0426 ms 30.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.8968353Z triton_convolution2d_16 0.0526 ms 24.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.8969659Z triton_convolution2d_18 0.0534 ms 24.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.8970951Z triton_convolution2d_19 0.0550 ms 23.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:44.8972081Z triton_convolution2d_14 0.0746 ms 17.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.8973204Z triton_convolution2d_13 0.0766 ms 16.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:44.8974328Z triton_convolution2d_15 0.1236 ms 10.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:57:44.8975220Z SingleProcess AUTOTUNE benchmarking takes 0.1347 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:57:45.0743349Z Autotune Choices Stats: 2025-09-07T08:57:45.0744524Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015072000212967396, "best_triton_pos": 1, "best_triton_time": 0.08054400235414505, "best_triton_kernel": "triton_convolution2d_24", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:57:45.0772776Z AUTOTUNE convolution(4x384x13x13, 256x384x3x3) 2025-09-07T08:57:45.0773116Z strides: [64896, 1, 4992, 384], [3456, 1, 1152, 384] 2025-09-07T08:57:45.0773447Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:45.0773734Z convolution 0.0151 ms 100.0% 2025-09-07T08:57:45.0774758Z triton_convolution2d_24 0.0805 ms 18.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.0776179Z triton_convolution2d_23 0.0991 ms 15.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.0777406Z triton_convolution2d_26 0.1036 ms 14.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.0778637Z triton_convolution2d_25 0.1078 ms 14.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.0779838Z triton_convolution2d_21 0.1396 ms 10.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.0781245Z triton_convolution2d_20 0.1516 ms 9.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.0782316Z triton_convolution2d_22 0.2539 ms 5.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:57:45.0783248Z SingleProcess AUTOTUNE benchmarking takes 0.1801 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:57:45.2235308Z Autotune Choices Stats: 2025-09-07T08:57:45.2236675Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013376000337302685, "best_triton_pos": 1, "best_triton_time": 0.053119998425245285, "best_triton_kernel": "triton_convolution2d_31", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T08:57:45.2264900Z AUTOTUNE convolution(4x256x13x13, 256x256x3x3) 2025-09-07T08:57:45.2265237Z strides: [43264, 1, 3328, 256], [2304, 1, 768, 256] 2025-09-07T08:57:45.2265554Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:45.2265839Z convolution 0.0134 ms 100.0% 2025-09-07T08:57:45.2266583Z triton_convolution2d_31 0.0531 ms 25.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.2267818Z triton_convolution2d_30 0.0683 ms 19.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.2269081Z triton_convolution2d_33 0.0716 ms 18.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.2270685Z triton_convolution2d_32 0.0736 ms 18.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T08:57:45.2271905Z triton_convolution2d_28 0.0955 ms 14.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.2273122Z triton_convolution2d_27 0.0990 ms 13.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T08:57:45.2274554Z triton_convolution2d_29 0.1729 ms 7.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T08:57:45.2275686Z SingleProcess AUTOTUNE benchmarking takes 0.1485 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T08:57:45.5363246Z Autotune Choices Stats: 2025-09-07T08:57:45.5364672Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "bias_addmm", "best_time": 0.014816000126302242, "best_triton_pos": 1, "best_triton_time": 0.01833599992096424, "best_triton_kernel": "triton_mm_76", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:57:45.5399568Z AUTOTUNE addmm(4x1000, 4x4096, 4096x1000) 2025-09-07T08:57:45.5399914Z strides: [0, 1], [4096, 1], [1, 4096] 2025-09-07T08:57:45.5400616Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:57:45.5400940Z bias_addmm 0.0148 ms 100.0% 2025-09-07T08:57:45.5401593Z triton_mm_76 0.0183 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:45.5402639Z triton_mm_80 0.0200 ms 74.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:45.5403379Z addmm 0.0205 ms 72.1% 2025-09-07T08:57:45.5403978Z triton_mm_72 0.0214 ms 69.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:45.5405010Z triton_mm_84 0.0240 ms 61.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:45.5406054Z triton_mm_71 0.0292 ms 50.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:45.5407100Z triton_mm_69 0.0300 ms 49.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T08:57:45.5408038Z triton_mm_75 0.0317 ms 46.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:45.5408910Z triton_mm_70 0.0319 ms 46.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:45.5409778Z SingleProcess AUTOTUNE benchmarking takes 0.3127 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T08:57:53.1657932Z Autotune Choices Stats: 2025-09-07T08:57:53.1659276Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_178", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.028575999662280083, "best_triton_pos": 0} 2025-09-07T08:57:53.2032241Z AUTOTUNE mm(4096x4, 4x9216) 2025-09-07T08:57:53.2032551Z strides: [1, 4096], [9216, 1] 2025-09-07T08:57:53.2032845Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:53.2033624Z triton_mm_178 0.0286 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:53.2034815Z triton_mm_176 0.0287 ms 99.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:53.2036421Z triton_mm_173 0.0288 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:57:53.2037797Z triton_mm_175 0.0289 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:53.2038968Z triton_mm_177 0.0291 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:53.2040138Z triton_mm_182 0.0291 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:53.2041499Z triton_mm_174 0.0293 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:57:53.2042671Z triton_mm_179 0.0293 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:53.2043840Z triton_mm_180 0.0296 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:53.6032114Z triton_mm_181 0.0303 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:57:53.6033103Z SingleProcess AUTOTUNE benchmarking takes 0.4426 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T08:57:53.6033636Z Autotune Choices Stats: 2025-09-07T08:57:53.6034658Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_144", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8", "best_time": 0.016063999384641647, "best_triton_pos": 0} 2025-09-07T08:57:53.6167137Z AUTOTUNE mm(4096x4, 4x4096) 2025-09-07T08:57:53.6167438Z strides: [1, 4096], [4096, 1] 2025-09-07T08:57:53.6167746Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:53.6168495Z triton_mm_144 0.0161 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:53.6169632Z triton_mm_141 0.0161 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:57:53.6170910Z triton_mm_143 0.0161 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:53.6172024Z triton_mm_150 0.0161 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:53.6172981Z triton_mm_140 0.0162 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:57:53.6173941Z triton_mm_148 0.0162 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:57:53.6174905Z triton_mm_142 0.0162 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:53.6175880Z triton_mm_145 0.0162 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:53.6177104Z triton_mm_147 0.0163 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:53.6178221Z triton_mm_139 0.0163 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:53.6179055Z SingleProcess AUTOTUNE benchmarking takes 0.1854 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:57:54.2265182Z Autotune Choices Stats: 2025-09-07T08:57:54.2266260Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_109", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00800000037997961, "best_triton_pos": 0} 2025-09-07T08:57:54.2464786Z AUTOTUNE mm(1000x4, 4x4096) 2025-09-07T08:57:54.2465077Z strides: [1, 1000], [4096, 1] 2025-09-07T08:57:54.2465351Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:54.2466077Z triton_mm_109 0.0080 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:54.2467082Z triton_mm_111 0.0081 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:54.2468047Z triton_mm_107 0.0082 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:57:54.2469057Z triton_mm_110 0.0082 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:54.2470030Z triton_mm_112 0.0082 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:54.2471505Z triton_mm_114 0.0082 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:54.2472627Z triton_mm_113 0.0082 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:54.2473604Z triton_mm_115 0.0083 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:57:54.2474585Z triton_mm_117 0.0083 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:54.2475561Z triton_mm_108 0.0084 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:57:54.2476407Z SingleProcess AUTOTUNE benchmarking takes 0.1783 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T08:57:55.1150726Z Autotune Choices Stats: 2025-09-07T08:57:55.1152125Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.010432000271975994, "best_triton_pos": 1, "best_triton_time": 0.011392000131309032, "best_triton_kernel": "triton_mm_93", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:57:55.1381904Z AUTOTUNE mm(4x1000, 1000x4096) 2025-09-07T08:57:55.1382205Z strides: [1000, 1], [4096, 1] 2025-09-07T08:57:55.1382449Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:55.1382797Z mm 0.0104 ms 100.0% 2025-09-07T08:57:55.1383805Z triton_mm_93 0.0114 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:55.1384957Z triton_mm_101 0.0119 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:55.1385861Z triton_mm_97 0.0122 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:55.1386740Z triton_mm_87 0.0124 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:55.1387618Z triton_mm_92 0.0131 ms 79.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:55.1388500Z triton_mm_89 0.0137 ms 76.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:55.1389389Z triton_mm_99 0.0138 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:55.1390411Z triton_mm_95 0.0145 ms 71.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:57:55.1391296Z triton_mm_96 0.0151 ms 69.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:55.1392063Z SingleProcess AUTOTUNE benchmarking takes 0.2115 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:57:55.6067693Z Autotune Choices Stats: 2025-09-07T08:57:55.6069860Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.021183999255299568, "best_triton_pos": 1, "best_triton_time": 0.023840000852942467, "best_triton_kernel": "triton_mm_126", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:57:55.6396793Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T08:57:55.6397109Z strides: [4096, 1], [4096, 1] 2025-09-07T08:57:55.6397369Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:55.6397633Z mm 0.0212 ms 100.0% 2025-09-07T08:57:55.6398232Z triton_mm_126 0.0238 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:55.6399205Z triton_mm_122 0.0256 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:55.6400365Z triton_mm_130 0.0261 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:55.6401357Z triton_mm_134 0.0285 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:55.6402324Z triton_mm_120 0.0348 ms 61.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:55.6403267Z triton_mm_121 0.0367 ms 57.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:55.6404213Z triton_mm_125 0.0382 ms 55.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:55.6405588Z triton_mm_129 0.0391 ms 54.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:55.6406759Z triton_mm_132 0.0414 ms 51.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:55.6407611Z SingleProcess AUTOTUNE benchmarking takes 0.2851 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:57:56.5103935Z Autotune Choices Stats: 2025-09-07T08:57:56.5106030Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.03830400109291077, "best_triton_pos": 1, "best_triton_time": 0.03888000175356865, "best_triton_kernel": "triton_mm_163", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T08:57:56.5490927Z AUTOTUNE mm(4x4096, 4096x9216) 2025-09-07T08:57:56.5491421Z strides: [4096, 1], [9216, 1] 2025-09-07T08:57:56.5491878Z dtypes: torch.float16, torch.float16 2025-09-07T08:57:56.5492313Z mm 0.0383 ms 100.0% 2025-09-07T08:57:56.5493298Z triton_mm_163 0.0389 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:56.5494891Z triton_mm_167 0.0401 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:57:56.5496463Z triton_mm_159 0.0406 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:56.5497998Z triton_mm_155 0.0442 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:56.5499548Z triton_mm_153 0.0461 ms 83.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:57:56.5501356Z triton_mm_158 0.0477 ms 80.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:56.5503059Z triton_mm_162 0.0483 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:57:56.5503951Z triton_mm_154 0.0492 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T08:57:56.5504842Z triton_mm_165 0.0500 ms 76.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:57:56.5505623Z SingleProcess AUTOTUNE benchmarking takes 0.3079 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T08:58:01.7958901Z pass 2025-09-07T08:58:04.9638197Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:58:04.9639309Z import pynvml # type: ignore[import] 2025-09-07T08:58:07.3725927Z 2025-09-07T08:58:09.6995187Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:58:09.6995544Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:58:09.6995824Z cuda train basic_gnn_edgecnn 2025-09-07T08:58:14.9607253Z Autotune Choices Stats: 2025-09-07T08:58:14.9608636Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_11", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.03283200040459633, "best_triton_pos": 0} 2025-09-07T08:58:14.9646286Z AUTOTUNE mm(200000x128, 128x64) 2025-09-07T08:58:14.9646578Z strides: [128, 1], [1, 128] 2025-09-07T08:58:14.9646804Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:14.9647370Z triton_mm_11 0.0328 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:14.9648253Z triton_mm_16 0.0332 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:14.9649138Z triton_mm_7 0.0332 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:58:14.9649665Z mm 0.0360 ms 91.3% 2025-09-07T08:58:14.9650158Z triton_mm_13 0.0367 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:14.9651250Z triton_mm_14 0.0377 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:14.9652080Z triton_mm_15 0.0381 ms 86.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:58:14.9652907Z triton_mm_12 0.0383 ms 85.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:14.9653744Z triton_mm_8 0.0387 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:14.9654568Z triton_mm_10 0.0392 ms 83.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:14.9655307Z SingleProcess AUTOTUNE benchmarking takes 0.2109 seconds and 0.2707 seconds precompiling for 19 choices 2025-09-07T08:58:16.2696052Z Autotune Choices Stats: 2025-09-07T08:58:16.2697756Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_34", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.023231999948620796, "best_triton_pos": 0} 2025-09-07T08:58:16.3083011Z AUTOTUNE addmm(200000x64, 200000x64, 64x64) 2025-09-07T08:58:16.3083532Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T08:58:16.3093103Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:58:16.3093760Z triton_mm_34 0.0232 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:16.3094377Z bias_addmm 0.0249 ms 93.4% 2025-09-07T08:58:16.3094941Z triton_mm_35 0.0254 ms 91.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:16.3095827Z triton_mm_26 0.0255 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:16.3096705Z triton_mm_29 0.0256 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:16.3097984Z triton_mm_30 0.0257 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:16.3099053Z triton_mm_32 0.0264 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:16.3099864Z triton_mm_31 0.0265 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:16.3100854Z triton_mm_24 0.0279 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:58:16.3101644Z triton_mm_33 0.0281 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T08:58:16.3102342Z SingleProcess AUTOTUNE benchmarking takes 0.5041 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:58:17.2915147Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in torch_dynamo_resume_in_scatter_at_93 2025-09-07T08:58:17.2916410Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T08:58:17.2916636Z 2025-09-07T08:58:17.2916640Z 2025-09-07T08:58:20.3709930Z Autotune Choices Stats: 2025-09-07T08:58:20.3711381Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_88", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.02316799946129322, "best_triton_pos": 0} 2025-09-07T08:58:20.4111526Z AUTOTUNE mm(200000x64, 64x64) 2025-09-07T08:58:20.4111814Z strides: [64, 1], [64, 1] 2025-09-07T08:58:20.4112083Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:20.4112824Z triton_mm_88 0.0232 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:20.4113900Z triton_mm_89 0.0233 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:20.4114931Z triton_mm_79 0.0233 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:58:20.4115581Z mm 0.0240 ms 96.5% 2025-09-07T08:58:20.4116194Z triton_mm_81 0.0243 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:20.4117231Z triton_mm_85 0.0243 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:20.4118268Z triton_mm_86 0.0244 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:20.4119297Z triton_mm_82 0.0244 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:20.4120469Z triton_mm_80 0.0246 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:20.4121547Z triton_mm_84 0.0247 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:20.4122859Z SingleProcess AUTOTUNE benchmarking takes 0.2673 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T08:58:23.0907893Z Autotune Choices Stats: 2025-09-07T08:58:23.0909246Z {"num_choices": 28, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.04460800066590309, "best_triton_pos": 11, "best_triton_time": 0.4083839952945709, "best_triton_kernel": "triton_mm_128", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:58:23.0969954Z AUTOTUNE mm(64x200000, 200000x128) 2025-09-07T08:58:23.0970431Z strides: [1, 64], [128, 1] 2025-09-07T08:58:23.0970722Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:23.0971011Z mm 0.0446 ms 100.0% 2025-09-07T08:58:23.0971291Z decompose_k_mm_50_split_14 0.0447 ms 99.7% k_split=50 2025-09-07T08:58:23.0971654Z decompose_k_mm_125_split_15 0.0449 ms 99.3% k_split=125 2025-09-07T08:58:23.0972019Z decompose_k_mm_250_split_16 0.0477 ms 93.4% k_split=250 2025-09-07T08:58:23.0972387Z decompose_k_mm_25_split_13 0.0493 ms 90.5% k_split=25 2025-09-07T08:58:23.0972741Z decompose_k_mm_10_split_12 0.0527 ms 84.6% k_split=10 2025-09-07T08:58:23.0973094Z decompose_k_mm_5_split_11 0.0663 ms 67.3% k_split=5 2025-09-07T08:58:23.0973451Z decompose_k_mm_1250_split_18 0.0685 ms 65.1% k_split=1250 2025-09-07T08:58:23.0973812Z decompose_k_mm_4_split_19 0.0786 ms 56.7% k_split=4 2025-09-07T08:58:23.0974160Z decompose_k_mm_625_split_17 0.1332 ms 33.5% k_split=625 2025-09-07T08:58:23.0974702Z SingleProcess AUTOTUNE benchmarking takes 2.4520 seconds and 0.0002 seconds precompiling for 28 choices 2025-09-07T08:58:25.4588159Z Autotune Choices Stats: 2025-09-07T08:58:25.4589672Z {"num_choices": 26, "num_triton_choices": 15, "best_kernel": "decompose_k_mm_125_split_5", "best_kernel_desc": "k_split=125", "best_time": 0.03283200040459633, "best_triton_pos": 11, "best_triton_time": 0.4359680116176605, "best_triton_kernel": "triton_mm_98", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:58:25.5840189Z AUTOTUNE mm(64x200000, 200000x64) 2025-09-07T08:58:25.5840864Z strides: [1, 64], [64, 1] 2025-09-07T08:58:25.5841178Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:25.5841590Z decompose_k_mm_125_split_5 0.0328 ms 100.0% k_split=125 2025-09-07T08:58:25.5842035Z decompose_k_mm_50_split_4 0.0333 ms 98.5% k_split=50 2025-09-07T08:58:25.5842399Z decompose_k_mm_25_split_3 0.0352 ms 93.2% k_split=25 2025-09-07T08:58:25.5842759Z decompose_k_mm_250_split_6 0.0356 ms 92.3% k_split=250 2025-09-07T08:58:25.5843092Z mm 0.0356 ms 92.1% 2025-09-07T08:58:25.5843386Z decompose_k_mm_625_split_7 0.0418 ms 78.5% k_split=625 2025-09-07T08:58:25.5843748Z decompose_k_mm_10_split_2 0.0445 ms 73.8% k_split=10 2025-09-07T08:58:25.5844115Z decompose_k_mm_1250_split_8 0.0495 ms 66.4% k_split=1250 2025-09-07T08:58:25.5844476Z decompose_k_mm_5_split_1 0.0623 ms 52.7% k_split=5 2025-09-07T08:58:25.5844820Z decompose_k_mm_4_split_9 0.0767 ms 42.8% k_split=4 2025-09-07T08:58:25.5845380Z SingleProcess AUTOTUNE benchmarking takes 2.3170 seconds and 0.0002 seconds precompiling for 26 choices 2025-09-07T08:58:26.1712445Z Autotune Choices Stats: 2025-09-07T08:58:26.1713464Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_121", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.031808000057935715, "best_triton_pos": 0} 2025-09-07T08:58:26.1746327Z AUTOTUNE mm(200000x64, 64x128) 2025-09-07T08:58:26.1746588Z strides: [64, 1], [128, 1] 2025-09-07T08:58:26.1746870Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:26.1747579Z triton_mm_121 0.0318 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:26.1748979Z triton_mm_117 0.0319 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:26.1750560Z triton_mm_114 0.0320 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:26.1751717Z triton_mm_116 0.0320 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:26.1752676Z triton_mm_113 0.0325 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:26.1753642Z triton_mm_118 0.0325 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:26.1754252Z mm 0.0330 ms 96.4% 2025-09-07T08:58:26.1754822Z triton_mm_123 0.0332 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:26.1755796Z triton_mm_115 0.0333 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:26.1756761Z triton_mm_122 0.0341 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:26.1757605Z SingleProcess AUTOTUNE benchmarking takes 0.2498 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T08:58:26.6497599Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 190, in propagate 2025-09-07T08:58:26.6498403Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:58:26.6498816Z File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 141, in _collect 2025-09-07T08:58:26.6499162Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:58:26.6499461Z File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 88, in _lift 2025-09-07T08:58:26.6499808Z return src.index_select(self.node_dim, index) 2025-09-07T08:58:26.6500010Z 2025-09-07T08:58:26.6500014Z 2025-09-07T08:58:26.8754388Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 190, in propagate 2025-09-07T08:58:26.8755226Z kwargs = self._collect(edge_index, the_size, in_kwargs) 2025-09-07T08:58:26.8755635Z File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 141, in _collect 2025-09-07T08:58:26.8755986Z x_j = self._lift(x_j, edge_def, j) 2025-09-07T08:58:26.8756332Z File "/tmp/jenkins_pyg/tmpf1yuy4qu.py", line 88, in _lift 2025-09-07T08:58:26.8756719Z return src.index_select(self.node_dim, index) 2025-09-07T08:58:26.8756932Z 2025-09-07T08:58:26.8756951Z 2025-09-07T08:58:27.5041935Z W0907 08:58:27.503000 42640 site-packages/torch/_logging/_internal.py:1199] [24/0] Profiler function will be ignored 2025-09-07T08:58:29.4077985Z pass 2025-09-07T08:58:32.7297168Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:58:32.7298323Z import pynvml # type: ignore[import] 2025-09-07T08:58:35.2447180Z 2025-09-07T08:58:37.6186802Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:58:37.6187096Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:58:37.6187343Z cuda train basic_gnn_gcn 2025-09-07T08:58:40.3947529Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T08:58:40.3949009Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T08:58:40.3949683Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:58:40.3950578Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:58:40.3950834Z 2025-09-07T08:58:40.3950839Z 2025-09-07T08:58:42.3871483Z Autotune Choices Stats: 2025-09-07T08:58:42.3872598Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_4", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T08:58:42.4045314Z AUTOTUNE mm(10000x64, 64x64) 2025-09-07T08:58:42.4045664Z strides: [64, 1], [1, 64] 2025-09-07T08:58:42.4045994Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:42.4046810Z triton_mm_4 0.0069 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:42.4047835Z triton_mm_7 0.0070 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:58:42.4048841Z triton_mm_16 0.0070 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:42.4049820Z triton_mm_1 0.0071 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:58:42.4050939Z triton_mm_8 0.0071 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:42.4051899Z triton_mm_17 0.0071 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:42.4052862Z triton_mm_11 0.0072 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:42.4053889Z triton_mm_12 0.0072 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:42.4054842Z triton_mm_14 0.0072 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:42.4055878Z triton_mm_9 0.0073 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:42.4056696Z SingleProcess AUTOTUNE benchmarking takes 0.2176 seconds and 0.4151 seconds precompiling for 19 choices 2025-09-07T08:58:42.8697849Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpqh6b0lhr.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:58:42.8698766Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:58:42.8699173Z File "/tmp/jenkins_pyg/tmpqh6b0lhr.py", line 188, in propagate 2025-09-07T08:58:42.8699655Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:58:42.8701160Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:58:42.8701820Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:58:42.8702595Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:58:42.8703258Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:58:42.8703803Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:58:42.8704358Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:58:42.8704898Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:58:42.8705425Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:58:42.8705970Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:58:42.8706522Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:58:42.8706748Z 2025-09-07T08:58:42.8706752Z 2025-09-07T08:58:43.5657325Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp8t_361dp.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:58:43.5658215Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:58:43.5658613Z File "/tmp/jenkins_pyg/tmp8t_361dp.py", line 188, in propagate 2025-09-07T08:58:43.5659074Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:58:43.5659762Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:58:43.5660733Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:58:43.5661347Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:58:43.5661895Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:58:43.5662453Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:58:43.5663081Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:58:43.5663621Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:58:43.5664120Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:58:43.5664615Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:58:43.5665147Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:58:43.5665374Z 2025-09-07T08:58:43.5665378Z 2025-09-07T08:58:44.0590549Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmp8t_361dp.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T08:58:44.0591590Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T08:58:44.0592050Z File "/tmp/jenkins_pyg/tmp8t_361dp.py", line 188, in propagate 2025-09-07T08:58:44.0592578Z out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size) 2025-09-07T08:58:44.0593367Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:58:44.0594074Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:58:44.0594708Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:58:44.0595320Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:58:44.0596398Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:58:44.0597019Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:58:44.0597796Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:58:44.0598346Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:58:44.0598893Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:58:44.0599463Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:58:44.0599718Z 2025-09-07T08:58:44.0599721Z 2025-09-07T08:58:45.1489460Z Autotune Choices Stats: 2025-09-07T08:58:45.1490898Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_58", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.007135999854654074, "best_triton_pos": 0} 2025-09-07T08:58:45.1527049Z AUTOTUNE mm(10000x64, 64x64) 2025-09-07T08:58:45.1527309Z strides: [64, 1], [64, 1] 2025-09-07T08:58:45.1527596Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:45.1528278Z triton_mm_58 0.0071 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:58:45.1529249Z triton_mm_63 0.0072 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:58:45.1530351Z triton_mm_59 0.0072 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:58:45.1531318Z triton_mm_68 0.0072 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:45.1532266Z triton_mm_65 0.0073 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:45.1533221Z triton_mm_61 0.0075 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:58:45.1534157Z triton_mm_62 0.0075 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:45.1535105Z triton_mm_67 0.0075 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:45.1536043Z triton_mm_53 0.0076 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:58:45.1537019Z triton_mm_60 0.0076 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:58:45.1537753Z SingleProcess AUTOTUNE benchmarking takes 0.1769 seconds and 0.2157 seconds precompiling for 19 choices 2025-09-07T08:58:46.5406862Z Autotune Choices Stats: 2025-09-07T08:58:46.5408225Z {"num_choices": 26, "num_triton_choices": 15, "best_kernel": "decompose_k_mm_40_split_8", "best_kernel_desc": "k_split=40", "best_time": 0.011392000131309032, "best_triton_pos": 11, "best_triton_time": 0.028031999245285988, "best_triton_kernel": "triton_mm_44", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T08:58:46.5458445Z AUTOTUNE mm(64x10000, 10000x64) 2025-09-07T08:58:46.5458774Z strides: [1, 64], [64, 1] 2025-09-07T08:58:46.5459526Z dtypes: torch.float16, torch.float16 2025-09-07T08:58:46.5459820Z decompose_k_mm_40_split_8 0.0114 ms 100.0% k_split=40 2025-09-07T08:58:46.5460716Z decompose_k_mm_50_split_9 0.0116 ms 97.8% k_split=50 2025-09-07T08:58:46.5461016Z decompose_k_mm_5_split_2 0.0125 ms 90.8% k_split=5 2025-09-07T08:58:46.5461307Z decompose_k_mm_4_split_1 0.0128 ms 89.0% k_split=4 2025-09-07T08:58:46.5461558Z mm 0.0130 ms 87.5% 2025-09-07T08:58:46.5461789Z decompose_k_mm_20_split_6 0.0135 ms 84.6% k_split=20 2025-09-07T08:58:46.5462080Z decompose_k_mm_16_split_5 0.0137 ms 83.0% k_split=16 2025-09-07T08:58:46.5462366Z decompose_k_mm_8_split_3 0.0140 ms 81.3% k_split=8 2025-09-07T08:58:46.5462735Z decompose_k_mm_10_split_4 0.0142 ms 80.4% k_split=10 2025-09-07T08:58:46.5463017Z decompose_k_mm_25_split_7 0.0142 ms 80.4% k_split=25 2025-09-07T08:58:46.5463480Z SingleProcess AUTOTUNE benchmarking takes 1.1866 seconds and 0.0005 seconds precompiling for 26 choices 2025-09-07T08:58:47.2729401Z W0907 08:58:47.272000 44771 site-packages/torch/_logging/_internal.py:1199] [18/0] Profiler function will be ignored 2025-09-07T08:58:48.2517693Z pass 2025-09-07T08:58:51.1572268Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:58:51.1573421Z import pynvml # type: ignore[import] 2025-09-07T08:58:53.6317833Z 2025-09-07T08:58:55.7744789Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:58:55.7745170Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:58:55.7745513Z cuda train basic_gnn_gin 2025-09-07T08:59:02.2190774Z Autotune Choices Stats: 2025-09-07T08:59:02.2192034Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "triton_mm_101", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.007296000141650438, "best_triton_pos": 0} 2025-09-07T08:59:02.2226796Z AUTOTUNE addmm(10000x64, 10000x64, 64x64) 2025-09-07T08:59:02.2227095Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T08:59:02.2227417Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:59:02.2228156Z triton_mm_101 0.0073 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:59:02.2229180Z triton_mm_98 0.0074 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:59:02.2230142Z triton_mm_102 0.0075 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:59:02.2231364Z triton_mm_94 0.0075 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:59:02.2232389Z triton_mm_91 0.0075 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:59:02.2233343Z triton_mm_106 0.0076 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:59:02.2234304Z triton_mm_97 0.0076 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:59:02.2235691Z triton_mm_107 0.0076 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:59:02.2236674Z triton_mm_100 0.0077 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:59:02.2237840Z triton_mm_99 0.0078 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:59:02.2238690Z SingleProcess AUTOTUNE benchmarking takes 0.1919 seconds and 0.0010 seconds precompiling for 20 choices 2025-09-07T08:59:02.8361704Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:59:02.8362788Z pred = mod(*cloned_inputs) 2025-09-07T08:59:02.8363363Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:59:02.8363902Z x = self.convs[i](x, edge_index) 2025-09-07T08:59:02.8364231Z File "/tmp/jenkins_pyg/tmph4ucdy3r.py", line 225, in forward 2025-09-07T08:59:02.8364584Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:59:02.8364935Z File "/tmp/jenkins_pyg/tmph4ucdy3r.py", line 182, in propagate 2025-09-07T08:59:02.8365394Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T08:59:02.8366073Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:59:02.8366689Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:59:02.8367279Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:59:02.8367825Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:59:02.8368374Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T08:59:02.8368928Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T08:59:02.8369472Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:59:02.8369979Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:59:02.8370606Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T08:59:02.8371160Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T08:59:02.8371390Z 2025-09-07T08:59:02.8371394Z 2025-09-07T08:59:05.7204606Z W0907 08:59:05.719000 45955 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:59:07.2845200Z pass 2025-09-07T08:59:10.4015538Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:59:10.4017731Z import pynvml # type: ignore[import] 2025-09-07T08:59:13.3577584Z 2025-09-07T08:59:15.6115487Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:59:15.6115872Z loading model: 0it [00:02, ?it/s] 2025-09-07T08:59:15.6116186Z cuda train basic_gnn_sage 2025-09-07T08:59:22.3867098Z Autotune Choices Stats: 2025-09-07T08:59:22.3868351Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_101", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.0074880002066493034, "best_triton_pos": 0} 2025-09-07T08:59:22.4358151Z AUTOTUNE addmm(10000x64, 10000x64, 64x64) 2025-09-07T08:59:22.4359005Z strides: [64, 1], [64, 1], [1, 64] 2025-09-07T08:59:22.4359367Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T08:59:22.4360870Z triton_mm_101 0.0075 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:59:22.4361925Z triton_mm_98 0.0076 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:59:22.4362944Z triton_mm_91 0.0076 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T08:59:22.4363950Z triton_mm_94 0.0077 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T08:59:22.4364949Z triton_mm_102 0.0077 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T08:59:22.4365940Z triton_mm_97 0.0078 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T08:59:22.4366917Z triton_mm_100 0.0078 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T08:59:22.4367940Z triton_mm_99 0.0080 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T08:59:22.4368832Z triton_mm_107 0.0080 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:59:22.4369726Z triton_mm_92 0.0080 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T08:59:22.4370653Z SingleProcess AUTOTUNE benchmarking takes 0.2240 seconds and 0.0012 seconds precompiling for 19 choices 2025-09-07T08:59:23.0767338Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T08:59:23.0768459Z pred = mod(*cloned_inputs) 2025-09-07T08:59:23.0768993Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T08:59:23.0769522Z x = self.convs[i](x, edge_index) 2025-09-07T08:59:23.0769833Z File "/tmp/jenkins_pyg/tmp5qvy2mc7.py", line 228, in forward 2025-09-07T08:59:23.0770558Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T08:59:23.0770916Z File "/tmp/jenkins_pyg/tmp5qvy2mc7.py", line 182, in propagate 2025-09-07T08:59:23.0771393Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T08:59:23.0772082Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T08:59:23.0772715Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T08:59:23.0773287Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T08:59:23.0773839Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T08:59:23.0774380Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T08:59:23.0774929Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T08:59:23.0775904Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T08:59:23.0776638Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T08:59:23.0777148Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter 2025-09-07T08:59:23.0777709Z count.scatter_add_(0, index, src.new_ones(src.size(dim))) 2025-09-07T08:59:23.0777952Z 2025-09-07T08:59:23.0777956Z 2025-09-07T08:59:26.0284049Z W0907 08:59:26.027000 46867 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:59:27.2947191Z pass 2025-09-07T08:59:29.8307507Z accuracy pass_rate=80.00% 2025-09-07T08:59:29.8319215Z calls_captured gmean=0.00x mean=239.300x 2025-09-07T08:59:29.8322657Z unique_graphs gmean=0.00x mean=3.600x 2025-09-07T08:59:29.8325568Z graph_breaks gmean=0.00x mean=7.900x 2025-09-07T08:59:29.8328859Z unique_graph_breaks gmean=0.00x mean=4.700x 2025-09-07T08:59:29.8332274Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:59:29.8335363Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:59:29.8338487Z cudagraph_skips gmean=0.00x mean=1.000x 2025-09-07T08:59:29.8339413Z compilation_latency mean=28.154 seconds 2025-09-07T08:59:30.6858734Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs_low_precision-true* ]] 2025-09-07T08:59:30.6860391Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:59:30.6860647Z + for target in "${targets[@]}" 2025-09-07T08:59:30.6860867Z + target_flag=('--performance') 2025-09-07T08:59:30.6861088Z + local target_flag 2025-09-07T08:59:30.6861295Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T08:59:30.6861560Z + target_flag+=(--cold-start-latency) 2025-09-07T08:59:30.6862627Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T08:59:30.6864518Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T08:59:30.6866407Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv 2025-09-07T08:59:31.2291197Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:59:31.2292383Z import pynvml # type: ignore[import] 2025-09-07T08:59:35.0386770Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:59:35.0387797Z import pynvml # type: ignore[import] 2025-09-07T08:59:37.5427208Z 2025-09-07T08:59:37.7359325Z loading model: 0it [00:00, ?it/s][rank0]:W0907 08:59:37.735000 47861 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T08:59:38.6409267Z 2025-09-07T08:59:38.6410830Z loading model: 0it [00:01, ?it/s] 2025-09-07T08:59:38.6411271Z cuda train torchrec_dlrm 2025-09-07T08:59:48.1386655Z [rank0]:W0907 08:59:48.137000 47861 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:59:55.2387105Z 2025-09-07T08:59:55.3534152Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:02:02.8985362Z 2025-09-07T09:02:03.0799851Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:03:41.4356973Z 2025-09-07T09:03:41.5679799Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:04:31.7732563Z 2025-09-07T09:04:31.8814953Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:04:49.6146563Z 2025-09-07T09:04:49.7185049Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:05:06.7052064Z 2025-09-07T09:05:06.8080022Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:05:24.2265707Z 2025-09-07T09:05:24.3315872Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:06:01.0521624Z 2025-09-07T09:06:01.1654751Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:08:14.4805027Z 2025-09-07T09:08:14.7485436Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:09:58.7745708Z 2025-09-07T09:09:58.9617480Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:10:51.3966010Z 2025-09-07T09:10:51.5028781Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:11:09.5826996Z 2025-09-07T09:11:09.6866293Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:11:29.8357869Z 2025-09-07T09:11:29.9403228Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:11:50.0788202Z 2025-09-07T09:11:50.1851375Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:12:26.4136528Z 2025-09-07T09:12:26.4234398Z running benchmark: 0% 0/30 [00:00 2025-09-07T09:12:26.4270991Z [rank0]: torchbench_main() 2025-09-07T09:12:26.4271418Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T09:12:26.4271897Z [rank0]: main(TorchBenchmarkRunner(), original_dir) 2025-09-07T09:12:26.4272406Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T09:12:26.4272913Z [rank0]: process_entry(0, runner, original_dir, args) 2025-09-07T09:12:26.4273441Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T09:12:26.4273962Z [rank0]: result = run(runner, args, original_dir) 2025-09-07T09:12:26.4274437Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4279, in run 2025-09-07T09:12:26.4274894Z [rank0]: runner.run_one_model( 2025-09-07T09:12:26.4275367Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2886, in run_one_model 2025-09-07T09:12:26.4275872Z [rank0]: status = self.run_performance_test( 2025-09-07T09:12:26.4276405Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2796, in run_performance_test 2025-09-07T09:12:26.4277047Z [rank0]: results.append(experiment(model, example_inputs, **experiment_kwargs)) 2025-09-07T09:12:26.4277678Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1124, in speedup_experiment 2025-09-07T09:12:26.4278211Z [rank0]: timings[rep, 0], expected_output = timed( 2025-09-07T09:12:26.4278675Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 751, in timed 2025-09-07T09:12:26.4279267Z [rank0]: result = model_iter_fn(model, example_inputs, collect_outputs=collect_outputs) 2025-09-07T09:12:26.4279954Z [rank0]: File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:12:26.4281276Z [rank0]: pred = mod(*cloned_inputs) 2025-09-07T09:12:26.4281884Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:12:26.4282733Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T09:12:26.4283296Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:12:26.4283817Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T09:12:26.4284250Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T09:12:26.4284745Z [rank0]: logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T09:12:26.4285291Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:12:26.4285778Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T09:12:26.4286236Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:12:26.4286706Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T09:12:26.4287138Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T09:12:26.4287570Z [rank0]: concatenated_dense = self.inter_arch( 2025-09-07T09:12:26.4288058Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:12:26.4288563Z [rank0]: return self._call_impl(*args, **kwargs) 2025-09-07T09:12:26.4289017Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:12:26.4289461Z [rank0]: return forward_call(*args, **kwargs) 2025-09-07T09:12:26.4289885Z [rank0]: File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 279, in forward 2025-09-07T09:12:26.4290483Z [rank0]: combined_values = torch.cat( 2025-09-07T09:12:26.4290978Z [rank0]: RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1072 but got size 1024 for tensor number 1 in the list. 2025-09-07T09:12:28.3474283Z [rank0]:[W907 09:12:28.440893586 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T09:12:29.0767271Z Run failed with return code: 1 2025-09-07T09:12:29.0767576Z Output: None 2025-09-07T09:12:29.0767786Z Error: None 2025-09-07T09:12:29.5718421Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:12:29.5719469Z import pynvml # type: ignore[import] 2025-09-07T09:12:32.0040853Z 2025-09-07T09:12:34.2853489Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:12:34.2853849Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:12:34.2854153Z cuda train BERT_pytorch 2025-09-07T09:13:11.9957790Z 2025-09-07T09:13:12.1543189Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:14:47.4482150Z 2025-09-07T09:14:47.5662003Z running benchmark: 0% 0/30 [00:00 2025-09-07T09:14:47.5663828Z torchbench_main() 2025-09-07T09:14:47.5664340Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 504, in torchbench_main 2025-09-07T09:14:47.5664904Z main(TorchBenchmarkRunner(), original_dir) 2025-09-07T09:14:47.5665372Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3636, in main 2025-09-07T09:14:47.5668380Z process_entry(0, runner, original_dir, args) 2025-09-07T09:14:47.5668875Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 3561, in process_entry 2025-09-07T09:14:47.5671329Z result = run(runner, args, original_dir) 2025-09-07T09:14:47.5671732Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4279, in run 2025-09-07T09:14:47.5674918Z runner.run_one_model( 2025-09-07T09:14:47.5675364Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2886, in run_one_model 2025-09-07T09:14:47.5677625Z status = self.run_performance_test( 2025-09-07T09:14:47.5678247Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2796, in run_performance_test 2025-09-07T09:14:47.5680642Z results.append(experiment(model, example_inputs, **experiment_kwargs)) 2025-09-07T09:14:47.5681283Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1124, in speedup_experiment 2025-09-07T09:14:47.5681811Z timings[rep, 0], expected_output = timed( 2025-09-07T09:14:47.5682370Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 751, in timed 2025-09-07T09:14:47.5682937Z result = model_iter_fn(model, example_inputs, collect_outputs=collect_outputs) 2025-09-07T09:14:47.5683583Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:14:47.5684172Z pred = mod(*cloned_inputs) 2025-09-07T09:14:47.5684655Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:14:47.5685457Z return self._call_impl(*args, **kwargs) 2025-09-07T09:14:47.5686500Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:14:47.5687344Z return forward_call(*args, **kwargs) 2025-09-07T09:14:47.5687783Z File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 241, in forward 2025-09-07T09:14:47.5688351Z multi_feat = self.model_enc_multi(multi) 2025-09-07T09:14:47.5688844Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:14:47.5689864Z return self._call_impl(*args, **kwargs) 2025-09-07T09:14:47.5690577Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:14:47.5692176Z return forward_call(*args, **kwargs) 2025-09-07T09:14:47.5692683Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py", line 250, in forward 2025-09-07T09:14:47.5693136Z input = module(input) 2025-09-07T09:14:47.5693568Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:14:47.5694464Z return self._call_impl(*args, **kwargs) 2025-09-07T09:14:47.5694904Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:14:47.5696361Z return forward_call(*args, **kwargs) 2025-09-07T09:14:47.5696796Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 548, in forward 2025-09-07T09:14:47.5697272Z return self._conv_forward(input, self.weight, self.bias) 2025-09-07T09:14:47.5697739Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 543, in _conv_forward 2025-09-07T09:14:47.5698291Z return F.conv2d( 2025-09-07T09:14:47.5698692Z RuntimeError: Given groups=1, weight of size [64, 4, 7, 7], expected input[3, 3, 518, 518] to have 4 channels, but got 3 channels instead 2025-09-07T09:14:52.0886340Z Run failed with return code: 1 2025-09-07T09:14:52.0886691Z Output: None 2025-09-07T09:14:52.0886966Z Error: None 2025-09-07T09:14:52.5842832Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:52.5844619Z import pynvml # type: ignore[import] 2025-09-07T09:14:55.0211021Z 2025-09-07T09:14:58.1649632Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:14:58.1650010Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:14:58.1650573Z cuda train LearningToPaint 2025-09-07T09:15:18.7817187Z 2025-09-07T09:15:18.9678273Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:16:27.0954132Z 2025-09-07T09:16:27.2870796Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:17:23.4824521Z 2025-09-07T09:17:23.5842862Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:17:42.5339054Z 2025-09-07T09:17:42.6420019Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:18:00.9285682Z 2025-09-07T09:18:01.0299145Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:18:18.1809624Z 2025-09-07T09:18:18.2845760Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:19:08.3618775Z 2025-09-07T09:19:08.4655959Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:22:34.8858052Z 2025-09-07T09:22:35.0709345Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:24:57.7851150Z 2025-09-07T09:24:57.9191353Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:25:58.2221804Z 2025-09-07T09:25:58.3255623Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:26:26.2461181Z 2025-09-07T09:26:26.3526332Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:26:48.1432694Z 2025-09-07T09:26:48.2464106Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:27:10.2146537Z 2025-09-07T09:27:10.3181724Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:28:04.5950962Z 2025-09-07T09:28:04.7065728Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:31:11.3000160Z 2025-09-07T09:31:11.5649720Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:34:00.6078832Z 2025-09-07T09:34:00.7948275Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:35:17.1886416Z 2025-09-07T09:35:17.2943770Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:35:42.0803650Z 2025-09-07T09:35:42.1817276Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:36:03.1052533Z 2025-09-07T09:36:03.2088313Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T09:36:25.7188940Z 2025-09-07T09:36:25.8211953Z running benchmark: 0% 0/30 [00:00 0:`). Dynamo does not support tracing dynamic control flow. 2025-09-07T10:00:40.1803275Z Hint: This graph break is fundamental - it is unlikely that Dynamo will ever be able to trace through your code. Consider finding a workaround. 2025-09-07T10:00:40.1803807Z Hint: Use `torch.cond` to express dynamic control flow. 2025-09-07T10:00:40.1804003Z 2025-09-07T10:00:40.1804155Z Developer debug context: attempted to jump with TensorVariable() 2025-09-07T10:00:40.1804379Z 2025-09-07T10:00:40.1804731Z For more details about this graph break, please visit: https://meta-pytorch.github.io/compile-graph-break-site/gb/gb0170.html 2025-09-07T10:00:40.1805122Z 2025-09-07T10:00:40.1805192Z from user code: 2025-09-07T10:00:40.1805514Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1130, in forward 2025-09-07T10:00:40.1805894Z model_out = self.model( 2025-09-07T10:00:40.1806301Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:00:40.1806747Z return forward_call(*args, **kwargs) 2025-09-07T10:00:40.1807115Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 983, in forward 2025-09-07T10:00:40.1807478Z x = self.extract_features( 2025-09-07T10:00:40.1807854Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1008, in extract_features 2025-09-07T10:00:40.1808249Z self_attn_padding_mask is None 2025-09-07T10:00:40.1808387Z 2025-09-07T10:00:40.1808807Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T10:00:40.1809301Z 2025-09-07T10:00:40.1809466Z TorchDynamo optimized model failed to run because of following error 2025-09-07T10:00:40.1964162Z fail_to_run 2025-09-07T10:00:41.2558218Z accuracy pass_rate=63.64% 2025-09-07T10:00:41.2563778Z calls_captured gmean=0.00x mean=67.909x 2025-09-07T10:00:41.2568036Z unique_graphs gmean=0.00x mean=0.636x 2025-09-07T10:00:41.2571194Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T10:00:41.2574801Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T10:00:41.2578041Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:00:41.2581360Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:00:41.2584697Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:00:41.2585815Z compilation_latency mean=1.599 seconds 2025-09-07T10:00:42.1234525Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T10:00:42.6641972Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:00:42.6643169Z import pynvml # type: ignore[import] 2025-09-07T10:00:46.9220372Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:00:46.9222634Z import pynvml # type: ignore[import] 2025-09-07T10:00:49.5484532Z 2025-09-07T10:00:49.7379218Z loading model: 0it [00:00, ?it/s][rank0]:W0907 10:00:49.737000 190776 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T10:00:50.4900084Z 2025-09-07T10:00:50.4900937Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:00:50.4901481Z cuda eval torchrec_dlrm 2025-09-07T10:00:50.4912635Z Traceback (most recent call last): 2025-09-07T10:00:50.4913139Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T10:00:50.4913640Z self.model_iter_fn(model, example_inputs) 2025-09-07T10:00:50.4914137Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:00:50.4914608Z return mod(*inputs) 2025-09-07T10:00:50.4915124Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:00:50.4915703Z return self._call_impl(*args, **kwargs) 2025-09-07T10:00:50.4916230Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:00:50.4916757Z return forward_call(*args, **kwargs) 2025-09-07T10:00:50.4917269Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:00:50.4917864Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:00:50.4918505Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:00:50.4919046Z return self._call_impl(*args, **kwargs) 2025-09-07T10:00:50.4919530Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:00:50.4920022Z return forward_call(*args, **kwargs) 2025-09-07T10:00:50.4920620Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:00:50.4921089Z concatenated_dense = self.inter_arch( 2025-09-07T10:00:50.4922092Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:00:50.4922646Z return self._call_impl(*args, **kwargs) 2025-09-07T10:00:50.4923155Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:00:50.4923771Z return forward_call(*args, **kwargs) 2025-09-07T10:00:50.4924218Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T10:00:50.4924731Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T10:00:50.4925312Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:00:50.4925850Z return self._call_impl(*args, **kwargs) 2025-09-07T10:00:50.4926362Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:00:50.4927012Z return forward_call(*args, **kwargs) 2025-09-07T10:00:50.4927490Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T10:00:50.4928049Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T10:00:50.4928552Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T10:00:50.4928869Z 2025-09-07T10:00:50.4929042Z The above exception was the direct cause of the following exception: 2025-09-07T10:00:50.4929270Z 2025-09-07T10:00:50.4929350Z Traceback (most recent call last): 2025-09-07T10:00:50.4929690Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:00:50.4930037Z ) = runner.load_model( 2025-09-07T10:00:50.4930512Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:00:50.4930916Z self.validate_model(model, example_inputs) 2025-09-07T10:00:50.4931304Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:00:50.4931711Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:00:50.4931958Z RuntimeError: Eager run failed 2025-09-07T10:00:50.4932103Z 2025-09-07T10:00:50.4932179Z eager_fail_to_run 2025-09-07T10:00:51.0182217Z [rank0]:[W907 10:00:51.111710829 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:00:52.1120638Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:00:52.1121761Z import pynvml # type: ignore[import] 2025-09-07T10:00:54.6529326Z 2025-09-07T10:00:57.4011398Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:00:57.4011938Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:00:57.4072123Z cuda eval BERT_pytorch 2025-09-07T10:01:23.8471427Z pass 2025-09-07T10:01:26.9354519Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:01:26.9355765Z import pynvml # type: ignore[import] 2025-09-07T10:01:29.4617358Z 2025-09-07T10:01:31.7803734Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:01:31.7804098Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:01:31.7855916Z cuda eval Background_Matting 2025-09-07T10:01:31.8060858Z pass_due_to_skip 2025-09-07T10:01:33.4707307Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:01:33.4708840Z import pynvml # type: ignore[import] 2025-09-07T10:01:36.0199974Z 2025-09-07T10:01:38.7438830Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:01:38.7439172Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:01:38.7463653Z cuda eval LearningToPaint 2025-09-07T10:01:50.6929331Z pass 2025-09-07T10:01:53.6754780Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:01:53.6756181Z import pynvml # type: ignore[import] 2025-09-07T10:01:56.1720536Z 2025-09-07T10:01:58.2577574Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:01:58.5902563Z 2025-09-07T10:01:58.5902976Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:01:58.5903517Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:01:58.5904009Z cuda eval Super_SloMo 2025-09-07T10:01:58.9332838Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:02:32.7795777Z pass 2025-09-07T10:02:36.8155299Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:02:36.8156544Z import pynvml # type: ignore[import] 2025-09-07T10:02:39.2922901Z 2025-09-07T10:02:40.7412709Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:02:40.7413072Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:02:40.7417854Z cuda eval alexnet 2025-09-07T10:02:51.4258412Z pass 2025-09-07T10:02:54.1392154Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:02:54.1393205Z import pynvml # type: ignore[import] 2025-09-07T10:02:56.6139922Z 2025-09-07T10:02:58.6330929Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:02:58.6331324Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:02:58.6335631Z cuda eval basic_gnn_edgecnn 2025-09-07T10:03:06.3479350Z pass 2025-09-07T10:03:09.1419897Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:03:09.1422504Z import pynvml # type: ignore[import] 2025-09-07T10:03:11.6493814Z 2025-09-07T10:03:13.7795159Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:03:13.7795570Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:03:13.7798181Z cuda eval basic_gnn_gcn 2025-09-07T10:03:24.6428702Z pass 2025-09-07T10:03:27.3935072Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:03:27.3936318Z import pynvml # type: ignore[import] 2025-09-07T10:03:29.8593720Z 2025-09-07T10:03:31.9828675Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:03:31.9829046Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:03:31.9833282Z cuda eval basic_gnn_gin 2025-09-07T10:03:41.3611524Z pass 2025-09-07T10:03:44.2397892Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:03:44.2399655Z import pynvml # type: ignore[import] 2025-09-07T10:03:46.7685096Z 2025-09-07T10:03:48.8768029Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:03:48.8768411Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:03:48.8771501Z cuda eval basic_gnn_sage 2025-09-07T10:03:56.7304216Z pass 2025-09-07T10:03:58.9918256Z accuracy pass_rate=80.00% 2025-09-07T10:03:58.9923339Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9926756Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9930071Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9933803Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9937011Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9940447Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9943836Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:03:58.9944651Z compilation_latency mean=0.000 seconds 2025-09-07T10:03:59.8355322Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *maxautotune-true* ]] 2025-09-07T10:03:59.8356599Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T10:03:59.8357876Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T10:04:00.3509946Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:00.3511509Z import pynvml # type: ignore[import] 2025-09-07T10:04:04.1875018Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:04.1876162Z import pynvml # type: ignore[import] 2025-09-07T10:04:06.6764598Z 2025-09-07T10:04:06.8661128Z loading model: 0it [00:00, ?it/s][rank0]:W0907 10:04:06.865000 196035 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T10:04:07.6457909Z 2025-09-07T10:04:07.6458350Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:04:07.6458728Z cuda eval torchrec_dlrm 2025-09-07T10:04:07.6470535Z Traceback (most recent call last): 2025-09-07T10:04:07.6471039Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T10:04:07.6471508Z self.model_iter_fn(model, example_inputs) 2025-09-07T10:04:07.6471969Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:04:07.6472397Z return mod(*inputs) 2025-09-07T10:04:07.6472893Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:04:07.6473422Z return self._call_impl(*args, **kwargs) 2025-09-07T10:04:07.6473940Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:04:07.6475209Z return forward_call(*args, **kwargs) 2025-09-07T10:04:07.6475723Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:04:07.6476427Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:04:07.6477071Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:04:07.6477634Z return self._call_impl(*args, **kwargs) 2025-09-07T10:04:07.6478144Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:04:07.6478667Z return forward_call(*args, **kwargs) 2025-09-07T10:04:07.6479147Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:04:07.6479781Z concatenated_dense = self.inter_arch( 2025-09-07T10:04:07.6480497Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:04:07.6481080Z return self._call_impl(*args, **kwargs) 2025-09-07T10:04:07.6481605Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:04:07.6482132Z return forward_call(*args, **kwargs) 2025-09-07T10:04:07.6482614Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T10:04:07.6483164Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T10:04:07.6483766Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:04:07.6484350Z return self._call_impl(*args, **kwargs) 2025-09-07T10:04:07.6484809Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:04:07.6485241Z return forward_call(*args, **kwargs) 2025-09-07T10:04:07.6485665Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T10:04:07.6486172Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T10:04:07.6486625Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T10:04:07.6486911Z 2025-09-07T10:04:07.6487072Z The above exception was the direct cause of the following exception: 2025-09-07T10:04:07.6487298Z 2025-09-07T10:04:07.6487384Z Traceback (most recent call last): 2025-09-07T10:04:07.6487722Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:04:07.6488071Z ) = runner.load_model( 2025-09-07T10:04:07.6488431Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:04:07.6488835Z self.validate_model(model, example_inputs) 2025-09-07T10:04:07.6489232Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:04:07.6489627Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:04:07.6489878Z RuntimeError: Eager run failed 2025-09-07T10:04:07.6490016Z 2025-09-07T10:04:07.6490087Z eager_fail_to_run 2025-09-07T10:04:08.1621012Z [rank0]:[W907 10:04:08.255631874 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:04:09.2213936Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:09.2215214Z import pynvml # type: ignore[import] 2025-09-07T10:04:11.7054530Z 2025-09-07T10:04:13.8965485Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:04:13.8966790Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:04:13.9025546Z cuda eval BERT_pytorch 2025-09-07T10:04:31.6566088Z pass 2025-09-07T10:04:34.7575568Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:34.7576908Z import pynvml # type: ignore[import] 2025-09-07T10:04:37.2416838Z 2025-09-07T10:04:40.2031287Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:04:40.2033519Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:04:40.2081658Z cuda eval Background_Matting 2025-09-07T10:04:40.2285943Z pass_due_to_skip 2025-09-07T10:04:41.8273587Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:41.8274693Z import pynvml # type: ignore[import] 2025-09-07T10:04:44.3863627Z 2025-09-07T10:04:47.0916670Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:04:47.0917017Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:04:47.0941894Z cuda eval LearningToPaint 2025-09-07T10:04:54.6929327Z pass 2025-09-07T10:04:57.7634774Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:04:57.7635973Z import pynvml # type: ignore[import] 2025-09-07T10:05:00.2951786Z 2025-09-07T10:05:02.4108474Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:05:02.7222078Z 2025-09-07T10:05:02.7222458Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:05:02.7223074Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:05:02.7223564Z cuda eval Super_SloMo 2025-09-07T10:05:03.0667768Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead 2025-09-07T10:05:30.9637159Z pass 2025-09-07T10:05:35.0047711Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:05:35.0049577Z import pynvml # type: ignore[import] 2025-09-07T10:05:37.4978803Z 2025-09-07T10:05:38.9925266Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:05:38.9925633Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:05:38.9930038Z cuda eval alexnet 2025-09-07T10:05:46.4545871Z pass 2025-09-07T10:05:49.1779590Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:05:49.1781596Z import pynvml # type: ignore[import] 2025-09-07T10:05:51.6691498Z 2025-09-07T10:05:53.6339734Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:05:53.6340100Z loading model: 0it [00:01, ?it/s] 2025-09-07T10:05:53.6344797Z cuda eval basic_gnn_edgecnn 2025-09-07T10:05:56.6425793Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_reduce.two Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:05:56.6427159Z return mod(*inputs) 2025-09-07T10:05:56.6428554Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T10:05:56.6429412Z x = self.convs[i](x, edge_index) 2025-09-07T10:05:56.6430053Z File "/tmp/jenkins_pyg/tmpjtr04quz.py", line 233, in forward 2025-09-07T10:05:56.6431042Z return self.propagate(edge_index, x=x, size=None) 2025-09-07T10:05:56.6431611Z File "/tmp/jenkins_pyg/tmpjtr04quz.py", line 192, in propagate 2025-09-07T10:05:56.6432334Z out = self.aggregate(out, index=kwargs.index, dim_size=kwargs.dim_size, ptr=kwargs.ptr) 2025-09-07T10:05:56.6433397Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:05:56.6434366Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:05:56.6435248Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:05:56.6436329Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:05:56.6437180Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward 2025-09-07T10:05:56.6438058Z return self.reduce(x, index, ptr, dim_size, dim, reduce='max') 2025-09-07T10:05:56.6438907Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:05:56.6439699Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:05:56.6440699Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter 2025-09-07T10:05:56.6441489Z return src.new_zeros(size).scatter_reduce_( 2025-09-07T10:05:56.6441784Z 2025-09-07T10:05:56.6441790Z 2025-09-07T10:05:56.8567764Z pass 2025-09-07T10:06:00.0718250Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:00.0719346Z import pynvml # type: ignore[import] 2025-09-07T10:06:02.6283085Z 2025-09-07T10:06:04.8433979Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:06:04.8434313Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:06:04.8436515Z cuda eval basic_gnn_gcn 2025-09-07T10:06:06.4922205Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91 2025-09-07T10:06:06.4923468Z deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum') 2025-09-07T10:06:06.4924145Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T10:06:06.4924808Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:06.4925091Z 2025-09-07T10:06:06.4925097Z 2025-09-07T10:06:07.0633825Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T10:06:07.0634805Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T10:06:07.0635244Z File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 188, in propagate 2025-09-07T10:06:07.0635751Z out = self.aggregate(out, dim_size=kwargs.dim_size, ptr=kwargs.ptr, index=kwargs.index) 2025-09-07T10:06:07.0636501Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:06:07.0637176Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:06:07.0637787Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:06:07.0639206Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:06:07.0639809Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T10:06:07.0640935Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T10:06:07.0641495Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:06:07.0642001Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:06:07.0642508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T10:06:07.0643039Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:07.0643261Z 2025-09-07T10:06:07.0643421Z 2025-09-07T10:06:07.2206234Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T10:06:07.2207233Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T10:06:07.2207735Z File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 188, in propagate 2025-09-07T10:06:07.2208290Z out = self.aggregate(out, dim_size=kwargs.dim_size, ptr=kwargs.ptr, index=kwargs.index) 2025-09-07T10:06:07.2209089Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:06:07.2209777Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:06:07.2210630Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:06:07.2211280Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:06:07.2211899Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T10:06:07.2212515Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T10:06:07.2213112Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:06:07.2213673Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:06:07.2214226Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T10:06:07.2214816Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:07.2215067Z 2025-09-07T10:06:07.2215071Z 2025-09-07T10:06:07.3531081Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 243, in torch_dynamo_resume_in_forward_at_221 2025-09-07T10:06:07.3532005Z out = self.propagate(edge_index, x=x, edge_weight=edge_weight, 2025-09-07T10:06:07.3532456Z File "/tmp/jenkins_pyg/tmpp5j3yycj.py", line 188, in propagate 2025-09-07T10:06:07.3532987Z out = self.aggregate(out, dim_size=kwargs.dim_size, ptr=kwargs.ptr, index=kwargs.index) 2025-09-07T10:06:07.3533746Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:06:07.3534417Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:06:07.3535033Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:06:07.3535635Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:06:07.3536230Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T10:06:07.3536835Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T10:06:07.3537432Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:06:07.3538490Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:06:07.3539050Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T10:06:07.3539673Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:07.3539895Z 2025-09-07T10:06:07.3539899Z 2025-09-07T10:06:07.4875014Z pass 2025-09-07T10:06:11.1225982Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:11.1227093Z import pynvml # type: ignore[import] 2025-09-07T10:06:13.8779182Z 2025-09-07T10:06:16.1360152Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:06:16.1362102Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:06:16.1365059Z cuda eval basic_gnn_gin 2025-09-07T10:06:19.2305054Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:06:19.2306318Z return mod(*inputs) 2025-09-07T10:06:19.2307078Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T10:06:19.2307866Z x = self.convs[i](x, edge_index) 2025-09-07T10:06:19.2308330Z File "/tmp/jenkins_pyg/tmpkt5546uy.py", line 225, in forward 2025-09-07T10:06:19.2308845Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T10:06:19.2309363Z File "/tmp/jenkins_pyg/tmpkt5546uy.py", line 182, in propagate 2025-09-07T10:06:19.2310050Z out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr) 2025-09-07T10:06:19.2311521Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:06:19.2312463Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:06:19.2313321Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:06:19.2314157Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:06:19.2314975Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward 2025-09-07T10:06:19.2315798Z return self.reduce(x, index, ptr, dim_size, dim, reduce='sum') 2025-09-07T10:06:19.2316616Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:06:19.2317373Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:06:19.2318143Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter 2025-09-07T10:06:19.2318953Z return src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:19.2319295Z 2025-09-07T10:06:19.2319300Z 2025-09-07T10:06:19.4725420Z pass 2025-09-07T10:06:22.2132254Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:22.2133893Z import pynvml # type: ignore[import] 2025-09-07T10:06:24.8189748Z 2025-09-07T10:06:26.8734779Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:06:26.8735290Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:06:26.8737907Z cuda eval basic_gnn_sage 2025-09-07T10:06:30.9138254Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.scatter_add.default Found from File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:06:30.9139610Z return mod(*inputs) 2025-09-07T10:06:30.9141295Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward 2025-09-07T10:06:30.9285796Z x = self.convs[i](x, edge_index) 2025-09-07T10:06:30.9286294Z File "/tmp/jenkins_pyg/tmpaica9bt1.py", line 228, in forward 2025-09-07T10:06:30.9286859Z out = self.propagate(edge_index, x=x, size=size) 2025-09-07T10:06:30.9287439Z File "/tmp/jenkins_pyg/tmpaica9bt1.py", line 182, in propagate 2025-09-07T10:06:30.9288175Z out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index) 2025-09-07T10:06:30.9289251Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate 2025-09-07T10:06:30.9290426Z return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size, 2025-09-07T10:06:30.9291682Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__ 2025-09-07T10:06:30.9292563Z return super().__call__(x, index, ptr, dim_size, dim, **kwargs) 2025-09-07T10:06:30.9293408Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward 2025-09-07T10:06:30.9294266Z return self.reduce(x, index, ptr, dim_size, dim, reduce='mean') 2025-09-07T10:06:30.9295105Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce 2025-09-07T10:06:30.9295898Z return scatter(x, index, dim, dim_size, reduce) 2025-09-07T10:06:30.9296684Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter 2025-09-07T10:06:30.9297499Z out = src.new_zeros(size).scatter_add_(dim, index, src) 2025-09-07T10:06:30.9297857Z 2025-09-07T10:06:30.9297867Z 2025-09-07T10:06:31.0922585Z pass 2025-09-07T10:06:33.2348030Z accuracy pass_rate=80.00% 2025-09-07T10:06:33.2363782Z calls_captured gmean=0.00x mean=123.400x 2025-09-07T10:06:33.2369361Z unique_graphs gmean=0.00x mean=1.300x 2025-09-07T10:06:33.2375015Z graph_breaks gmean=0.00x mean=0.600x 2025-09-07T10:06:33.2380118Z unique_graph_breaks gmean=0.00x mean=0.100x 2025-09-07T10:06:33.2385872Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:06:33.2391249Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:06:33.2397316Z cudagraph_skips gmean=0.00x mean=0.700x 2025-09-07T10:06:33.2399032Z compilation_latency mean=6.740 seconds 2025-09-07T10:06:34.1013622Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs_low_precision-true* ]] 2025-09-07T10:06:34.1014981Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:06:34.1016402Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T10:06:34.6488694Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:34.6490988Z import pynvml # type: ignore[import] 2025-09-07T10:06:37.1961881Z usage: torchbench.py 2025-09-07T10:06:37.1962187Z [-h] 2025-09-07T10:06:37.1962398Z [--filter FILTER] 2025-09-07T10:06:37.1962644Z [--exclude EXCLUDE] 2025-09-07T10:06:37.1962902Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T10:06:37.1963273Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T10:06:37.1963627Z [--partition-id PARTITION_ID] 2025-09-07T10:06:37.1964529Z [--devices DEVICES] 2025-09-07T10:06:37.1964830Z [--device-index DEVICE_INDEX] 2025-09-07T10:06:37.1965109Z [--repeat REPEAT] 2025-09-07T10:06:37.1965554Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T10:06:37.1965859Z [--randomize-input] 2025-09-07T10:06:37.1966101Z [--threads THREADS] 2025-09-07T10:06:37.1966323Z [--nopython] 2025-09-07T10:06:37.1966527Z [--no-skip] 2025-09-07T10:06:37.1966733Z [--prims-nvfuser] 2025-09-07T10:06:37.1966994Z [--dump-raw-metrics] 2025-09-07T10:06:37.1967266Z [--log-operator-inputs] 2025-09-07T10:06:37.1967487Z [--channels-last] 2025-09-07T10:06:37.1967693Z [--batch-size BATCH_SIZE] 2025-09-07T10:06:37.1967923Z [--iterations ITERATIONS] 2025-09-07T10:06:37.1968160Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T10:06:37.1968557Z [--cosine] 2025-09-07T10:06:37.1968729Z [--freezing] 2025-09-07T10:06:37.1968930Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T10:06:37.1969177Z [--ci] 2025-09-07T10:06:37.1969351Z [--dashboard] 2025-09-07T10:06:37.1969540Z [--skip-fp64-check] 2025-09-07T10:06:37.1969746Z [--fast] 2025-09-07T10:06:37.1969922Z [--only ONLY] 2025-09-07T10:06:37.1970107Z [--multiprocess] 2025-09-07T10:06:37.1970754Z [--ddp] 2025-09-07T10:06:37.1970930Z [--fsdp] 2025-09-07T10:06:37.1971135Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T10:06:37.1971453Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T10:06:37.1971765Z [--dynamic-shapes] 2025-09-07T10:06:37.1971994Z [--propagate-real-tensors] 2025-09-07T10:06:37.1972238Z [--dynamic-batch-only] 2025-09-07T10:06:37.1972459Z [--specialize-int] 2025-09-07T10:06:37.1972659Z [--use-eval-mode] 2025-09-07T10:06:37.1972870Z [--skip-accuracy-check] 2025-09-07T10:06:37.1973111Z [--generate-aot-autograd-stats] 2025-09-07T10:06:37.1973361Z [--inductor-settings] 2025-09-07T10:06:37.1973579Z [--suppress-errors] 2025-09-07T10:06:37.1973783Z [--output OUTPUT] 2025-09-07T10:06:37.1974008Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T10:06:37.1974305Z [--disable-output] 2025-09-07T10:06:37.1974508Z [--baseline BASELINE] 2025-09-07T10:06:37.1974719Z [--part PART] 2025-09-07T10:06:37.1974932Z [--export-profiler-trace] 2025-09-07T10:06:37.1975207Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T10:06:37.1975484Z [--profile-details] 2025-09-07T10:06:37.1975707Z [--export-perfdoctor] 2025-09-07T10:06:37.1975936Z [--diff-branch DIFF_BRANCH] 2025-09-07T10:06:37.1976160Z [--tag TAG] 2025-09-07T10:06:37.1976332Z [--explain] 2025-09-07T10:06:37.1976509Z [--stats] 2025-09-07T10:06:37.1976702Z [--use-warm-peak-memory] 2025-09-07T10:06:37.1976933Z [--print-memory] 2025-09-07T10:06:37.1977137Z [--print-compilation-time] 2025-09-07T10:06:37.1977387Z [--print-dataframe-summary] 2025-09-07T10:06:37.1977635Z [--disable-cudagraphs] 2025-09-07T10:06:37.1977867Z [--disable-split-reductions] 2025-09-07T10:06:37.1978122Z [--disable-persistent-reductions] 2025-09-07T10:06:37.1978376Z [--disable-divisible-by-16] 2025-09-07T10:06:37.1978629Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T10:06:37.1978886Z [--print-graph-breaks] 2025-09-07T10:06:37.1979081Z [--log-graph-breaks] 2025-09-07T10:06:37.1979271Z [--trace-on-xla] 2025-09-07T10:06:37.1979461Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T10:06:37.1979677Z [--collect-outputs] 2025-09-07T10:06:37.1979886Z [--enable-activation-checkpointing] 2025-09-07T10:06:37.1980107Z [--timing] 2025-09-07T10:06:37.1980439Z [--progress] 2025-09-07T10:06:37.1980617Z [--timeout TIMEOUT] 2025-09-07T10:06:37.1980854Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T10:06:37.1981144Z [--no-translation-validation] 2025-09-07T10:06:37.1981548Z [--minify] 2025-09-07T10:06:37.1981733Z [--compiled-autograd] 2025-09-07T10:06:37.1982032Z [--profile_dynamo_cache_lookup] 2025-09-07T10:06:37.1982247Z [--snapshot-memory] 2025-09-07T10:06:37.1982431Z [--retain-output] 2025-09-07T10:06:37.1982644Z [--caching-precompile] 2025-09-07T10:06:37.1982983Z [--cold-start-latency | --warm-start-latency] 2025-09-07T10:06:37.1983217Z [--nnc] 2025-09-07T10:06:37.1983403Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T10:06:37.1983650Z [--amp-dtype {bfloat16,float16}] 2025-09-07T10:06:37.1983869Z [--verbose | --quiet] 2025-09-07T10:06:37.1986227Z [--coverage | --overhead | --speedup-dynamo-ts | --speedup-fx2trt | --speedup-fx2trt-fp16 | --print-fx | --print-aten-ops | --inductor | --quantization {int8dynamic,int8weightonly,int4weightonly,autoquant,noquant} | --export | --export-aot-inductor | --export-nativert | --torchscript-jit-trace | --xla | --backend {aot_eager,aot_eager_decomp_partition,aot_eager_decomp_partition_crossref,aot_eager_decomp_partition_with_mode,aot_eager_default_partitioner,aot_ts,cudagraphs,dynamo_accuracy_minifier_backend,dynamo_minifier_backend,eager,eager_debug,eager_noexcept,inductor,non_leaf_compile_error_TESTING_ONLY,openxla,openxla_eval,pre_dispatch_eager,relu_accuracy_error_TESTING_ONLY,relu_compile_error_TESTING_ONLY,relu_runtime_error_TESTING_ONLY,ts,tvm} | --nothing | --log-conv-args | --recompile-profiler | --find-batch-sizes] 2025-09-07T10:06:37.1988714Z (--accuracy | --performance | --tolerance) 2025-09-07T10:06:37.1988955Z (--training | --inference) 2025-09-07T10:06:37.1989242Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T10:06:37.8124060Z + true 2025-09-07T10:06:37.8125066Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T10:06:37.8148609Z + for target in "${targets[@]}" 2025-09-07T10:06:37.8148899Z + target_flag=('--performance') 2025-09-07T10:06:37.8149145Z + local target_flag 2025-09-07T10:06:37.8149373Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T10:06:37.8149670Z + target_flag+=(--cold-start-latency) 2025-09-07T10:06:37.8151172Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T10:06:37.8153277Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T10:06:37.8155519Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv 2025-09-07T10:06:38.3185296Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:38.3186321Z import pynvml # type: ignore[import] 2025-09-07T10:06:42.2323156Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:42.2324256Z import pynvml # type: ignore[import] 2025-09-07T10:06:44.7435344Z 2025-09-07T10:06:44.9330371Z loading model: 0it [00:00, ?it/s][rank0]:W0907 10:06:44.932000 202443 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T10:06:45.6647263Z 2025-09-07T10:06:45.6647740Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:06:45.6648269Z cuda eval torchrec_dlrm 2025-09-07T10:06:45.6655259Z Traceback (most recent call last): 2025-09-07T10:06:45.6656120Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T10:06:45.6656950Z self.model_iter_fn(model, example_inputs) 2025-09-07T10:06:45.6658326Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:06:45.6659098Z return mod(*inputs) 2025-09-07T10:06:45.6660057Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:06:45.6660950Z return self._call_impl(*args, **kwargs) 2025-09-07T10:06:45.6661442Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:06:45.6661956Z return forward_call(*args, **kwargs) 2025-09-07T10:06:45.6662421Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:06:45.6663035Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:06:45.6663630Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:06:45.6664154Z return self._call_impl(*args, **kwargs) 2025-09-07T10:06:45.6664651Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:06:45.6665145Z return forward_call(*args, **kwargs) 2025-09-07T10:06:45.6665590Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:06:45.6666064Z concatenated_dense = self.inter_arch( 2025-09-07T10:06:45.6666588Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:06:45.6667110Z return self._call_impl(*args, **kwargs) 2025-09-07T10:06:45.6667586Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:06:45.6668062Z return forward_call(*args, **kwargs) 2025-09-07T10:06:45.6668503Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T10:06:45.6669011Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T10:06:45.6669576Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:06:45.6670070Z return self._call_impl(*args, **kwargs) 2025-09-07T10:06:45.6670668Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:06:45.6671087Z return forward_call(*args, **kwargs) 2025-09-07T10:06:45.6671493Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T10:06:45.6671964Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T10:06:45.6672401Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T10:06:45.6672700Z 2025-09-07T10:06:45.6672854Z The above exception was the direct cause of the following exception: 2025-09-07T10:06:45.6673092Z 2025-09-07T10:06:45.6673173Z Traceback (most recent call last): 2025-09-07T10:06:45.6673768Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:06:45.6674126Z ) = runner.load_model( 2025-09-07T10:06:45.6674478Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:06:45.6674986Z self.validate_model(model, example_inputs) 2025-09-07T10:06:45.6675377Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:06:45.6675777Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:06:45.6676018Z RuntimeError: Eager run failed 2025-09-07T10:06:45.6676156Z 2025-09-07T10:06:45.6676219Z eager_fail_to_run 2025-09-07T10:06:46.1867030Z [rank0]:[W907 10:06:46.280340529 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:06:47.2545647Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:06:47.2546883Z import pynvml # type: ignore[import] 2025-09-07T10:06:49.7357922Z 2025-09-07T10:06:51.8769838Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:06:51.8770190Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:06:51.8821432Z cuda eval BERT_pytorch 2025-09-07T10:07:05.9738312Z 2025-09-07T10:07:06.0887406Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:16:19.4637488Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:16:19.4638069Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T10:16:19.4638595Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:16:19.4639042Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T10:16:19.4639457Z self._cache.realize() 2025-09-07T10:16:19.4639841Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T10:16:19.4640436Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T10:16:19.4640933Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T10:16:19.4641353Z vt = self._wrap(value) 2025-09-07T10:16:19.4641836Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T10:16:19.4642268Z return type_dispatch(self, value) 2025-09-07T10:16:19.4642729Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T10:16:19.4643206Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T10:16:19.4643728Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T10:16:19.4644229Z fake_e = wrap_fake_exception( 2025-09-07T10:16:19.4644653Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T10:16:19.4645069Z return fn() 2025-09-07T10:16:19.4645449Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T10:16:19.4645899Z lambda: tx.fake_mode.from_tensor( 2025-09-07T10:16:19.4646335Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T10:16:19.4646818Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T10:16:19.4647323Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T10:16:19.4647770Z out = self.meta_converter( 2025-09-07T10:16:19.4648179Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T10:16:19.4648659Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T10:16:19.4649152Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T10:16:19.4649675Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T10:16:19.4650821Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:16:19.4651826Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:16:19.4652302Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T10:16:19.4653126Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T10:16:19.4653686Z 2025-09-07T10:16:19.4653766Z from user code: 2025-09-07T10:16:19.4654210Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:16:19.4654743Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:16:19.4655219Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T10:16:19.4655829Z self._future_mask.size(0) == 0 2025-09-07T10:16:19.4655987Z 2025-09-07T10:16:19.4656511Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T10:16:19.4657000Z 2025-09-07T10:16:19.4657076Z warmup_failed 2025-09-07T10:16:23.2077456Z Run failed with return code: 255 2025-09-07T10:16:23.2077784Z Output: None 2025-09-07T10:16:23.2077995Z Error: None 2025-09-07T10:16:23.2116840Z speedup gmean=0.00x mean=2.009x 2025-09-07T10:16:23.2120594Z abs_latency gmean=0.00x mean=1.800x 2025-09-07T10:16:23.2122406Z compilation_latency mean=6.634 seconds 2025-09-07T10:16:23.2122688Z compression_ratio mean=0.854x 2025-09-07T10:16:23.2126274Z eager_peak_mem gmean=0.00x mean=0.385x 2025-09-07T10:16:23.2137672Z dynamo_peak_mem gmean=0.00x mean=0.317x 2025-09-07T10:16:23.2141382Z calls_captured gmean=0.00x mean=128.818x 2025-09-07T10:16:23.2144900Z unique_graphs gmean=0.00x mean=1.273x 2025-09-07T10:16:23.2148222Z graph_breaks gmean=0.00x mean=0.545x 2025-09-07T10:16:23.2151832Z unique_graph_breaks gmean=0.00x mean=0.091x 2025-09-07T10:16:23.2154999Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:16:23.2158258Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:16:23.2161946Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:16:24.4687507Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *dynamic-true* ]] 2025-09-07T10:16:24.4690082Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.csv 2025-09-07T10:16:25.0197100Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:16:25.0198227Z import pynvml # type: ignore[import] 2025-09-07T10:16:28.8725906Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:16:28.8727226Z import pynvml # type: ignore[import] 2025-09-07T10:16:31.2984054Z 2025-09-07T10:16:31.4874178Z loading model: 0it [00:00, ?it/s][rank0]:W0907 10:16:31.486000 225544 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T10:16:32.2161591Z 2025-09-07T10:16:32.2162154Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:16:32.2162731Z cuda eval torchrec_dlrm 2025-09-07T10:16:32.2170019Z Traceback (most recent call last): 2025-09-07T10:16:32.2170834Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T10:16:32.2171333Z self.model_iter_fn(model, example_inputs) 2025-09-07T10:16:32.2171800Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:16:32.2172247Z return mod(*inputs) 2025-09-07T10:16:32.2172744Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:16:32.2173304Z return self._call_impl(*args, **kwargs) 2025-09-07T10:16:32.2174271Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:16:32.2174881Z return forward_call(*args, **kwargs) 2025-09-07T10:16:32.2175341Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:16:32.2175880Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:16:32.2176482Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:16:32.2177008Z return self._call_impl(*args, **kwargs) 2025-09-07T10:16:32.2177493Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:16:32.2178120Z return forward_call(*args, **kwargs) 2025-09-07T10:16:32.2178572Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:16:32.2179056Z concatenated_dense = self.inter_arch( 2025-09-07T10:16:32.2179572Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:16:32.2180089Z return self._call_impl(*args, **kwargs) 2025-09-07T10:16:32.2180742Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:16:32.2181224Z return forward_call(*args, **kwargs) 2025-09-07T10:16:32.2181678Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T10:16:32.2182179Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T10:16:32.2182747Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:16:32.2183331Z return self._call_impl(*args, **kwargs) 2025-09-07T10:16:32.2183811Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:16:32.2184290Z return forward_call(*args, **kwargs) 2025-09-07T10:16:32.2184765Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T10:16:32.2185304Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T10:16:32.2185804Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T10:16:32.2186129Z 2025-09-07T10:16:32.2186308Z The above exception was the direct cause of the following exception: 2025-09-07T10:16:32.2186566Z 2025-09-07T10:16:32.2186659Z Traceback (most recent call last): 2025-09-07T10:16:32.2187035Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:16:32.2187426Z ) = runner.load_model( 2025-09-07T10:16:32.2187814Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:16:32.2188271Z self.validate_model(model, example_inputs) 2025-09-07T10:16:32.2188716Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:16:32.2189171Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:16:32.2189421Z RuntimeError: Eager run failed 2025-09-07T10:16:32.2189561Z 2025-09-07T10:16:32.2189633Z eager_fail_to_run 2025-09-07T10:16:32.7300994Z [rank0]:[W907 10:16:32.823643568 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:16:33.7494760Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:16:33.7496008Z import pynvml # type: ignore[import] 2025-09-07T10:16:36.2470668Z 2025-09-07T10:16:38.4353372Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:16:38.4353707Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:16:38.4408347Z cuda eval BERT_pytorch 2025-09-07T10:17:01.8665646Z 2025-09-07T10:17:01.9748794Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:20:42.9188532Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:20:42.9188977Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T10:20:42.9189422Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:20:42.9189835Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T10:20:42.9190377Z self._cache.realize() 2025-09-07T10:20:42.9190782Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T10:20:42.9191276Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T10:20:42.9191943Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T10:20:42.9192391Z vt = self._wrap(value) 2025-09-07T10:20:42.9192791Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T10:20:42.9193315Z return type_dispatch(self, value) 2025-09-07T10:20:42.9193771Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T10:20:42.9194239Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T10:20:42.9194767Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T10:20:42.9195272Z fake_e = wrap_fake_exception( 2025-09-07T10:20:42.9195698Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T10:20:42.9196200Z return fn() 2025-09-07T10:20:42.9196592Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T10:20:42.9197028Z lambda: tx.fake_mode.from_tensor( 2025-09-07T10:20:42.9197455Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T10:20:42.9197925Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T10:20:42.9198403Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T10:20:42.9198851Z out = self.meta_converter( 2025-09-07T10:20:42.9199270Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T10:20:42.9199747Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T10:20:42.9200393Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T10:20:42.9200929Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T10:20:42.9201941Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:20:42.9202957Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:20:42.9203429Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T10:20:42.9204265Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T10:20:42.9204824Z 2025-09-07T10:20:42.9204901Z from user code: 2025-09-07T10:20:42.9205328Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:20:42.9205867Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:20:42.9206335Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T10:20:42.9206749Z self._future_mask.size(0) == 0 2025-09-07T10:20:42.9206897Z 2025-09-07T10:20:42.9207321Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T10:20:42.9207816Z 2025-09-07T10:20:42.9207884Z warmup_failed 2025-09-07T10:20:46.6350756Z Run failed with return code: 255 2025-09-07T10:20:46.6351134Z Output: None 2025-09-07T10:20:46.6351376Z Error: None 2025-09-07T10:20:46.6387373Z speedup gmean=0.00x mean=1.987x 2025-09-07T10:20:46.6391189Z abs_latency gmean=0.00x mean=2.114x 2025-09-07T10:20:46.6392587Z compilation_latency mean=8.123 seconds 2025-09-07T10:20:46.6392954Z compression_ratio mean=0.854x 2025-09-07T10:20:46.6396312Z eager_peak_mem gmean=0.00x mean=0.385x 2025-09-07T10:20:46.6407513Z dynamo_peak_mem gmean=0.00x mean=0.317x 2025-09-07T10:20:46.6410843Z calls_captured gmean=0.00x mean=128.818x 2025-09-07T10:20:46.6414144Z unique_graphs gmean=0.00x mean=1.273x 2025-09-07T10:20:46.6417207Z graph_breaks gmean=0.00x mean=0.545x 2025-09-07T10:20:46.6420443Z unique_graph_breaks gmean=0.00x mean=0.091x 2025-09-07T10:20:46.6423960Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:20:46.6426988Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:20:46.6430061Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:20:47.8126264Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cppwrapper-true* ]] 2025-09-07T10:20:47.8128135Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T10:20:47.8129501Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.csv 2025-09-07T10:20:48.3615220Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:20:48.3616411Z import pynvml # type: ignore[import] 2025-09-07T10:20:52.1900620Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:20:52.1901858Z import pynvml # type: ignore[import] 2025-09-07T10:20:54.6846363Z 2025-09-07T10:20:54.8743744Z loading model: 0it [00:00, ?it/s][rank0]:W0907 10:20:54.873000 237107 site-packages/torch/fx/_symbolic_trace.py:52] 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. 2025-09-07T10:20:55.6271700Z 2025-09-07T10:20:55.6272130Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:20:55.6272456Z cuda eval torchrec_dlrm 2025-09-07T10:20:55.6282323Z Traceback (most recent call last): 2025-09-07T10:20:55.6282914Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T10:20:55.6283446Z self.model_iter_fn(model, example_inputs) 2025-09-07T10:20:55.6283958Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T10:20:55.6284444Z return mod(*inputs) 2025-09-07T10:20:55.6284951Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:20:55.6285509Z return self._call_impl(*args, **kwargs) 2025-09-07T10:20:55.6286010Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:20:55.6286506Z return forward_call(*args, **kwargs) 2025-09-07T10:20:55.6286961Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 893, in forward 2025-09-07T10:20:55.6287511Z logits = self.model(batch.dense_features, batch.sparse_features) 2025-09-07T10:20:55.6288110Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:20:55.6288661Z return self._call_impl(*args, **kwargs) 2025-09-07T10:20:55.6289764Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:20:55.6290557Z return forward_call(*args, **kwargs) 2025-09-07T10:20:55.6291040Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 572, in forward 2025-09-07T10:20:55.6291508Z concatenated_dense = self.inter_arch( 2025-09-07T10:20:55.6292022Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:20:55.6292537Z return self._call_impl(*args, **kwargs) 2025-09-07T10:20:55.6293015Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:20:55.6293498Z return forward_call(*args, **kwargs) 2025-09-07T10:20:55.6294084Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/models/dlrm.py", line 284, in forward 2025-09-07T10:20:55.6294597Z return self.crossnet(combined_values.reshape([B, -1])) 2025-09-07T10:20:55.6295179Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T10:20:55.6295645Z return self._call_impl(*args, **kwargs) 2025-09-07T10:20:55.6296076Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T10:20:55.6296530Z return forward_call(*args, **kwargs) 2025-09-07T10:20:55.6296955Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchrec/modules/crossnet.py", line 175, in forward 2025-09-07T10:20:55.6297435Z x_l_v = torch.nn.functional.linear(x_l, self.V_kernels[layer]) 2025-09-07T10:20:55.6297880Z RuntimeError: expected mat1 and mat2 to have the same dtype, but got: float != c10::BFloat16 2025-09-07T10:20:55.6298162Z 2025-09-07T10:20:55.6298324Z The above exception was the direct cause of the following exception: 2025-09-07T10:20:55.6298553Z 2025-09-07T10:20:55.6298642Z Traceback (most recent call last): 2025-09-07T10:20:55.6298978Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T10:20:55.6299331Z ) = runner.load_model( 2025-09-07T10:20:55.6299692Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T10:20:55.6300098Z self.validate_model(model, example_inputs) 2025-09-07T10:20:55.6300603Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T10:20:55.6301019Z raise RuntimeError("Eager run failed") from e 2025-09-07T10:20:55.6301273Z RuntimeError: Eager run failed 2025-09-07T10:20:55.6301403Z 2025-09-07T10:20:55.6301477Z eager_fail_to_run 2025-09-07T10:20:56.1564559Z [rank0]:[W907 10:20:56.250026901 ProcessGroupNCCL.cpp:1524] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator()) 2025-09-07T10:20:57.2036215Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:20:57.2037449Z import pynvml # type: ignore[import] 2025-09-07T10:20:59.6623051Z 2025-09-07T10:21:01.8382054Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:21:01.8382577Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:21:01.8427494Z cuda eval BERT_pytorch 2025-09-07T10:21:24.5019631Z 2025-09-07T10:21:24.6144898Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:53:36.6948370Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:53:36.6949267Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builtin.py", line 967, in 2025-09-07T10:53:36.6950087Z tx, [v.realize() for v in args], kwargs 2025-09-07T10:53:36.6951006Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 72, in realize 2025-09-07T10:53:36.6951750Z self._cache.realize() 2025-09-07T10:53:36.6952449Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/lazy.py", line 33, in realize 2025-09-07T10:53:36.6953320Z self.vt = builder.VariableBuilder(tx, self.source)(self.value) 2025-09-07T10:53:36.6954212Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 445, in __call__ 2025-09-07T10:53:36.6955103Z vt = self._wrap(value) 2025-09-07T10:53:36.6955817Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 670, in _wrap 2025-09-07T10:53:36.6956607Z return type_dispatch(self, value) 2025-09-07T10:53:36.6957415Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 2116, in wrap_tensor 2025-09-07T10:53:36.6958265Z example_value = wrap_to_fake_tensor_and_record( 2025-09-07T10:53:36.6959203Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3500, in wrap_to_fake_tensor_and_record 2025-09-07T10:53:36.6960087Z fake_e = wrap_fake_exception( 2025-09-07T10:53:36.6961008Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/utils.py", line 2864, in wrap_fake_exception 2025-09-07T10:53:36.6961776Z return fn() 2025-09-07T10:53:36.6962455Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/variables/builder.py", line 3501, in 2025-09-07T10:53:36.6963259Z lambda: tx.fake_mode.from_tensor( 2025-09-07T10:53:36.6964046Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 2989, in from_tensor 2025-09-07T10:53:36.6964916Z return self.fake_tensor_converter.from_real_tensor( 2025-09-07T10:53:36.6965801Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/fake_tensor.py", line 404, in from_real_tensor 2025-09-07T10:53:36.6966611Z out = self.meta_converter( 2025-09-07T10:53:36.6967448Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 1898, in __call__ 2025-09-07T10:53:36.6968305Z t_desc = self.describer.describe_tensor(t, trace=trace) 2025-09-07T10:53:36.6969192Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/meta_utils.py", line 310, in describe_tensor 2025-09-07T10:53:36.6970132Z storage = self.describe_storage(t.untyped_storage(), trace=trace) 2025-09-07T10:53:36.6972165Z torch._dynamo.exc.InternalTorchDynamoError: RuntimeError: Error: accessing tensor output of CUDAGraphs that has been overwritten by a subsequent run. Stack trace: File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:53:36.6974033Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:53:36.6974900Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1077, in buffered_future_mask 2025-09-07T10:53:36.6976402Z self._future_mask = self._future_mask.to(tensor). To prevent overwriting, clone the tensor outside of torch.compile() or call torch.compiler.cudagraph_mark_step_begin() before each model invocation. 2025-09-07T10:53:36.6977430Z 2025-09-07T10:53:36.6977548Z from user code: 2025-09-07T10:53:36.6978309Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1023, in torch_dynamo_resume_in_extract_features_at_1008 2025-09-07T10:53:36.6979482Z self_attn_mask = self.buffered_future_mask(x, prev_output_tokens) 2025-09-07T10:53:36.6980490Z File "/torchbench/torchbenchmark/models/cm3leon_generate/model.py", line 1060, in buffered_future_mask 2025-09-07T10:53:36.6981357Z self._future_mask.size(0) == 0 2025-09-07T10:53:36.6981611Z 2025-09-07T10:53:36.6982379Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo" 2025-09-07T10:53:36.6983329Z 2025-09-07T10:53:36.6983440Z warmup_failed 2025-09-07T10:53:43.4944210Z Run failed with return code: 255 2025-09-07T10:53:43.4944751Z Output: None 2025-09-07T10:53:43.4945091Z Error: None 2025-09-07T10:53:43.4982277Z speedup gmean=0.00x mean=2.153x 2025-09-07T10:53:43.4985761Z abs_latency gmean=0.00x mean=1.758x 2025-09-07T10:53:43.4986787Z compilation_latency mean=12.129 seconds 2025-09-07T10:53:43.4987640Z compression_ratio mean=0.837x 2025-09-07T10:53:43.4991279Z eager_peak_mem gmean=0.00x mean=0.385x 2025-09-07T10:53:43.5001839Z dynamo_peak_mem gmean=0.00x mean=0.334x 2025-09-07T10:53:43.5005079Z calls_captured gmean=0.00x mean=128.818x 2025-09-07T10:53:43.5008219Z unique_graphs gmean=0.00x mean=1.273x 2025-09-07T10:53:43.5011728Z graph_breaks gmean=0.00x mean=0.545x 2025-09-07T10:53:43.5014800Z unique_graph_breaks gmean=0.00x mean=0.091x 2025-09-07T10:53:43.5017798Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:53:43.5020951Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:53:43.5024271Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T10:53:46.4075799Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs_low_precision-true* ]] 2025-09-07T10:53:46.4077156Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:53:46.4078461Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --quant --backend inductor --device cuda --total-partitions 9 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_performance.csv 2025-09-07T10:53:46.9438733Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:53:46.9441278Z import pynvml # type: ignore[import] 2025-09-07T10:53:49.3576218Z usage: torchbench.py 2025-09-07T10:53:49.3576598Z [-h] 2025-09-07T10:53:49.3576861Z [--filter FILTER] 2025-09-07T10:53:49.3577196Z [--exclude EXCLUDE] 2025-09-07T10:53:49.3577542Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T10:53:49.3578001Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T10:53:49.3578475Z [--partition-id PARTITION_ID] 2025-09-07T10:53:49.3578833Z [--devices DEVICES] 2025-09-07T10:53:49.3579164Z [--device-index DEVICE_INDEX] 2025-09-07T10:53:49.3579512Z [--repeat REPEAT] 2025-09-07T10:53:49.3579862Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T10:53:49.3580640Z [--randomize-input] 2025-09-07T10:53:49.3580963Z [--threads THREADS] 2025-09-07T10:53:49.3581260Z [--nopython] 2025-09-07T10:53:49.3581524Z [--no-skip] 2025-09-07T10:53:49.3581788Z [--prims-nvfuser] 2025-09-07T10:53:49.3582103Z [--dump-raw-metrics] 2025-09-07T10:53:49.3582427Z [--log-operator-inputs] 2025-09-07T10:53:49.3582801Z [--channels-last] 2025-09-07T10:53:49.3583106Z [--batch-size BATCH_SIZE] 2025-09-07T10:53:49.3583449Z [--iterations ITERATIONS] 2025-09-07T10:53:49.3583799Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T10:53:49.3584160Z [--cosine] 2025-09-07T10:53:49.3584859Z [--freezing] 2025-09-07T10:53:49.3585162Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T10:53:49.3585680Z [--ci] 2025-09-07T10:53:49.3585929Z [--dashboard] 2025-09-07T10:53:49.3586210Z [--skip-fp64-check] 2025-09-07T10:53:49.3586506Z [--fast] 2025-09-07T10:53:49.3586758Z [--only ONLY] 2025-09-07T10:53:49.3587029Z [--multiprocess] 2025-09-07T10:53:49.3587301Z [--ddp] 2025-09-07T10:53:49.3587549Z [--fsdp] 2025-09-07T10:53:49.3587845Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T10:53:49.3588316Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T10:53:49.3588747Z [--dynamic-shapes] 2025-09-07T10:53:49.3589067Z [--propagate-real-tensors] 2025-09-07T10:53:49.3589418Z [--dynamic-batch-only] 2025-09-07T10:53:49.3589918Z [--specialize-int] 2025-09-07T10:53:49.3590365Z [--use-eval-mode] 2025-09-07T10:53:49.3590694Z [--skip-accuracy-check] 2025-09-07T10:53:49.3591053Z [--generate-aot-autograd-stats] 2025-09-07T10:53:49.3591427Z [--inductor-settings] 2025-09-07T10:53:49.3591747Z [--suppress-errors] 2025-09-07T10:53:49.3592052Z [--output OUTPUT] 2025-09-07T10:53:49.3592384Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T10:53:49.3592760Z [--disable-output] 2025-09-07T10:53:49.3593054Z [--baseline BASELINE] 2025-09-07T10:53:49.3593365Z [--part PART] 2025-09-07T10:53:49.3593675Z [--export-profiler-trace] 2025-09-07T10:53:49.3594069Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T10:53:49.3594474Z [--profile-details] 2025-09-07T10:53:49.3594790Z [--export-perfdoctor] 2025-09-07T10:53:49.3595121Z [--diff-branch DIFF_BRANCH] 2025-09-07T10:53:49.3595453Z [--tag TAG] 2025-09-07T10:53:49.3595708Z [--explain] 2025-09-07T10:53:49.3595964Z [--stats] 2025-09-07T10:53:49.3596246Z [--use-warm-peak-memory] 2025-09-07T10:53:49.3596576Z [--print-memory] 2025-09-07T10:53:49.3596880Z [--print-compilation-time] 2025-09-07T10:53:49.3597244Z [--print-dataframe-summary] 2025-09-07T10:53:49.3597601Z [--disable-cudagraphs] 2025-09-07T10:53:49.3597942Z [--disable-split-reductions] 2025-09-07T10:53:49.3598316Z [--disable-persistent-reductions] 2025-09-07T10:53:49.3598706Z [--disable-divisible-by-16] 2025-09-07T10:53:49.3599109Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T10:53:49.3599526Z [--print-graph-breaks] 2025-09-07T10:53:49.3599846Z [--log-graph-breaks] 2025-09-07T10:53:49.3600444Z [--trace-on-xla] 2025-09-07T10:53:49.3600770Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T10:53:49.3601128Z [--collect-outputs] 2025-09-07T10:53:49.3601464Z [--enable-activation-checkpointing] 2025-09-07T10:53:49.3601832Z [--timing] 2025-09-07T10:53:49.3602118Z [--progress] 2025-09-07T10:53:49.3602390Z [--timeout TIMEOUT] 2025-09-07T10:53:49.3602787Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T10:53:49.3603261Z [--no-translation-validation] 2025-09-07T10:53:49.3603604Z [--minify] 2025-09-07T10:53:49.3603874Z [--compiled-autograd] 2025-09-07T10:53:49.3604204Z [--profile_dynamo_cache_lookup] 2025-09-07T10:53:49.3604561Z [--snapshot-memory] 2025-09-07T10:53:49.3604863Z [--retain-output] 2025-09-07T10:53:49.3605170Z [--caching-precompile] 2025-09-07T10:53:49.3605542Z [--cold-start-latency | --warm-start-latency] 2025-09-07T10:53:49.3605930Z [--nnc] 2025-09-07T10:53:49.3606227Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T10:53:49.3606631Z [--amp-dtype {bfloat16,float16}] 2025-09-07T10:53:49.3606984Z [--verbose | --quiet] 2025-09-07T10:53:49.3611382Z [--coverage | --overhead | --speedup-dynamo-ts | --speedup-fx2trt | --speedup-fx2trt-fp16 | --print-fx | --print-aten-ops | --inductor | --quantization {int8dynamic,int8weightonly,int4weightonly,autoquant,noquant} | --export | --export-aot-inductor | --export-nativert | --torchscript-jit-trace | --xla | --backend {aot_eager,aot_eager_decomp_partition,aot_eager_decomp_partition_crossref,aot_eager_decomp_partition_with_mode,aot_eager_default_partitioner,aot_ts,cudagraphs,dynamo_accuracy_minifier_backend,dynamo_minifier_backend,eager,eager_debug,eager_noexcept,inductor,non_leaf_compile_error_TESTING_ONLY,openxla,openxla_eval,pre_dispatch_eager,relu_accuracy_error_TESTING_ONLY,relu_compile_error_TESTING_ONLY,relu_runtime_error_TESTING_ONLY,ts,tvm} | --nothing | --log-conv-args | --recompile-profiler | --find-batch-sizes] 2025-09-07T10:53:49.3615705Z (--accuracy | --performance | --tolerance) 2025-09-07T10:53:49.3616098Z (--training | --inference) 2025-09-07T10:53:49.3616586Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T10:53:49.9425896Z + true 2025-09-07T10:53:49.9427469Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_performance.csv 2025-09-07T10:53:49.9447928Z + sccache_epilogue 2025-09-07T10:53:49.9448352Z + echo '::group::Sccache Compilation Log' 2025-09-07T10:53:49.9449234Z ##[group]Sccache Compilation Log 2025-09-07T10:53:49.9449702Z + echo '=================== sccache compilation log ===================' 2025-09-07T10:53:49.9450560Z =================== sccache compilation log =================== 2025-09-07T10:53:49.9451382Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log 2025-09-07T10:53:49.9733179Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ===========' 2025-09-07T10:53:49.9734084Z =========== If your build fails, please take a look at the log above for possible reasons =========== 2025-09-07T10:53:49.9734711Z + sccache --show-stats 2025-09-07T10:53:49.9762588Z Compile requests 785 2025-09-07T10:53:49.9763054Z Compile requests executed 34 2025-09-07T10:53:49.9763433Z Cache hits 17 2025-09-07T10:53:49.9763777Z Cache hits (C/C++) 17 2025-09-07T10:53:49.9764124Z Cache misses 17 2025-09-07T10:53:49.9764477Z Cache misses (C/C++) 17 2025-09-07T10:53:49.9764841Z Cache hits rate 50.00 % 2025-09-07T10:53:49.9765208Z Cache hits rate (C/C++) 50.00 % 2025-09-07T10:53:49.9765816Z Cache timeouts 0 2025-09-07T10:53:49.9766185Z Cache read errors 0 2025-09-07T10:53:49.9766539Z Forced recaches 0 2025-09-07T10:53:49.9766900Z Cache write errors 0 2025-09-07T10:53:49.9767251Z Cache errors 0 2025-09-07T10:53:49.9767601Z Compilations 17 2025-09-07T10:53:49.9767965Z Compilation failures 0 2025-09-07T10:53:49.9768342Z Non-cacheable compilations 0 2025-09-07T10:53:49.9768711Z Non-cacheable calls 72 2025-09-07T10:53:49.9769080Z Non-compilation calls 679 2025-09-07T10:53:49.9769455Z Unsupported compiler calls 0 2025-09-07T10:53:49.9769833Z Average cache write 0.098 s 2025-09-07T10:53:49.9770399Z Average compiler 3.899 s 2025-09-07T10:53:49.9770792Z Average cache read hit 0.030 s 2025-09-07T10:53:49.9771178Z Failed distributed compilations 0 2025-09-07T10:53:49.9771433Z 2025-09-07T10:53:49.9771559Z Non-cacheable reasons: 2025-09-07T10:53:49.9771856Z -E 55 2025-09-07T10:53:49.9772223Z unknown source language 17 2025-09-07T10:53:49.9772470Z 2025-09-07T10:53:49.9772750Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-09-07T10:53:49.9773281Z Version (client) 0.10.0 2025-09-07T10:53:49.9773793Z + sccache --stop-server 2025-09-07T10:53:49.9791093Z Stopping sccache server... 2025-09-07T10:53:49.9793773Z Compile requests 785 2025-09-07T10:53:49.9794231Z Compile requests executed 34 2025-09-07T10:53:49.9794638Z Cache hits 17 2025-09-07T10:53:49.9795024Z Cache hits (C/C++) 17 2025-09-07T10:53:49.9795410Z Cache misses 17 2025-09-07T10:53:49.9795784Z Cache misses (C/C++) 17 2025-09-07T10:53:49.9796169Z Cache hits rate 50.00 % 2025-09-07T10:53:49.9796584Z Cache hits rate (C/C++) 50.00 % 2025-09-07T10:53:49.9796982Z Cache timeouts 0 2025-09-07T10:53:49.9797371Z Cache read errors 0 2025-09-07T10:53:49.9797757Z Forced recaches 0 2025-09-07T10:53:49.9798342Z Cache write errors 0 2025-09-07T10:53:49.9798737Z Cache errors 0 2025-09-07T10:53:49.9799127Z Compilations 17 2025-09-07T10:53:49.9799527Z Compilation failures 0 2025-09-07T10:53:49.9799937Z Non-cacheable compilations 0 2025-09-07T10:53:49.9800554Z Non-cacheable calls 72 2025-09-07T10:53:49.9800959Z Non-compilation calls 679 2025-09-07T10:53:49.9801367Z Unsupported compiler calls 0 2025-09-07T10:53:49.9801778Z Average cache write 0.098 s 2025-09-07T10:53:49.9802212Z Average compiler 3.899 s 2025-09-07T10:53:49.9802632Z Average cache read hit 0.030 s 2025-09-07T10:53:49.9803070Z Failed distributed compilations 0 2025-09-07T10:53:49.9803354Z 2025-09-07T10:53:49.9803497Z Non-cacheable reasons: 2025-09-07T10:53:49.9803823Z -E 55 2025-09-07T10:53:49.9804226Z unknown source language 17 2025-09-07T10:53:49.9804491Z 2025-09-07T10:53:49.9804822Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-09-07T10:53:49.9805419Z Version (client) 0.10.0 2025-09-07T10:53:49.9805838Z + echo ::endgroup:: 2025-09-07T10:53:49.9806410Z ##[endgroup] 2025-09-07T10:53:49.9806704Z + cleanup_workspace 2025-09-07T10:53:49.9807338Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.' 2025-09-07T10:53:49.9808344Z sudo may print the following warning message that can be ignored. The chown command will still run. 2025-09-07T10:53:49.9809158Z + echo ' sudo: setrlimit(RLIMIT_STACK): Operation not permitted' 2025-09-07T10:53:49.9809947Z sudo: setrlimit(RLIMIT_STACK): Operation not permitted 2025-09-07T10:53:49.9810886Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42' 2025-09-07T10:53:49.9811653Z For more details refer to https://github.com/sudo-project/sudo/issues/42 2025-09-07T10:53:49.9812280Z + sudo chown -R 1000 /var/lib/jenkins/workspace 2025-09-07T10:53:50.8468829Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main 2025-09-07T10:53:50.8469195Z with: 2025-09-07T10:53:50.8469396Z benchmark-results-dir: test/test-reports 2025-09-07T10:53:50.8469644Z dry-run: false 2025-09-07T10:53:50.8469826Z schema-version: v3 2025-09-07T10:53:50.8470540Z github-token: *** 2025-09-07T10:53:50.8470739Z env: 2025-09-07T10:53:50.8470899Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:53:50.8471155Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:53:50.8471485Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:53:50.8471904Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:53:50.8472256Z ##[endgroup] 2025-09-07T10:53:50.8487369Z ##[group]Run set -eux 2025-09-07T10:53:50.8487585Z set -eux 2025-09-07T10:53:50.8487767Z  2025-09-07T10:53:50.8487934Z if [[ -n "" ]]; then 2025-09-07T10:53:50.8488156Z  source "" 2025-09-07T10:53:50.8488329Z fi 2025-09-07T10:53:50.8488590Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T10:53:50.8489041Z  2025-09-07T10:53:50.8489197Z DEVICE_NAME="" 2025-09-07T10:53:50.8489395Z DEVICE_TYPE="" 2025-09-07T10:53:50.8489574Z  2025-09-07T10:53:50.8489747Z if command -v nvidia-smi; then 2025-09-07T10:53:50.8490073Z  # NB: I'm using PyTorch here to get the device name, however, it needs to 2025-09-07T10:53:50.8490699Z  # install the correct version of PyTorch manually for now. Any PyTorch 2025-09-07T10:53:50.8491083Z  # version is fine, I just use 2.7.1 to satify PYPIDEP linter 2025-09-07T10:53:50.8491398Z  python3 -mpip install torch==2.7.1 2025-09-07T10:53:50.8491651Z elif command -v rocminfo; then 2025-09-07T10:53:50.8492096Z  # NB: Installing torch on ROCm runner with pip here causes CI to fail 2025-09-07T10:53:50.8492502Z  # with a memoryview is too large error only on MI300 runners. Is pip 2025-09-07T10:53:50.8492916Z  # version on ROCm runner there too old? As a workaround, let's use the 2025-09-07T10:53:50.8493270Z  # GPU device name coming from rocminfo instead 2025-09-07T10:53:50.8493527Z  DEVICE_NAME=rocm 2025-09-07T10:53:50.8493872Z  DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs) 2025-09-07T10:53:50.8494215Z fi 2025-09-07T10:53:50.8494370Z  2025-09-07T10:53:50.8494568Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV 2025-09-07T10:53:50.8494857Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T10:53:50.8509230Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:53:50.8509504Z env: 2025-09-07T10:53:50.8509680Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:53:50.8509928Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:53:50.8510466Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:53:50.8510892Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:53:50.8511260Z ##[endgroup] 2025-09-07T10:53:50.8543927Z + [[ -n '' ]] 2025-09-07T10:53:50.8544219Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T10:53:51.1476721Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T10:53:51.8674080Z Collecting boto3==1.35.33 2025-09-07T10:53:51.9252963Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T10:53:51.9618866Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 3.8 MB/s eta 0:00:00 2025-09-07T10:53:52.1045976Z Collecting psutil==7.0.0 2025-09-07T10:53:52.1151080Z 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) 2025-09-07T10:53:52.1516513Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 7.7 MB/s eta 0:00:00 2025-09-07T10:53:52.1722717Z Collecting pynvml==12.0.0 2025-09-07T10:53:52.1836520Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T10:53:52.2139414Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T10:53:52.2241999Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T10:53:52.2616232Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T10:53:52.2718143Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T10:53:52.2862554Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 5.8 MB/s eta 0:00:00 2025-09-07T10:53:52.9740629Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T10:53:52.9845465Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T10:53:53.4032042Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 41.6 MB/s eta 0:00:00 2025-09-07T10:53:53.4671764Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T10:53:53.4785181Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T10:53:53.4877014Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 5.0 MB/s eta 0:00:00 2025-09-07T10:53:53.4941369Z Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /usr/lib/python3/dist-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.26.5) 2025-09-07T10:53:53.4947794Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3/dist-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1) 2025-09-07T10:53:53.7811716Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T10:53:53.7812302Z Attempting uninstall: nvidia-ml-py 2025-09-07T10:53:53.7816921Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T10:53:53.7852828Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T10:53:53.7879114Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T10:53:53.8582240Z Attempting uninstall: psutil 2025-09-07T10:53:53.8588290Z Found existing installation: psutil 5.9.8 2025-09-07T10:53:53.8748959Z Uninstalling psutil-5.9.8: 2025-09-07T10:53:53.8757825Z Successfully uninstalled psutil-5.9.8 2025-09-07T10:53:54.5971601Z Successfully installed boto3-1.35.33 botocore-1.35.99 jmespath-1.0.1 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4 2025-09-07T10:53:54.6912428Z + DEVICE_NAME= 2025-09-07T10:53:54.6912689Z + DEVICE_TYPE= 2025-09-07T10:53:54.6912930Z + command -v nvidia-smi 2025-09-07T10:53:54.6913673Z /usr/bin/nvidia-smi 2025-09-07T10:53:54.6914048Z + python3 -mpip install torch==2.7.1 2025-09-07T10:53:54.9610533Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T10:53:55.1795322Z Collecting torch==2.7.1 2025-09-07T10:53:55.2392129Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T10:54:11.2542809Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 848.2 kB/s eta 0:00:00 2025-09-07T10:54:12.4946195Z Collecting triton==3.3.1 2025-09-07T10:54:12.5055722Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T10:54:16.2352251Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 3.3 MB/s eta 0:00:00 2025-09-07T10:54:16.6149659Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T10:54:16.6267608Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T10:54:18.5049879Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 8.3 MB/s eta 0:00:00 2025-09-07T10:54:18.6805741Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T10:54:18.6943671Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T10:54:20.7865945Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 8.3 MB/s eta 0:00:00 2025-09-07T10:54:21.0086744Z Collecting sympy>=1.13.3 2025-09-07T10:54:21.0192080Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T10:54:21.0708701Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 126.7 MB/s eta 0:00:00 2025-09-07T10:54:21.1277004Z Collecting networkx 2025-09-07T10:54:21.1381411Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T10:54:21.1578333Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 95.2 MB/s eta 0:00:00 2025-09-07T10:54:21.1809767Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T10:54:21.1929598Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T10:54:21.2092963Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 79.8 MB/s eta 0:00:00 2025-09-07T10:54:21.2505281Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T10:54:21.2612451Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T10:54:21.4070196Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 101.6 MB/s eta 0:00:00 2025-09-07T10:54:21.4560523Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T10:54:21.4672644Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T10:54:29.2746959Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.9 MB/s eta 0:00:00 2025-09-07T10:54:29.8385899Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T10:54:29.8491561Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T10:54:29.8576518Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 12.0 MB/s eta 0:00:00 2025-09-07T10:54:29.8831993Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T10:54:29.8939569Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T10:54:29.9091624Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 67.5 MB/s eta 0:00:00 2025-09-07T10:54:29.9117896Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/alice/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T10:54:29.9440033Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T10:54:29.9573339Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T10:54:31.4303219Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 12.6 MB/s eta 0:00:00 2025-09-07T10:54:31.6428378Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T10:54:31.6588451Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T10:54:31.7501821Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 101.2 MB/s eta 0:00:00 2025-09-07T10:54:31.8047769Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T10:54:31.8203615Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T10:54:32.4726948Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 30.2 MB/s eta 0:00:00 2025-09-07T10:54:32.5977571Z Collecting filelock 2025-09-07T10:54:32.6098754Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T10:54:32.6527907Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T10:54:32.6677953Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T10:54:35.3049053Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 6.4 MB/s eta 0:00:00 2025-09-07T10:54:35.5277479Z Collecting jinja2 2025-09-07T10:54:35.5383032Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T10:54:35.5475288Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 17.6 MB/s eta 0:00:00 2025-09-07T10:54:35.5930434Z Collecting fsspec 2025-09-07T10:54:35.6033586Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T10:54:35.6136905Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 22.0 MB/s eta 0:00:00 2025-09-07T10:54:35.6390379Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T10:54:35.6527675Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T10:54:35.8257424Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 91.5 MB/s eta 0:00:00 2025-09-07T10:54:35.8747977Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T10:54:35.8884416Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T10:54:38.2147134Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 7.2 MB/s eta 0:00:00 2025-09-07T10:54:38.4464941Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T10:54:38.4587011Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T10:54:43.6414758Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 2.9 MB/s eta 0:00:00 2025-09-07T10:54:44.0292958Z Requirement already satisfied: setuptools>=40.8.0 in /usr/lib/python3/dist-packages (from triton==3.3.1->torch==2.7.1) (59.6.0) 2025-09-07T10:54:44.5248054Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T10:54:44.5364189Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T10:54:44.6847822Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 3.6 MB/s eta 0:00:00 2025-09-07T10:54:44.9113969Z Collecting MarkupSafe>=2.0 2025-09-07T10:54:44.9229812Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T10:54:45.4741654Z Installing collected packages: nvidia-cusparselt-cu12, mpmath, triton, sympy, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, MarkupSafe, fsspec, filelock, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch 2025-09-07T10:54:49.7431579Z WARNING: The scripts proton and proton-viewer are installed in '/home/alice/.local/bin' which is not on PATH. 2025-09-07T10:54:49.7432453Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T10:54:53.9778886Z WARNING: The script isympy is installed in '/home/alice/.local/bin' which is not on PATH. 2025-09-07T10:54:53.9779691Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T10:55:28.8887007Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/alice/.local/bin' which is not on PATH. 2025-09-07T10:55:28.8887909Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T10:55:28.9767431Z Successfully installed MarkupSafe-3.0.2 filelock-3.19.1 fsspec-2025.9.0 jinja2-3.1.6 mpmath-1.3.0 networkx-3.4.2 nvidia-cublas-cu12-12.6.4.1 nvidia-cuda-cupti-cu12-12.6.80 nvidia-cuda-nvrtc-cu12-12.6.77 nvidia-cuda-runtime-cu12-12.6.77 nvidia-cudnn-cu12-9.5.1.17 nvidia-cufft-cu12-11.3.0.4 nvidia-cufile-cu12-1.11.1.6 nvidia-curand-cu12-10.3.7.77 nvidia-cusolver-cu12-11.7.1.2 nvidia-cusparse-cu12-12.5.4.2 nvidia-cusparselt-cu12-0.6.3 nvidia-nccl-cu12-2.26.2 nvidia-nvjitlink-cu12-12.6.85 nvidia-nvtx-cu12-12.6.77 sympy-1.14.0 torch-2.7.1 triton-3.3.1 2025-09-07T10:55:29.6768499Z + echo DEVICE_NAME= 2025-09-07T10:55:29.6768827Z + echo DEVICE_TYPE= 2025-09-07T10:55:29.6796690Z ##[group]Run set -eux 2025-09-07T10:55:29.6796945Z set -eux 2025-09-07T10:55:29.6797311Z  2025-09-07T10:55:29.6797531Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T10:55:29.6797840Z  echo "Missing github-token input" 2025-09-07T10:55:29.6798111Z  exit 1 2025-09-07T10:55:29.6798302Z fi 2025-09-07T10:55:29.6812435Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:29.6812735Z env: 2025-09-07T10:55:29.6812904Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:29.6813168Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:29.6813500Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:29.6813930Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:29.6814284Z DEVICE_NAME: 2025-09-07T10:55:29.6814449Z DEVICE_TYPE: 2025-09-07T10:55:29.6814820Z GITHUB_TOKEN: *** 2025-09-07T10:55:29.6815007Z ##[endgroup] 2025-09-07T10:55:29.6847536Z + [[ -z *** ]] 2025-09-07T10:55:29.6885122Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T10:55:29.6885442Z with: 2025-09-07T10:55:29.6885824Z github-token: *** 2025-09-07T10:55:29.6886005Z env: 2025-09-07T10:55:29.6886165Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:29.6886435Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:29.6886772Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:29.6887184Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:29.6887550Z DEVICE_NAME: 2025-09-07T10:55:29.6887908Z DEVICE_TYPE: 2025-09-07T10:55:29.6888071Z ##[endgroup] 2025-09-07T10:55:29.6900531Z ##[group]Run set -eux 2025-09-07T10:55:29.6900771Z set -eux 2025-09-07T10:55:29.6900943Z  2025-09-07T10:55:29.6901283Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T10:55:29.6915931Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:29.6916222Z env: 2025-09-07T10:55:29.6916384Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:29.6916635Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:29.6916968Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:29.6917382Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:29.6917735Z DEVICE_NAME: 2025-09-07T10:55:29.6917900Z DEVICE_TYPE: 2025-09-07T10:55:29.6918183Z GITHUB_TOKEN: *** 2025-09-07T10:55:29.6918353Z ##[endgroup] 2025-09-07T10:55:29.6951570Z + python3 /home/alice/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1001 2025-09-07T10:55:30.6526685Z setting job-id=49775781859 2025-09-07T10:55:30.6527153Z setting job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T10:55:30.7074282Z ##[group]Run set -eux 2025-09-07T10:55:30.7074569Z set -eux 2025-09-07T10:55:30.7074760Z  2025-09-07T10:55:30.7074943Z if [[ -n "" ]]; then 2025-09-07T10:55:30.7075168Z  source "" 2025-09-07T10:55:30.7075370Z fi 2025-09-07T10:55:30.7075555Z  2025-09-07T10:55:30.7075890Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T10:55:30.7076338Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T10:55:30.7076632Z  --repo "${REPO}" \ 2025-09-07T10:55:30.7076893Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T10:55:30.7077190Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T10:55:30.7077699Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T10:55:30.7078006Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T10:55:30.7078294Z  --job-id "${JOB_ID}" \ 2025-09-07T10:55:30.7078649Z  --job-name "${JOB_NAME}" 2025-09-07T10:55:30.7092334Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:30.7092624Z env: 2025-09-07T10:55:30.7092784Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:30.7093031Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:30.7093361Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:30.7093778Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:30.7106865Z DEVICE_NAME: 2025-09-07T10:55:30.7107062Z DEVICE_TYPE: 2025-09-07T10:55:30.7107233Z SCHEMA_VERSION: v3 2025-09-07T10:55:30.7107424Z REPO: pytorch/pytorch 2025-09-07T10:55:30.7107625Z HEAD_BRANCH: refs/heads/main 2025-09-07T10:55:30.7107864Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T10:55:30.7108115Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T10:55:30.7108296Z RUN_ATTEMPT: 1 2025-09-07T10:55:30.7108460Z JOB_ID: 49775781859 2025-09-07T10:55:30.7108765Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T10:55:30.7109097Z ##[endgroup] 2025-09-07T10:55:30.7560409Z + [[ -n '' ]] 2025-09-07T10:55:30.7562044Z + python3 /home/alice/_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 93fb23d6fae7c4e82c4239a1033e522088742634 --workflow-id 17525296438 --run-attempt 1 --job-id 49775781859 --job-name 'test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)' 2025-09-07T10:55:30.8365860Z ##[group]Run set -eux 2025-09-07T10:55:30.8366216Z set -eux 2025-09-07T10:55:30.8366399Z  2025-09-07T10:55:30.8366589Z if [[ -n "" ]]; then 2025-09-07T10:55:30.8366809Z  source "" 2025-09-07T10:55:30.8366998Z fi 2025-09-07T10:55:30.8367166Z  2025-09-07T10:55:30.8367475Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T10:55:30.8381464Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:30.8381746Z env: 2025-09-07T10:55:30.8381908Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:30.8382149Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:30.8382461Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:30.8382986Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:30.8383345Z DEVICE_NAME: 2025-09-07T10:55:30.8383518Z DEVICE_TYPE: 2025-09-07T10:55:30.8383674Z ##[endgroup] 2025-09-07T10:55:30.8878111Z + [[ -n '' ]] 2025-09-07T10:55:30.8878781Z + python3 /home/alice/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T10:55:31.6301438Z /home/alice/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T10:55:31.6302580Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T10:55:33.3575630Z ##[group]Run set -eux 2025-09-07T10:55:33.3575864Z set -eux 2025-09-07T10:55:33.3576046Z  2025-09-07T10:55:33.3576238Z # TODO (huydhn): Implement this part 2025-09-07T10:55:33.3576543Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T10:55:33.3591048Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:33.3591339Z env: 2025-09-07T10:55:33.3591501Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:33.3591765Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:33.3592305Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:33.3592733Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:33.3593193Z DEVICE_NAME: 2025-09-07T10:55:33.3593353Z DEVICE_TYPE: 2025-09-07T10:55:33.3593513Z ##[endgroup] 2025-09-07T10:55:33.4069467Z + echo 'dependencies={}' 2025-09-07T10:55:33.4983736Z ##[group]Run set -eux 2025-09-07T10:55:33.4983971Z set -eux 2025-09-07T10:55:33.4984141Z  2025-09-07T10:55:33.4984313Z if [[ -n "" ]]; then 2025-09-07T10:55:33.4984522Z  source "" 2025-09-07T10:55:33.4984701Z fi 2025-09-07T10:55:33.4984858Z  2025-09-07T10:55:33.4985060Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T10:55:33.4985417Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T10:55:33.4985806Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T10:55:33.4986117Z  exit 0 2025-09-07T10:55:33.4986299Z fi 2025-09-07T10:55:33.4986463Z  2025-09-07T10:55:33.4986644Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T10:55:33.4987025Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T10:55:33.4987445Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T10:55:33.4987771Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T10:55:33.4988045Z  --runners "${RUNNER_INFO}" \ 2025-09-07T10:55:33.4988319Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T10:55:33.4988563Z  --dry-run 2025-09-07T10:55:33.4988748Z else 2025-09-07T10:55:33.4989040Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T10:55:33.4989459Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T10:55:33.4989949Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T10:55:33.4990344Z  --runners "${RUNNER_INFO}" \ 2025-09-07T10:55:33.4990604Z  --dependencies "${DEPENDENCIES}" 2025-09-07T10:55:33.4990839Z fi 2025-09-07T10:55:33.5005128Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:33.5005413Z env: 2025-09-07T10:55:33.5005571Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:33.5005824Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:33.5006147Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:33.5006557Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:33.5006900Z DEVICE_NAME: 2025-09-07T10:55:33.5007064Z DEVICE_TYPE: 2025-09-07T10:55:33.5007248Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T10:55:33.5007477Z DRY_RUN: false 2025-09-07T10:55:33.5008404Z BENCHMARK_METADATA: {"timestamp": 1757242530, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781859} 2025-09-07T10:55:33.5009717Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "32ccf0b8d8bd"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}] 2025-09-07T10:55:33.5010399Z DEPENDENCIES: {} 2025-09-07T10:55:33.5010571Z ##[endgroup] 2025-09-07T10:55:33.5473715Z + [[ -n '' ]] 2025-09-07T10:55:33.5473978Z + [[ ! -d test/test-reports ]] 2025-09-07T10:55:33.5474241Z + [[ false == \t\r\u\e ]] 2025-09-07T10:55:33.5477213Z + python3 /home/alice/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757242530, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781859}' --runners '[{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "32ccf0b8d8bd"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}]' --dependencies '{}' 2025-09-07T10:55:33.6734489Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:33.7172864Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T10:55:33.9543543Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:34.0906516Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T10:55:34.2237266Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:34.3588177Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:34.4924833Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:34.6612299Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:34.8033777Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:34.9416559Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T10:55:35.0690790Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:35.2413639Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T10:55:35.3672137Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T10:55:35.5004568Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T10:55:35.6385486Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T10:55:35.7797093Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:35.9449603Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:36.1188493Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:36.3173074Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:36.5076716Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:36.6434748Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T10:55:36.7806613Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:36.9108298Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:37.0451731Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:37.1936276Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:37.3381705Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:37.5032821Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:37.6812414Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:37.8459694Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:38.0014272Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:38.2037638Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:38.3575571Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:38.5178590Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:38.6596097Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T10:55:38.7927532Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:38.9430988Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:39.1584198Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T10:55:39.2878076Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T10:55:39.4127878Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T10:55:39.5441587Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T10:55:39.6914077Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781859/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T10:55:39.9062317Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T10:55:39.9062657Z cat test/**/*_toprint.log || true 2025-09-07T10:55:39.9077021Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:39.9077309Z env: 2025-09-07T10:55:39.9077474Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:39.9077721Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:39.9078059Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:39.9078471Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:39.9078846Z DEVICE_NAME: 2025-09-07T10:55:39.9079006Z DEVICE_TYPE: 2025-09-07T10:55:39.9079168Z ##[endgroup] 2025-09-07T10:55:39.9631799Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T10:55:39.9885859Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T10:55:39.9886193Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T10:55:39.9900944Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:39.9901255Z env: 2025-09-07T10:55:39.9901423Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:39.9901676Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:39.9902012Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:39.9902469Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:39.9902947Z DEVICE_NAME: 2025-09-07T10:55:39.9903124Z DEVICE_TYPE: 2025-09-07T10:55:39.9903299Z MONITOR_SCRIPT_PID: 8173 2025-09-07T10:55:39.9903679Z ##[endgroup] 2025-09-07T10:55:40.0464195Z Prepare all required actions 2025-09-07T10:55:40.0464625Z Getting action download info 2025-09-07T10:55:40.2308095Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T10:55:41.0048765Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T10:55:42.4066471Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T10:55:42.4066755Z with: 2025-09-07T10:55:42.4067060Z file-suffix: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T10:55:42.4067486Z s3-bucket: gha-artifacts 2025-09-07T10:55:42.4067680Z env: 2025-09-07T10:55:42.4067840Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:42.4068083Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:42.4068408Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:42.4068851Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:42.4069198Z DEVICE_NAME: 2025-09-07T10:55:42.4069355Z DEVICE_TYPE: 2025-09-07T10:55:42.4069513Z ##[endgroup] 2025-09-07T10:55:42.4901636Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T10:55:42.4902034Z # Remove any previous test jsons if they exist 2025-09-07T10:55:42.4902338Z rm -f test-jsons-*.zip 2025-09-07T10:55:42.4902690Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T10:55:42.4917024Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:42.4917328Z env: 2025-09-07T10:55:42.4917528Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:42.4917801Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:42.4918142Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:42.4918573Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:42.4918964Z DEVICE_NAME: 2025-09-07T10:55:42.4919161Z DEVICE_TYPE: 2025-09-07T10:55:42.4919492Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T10:55:42.4919848Z ##[endgroup] 2025-09-07T10:55:42.5485630Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.5500661Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5517825Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5533797Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5549481Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5622634Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.5706158Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.5729322Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.5746561Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5772138Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.5792577Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json (deflated 98%) 2025-09-07T10:55:42.5809943Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5826993Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.5852746Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.5926623Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.5976551Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6048224Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6115693Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6141381Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6166597Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6183719Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6198969Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6224497Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6318000Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6334981Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6401138Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6484091Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6507499Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6590697Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6614146Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6678337Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.6701330Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6726665Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6741950Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6757414Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6782982Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6799998Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6817258Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T10:55:42.6843572Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T10:55:42.6922194Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T10:55:42.7251448Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T10:55:42.7251899Z # Remove any previous test reports if they exist 2025-09-07T10:55:42.7252250Z rm -f test-reports-*.zip 2025-09-07T10:55:42.7252696Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T10:55:42.7267085Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:42.7267379Z env: 2025-09-07T10:55:42.7267543Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:42.7267798Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:42.7268146Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:42.7268551Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:42.7268909Z DEVICE_NAME: 2025-09-07T10:55:42.7269086Z DEVICE_TYPE: 2025-09-07T10:55:42.7269383Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T10:55:42.7269718Z ##[endgroup] 2025-09-07T10:55:42.7751390Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T10:55:42.7752218Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T10:55:42.7753082Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7753899Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T10:55:42.7754815Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T10:55:42.7755725Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7756667Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7757561Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T10:55:42.7758450Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T10:55:42.7759364Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T10:55:42.7760406Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7761381Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 53%) 2025-09-07T10:55:42.7762341Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T10:55:42.7763146Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 62%) 2025-09-07T10:55:42.7763773Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.csv (deflated 47%) 2025-09-07T10:55:42.7764475Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T10:55:42.7765174Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 55%) 2025-09-07T10:55:42.7766100Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 50%) 2025-09-07T10:55:42.7766754Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.csv (deflated 48%) 2025-09-07T10:55:42.7767394Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.csv (deflated 47%) 2025-09-07T10:55:42.7768100Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T10:55:42.7768839Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T10:55:42.7769581Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 49%) 2025-09-07T10:55:42.7770459Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7771162Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 49%) 2025-09-07T10:55:42.7771836Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T10:55:42.7772547Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T10:55:42.7773262Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 47%) 2025-09-07T10:55:42.7774226Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T10:55:42.7776004Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T10:55:42.7776689Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 51%) 2025-09-07T10:55:42.7778362Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T10:55:42.7779155Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 53%) 2025-09-07T10:55:42.7779775Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7780526Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 47%) 2025-09-07T10:55:42.7781240Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7782046Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T10:55:42.7783765Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T10:55:42.7784495Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 52%) 2025-09-07T10:55:42.7785168Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T10:55:42.7786104Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T10:55:42.7786788Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 50%) 2025-09-07T10:55:42.8149309Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T10:55:42.8149684Z # Remove any previous usage logs if they exist 2025-09-07T10:55:42.8150133Z rm -f logs-*.zip 2025-09-07T10:55:42.8150829Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T10:55:42.8151263Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T10:55:42.8164666Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:42.8164965Z env: 2025-09-07T10:55:42.8165128Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:42.8165382Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:42.8165723Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:42.8166138Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:42.8166481Z DEVICE_NAME: 2025-09-07T10:55:42.8166646Z DEVICE_TYPE: 2025-09-07T10:55:42.8166935Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T10:55:42.8167269Z ##[endgroup] 2025-09-07T10:55:42.8733251Z adding: usage_log.txt (deflated 91%) 2025-09-07T10:55:42.8749364Z 2025-09-07T10:55:42.8749903Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip) 2025-09-07T10:55:42.9498067Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T10:55:42.9498465Z # Remove any previous debugging artifacts if they exist 2025-09-07T10:55:42.9498778Z rm -f debug-*.zip 2025-09-07T10:55:42.9498990Z if [ -d 'test/debug' ]; then 2025-09-07T10:55:42.9499273Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T10:55:42.9499532Z fi 2025-09-07T10:55:42.9512221Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:42.9512514Z env: 2025-09-07T10:55:42.9512684Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:42.9512944Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:42.9513275Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:42.9513708Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:42.9514065Z DEVICE_NAME: 2025-09-07T10:55:42.9514234Z DEVICE_TYPE: 2025-09-07T10:55:42.9514526Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859 2025-09-07T10:55:42.9514864Z ##[endgroup] 2025-09-07T10:55:43.0883088Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T10:55:43.0883485Z with: 2025-09-07T10:55:43.0883745Z s3-bucket: gha-artifacts 2025-09-07T10:55:43.0884091Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:43.0884459Z retention-days: 14 2025-09-07T10:55:43.0884732Z if-no-files-found: warn 2025-09-07T10:55:43.0885016Z path: test-jsons-*.zip 2025-09-07T10:55:43.0885289Z name: artifact 2025-09-07T10:55:43.0885538Z region: us-east-1 2025-09-07T10:55:43.0885776Z env: 2025-09-07T10:55:43.0886006Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:43.0886369Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:43.0886848Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:43.0887483Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:43.0887998Z DEVICE_NAME: 2025-09-07T10:55:43.0888250Z DEVICE_TYPE: 2025-09-07T10:55:43.0888485Z ##[endgroup] 2025-09-07T10:55:43.4930145Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T10:55:43.4930937Z With the provided path, there will be 1 file uploaded 2025-09-07T10:55:43.4931487Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:43.4944094Z Starting upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:43.8836111Z Finished upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:43.9457805Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T10:55:43.9458239Z with: 2025-09-07T10:55:43.9458505Z s3-bucket: gha-artifacts 2025-09-07T10:55:43.9459124Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:43.9459818Z retention-days: 14 2025-09-07T10:55:43.9460121Z if-no-files-found: error 2025-09-07T10:55:43.9460685Z path: test-reports-*.zip 2025-09-07T10:55:43.9461001Z name: artifact 2025-09-07T10:55:43.9461272Z region: us-east-1 2025-09-07T10:55:43.9461551Z env: 2025-09-07T10:55:43.9461805Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:43.9462204Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:43.9462860Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:43.9463569Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:43.9464160Z DEVICE_NAME: 2025-09-07T10:55:43.9464432Z DEVICE_TYPE: 2025-09-07T10:55:43.9464693Z ##[endgroup] 2025-09-07T10:55:44.2509251Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T10:55:44.2509794Z With the provided path, there will be 1 file uploaded 2025-09-07T10:55:44.2510497Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:44.2518582Z Starting upload of test-reports-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:44.4527558Z Finished upload of test-reports-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:44.5182291Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T10:55:44.5182590Z with: 2025-09-07T10:55:44.5182851Z s3-bucket: gha-artifacts 2025-09-07T10:55:44.5183126Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:44.5183404Z retention-days: 14 2025-09-07T10:55:44.5183619Z if-no-files-found: ignore 2025-09-07T10:55:44.5183836Z path: logs-*.zip 2025-09-07T10:55:44.5184033Z name: artifact 2025-09-07T10:55:44.5184212Z region: us-east-1 2025-09-07T10:55:44.5184394Z env: 2025-09-07T10:55:44.5184553Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:44.5184810Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:44.5185155Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:44.5185573Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:44.5185920Z DEVICE_NAME: 2025-09-07T10:55:44.5186089Z DEVICE_TYPE: 2025-09-07T10:55:44.5186249Z ##[endgroup] 2025-09-07T10:55:44.8182647Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T10:55:44.8183160Z With the provided path, there will be 1 file uploaded 2025-09-07T10:55:44.8183567Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:44.8192006Z Starting upload of logs-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:44.9866976Z Finished upload of logs-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:55:45.1356482Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T10:55:45.1356935Z with: 2025-09-07T10:55:45.1357243Z s3-bucket: gha-artifacts 2025-09-07T10:55:45.1357693Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T10:55:45.1358164Z retention-days: 14 2025-09-07T10:55:45.1358510Z if-no-files-found: ignore 2025-09-07T10:55:45.1358871Z path: debug-*.zip 2025-09-07T10:55:45.1359171Z name: artifact 2025-09-07T10:55:45.1359467Z region: us-east-1 2025-09-07T10:55:45.1359770Z env: 2025-09-07T10:55:45.1360043Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:45.1360825Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:45.1361417Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:45.1362168Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:45.1362806Z DEVICE_NAME: 2025-09-07T10:55:45.1363093Z DEVICE_TYPE: 2025-09-07T10:55:45.1363377Z ##[endgroup] 2025-09-07T10:55:45.4671045Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T10:55:45.5155524Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T10:55:45.5156026Z # shellcheck disable=SC2156 2025-09-07T10:55:45.5156538Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T10:55:45.5171550Z shell: /usr/bin/bash -e {0} 2025-09-07T10:55:45.5171767Z env: 2025-09-07T10:55:45.5171944Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:45.5172183Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:45.5172521Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:45.5172950Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:45.5173315Z DEVICE_NAME: 2025-09-07T10:55:45.5173494Z DEVICE_TYPE: 2025-09-07T10:55:45.5173649Z ##[endgroup] 2025-09-07T10:55:46.2742362Z Prepare all required actions 2025-09-07T10:55:46.2742815Z Getting action download info 2025-09-07T10:55:46.4286493Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T10:55:46.4286794Z with: 2025-09-07T10:55:46.4286974Z job_id: 49775781859 2025-09-07T10:55:46.4287312Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T10:55:46.4287733Z workflow_name: inductor-perf-nightly-h100 2025-09-07T10:55:46.4288009Z workflow_run_id: 17525296438 2025-09-07T10:55:46.4288238Z workflow_attempt: 1 2025-09-07T10:55:46.4288425Z env: 2025-09-07T10:55:46.4288586Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:46.4288850Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:46.4289220Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:46.4289692Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:46.4290084Z DEVICE_NAME: 2025-09-07T10:55:46.4290464Z DEVICE_TYPE: 2025-09-07T10:55:46.4290652Z ##[endgroup] 2025-09-07T10:55:46.5668386Z ##[group]Run echo "workflow_id: 17525296438" 2025-09-07T10:55:46.5668694Z echo "workflow_id: 17525296438" 2025-09-07T10:55:46.5668950Z echo "workflow_attempt: 1" 2025-09-07T10:55:46.5669237Z echo "workflow_Name: inductor-perf-nightly-h100" 2025-09-07T10:55:46.5669527Z echo "job_id: 49775781859" 2025-09-07T10:55:46.5669911Z echo "job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)" 2025-09-07T10:55:46.5670655Z echo "artifact_prefix: " 2025-09-07T10:55:46.5686692Z python3 --version 2025-09-07T10:55:46.5701533Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:55:46.5701822Z env: 2025-09-07T10:55:46.5701988Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:46.5702231Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:46.5702577Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:46.5703084Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:46.5703438Z DEVICE_NAME: 2025-09-07T10:55:46.5703599Z DEVICE_TYPE: 2025-09-07T10:55:46.5703774Z ##[endgroup] 2025-09-07T10:55:46.6169356Z workflow_id: 17525296438 2025-09-07T10:55:46.6169709Z workflow_attempt: 1 2025-09-07T10:55:46.6170045Z workflow_Name: inductor-perf-nightly-h100 2025-09-07T10:55:46.6170600Z job_id: 49775781859 2025-09-07T10:55:46.6171097Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100) 2025-09-07T10:55:46.6171701Z artifact_prefix: 2025-09-07T10:55:46.6188609Z Python 3.10.12 2025-09-07T10:55:46.6580749Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T10:55:46.6581023Z with: 2025-09-07T10:55:46.6581188Z shell: bash 2025-09-07T10:55:46.6581370Z timeout_minutes: 5 2025-09-07T10:55:46.6581565Z max_attempts: 5 2025-09-07T10:55:46.6581757Z retry_wait_seconds: 30 2025-09-07T10:55:46.6582234Z command: set -eu python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3 dataclasses_json==0.6.7 2025-09-07T10:55:46.6582804Z polling_interval_seconds: 1 2025-09-07T10:55:46.6583037Z warning_on_retry: true 2025-09-07T10:55:46.6583416Z continue_on_error: false 2025-09-07T10:55:46.6583620Z env: 2025-09-07T10:55:46.6583785Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:55:46.6584054Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:55:46.6584408Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:55:46.6584838Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:55:46.6585181Z DEVICE_NAME: 2025-09-07T10:55:46.6585348Z DEVICE_TYPE: 2025-09-07T10:55:46.6585505Z ##[endgroup] 2025-09-07T10:55:46.9977001Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T10:55:47.5340124Z Collecting python-dateutil==2.8.2 2025-09-07T10:55:47.5901759Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T10:55:48.0005407Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 582.5 kB/s eta 0:00:00 2025-09-07T10:55:48.8993939Z Collecting boto3==1.35.42 2025-09-07T10:55:48.9097693Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T10:55:49.3516042Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 293.4 kB/s eta 0:00:00 2025-09-07T10:55:50.0061558Z Collecting pandas==2.1.3 2025-09-07T10:55:50.0181060Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T10:55:50.5982650Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 22.8 MB/s eta 0:00:00 2025-09-07T10:55:50.6339301Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/alice/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T10:55:50.6355286Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T10:55:50.6399584Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/alice/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T10:55:50.6404673Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/alice/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T10:55:50.6409079Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/alice/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T10:55:50.7809580Z Collecting pytz>=2020.1 2025-09-07T10:55:50.7910459Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T10:55:50.8349343Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 11.9 MB/s eta 0:00:00 2025-09-07T10:55:50.8831901Z Collecting tzdata>=2022.1 2025-09-07T10:55:50.8931174Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T10:55:50.9264881Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 10.7 MB/s eta 0:00:00 2025-09-07T10:55:51.3357254Z Collecting numpy<2,>=1.22.4 2025-09-07T10:55:51.3461331Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T10:55:52.2373119Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 12.6 MB/s eta 0:00:00 2025-09-07T10:55:52.2688268Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/alice/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T10:55:52.2695931Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/alice/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T10:55:52.2766986Z Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /usr/lib/python3/dist-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.26.5) 2025-09-07T10:55:52.2912199Z Requirement already satisfied: packaging>=17.0 in /home/alice/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T10:55:52.3012740Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/alice/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-09-07T10:55:52.3017547Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/alice/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-09-07T10:55:52.5802792Z Installing collected packages: pytz, tzdata, python-dateutil, numpy, pandas, boto3 2025-09-07T10:55:56.5585691Z WARNING: The script f2py is installed in '/home/alice/.local/bin' which is not on PATH. 2025-09-07T10:55:56.5586576Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T10:56:00.5603196Z Attempting uninstall: boto3 2025-09-07T10:56:00.5609026Z Found existing installation: boto3 1.35.33 2025-09-07T10:56:00.5839887Z Uninstalling boto3-1.35.33: 2025-09-07T10:56:00.5860402Z Successfully uninstalled boto3-1.35.33 2025-09-07T10:56:00.7289256Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 pytz-2025.2 tzdata-2025.2 2025-09-07T10:56:01.7405245Z Command completed after 1 attempt(s). 2025-09-07T10:56:01.7765580Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T10:56:01.7768285Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T10:56:01.7768714Z  --workflow-run-id "17525296438" \ 2025-09-07T10:56:01.7769024Z  --workflow-name "inductor-perf-nightly-h100" \ 2025-09-07T10:56:01.7769332Z  --workflow-run-attempt "1" \ 2025-09-07T10:56:01.7769565Z  --job-id "49775781859" \ 2025-09-07T10:56:01.7769948Z  --job-name "test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)" \ 2025-09-07T10:56:01.7770515Z  --local-path "" \ 2025-09-07T10:56:01.7770729Z  --artifact-prefix "" 2025-09-07T10:56:01.7785279Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T10:56:01.7785568Z env: 2025-09-07T10:56:01.7785723Z GIT_DEFAULT_BRANCH: main 2025-09-07T10:56:01.7785971Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T10:56:01.7786305Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5227 2025-09-07T10:56:01.7786714Z DOCKER_CONTAINER_ID: c52ec34ab4173db330a91909043dba82889fcad387738805133319dfc27ce796 2025-09-07T10:56:01.7787068Z DEVICE_NAME: 2025-09-07T10:56:01.7787237Z DEVICE_TYPE: 2025-09-07T10:56:01.7787406Z ##[endgroup] 2025-09-07T10:56:03.8899914Z repo: pytorch/pytorch 2025-09-07T10:56:03.8900647Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T10:56:03.8901209Z Downloading logs-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:56:03.8901936Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf_cuda_h100-1-9-linux.aws.h100_49775781859.zip 2025-09-07T10:56:03.8902541Z Converted Log Model: UtilizationMetadata: 2025-09-07T10:56:03.8903939Z UtilizationMetadata(level='metadata', workflow_id='17525296438', job_id='49775781859', workflow_name='inductor-perf-nightly-h100', job_name='test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757232954, gpu_count=1, cpu_count=192, gpu_type='pynvml', error=None) 2025-09-07T10:56:03.8905792Z [Db Segments] detected pytest cmd: 2, generated segments: 2 2025-09-07T10:56:03.8906163Z [db model] Peek db timeseries 2025-09-07T10:56:03.8906414Z :{ 2025-09-07T10:56:03.8906600Z "created_at": 1757242563, 2025-09-07T10:56:03.8906846Z "type": "utilization", 2025-09-07T10:56:03.8907071Z "tags": [ 2025-09-07T10:56:03.8907250Z "record" 2025-09-07T10:56:03.8907440Z ], 2025-09-07T10:56:03.8907627Z "time_stamp": 1757232954, 2025-09-07T10:56:03.8907868Z "repo": "pytorch/pytorch", 2025-09-07T10:56:03.8908107Z "workflow_id": 17525296438, 2025-09-07T10:56:03.8908351Z "run_attempt": 1, 2025-09-07T10:56:03.8908612Z "job_id": 49775781859, 2025-09-07T10:56:03.8908942Z "workflow_name": "inductor-perf-nightly-h100", 2025-09-07T10:56:03.8909467Z "job_name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 1, 9, linux.aws.h100)", 2025-09-07T10:56:03.8909893Z "json_data": "{}" 2025-09-07T10:56:03.8910091Z } 2025-09-07T10:56:03.8910678Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781859/metadata 2025-09-07T10:56:03.8911467Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781859/metadata 2025-09-07T10:56:03.8912287Z Writing 630 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781859/time_series 2025-09-07T10:56:03.8913123Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781859/time_series 2025-09-07T10:56:04.0285208Z Post job cleanup. 2025-09-07T10:56:04.1696125Z Post job cleanup. 2025-09-07T10:56:04.2601664Z [command]/usr/bin/git version 2025-09-07T10:56:04.2641800Z git version 2.50.1 2025-09-07T10:56:04.2680632Z Temporarily overriding HOME='/home/alice/_work/_temp/561e342f-3716-4339-b223-e3c27623bacb' before making global git config changes 2025-09-07T10:56:04.2681386Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T10:56:04.2685267Z [command]/usr/bin/git config --global --add safe.directory /home/alice/_work/pytorch/pytorch 2025-09-07T10:56:04.3078333Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T10:56:04.3121252Z [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' || :" 2025-09-07T10:56:04.3396750Z Entering 'android/libs/fbjni' 2025-09-07T10:56:04.3448037Z Entering 'third_party/FP16' 2025-09-07T10:56:04.3498001Z Entering 'third_party/FXdiv' 2025-09-07T10:56:04.3547299Z Entering 'third_party/NNPACK' 2025-09-07T10:56:04.3596934Z Entering 'third_party/NVTX' 2025-09-07T10:56:04.3647463Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T10:56:04.3696515Z Entering 'third_party/XNNPACK' 2025-09-07T10:56:04.3761058Z Entering 'third_party/aiter' 2025-09-07T10:56:04.3811176Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T10:56:04.3869410Z Entering 'third_party/benchmark' 2025-09-07T10:56:04.3919816Z Entering 'third_party/composable_kernel' 2025-09-07T10:56:04.3977752Z Entering 'third_party/cpp-httplib' 2025-09-07T10:56:04.4027467Z Entering 'third_party/cpuinfo' 2025-09-07T10:56:04.4077669Z Entering 'third_party/cudnn_frontend' 2025-09-07T10:56:04.4128521Z Entering 'third_party/cutlass' 2025-09-07T10:56:04.4186321Z Entering 'third_party/fbgemm' 2025-09-07T10:56:04.4237375Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T10:56:04.4285455Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T10:56:04.4339633Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T10:56:04.4386897Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T10:56:04.4442399Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T10:56:04.4489057Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T10:56:04.4535459Z Entering 'third_party/fbgemm/external/json' 2025-09-07T10:56:04.4586549Z Entering 'third_party/flash-attention' 2025-09-07T10:56:04.4637039Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T10:56:04.4690346Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T10:56:04.4747219Z Entering 'third_party/flatbuffers' 2025-09-07T10:56:04.4799371Z Entering 'third_party/fmt' 2025-09-07T10:56:04.4848601Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T10:56:04.4898373Z Entering 'third_party/gloo' 2025-09-07T10:56:04.4947996Z Entering 'third_party/googletest' 2025-09-07T10:56:04.4997100Z Entering 'third_party/ideep' 2025-09-07T10:56:04.5045009Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T10:56:04.5101153Z Entering 'third_party/ittapi' 2025-09-07T10:56:04.5152073Z Entering 'third_party/kineto' 2025-09-07T10:56:04.5200570Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T10:56:04.5247959Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T10:56:04.5297626Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T10:56:04.5344632Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T10:56:04.5391699Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T10:56:04.5437574Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T10:56:04.5489148Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T10:56:04.5537421Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T10:56:04.5584282Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T10:56:04.5631969Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T10:56:04.5683671Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T10:56:04.5730577Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T10:56:04.5779331Z Entering 'third_party/kleidiai' 2025-09-07T10:56:04.5829435Z Entering 'third_party/mimalloc' 2025-09-07T10:56:04.5878940Z Entering 'third_party/nlohmann' 2025-09-07T10:56:04.5929426Z Entering 'third_party/onnx' 2025-09-07T10:56:04.5992425Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T10:56:04.6047639Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T10:56:04.6097611Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T10:56:04.6145264Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T10:56:04.6191524Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T10:56:04.6237175Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T10:56:04.6284815Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T10:56:04.6330057Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T10:56:04.6378746Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T10:56:04.6424576Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T10:56:04.6475293Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T10:56:04.6524690Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T10:56:04.6591690Z Entering 'third_party/pocketfft' 2025-09-07T10:56:04.6641383Z Entering 'third_party/protobuf' 2025-09-07T10:56:04.6692472Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T10:56:04.6739834Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T10:56:04.6789902Z Entering 'third_party/psimd' 2025-09-07T10:56:04.6839466Z Entering 'third_party/pthreadpool' 2025-09-07T10:56:04.6888766Z Entering 'third_party/pybind11' 2025-09-07T10:56:04.6938447Z Entering 'third_party/python-peachpy' 2025-09-07T10:56:04.6987301Z Entering 'third_party/sleef' 2025-09-07T10:56:04.7035814Z Entering 'third_party/tensorpipe' 2025-09-07T10:56:04.7084194Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T10:56:04.7131655Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T10:56:04.7177247Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T10:56:04.7223884Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T10:56:04.7267808Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T10:56:04.7342337Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T10:56:04.7366494Z http.https://github.com/.extraheader 2025-09-07T10:56:04.7375934Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-09-07T10:56:04.7805074Z [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' || :" 2025-09-07T10:56:04.8067040Z Entering 'android/libs/fbjni' 2025-09-07T10:56:04.8095622Z http.https://github.com/.extraheader 2025-09-07T10:56:04.8316753Z Entering 'third_party/FP16' 2025-09-07T10:56:04.8344888Z http.https://github.com/.extraheader 2025-09-07T10:56:04.8776293Z Entering 'third_party/FXdiv' 2025-09-07T10:56:04.8806315Z http.https://github.com/.extraheader 2025-09-07T10:56:04.9184750Z Entering 'third_party/NNPACK' 2025-09-07T10:56:04.9212710Z http.https://github.com/.extraheader 2025-09-07T10:56:04.9666491Z Entering 'third_party/NVTX' 2025-09-07T10:56:04.9694149Z http.https://github.com/.extraheader 2025-09-07T10:56:05.0085904Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T10:56:05.0113603Z http.https://github.com/.extraheader 2025-09-07T10:56:05.0567912Z Entering 'third_party/XNNPACK' 2025-09-07T10:56:05.0596906Z http.https://github.com/.extraheader 2025-09-07T10:56:05.1059511Z Entering 'third_party/aiter' 2025-09-07T10:56:05.1088606Z http.https://github.com/.extraheader 2025-09-07T10:56:05.1492721Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T10:56:05.1520199Z http.https://github.com/.extraheader 2025-09-07T10:56:05.1979995Z Entering 'third_party/benchmark' 2025-09-07T10:56:05.2008881Z http.https://github.com/.extraheader 2025-09-07T10:56:05.2448892Z Entering 'third_party/composable_kernel' 2025-09-07T10:56:05.2476486Z http.https://github.com/.extraheader 2025-09-07T10:56:05.2871029Z Entering 'third_party/cpp-httplib' 2025-09-07T10:56:05.2897968Z http.https://github.com/.extraheader 2025-09-07T10:56:05.3342120Z Entering 'third_party/cpuinfo' 2025-09-07T10:56:05.3369785Z http.https://github.com/.extraheader 2025-09-07T10:56:05.3766238Z Entering 'third_party/cudnn_frontend' 2025-09-07T10:56:05.3793743Z http.https://github.com/.extraheader 2025-09-07T10:56:05.4226551Z Entering 'third_party/cutlass' 2025-09-07T10:56:05.4255205Z http.https://github.com/.extraheader 2025-09-07T10:56:05.4716347Z Entering 'third_party/fbgemm' 2025-09-07T10:56:05.4744939Z http.https://github.com/.extraheader 2025-09-07T10:56:05.5129649Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T10:56:05.5157113Z http.https://github.com/.extraheader 2025-09-07T10:56:05.5605673Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T10:56:05.5631944Z http.https://github.com/.extraheader 2025-09-07T10:56:05.6094169Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T10:56:05.6120011Z http.https://github.com/.extraheader 2025-09-07T10:56:05.6537461Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T10:56:05.6563391Z http.https://github.com/.extraheader 2025-09-07T10:56:05.7045233Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T10:56:05.7074441Z http.https://github.com/.extraheader 2025-09-07T10:56:05.9328502Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T10:56:05.9356093Z http.https://github.com/.extraheader 2025-09-07T10:56:05.9801992Z Entering 'third_party/fbgemm/external/json' 2025-09-07T10:56:05.9830868Z http.https://github.com/.extraheader 2025-09-07T10:56:06.0286543Z Entering 'third_party/flash-attention' 2025-09-07T10:56:06.0316581Z http.https://github.com/.extraheader 2025-09-07T10:56:06.0764467Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T10:56:06.0795010Z http.https://github.com/.extraheader 2025-09-07T10:56:06.1187071Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T10:56:06.1214895Z http.https://github.com/.extraheader 2025-09-07T10:56:06.1642692Z Entering 'third_party/flatbuffers' 2025-09-07T10:56:06.1674071Z http.https://github.com/.extraheader 2025-09-07T10:56:06.2052170Z Entering 'third_party/fmt' 2025-09-07T10:56:06.2080722Z http.https://github.com/.extraheader 2025-09-07T10:56:06.2447746Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T10:56:06.2473156Z http.https://github.com/.extraheader 2025-09-07T10:56:06.2924226Z Entering 'third_party/gloo' 2025-09-07T10:56:06.2953296Z http.https://github.com/.extraheader 2025-09-07T10:56:06.3405956Z Entering 'third_party/googletest' 2025-09-07T10:56:06.3435307Z http.https://github.com/.extraheader 2025-09-07T10:56:06.3855567Z Entering 'third_party/ideep' 2025-09-07T10:56:06.3886771Z http.https://github.com/.extraheader 2025-09-07T10:56:06.4333535Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T10:56:06.4363521Z http.https://github.com/.extraheader 2025-09-07T10:56:06.4762057Z Entering 'third_party/ittapi' 2025-09-07T10:56:06.4793678Z http.https://github.com/.extraheader 2025-09-07T10:56:06.5233544Z Entering 'third_party/kineto' 2025-09-07T10:56:06.5261203Z http.https://github.com/.extraheader 2025-09-07T10:56:06.5715315Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T10:56:06.5747536Z http.https://github.com/.extraheader 2025-09-07T10:56:06.6134702Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T10:56:06.6162561Z http.https://github.com/.extraheader 2025-09-07T10:56:06.6614153Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T10:56:06.6642839Z http.https://github.com/.extraheader 2025-09-07T10:56:06.7097901Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T10:56:06.7125332Z http.https://github.com/.extraheader 2025-09-07T10:56:06.7575336Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T10:56:06.7604349Z http.https://github.com/.extraheader 2025-09-07T10:56:06.8066958Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T10:56:06.8095571Z http.https://github.com/.extraheader 2025-09-07T10:56:06.8495979Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T10:56:06.8527077Z http.https://github.com/.extraheader 2025-09-07T10:56:06.8974322Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T10:56:06.9004164Z http.https://github.com/.extraheader 2025-09-07T10:56:06.9450606Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T10:56:06.9479683Z http.https://github.com/.extraheader 2025-09-07T10:56:06.9901030Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T10:56:06.9928750Z http.https://github.com/.extraheader 2025-09-07T10:56:07.0389885Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T10:56:07.0418231Z http.https://github.com/.extraheader 2025-09-07T10:56:07.0799902Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T10:56:07.0829420Z http.https://github.com/.extraheader 2025-09-07T10:56:07.1286202Z Entering 'third_party/kleidiai' 2025-09-07T10:56:07.1316487Z http.https://github.com/.extraheader 2025-09-07T10:56:07.1761881Z Entering 'third_party/mimalloc' 2025-09-07T10:56:07.1792351Z http.https://github.com/.extraheader 2025-09-07T10:56:07.2182546Z Entering 'third_party/nlohmann' 2025-09-07T10:56:07.2209195Z http.https://github.com/.extraheader 2025-09-07T10:56:07.2661395Z Entering 'third_party/onnx' 2025-09-07T10:56:07.2687664Z http.https://github.com/.extraheader 2025-09-07T10:56:07.3155352Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T10:56:07.3182376Z http.https://github.com/.extraheader 2025-09-07T10:56:07.3562856Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T10:56:07.3588631Z http.https://github.com/.extraheader 2025-09-07T10:56:07.4039894Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T10:56:07.4064551Z http.https://github.com/.extraheader 2025-09-07T10:56:07.4457086Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T10:56:07.4481828Z http.https://github.com/.extraheader 2025-09-07T10:56:07.4938519Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T10:56:07.4962984Z http.https://github.com/.extraheader 2025-09-07T10:56:07.5421628Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T10:56:07.5446356Z http.https://github.com/.extraheader 2025-09-07T10:56:07.5846410Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T10:56:07.5871442Z http.https://github.com/.extraheader 2025-09-07T10:56:07.6324383Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T10:56:07.6352691Z http.https://github.com/.extraheader 2025-09-07T10:56:07.6811397Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T10:56:07.6840006Z http.https://github.com/.extraheader 2025-09-07T10:56:07.7247723Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T10:56:07.7274857Z http.https://github.com/.extraheader 2025-09-07T10:56:07.7739926Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T10:56:07.7766569Z http.https://github.com/.extraheader 2025-09-07T10:56:07.8159087Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T10:56:07.8189304Z http.https://github.com/.extraheader 2025-09-07T10:56:07.8655812Z Entering 'third_party/pocketfft' 2025-09-07T10:56:07.8687364Z http.https://github.com/.extraheader 2025-09-07T10:56:07.9114388Z Entering 'third_party/protobuf' 2025-09-07T10:56:07.9144155Z http.https://github.com/.extraheader 2025-09-07T10:56:07.9536871Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T10:56:07.9567335Z http.https://github.com/.extraheader 2025-09-07T10:56:08.0013562Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T10:56:08.0039551Z http.https://github.com/.extraheader 2025-09-07T10:56:08.0497930Z Entering 'third_party/psimd' 2025-09-07T10:56:08.0528144Z http.https://github.com/.extraheader 2025-09-07T10:56:08.0948101Z Entering 'third_party/pthreadpool' 2025-09-07T10:56:08.0977731Z http.https://github.com/.extraheader 2025-09-07T10:56:08.1425932Z Entering 'third_party/pybind11' 2025-09-07T10:56:08.1455518Z http.https://github.com/.extraheader 2025-09-07T10:56:08.1843370Z Entering 'third_party/python-peachpy' 2025-09-07T10:56:08.1870584Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2326075Z Entering 'third_party/sleef' 2025-09-07T10:56:08.2355723Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2391093Z Entering 'third_party/tensorpipe' 2025-09-07T10:56:08.2419182Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2453701Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T10:56:08.2481273Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2517278Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T10:56:08.2544804Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2579453Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T10:56:08.2608428Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2644845Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T10:56:08.2671596Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2705401Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T10:56:08.2733348Z http.https://github.com/.extraheader 2025-09-07T10:56:08.2926182Z Post job cleanup. 2025-09-07T10:56:08.3827382Z [command]/usr/bin/git version 2025-09-07T10:56:08.3869386Z git version 2.50.1 2025-09-07T10:56:08.3909231Z Temporarily overriding HOME='/home/alice/_work/_temp/18a34688-b74e-4668-9cf2-40697b2f2b09' before making global git config changes 2025-09-07T10:56:08.3909957Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T10:56:08.3914118Z [command]/usr/bin/git config --global --add safe.directory /home/alice/_work/pytorch/pytorch 2025-09-07T10:56:08.3949759Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T10:56:08.3991674Z [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' || :" 2025-09-07T10:56:08.4261246Z Entering 'android/libs/fbjni' 2025-09-07T10:56:08.4309963Z Entering 'third_party/FP16' 2025-09-07T10:56:08.4360530Z Entering 'third_party/FXdiv' 2025-09-07T10:56:08.4409737Z Entering 'third_party/NNPACK' 2025-09-07T10:56:08.4458772Z Entering 'third_party/NVTX' 2025-09-07T10:56:08.4508804Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T10:56:08.4558410Z Entering 'third_party/XNNPACK' 2025-09-07T10:56:08.4623173Z Entering 'third_party/aiter' 2025-09-07T10:56:08.4672693Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T10:56:08.4730589Z Entering 'third_party/benchmark' 2025-09-07T10:56:08.4781897Z Entering 'third_party/composable_kernel' 2025-09-07T10:56:08.4839266Z Entering 'third_party/cpp-httplib' 2025-09-07T10:56:08.4890098Z Entering 'third_party/cpuinfo' 2025-09-07T10:56:08.4939593Z Entering 'third_party/cudnn_frontend' 2025-09-07T10:56:08.4989285Z Entering 'third_party/cutlass' 2025-09-07T10:56:08.5046736Z Entering 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